Nothing Special   »   [go: up one dir, main page]
Next Issue
Volume 11, January
Previous Issue
Volume 10, November
You seem to have javascript disabled. Please note that many of the page functionalities won't work as expected without javascript enabled.
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
4.9
3.2
Journals
Land
Volume 10
Issue 12
share announcement

Land, Volume 10, Issue 12 (December 2021) – 128 articles

Cover Story (view full-size image): This 2015 image shows the role of a road and associated drainage ditch in accelerating ecosystem transition from healthy pond pine forest to ghost forest in response to sea level rise at the Alligator River National Wildlife Refuge in eastern North Carolina. Regionally, coastal ecosystem transition in response to sea-level rise is widespread, but our study shows that road networks and drainage systems accelerate the process due to enhanced inland propagation of flooding and salinity. Therefore, design of infrastructure in coastal forested landscapes must balance the need to protect human interests with the potential to alter hydrologic and salinity regimes in ways that compromise ecosystem function, currently manifested by the extensive formation of ghost forests along the US Atlantic and Gulf coastal plains, with significant implications for regional terrestrial C cycling and storage. View this paper.
  • Issues are regarded as officially published after their release is announced to the table of contents alert mailing list.
  • You may sign up for e-mail alerts to receive table of contents of newly released issues.
  • PDF is the official format for papers published in both, html and pdf forms. To view the papers in pdf format, click on the "PDF Full-text" link, and use the free Adobe Reader to open them.
Order results
Result details
Section
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
23 pages, 4889 KiB  
Article
Evaluation and Factor Analysis of Industrial Carbon Emission Efficiency Based on “Green-Technology Efficiency”—The Case of Yangtze River Basin, China
by Jingyi Wang, Kaisi Sun, Jiupai Ni and Deti Xie
Land 2021, 10(12), 1408; https://doi.org/10.3390/land10121408 - 20 Dec 2021
Cited by 23 | Viewed by 3352
Abstract
In the context of low-carbon development, effectively improving carbon emission efficiency is an inevitable requirement for achieving sustainable economic and social development. Based on panel data of 11 provinces and municipalities in the Yangtze River Basin (YRB), ranging from 2000 to 2019, this [...] Read more.
In the context of low-carbon development, effectively improving carbon emission efficiency is an inevitable requirement for achieving sustainable economic and social development. Based on panel data of 11 provinces and municipalities in the Yangtze River Basin (YRB), ranging from 2000 to 2019, this paper uses green-technology efficiency to measure industrial carbon emission efficiency via stochastic frontier analysis (SFA) incorporated with carbon productivity. This provides a comprehensive analytical framework for assessing the carbon emission efficiency, quantitatively measuring the reduction potential, and clarifying the incentive channels. The results are as follows: (1) The industrial carbon emission efficiency (ICEE) of YRB presents an increasing trend. Although differences in emission efficiency among provinces and municipalities are narrowing, their emission efficiency is still prominently imbalanced. (2) The potential for reducing industrial carbon emissions in this region shows an upward-to-downward trend. The decline in such potential of each province and municipality in recent years indicates that further reduction is becoming more difficult. (3) Effective means to improve ICEE are to improve the level of industrialization, promote technological innovation in industrial low-carbonization, and raise industrial productivity. Meanwhile, the significant spatial spillover effect of ICEE further emphasizes the necessity of strengthening the coordination of carbon reduction policies in YRB. The research in this paper adds a new perspective to the evaluation of ICEE and also provides reference and technical support for the government to enhance ICEE and formulate green and sustainable development policies. Full article
►▼ Show Figures

Figure 1

Figure 1
<p>Geographical location and socio-economic development of the research area.</p> Full article ">Figure 2
<p>Industrial structure of provinces and municipalities in YRB in 2019.</p> Full article ">Figure 3
<p>Industrial GDP per unit of CO2 for provinces and municipalities in YRB from 2000 to 2019.</p> Full article ">Figure 4
<p>Kernel density estimation of ICEE spanning 2000 to 2019.</p> Full article ">Figure 5
<p>Spatial dynamics of the ICEE in YRB.</p> Full article ">Figure 6
<p>Global Moran’s I and Z-value dynamics of the ICEE in YRB from 2000 to 2019.</p> Full article ">Figure 7
<p>Evolution of ICRP for provinces and municipalities in YRB from 2000 to 2019.</p> Full article ">Figure 8
<p>The scale of ICRP for provinces and municipalities in YRB in 2019.</p> Full article ">Figure 9
<p>Evolution of the ratio of ICRP for provinces and municipalities in YRB from 2000 to 2019.</p> Full article ">Figure 10
<p>The ratio of ICRP for provinces and municipalities in YRB in 2019.</p> Full article ">
15 pages, 5075 KiB  
Article
Hydrogeomorphology as a Tool in the Evolutionary Analysis of the Dynamic Landscape—Application to Larrodrigo, Salamanca, Spain
by Lorena Lombana, Antonio Martínez-Graña, Marco Criado and Carlos Palacios
Land 2021, 10(12), 1407; https://doi.org/10.3390/land10121407 - 20 Dec 2021
Viewed by 2386
Abstract
Evolutionary analysis of the fluvial landscape provides relevant inputs for the environmental management of a territory, in such a way that the understanding of the dynamics of fluvial spaces becomes a preponderant factor in the definition of protection and management strategies. Although the [...] Read more.
Evolutionary analysis of the fluvial landscape provides relevant inputs for the environmental management of a territory, in such a way that the understanding of the dynamics of fluvial spaces becomes a preponderant factor in the definition of protection and management strategies. Although the development of geographic information systems is a step forward in the study of the landscape, it is necessary to establish methodological frameworks that make remote sensing techniques available at multiple spatio-temporal scales, especially in basins with high levels of intervention. In the present study, we develop a methodology for the analysis of the fluvial landscape development in the last century of a highly modified water body, through the detailed study of hydrogeomorphic elements, using remote sensing techniques including high-density surface data (LiDAR) and historical aerial imageries; when supported by fieldwork, these allow for the identification of the sequence of sedimentation–erosion zones, differentiating in detail the zones denominated as areas of current erosion, accretion zones, and historical erosion zones. An application of the methodology was carried out in the Larrodrigo stream, located in Salamanca, Spain. Full article
(This article belongs to the Special Issue Landscape Planning as a Catalyst for Sustainable Development)
►▼ Show Figures

Figure 1

Figure 1
<p>Study area.</p> Full article ">Figure 2
<p>Diagrams of the generated raster models: (<b>A</b>) Discretized digital terrain model; (<b>B</b>) Reclassified slope raster; (<b>C</b>) Shaded raster; (<b>D</b>) Terrain orientation model.</p> Full article ">Figure 3
<p>Diagram of the geomorphic elements identified on the slope model: (<b>A</b>) Colluvium; (<b>B</b>) Alluvial cones; (<b>C</b>) Abandoned channel; (<b>D</b>) Current low-water channel.</p> Full article ">Figure 4
<p>Topographic evidence identified in the field: (<b>A</b>–<b>C</b>) Escarpments marking erosion margins; (<b>B</b>) Escarpment of a low terrace; (<b>D</b>) Low-water channel escarpment (erosion zone).</p> Full article ">Figure 5
<p>Reclassification of models: (<b>A</b>) Elevation reclassified; (<b>B</b>) Slopes reclassified; (<b>C</b>) Hypsometric curve.</p> Full article ">Figure 6
<p>Control points used in georeferencing: (<b>A</b>) American flight photo; (<b>B</b>) 2017 Orthophoto.</p> Full article ">Figure 7
<p>Geomorphological mapping of <a href="#sec2-land-10-01407" class="html-sec">Section 2</a> of the stream studied.</p> Full article ">Figure 8
<p>Stream classification scheme according to flow type: (<b>A</b>) Geomorphological mapping; (<b>B</b>) Categorized flows.</p> Full article ">Figure 9
<p>Diagram of fluvial dynamics analysis: (<b>A</b>).American flight photo; (<b>B</b>).Study sections; (<b>C</b>).Orto-photo 2017.</p> Full article ">Figure 10
<p>Comparison of the main channel, 1957–2017: (<b>A</b>) Mapping on orthophoto 2017; (<b>B</b>) Aerial photograph of the current low-water channel.</p> Full article ">
20 pages, 2751 KiB  
Article
Multi-Scale Features of Regional Poverty and the Impact of Geographic Capital: A Case Study of Yanbian Korean Autonomous Prefecture in Jilin Province, China
by Binyan Wang, Junfeng Tian, Peifeng Yang and Baojie He
Land 2021, 10(12), 1406; https://doi.org/10.3390/land10121406 - 20 Dec 2021
Cited by 9 | Viewed by 3556
Abstract
Poverty is a challenge worldwide. Policy and regulations guiding anti-poverty measures for governments, NGOs, and multilateral institutions have not considered the spatial scale effect of regional poverty, resulting in low-efficiency poverty alleviation actions. This study addressed research gaps by analyzing the multi-scale (county, [...] Read more.
Poverty is a challenge worldwide. Policy and regulations guiding anti-poverty measures for governments, NGOs, and multilateral institutions have not considered the spatial scale effect of regional poverty, resulting in low-efficiency poverty alleviation actions. This study addressed research gaps by analyzing the multi-scale (county, township, and village) features of regional poverty in Yanbian Korean Autonomous Prefecture in Jilin province, China. It examined the impact of geographic capital and associated spatial heterogeneity from four dimensions: natural environment, transport location, facilities accessibility, and socioeconomic development. The results identified that regional poverty varied at different scales: lower-scale poverty had higher levels of spatial differences, agglomeration, and spatial autocorrelation than higher-scale poverty, and the “island effect” was prominent. The factors potentially impacting regional poverty varied at different scales for geographical capital. At the township scale, only transport location and socioeconomic development dimensions could make significant differences. Factors in all four dimensions could affect village-scale poverty significantly, and the natural environment dimension was more effective than the other three dimensions. The impact of geographic capital and its spatial heterogeneity at the village scale varied, implying that local and diverse anti-poverty measures should increase. This study improves understanding of the multi-scale features of regional poverty and supports the formulation of effective anti-poverty measures. Full article
(This article belongs to the Topic Climate Change and Environmental Sustainability)
►▼ Show Figures

Figure 1

Figure 1
<p>Overview of the study area.</p> Full article ">Figure 2
<p>Theoretical framework of the impact of geographical capital on regional poverty.</p> Full article ">Figure 3
<p>Spatial distribution patterns of poverty in YKAP at different scales. (<b>a</b>) Poverty patterns at the township scale, (<b>b</b>) Poverty patterns at the village scale, (<b>c</b>) Kernel density at the village scale.</p> Full article ">Figure 4
<p>Results of the local spatial autocorrelation of poverty at the township scale. (<b>a</b>) Diagram of hot and cold spots, (<b>b</b>) LISA scatter plot, (<b>c</b>) LISA cluster map.</p> Full article ">Figure 5
<p>Results of the local spatial autocorrelation of poverty at the village scale. (<b>a</b>) Diagram of hot and cold spots, (<b>b</b>) LISA scatter plot, (<b>c</b>) LISA cluster map.</p> Full article ">Figure 6
<p>Spatial variation of the coefficient estimates of variables at the township scale. (<b>a</b>) DNNR, (<b>b</b>) DNPR, (<b>c</b>) PS, (<b>d</b>) UR.</p> Full article ">Figure 7
<p>Spatial variation of the coefficient estimates of variables at the village scale. (<b>a</b>) AA, (<b>b</b>) TR, (<b>c</b>) AS, (<b>d</b>) AR, (<b>e</b>) TTCC, (<b>f</b>) PS.</p> Full article ">
13 pages, 2013 KiB  
Article
The Impact of China’s Grassland Ecological Compensation Policy on the Income Gap between Herder Households? A Case Study from a Typical Pilot Area
by Zhidong Li, Didi Rao and Moucheng Liu
Land 2021, 10(12), 1405; https://doi.org/10.3390/land10121405 - 20 Dec 2021
Cited by 12 | Viewed by 3097
Abstract
China’s policy of subsidies and rewards for grassland ecological protection (PSRGEP) aims to maintain the ecological function of grasslands and increase the income of herder households. Since 2011, the Chinese government has invested more than 150 billion yuan in this policy, making it [...] Read more.
China’s policy of subsidies and rewards for grassland ecological protection (PSRGEP) aims to maintain the ecological function of grasslands and increase the income of herder households. Since 2011, the Chinese government has invested more than 150 billion yuan in this policy, making it currently the largest grassland ecological compensation project in China. Based on a survey of 203 herder households in Xin Barag Left Banner, Inner Mongolia Autonomous Region, this study used the Lorenz curve and Gini index to describe the imbalance in the distribution of compensation funds. Then, the integrated livelihood capital scores before compensation were used as a baseline. The changes in ranking and standard deviation of the scores after receiving compensation funds were analysed to draw a conclusion about the impact on the income gap between herder households. Finally, we described the absolute income gap through a group comparison. The results show that the distribution of compensation funds is unbalanced (Gini index is 0.46). According to the order of compensation funds from high to low, the top 20% of sample herder households received 49% of the total funds. Given the unbalanced distribution, households with better family economic conditions received more compensation funds. After receiving the compensation funds, the change in the ranking of the household’s livelihood capital integrated score was small, but the standard deviation increased from 0.1697 to 0.1734, and the Gini index of the households’ capital integrated scores decreased from 0.35 to 0.34 (the coefficient of variation decreased from 0.66 to 0.63). The group with the highest integrated livelihood capital score received 3.6 times the compensation funds of the group with the lowest score. As a result, under the promotion of PSRGEP, the local absolute income gap has widened, but the relative income gap has reduced. This study evaluated the current distribution of compensation funds for PSRGEP, which could provide a scientific basis for managers to optimize the fund distribution in the future. Full article
(This article belongs to the Special Issue Economic, Social and Demographic Challenges of Rural Areas: Contributions From the Analysis of the Economic Activity Location and the Study of Depopulation)
►▼ Show Figures

Figure 1

Figure 1
<p>Location of Xin Barag Left Banner.</p> Full article ">Figure 2
<p>Lorenz curve of compensation fund allocation.</p> Full article ">Figure 3
<p>(<b>a</b>) The trend in the relationship between herder households’ integrated livelihood capital and compensation amount; and (<b>b</b>) between herder households’ three major types of livelihood capital and compensation amount. (scores ∈ (0, 1], Compensation amounts ∈ (229, 215, 410)).</p> Full article ">Figure 4
<p>Changes in the ranking of integrated livelihood capital scores households before and after compensation.</p> Full article ">Figure 5
<p>(<b>a</b>) Group comparison of herder households’ compensation amount based on integrated livelihood capital. (<b>b</b>) Group comparison of herder households’ compensation amount based on physical capital. (<b>c</b>) Group comparison of herder households’ compensation amount based on financial capital. (<b>d</b>) Group comparison of herder households’ compensation amount based on natural capital.</p> Full article ">
16 pages, 946 KiB  
Article
Difference in Housing Finance Usage and Its Impact on Housing Wealth Inequality in Urban China
by Shan Yu and Can Cui
Land 2021, 10(12), 1404; https://doi.org/10.3390/land10121404 - 19 Dec 2021
Cited by 3 | Viewed by 3657
Abstract
With the increasing importance of financial loans in home purchases in urban China, the role of housing loans in the accumulation of housing wealth needs to be unraveled. Using the data from the 2017 China Household Finance Survey (CHFS), this study investigates the [...] Read more.
With the increasing importance of financial loans in home purchases in urban China, the role of housing loans in the accumulation of housing wealth needs to be unraveled. Using the data from the 2017 China Household Finance Survey (CHFS), this study investigates the use of housing loans and their impact on housing wealth inequality. It has been found that people with higher socioeconomic status and institutional advantages benefit more from housing provident fund loans and are more likely to fully invoke different financing channels to accumulate housing wealth. On the contrary, disadvantaged groups have to resort to costly market-based mortgages to finance their home purchases. This leads them to fall further behind in housing wealth accumulation. The spatial stratification of housing wealth accompanying the urban hierarchy was also observed and found to be closely linked to the type of housing loans. In this increasingly financialized era, relying on financial instruments in the process of household asset accumulation may further amplify the existing wealth inequality among social groups. Full article
(This article belongs to the Special Issue Reinvigorating Research on Housing Inequalities and Housing Price Mechanism Using Emerging Data and Technologies)
►▼ Show Figures

Figure 1

Figure 1
<p>The framework of generalized structural equation model.</p> Full article ">Figure 2
<p>Housing wealth across different groups.</p> Full article ">
27 pages, 1917 KiB  
Article
Comparative Study on Flora Characteristics and Species Diversity on Dam Slopes for Sustainable Ecological Management: Cases of Eight Dams in Korea
by Gwon-Soo Bahn, Sung-Yeol Kim and Jaeyong Choi
Land 2021, 10(12), 1403; https://doi.org/10.3390/land10121403 - 19 Dec 2021
Viewed by 3396
Abstract
Dams are gray infrastructure, providing various benefits such as flood control, water supply, and power generation. In order to create the next generation of infrastructure that explores how nature can act as infrastructure to meet development and ecological sustainability, artificial plantings have been [...] Read more.
Dams are gray infrastructure, providing various benefits such as flood control, water supply, and power generation. In order to create the next generation of infrastructure that explores how nature can act as infrastructure to meet development and ecological sustainability, artificial plantings have been attempted on dam slopes in Korea since 2000. As the planted trees are now stabilized to form a forest, it is time to study the floral characteristics and functions for effective ecological management and the safety of the dams. In this study, we investigated and analyzed flora in the slopes of eight dams in Korea. The comparative study of the whole flora in both the planted zones of the slopes of dams and left and right forests of dams revealed that the number of plant species was higher in the planted zones than in the left and right forests of the same size area. The plant family containing the greatest number of species in the slopes was Asteraceae, followed by Poaceae, Fabaceae, and Rosaceae. Currently, the community structures and families in the slopes of dams exhibit the characteristics of habitats in the initial stage of vegetation succession. Our investigation of planted species and immigration species in the slopes revealed that the latter comprised 89.9%. An average of 34.4% of species were interacting with the dam slope and the left and right forests. The species diversity index on dam slopes showed a tendency to be higher as the number of planted species increased and the period time increased. Average growth heights of planted trees were identified as 0.5–1.6 m for the shrubs layer, 3.5–4.5 m for the small trees layer, and 6.0–7.2 m for the trees layer. The heights of major trees, including Pinus densiflora, Quercus spp., Prunus sargentii, Styrax japonicus, and Cornus controversa, were similar to or higher than those of their counterparts in natural forests. As a result, dam slopes were similar to natural forests, having potential as habitats for various flora. To harmoniously maintain the ecological health and safety of water resource facilities of the slopes of dams, however, it is necessary to conduct periodic and various investigations on changes of the flora and growth of trees, and actively manage them. Full article
(This article belongs to the Special Issue Landscape Based Land Solutions and Big Data)
►▼ Show Figures

Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>The study area for the eight sampled dams in Korea with the planted and forest zones outlined in white using bird’s eye view (<b>left</b>) and satellite imagery (<b>right</b>). 1: Dam slope, 2: <b>left</b> slope, 3: <b>right</b> slope. Source: bird’s eye view, <a href="http://www.kwater.or.kr" target="_blank">http://www.kwater.or.kr</a> (accessed on 1 September 2020); satellite image, <a href="https://www.google.com/maps" target="_blank">https://www.google.com/maps</a> (accessed on 1 September 2020).</p> Full article ">Figure 2
<p>Research methods flowchart.</p> Full article ">Figure 3
<p>Number of vascular plants per dam.</p> Full article ">Figure 4
<p>Diagram of family diversity analysis.</p> Full article ">Figure 5
<p>Number of species and percentage of life-forms per dam. LF: left forest, DS: dam slope, RF: right forest.</p> Full article ">Figure 6
<p>Number of alien plants per dam. Arc: archaeophyte; IAP: invasive alien plant; PIP: potentially invasive plant.</p> Full article ">
11 pages, 1270 KiB  
Communication
Improving Best Management Practice Decisions in Mixed Land Use and/or Municipal Watersheds: Should Approaches Be Standardized?
by Jason A. Hubbart
Land 2021, 10(12), 1402; https://doi.org/10.3390/land10121402 - 18 Dec 2021
Cited by 6 | Viewed by 2901
Abstract
Best management practices (BMP) are defined in the United States Clean Water Act (CWA) as practices or measures that have been demonstrated to be successful in protecting a given water resource from nonpoint source pollution. Unfortunately, the greatest majority of BMPs remain unvalidated [...] Read more.
Best management practices (BMP) are defined in the United States Clean Water Act (CWA) as practices or measures that have been demonstrated to be successful in protecting a given water resource from nonpoint source pollution. Unfortunately, the greatest majority of BMPs remain unvalidated in terms of demonstrations of success. Further, there is not a broadly accepted or standardized process of BMP implementation and monitoring methods. Conceivably, if standardized BMP validations were a possibility, practices would be much more transferrable, comparable, and prescriptive. The purpose of this brief communication is to present a generalized yet integrated and customizable BMP decision-making process to encourage decision makers to more deliberately work towards the establishment of standardized approaches to BMP monitoring and validation in mixed-use and/or municipal watersheds. Decision-making processes and challenges to BMP implementation and monitoring are presented that should be considered to advance the practice(s) of BMP implementation. Acceptance of standard approaches may result in more organized and transferrable BMP implementation policies and increased confidence in the responsible use of taxpayer dollars through broad acceptance of methods that yield predictable and replicable results. Full article
(This article belongs to the Special Issue Land Use Change from Non-urban to Urban Areas: Problems, Challenges and Opportunities)
►▼ Show Figures

Figure 1

Figure 1
<p>Process for integrating necessary information to develop critical source area (CSA) assessments and prioritize best management practice (BMP) implementation. Simplified after [<a href="#B14-land-10-01402" class="html-bibr">14</a>].</p> Full article ">Figure 2
<p>Nested figures include idealized catchments with examples of (<b>A</b>,<b>B</b>) paired and nested EWSD with (<b>A</b>), control (left) and treatment (right) catchments, and monitoring during a calibration period, (<b>B</b>) control (left) and treatment (right) catchments, and monitoring after changes (arbitrary) in management practices (shaded area in B), modelled after [<a href="#B71-land-10-01402" class="html-bibr">71</a>], (<b>C</b>) the nested scale design, modelled after [<a href="#B4-land-10-01402" class="html-bibr">4</a>], and (<b>D</b>), the scale-nested and paired design, modelled after [<a href="#B72-land-10-01402" class="html-bibr">72</a>,<a href="#B74-land-10-01402" class="html-bibr">74</a>]. These can be considered in-situ designs as there may be land use practices occurring (pre-existing) before, during and after subsequent BMP implementation. Monitoring site locations shown are arbitrary and must be user-defined.</p> Full article ">Figure 3
<p>Example of a nine-step planning process to develop and implement plans that protect, conserve, and enhance natural resources within a social and economic construct, recreated from [<a href="#B79-land-10-01402" class="html-bibr">79</a>].</p> Full article ">
20 pages, 5661 KiB  
Article
Assessment of the Selected Regulating Ecosystem Services Using Ecosystem Services Matrix in Two Model Areas: Special Nature Reserve Obedska Bara (Serbia) and Protected Landscape Area Dunajske Luhy (Slovakia)
by Ivan Laco
Land 2021, 10(12), 1401; https://doi.org/10.3390/land10121401 - 18 Dec 2021
Cited by 4 | Viewed by 2515
Abstract
In this paper we are analyzing the potential of land cover features to provide three regulating ecosystem services (ESs), ES Local climate regulation, ES Water quality regulation and ES Biodiversity promotion, in two case study areas: Special nature reserve (SNR) Obedska bara (Serbia) [...] Read more.
In this paper we are analyzing the potential of land cover features to provide three regulating ecosystem services (ESs), ES Local climate regulation, ES Water quality regulation and ES Biodiversity promotion, in two case study areas: Special nature reserve (SNR) Obedska bara (Serbia) and Protected landscape area (PLA) Dunajske luhy (Slovakia). Regulating ESs are not only important for proper functioning of ecosystems, but they are also crucial for the existence of human society. To assess the potential of land cover features to provide regulating ESs, we used biophysical methods. The maps of land cover potential to provide regulating ES are the result of the analyses. The results indicate that forests are the most important ecosystems that provide ES Local climate regulation and ES Water quality regulation. For ES Biodiversity promotion, the most important ecosystems were natural and seminatural meadows, wetlands, natural and seminatural rivers and water bodies as well as forests. Overall SNR Obedska bara has higher potential to provide all three regulating ESs than PLA Dunajske luhy. These findings point to the importance of natural areas in ensuring the provision of regulating ESs. Properly selected landscape management is the key for maintaining or improving the potential of land cover features to provide regulating ESs. The research can help local authorities in decision making and in creating conservation strategies for selected protected areas. Full article
(This article belongs to the Special Issue Integrated Approach to Land Use Change Assessment)
►▼ Show Figures

Figure 1

Figure 1
<p>Case study area SNR Obedska bara.</p> Full article ">Figure 2
<p>Case study area PLA Dunajske luhy.</p> Full article ">Figure 3
<p>Comparison of the potential of case study areas to provide ES Local climate regulation.</p> Full article ">Figure 4
<p>The potential of land cover features in case study areas to provide ES Local climate regulation.</p> Full article ">Figure 5
<p>Comparison of the potential of case study areas to provide ES Water quality regulation.</p> Full article ">Figure 6
<p>The potential of land cover features in case study areas to provide ES Water quality regulation.</p> Full article ">Figure 7
<p>Comparison of the potential of case study areas to provide ES Biodiversity promotion.</p> Full article ">Figure 8
<p>The potential of land cover features in case study areas to provide ES Biodiversity promotion.</p> Full article ">
23 pages, 1886 KiB  
Article
The Influence of Subjective and Objective Characteristics of Urban Human Settlements on Residents’ Life Satisfaction in China
by Xueming Li and He Liu
Land 2021, 10(12), 1400; https://doi.org/10.3390/land10121400 - 18 Dec 2021
Cited by 18 | Viewed by 3878
Abstract
Under the guidance of people-oriented development concepts, improving residents’ life satisfaction has gradually become the goal of urban governance. Based on Chinese household tracking survey data and national socio-economic statistics, this study used the entropy method, multi-layer linear regression model and geographically weighted [...] Read more.
Under the guidance of people-oriented development concepts, improving residents’ life satisfaction has gradually become the goal of urban governance. Based on Chinese household tracking survey data and national socio-economic statistics, this study used the entropy method, multi-layer linear regression model and geographically weighted regression model and discusses the spatial heterogeneity of the impact of objective environmental characteristics and subjective perceived characteristics of urban residential environments on residents’ life satisfaction. It is of great importance to study the mechanisms through which subjective and objective characteristics of urban human settlements influence living satisfaction among residents. It is also important to discuss how to improve living satisfaction levels through the urban human settlements and to realize high-quality urban development. The research results show that in 2018, the overall level of life satisfaction among Chinese urban residents was relatively high. However, it is still necessary to continue to optimize the urban human settlements to improve residents’ life satisfaction. The objective characteristics of the urban human settlements, such as natural environmental comfort and environmental health, have a significant positive impact on residents’ life satisfaction. Residents’ subjective perceptions of government integrity, environmental protection, wealth gap, social security, medical conditions and medical level, as well as residents’ individual gender, age and health status also have a significant impact on residents’ life satisfaction. The direction and intensity of effects of different elements of the urban human settlements and residents’ personal attributes on urban residents’ life satisfaction have different characteristics in different regions. Full article
(This article belongs to the Special Issue Quality of Urban Space versus Quality of Urban Life)
►▼ Show Figures

Figure 1

Figure 1
<p>Study area.</p> Full article ">Figure 2
<p>Connotation of the objective characteristics of the urban living environment.</p> Full article ">Figure 3
<p>Campbell’s Model.</p> Full article ">Figure 4
<p>Life satisfaction distribution of Chinese residents.</p> Full article ">Figure 5
<p>Spatial distribution of the regression coefficients estimated for significant variables.</p> Full article ">
27 pages, 3988 KiB  
Article
Conserving Working Rangelands: A Social–Ecological Case Study from Northeastern Colorado
by Jasmine E. Bruno, Stephen J. Leisz, Jake S. Bobula and María E. Fernández-Giménez
Land 2021, 10(12), 1399; https://doi.org/10.3390/land10121399 - 17 Dec 2021
Cited by 2 | Viewed by 2937
Abstract
Land changes in rangeland systems cascade through interconnected social and ecological spheres, affecting both humans and the environment. This study applied a multi-method approach to examine the causes and consequences of change in two rangeland communities in northeastern (NE) Colorado. First, this study [...] Read more.
Land changes in rangeland systems cascade through interconnected social and ecological spheres, affecting both humans and the environment. This study applied a multi-method approach to examine the causes and consequences of change in two rangeland communities in northeastern (NE) Colorado. First, this study used a Random Forest supervised classifier to analyze 36 years of land-cover data and create a land-cover/use change classification model. Second, the research team analyzed transcripts of interviews with 32 ranchers, examining how ranchers’ adaptive strategies influence land-cover change trends. Lastly, the analysis integrated the quantitative and qualitative data, constructing a social–ecological rangeland change conceptual model. This study found that the cultivated area decreased in both study sites from 1984–2019, with 16.0% and 18.7% of each site transitioning out of the cultivated area. Moreover, 10.3% and 18.4% of each site, respectively, transitioned to herbaceous/grassland cover from 1984–2019. The qualitative analysis identified the role of conservation policies, such as open space programs, on land change. Also, despite the relatively small area that transitioned to developed cover—1.83% and 0.183% of each site—participants emphasized that the associated demographic and cultural shifts drive land-use change. This study highlights that while rangelands are undergoing social–ecological change, land-use decisions and land conservation programs can help mitigate the global trend of declining rangeland and grassland cover. Full article
►▼ Show Figures

Figure 1

Figure 1
<p>A land change conceptual model in which the interaction between change factors—underlying and direct—and ranchers’ adaptive strategies influence land-cover/use change (and vice versa) (adapted from Hersperger et al.’s [<a href="#B30-land-10-01399" class="html-bibr">30</a>]).</p> Full article ">Figure 2
<p>The two adjacent study sites, one centered in northeastern (NE) Larimer County and the other in northcentral (NC) Weld County, Colorado [<a href="#B33-land-10-01399" class="html-bibr">33</a>]. Randomly positioned points fall within the area of the interviews, and the circles indicate the area analyzed for land-cover, 922,505 acres (1441 square miles) and 847,548 acres (1324 square miles) in the NE Larimer and NC Weld County sites, respectively.</p> Full article ">Figure 3
<p>The multi-method research process to examine social–ecological land change in northeastern Colorado.</p> Full article ">Figure 4
<p>(<b>a</b>,<b>b</b>). Three-year medians of the proportions (%) of the total land area of cover classes—cultivated (i.e., planted vegetation), developed (i.e., human-constructed materials), herbaceous (i.e., grasslands), and shrubland (i.e., shrubs)—graphed along with critical events in northeastern Colorado in the (<b>a</b>) northeastern Larimer County, Colorado study site (922,505 acres) and the (<b>b</b>) northcentral Weld County, Colorado study site (847,548 acres) [<a href="#B62-land-10-01399" class="html-bibr">62</a>] from 1984–2019.</p> Full article ">Figure 5
<p>The map illustrates the transition of cultivated, herbaceous, other (wetlands, water, barren, forest), and shrubland to the developed land-use class from 1985<sub>M</sub> (3-year median of 1984–1986) and 2018<sub>M</sub> in the northeastern Larimer County, Colorado study site. The stacked bar graph depicts the acres transitioned from 1985<sub>M</sub>–2018<sub>M</sub>.</p> Full article ">Figure 6
<p>The map illustrates the transition from the cultivated land-use class to developed, herbaceous, other (wetlands, water, barren, forest), and shrubland classes between 1985<sub>M</sub> (3-year median of 1984–1986) and 2018<sub>M</sub> in the northeastern Larimer County, Colorado study site. The stacked bar graph depicts the acres that transitioned from 1985<sub>M</sub>–2018<sub>M</sub>.</p> Full article ">Figure 7
<p>The map illustrates the transition from the cultivated land-use class to developed, herbaceous, other (wetlands, water, barren, forest), and shrubland classes between 1985<sub>M</sub> (3-year median of 1984–1986) and 2018<sub>M</sub> in the northcentral Weld County, Colorado study site. The stacked bar graph depicts the acres transitioned from 1985<sub>M</sub>–2018<sub>M</sub>.</p> Full article ">Figure 8
<p>Social–ecological rangeland change model. The model captures how forces of change—underlying and direct forces of change in dark and light blue, respectively—and ranchers’ adaptive strategies around land-use (depicted in orange) (outlined in detail in Bruno et al. [<a href="#B32-land-10-01399" class="html-bibr">32</a>]) interact to affect land-cover/use change (depicted in gray) in northeastern Colorado. The dashed arrows indicate ranchers’ limited influence on the land change outcomes.</p> Full article ">
23 pages, 4946 KiB  
Article
A Geospatial Approach to Measure Social Benefits in Urban Land Use Optimization Problem
by Md. Mostafizur Rahman and György Szabó
Land 2021, 10(12), 1398; https://doi.org/10.3390/land10121398 - 17 Dec 2021
Cited by 10 | Viewed by 3358
Abstract
Different conflicting objectives are used in urban land use optimization problems. The maximization of social benefit is one of the important objectives in urban land use optimization problems. Many researchers have used different methods to measure social benefits in land use optimization. Studies [...] Read more.
Different conflicting objectives are used in urban land use optimization problems. The maximization of social benefit is one of the important objectives in urban land use optimization problems. Many researchers have used different methods to measure social benefits in land use optimization. Studies show that there is no established method to measure social benefit in the urban land use allocation game. Against this background, this study aims to (a) identify the appropriate indicators as a measure of social benefit, and (b) propose a composite index to measure social benefit in urban land use optimization problems. Based on the literature review and expert opinion, this study identifies four indicators as a measure of social benefit. These are spatial compactness, land use compatibility, land use mix, and evenness of population distribution. Using the weighted sum approach, this study proposes a composite social benefit index (SBI) to measure social benefit in urban land use allocation/optimization problems and planning. The study suggests that spatial compactness is the most influential indicator to the SBI, but the most critical indicator is compatibility, whose 11.60% value reduction from 0.5 alters the decision of choice. Finally, the proposed method was applied in Rajshahi city in Bangladesh. The result suggests the potential of using SBI in the land use allocation problem. It is expected that the proposed social benefit index (SBI) will help the land use optimization and planning and will be helpful for decision makers. Full article
(This article belongs to the Special Issue Land: 10th Anniversary)
►▼ Show Figures

Figure 1

Figure 1
<p>(<b>a</b>) Location Rajshahi district with respect to Bangladesh; (<b>b</b>) location of study area with respect to Rajshahi district; (<b>c</b>) administrative boundary of study area.</p> Full article ">Figure 2
<p>Hypothetical land use (<b>left</b>) and population (<b>right</b>) data used in this study.</p> Full article ">Figure 3
<p>Spatial distribution of different land use types in this study area.</p> Full article ">Figure 4
<p>Land use distribution in a typical 3 × 3 cell zone.</p> Full article ">Figure 5
<p>Index value of four indicators derived from the hypothetical dataset. (<b>a</b>) Spatial compactness; (<b>b</b>) land use compatibility; (<b>c</b>) land use entropy; and (<b>d</b>) evenness.</p> Full article ">Figure 6
<p>Value of SBI of each cell for the hypothetical dataset.</p> Full article ">Figure 7
<p>Sensitivity of SBI with respect to (<b>a</b>) compatibility, (<b>b</b>) compactness, (<b>c</b>) land use mix, and (<b>d</b>) evenness of population distribution.</p> Full article ">Figure 8
<p>Level of social benefit in the study area using proposed SBI.</p> Full article ">
10 pages, 1302 KiB  
Article
Comparison of Compaction Alleviation Methods on Soil Health and Greenhouse Gas Emissions
by Jennifer Bussell, Felicity Crotty and Chris Stoate
Land 2021, 10(12), 1397; https://doi.org/10.3390/land10121397 - 17 Dec 2021
Cited by 6 | Viewed by 3290
Abstract
Soil compaction can occur due to trafficking by heavy equipment and be exacerbated by unfavourable conditions such as wet weather. Compaction can restrict crop growth and increase waterlogging, which can increase the production of the greenhouse gas nitrous oxide. Cultivation can be used [...] Read more.
Soil compaction can occur due to trafficking by heavy equipment and be exacerbated by unfavourable conditions such as wet weather. Compaction can restrict crop growth and increase waterlogging, which can increase the production of the greenhouse gas nitrous oxide. Cultivation can be used to alleviate compaction, but this can have negative impacts on earthworm abundance and increase the production of the greenhouse gas carbon dioxide. In this study, a field was purposefully compacted using trafficking, then in a replicated plot experiment, ploughing, low disturbance subsoiling and the application of a mycorrhizal inoculant were compared as methods of compaction alleviation, over two years of cropping. These methods were compared in terms of bulk density, penetration resistance, crop yield, greenhouse gas emissions and earthworm abundance. Ploughing alleviated topsoil compaction, as measured by bulk density and penetrometer resistance, and increased the crop biomass in one year of the study, although no yield differences were seen. Earthworm abundance was reduced in both years in the cultivated plots, and carbon dioxide flux increased significantly, although this was not significant in summer months. Outside of the summer months, nitrous oxide production increased in the non-cultivated treatments, which was attributed to increased denitrifying activity under compacted conditions. Full article
(This article belongs to the Special Issue Soil Improving Cropping Systems for Sustainable and Profitable Farming in Europe)
►▼ Show Figures

Figure 1

Figure 1
<p>Penetration resistance (kPa) measured 0–45 cm depth through the soil profile. Graph shows average ± SE of all readings taken across the two years of measurements.</p> Full article ">Figure 2
<p>Soil bulk density (g cm<sup>−3</sup>) measured in the topsoil 0–10 cm in 2018. Bars show mean ± SE. Letters denote significant differences at <span class="html-italic">p</span> &lt; 0.05.</p> Full article ">Figure 3
<p>Barley crop (<span class="html-italic">Hordeum vulgare</span>) plant biomass measured in May 2018. Bars show mean ± SE. Letters denote significant differences at <span class="html-italic">p</span> &lt; 0.05.</p> Full article ">Figure 4
<p>Average earthworm number (per m<sup>2</sup>) measured in 2018 and 2019, to a depth of 25 cm. Bars show mean ± SE. Letters denote significant differences between cultivation treatments for both years at <span class="html-italic">p</span> &lt; 0.05.</p> Full article ">Figure 5
<p>CO<sub>2</sub> flux measured monthly during 2018–2019 cropping and averaged over summer (June, July, August) and winter (all other months). Bars show mean ± SE. Letters denote significant differences between winter treatments at <span class="html-italic">p</span> &lt; 0.05.</p> Full article ">Figure 6
<p>N<sub>2</sub>O flux measured monthly during 2018–2019 cropping and averaged over summer (June, July, August) and winter (all other months). N<sub>2</sub>O flux is displayed as CO<sub>2</sub> equivalent by 298. Bars show mean ± SE. Letters denote significant differences at <span class="html-italic">p</span> &lt; 0.05.</p> Full article ">
9 pages, 231 KiB  
Article
Who Started, Stopped, and Continued Participating in Outdoor Recreation during the COVID-19 Pandemic in the United States? Results from a National Panel Study
by B. Derrick Taff, William L. Rice, Ben Lawhon and Peter Newman
Land 2021, 10(12), 1396; https://doi.org/10.3390/land10121396 - 17 Dec 2021
Cited by 48 | Viewed by 11824
Abstract
The COVID-19 pandemic has been proposed as a catalyst for many U.S. residents to re-engage in outdoor recreation or engage in outdoor recreation for the first time. This manuscript describes the results of a representative U.S. national panel study aimed at better understanding [...] Read more.
The COVID-19 pandemic has been proposed as a catalyst for many U.S. residents to re-engage in outdoor recreation or engage in outdoor recreation for the first time. This manuscript describes the results of a representative U.S. national panel study aimed at better understanding the socio-demographic profile (gender, ethnicity, community type, income, and age) of those participants new to outdoor recreation since the start of the COVID-19 pandemic. In doing so, we address how these new outdoor recreationists differ from (1) those who frequently participated in outdoor recreation prior to the pandemic and continue to participate in outdoor recreation, (2) those who did not frequently participate in outdoor recreation prior to the pandemic and remain un-engaged, and (3) those who frequently participated in outdoor recreation prior to the pandemic but stopped their frequent participation following the onset of the pandemic. Results from this U.S. national study suggest that 35.8% of respondents indicated that they did not participate regularly in outdoor recreation prior to the pandemic or during the pandemic, 30.4% indicated that they did participate regularly in outdoor recreation prior to the pandemic and continued to do so regularly during the pandemic, and 13.5% indicated that they did participate regularly in outdoor recreation prior to the pandemic, but did not continue to do so during the pandemic. More than 20% of the sample indicated that they were new outdoor recreationists. The majority of respondents in all categories, including those that were new to outdoor recreation amidst the pandemic, identified as being white, however these new outdoor recreationists were also the least ethnically diverse. The previously but no longer outdoor recreationist respondents were significantly more ethnically diverse than the other three groups, and they tended to live in more urbanized settings. Discussion of these results includes implications for outdoor recreation managers, and researchers who seek to better understand who the COVID-19 pandemic has influenced with regard to outdoor recreation participation. Implications regarding social justice, access and equity to public places that facilitate outdoor recreation, and health-related policies are discussed. Full article
(This article belongs to the Special Issue Effects of the COVID-19 Pandemic on the Use and Perception of Urban Green Space)
20 pages, 3718 KiB  
Article
Safeguarding Intangible Cultural Heritage: The Amazonian Kichwa People
by Claudia Patricia Maldonado-Erazo, Nancy P. Tierra-Tierra, María de la Cruz del Río-Rama and José Álvarez-García
Land 2021, 10(12), 1395; https://doi.org/10.3390/land10121395 - 17 Dec 2021
Cited by 9 | Viewed by 4563
Abstract
Indigenous communities express their concern about the weakening and low appreciation of their millenary and ancestral manifestations and knowledge, due to society’s accelerated globalization. This fact has caused intergenerational transmission to be minimal, resulting in a gradual cultural erosion and loss of collective [...] Read more.
Indigenous communities express their concern about the weakening and low appreciation of their millenary and ancestral manifestations and knowledge, due to society’s accelerated globalization. This fact has caused intergenerational transmission to be minimal, resulting in a gradual cultural erosion and loss of collective memory of human groups. The purpose of this study is to safeguard of the Intangible Cultural Heritage (ICH) of the Amazonian Kichwa nationality through identification and records of cultural manifestations. The analysis corresponds to a descriptive process of all the information collected, which was built from the development of multiple processes of cultural revitalization that correspond to in-depth interviews with community leaders and participatory workshops with all members of the community. During the process, an increase in the exchange of knowledge was observed, in addition to constant cultural insurgency in which the peoples maintain themselves in order to safeguard their cultures. Full article
(This article belongs to the Special Issue Use of Natural and Cultural Resources through Tourism Activity for Regional Development)
►▼ Show Figures

Figure 1

Figure 1
<p>Ecuador Political Map.</p> Full article ">Figure 2
<p>Political organization by levels.</p> Full article ">Figure 3
<p>Organization of space and time. Source: Calapucha, [<a href="#B40-land-10-01395" class="html-bibr">40</a>] (p. 226).</p> Full article ">Figure 4
<p>Organization of all time-spaces. Source: Calapucha, [<a href="#B34-land-10-01395" class="html-bibr">34</a>] (p. 226).</p> Full article ">
26 pages, 1846 KiB  
Article
Determinants of the Land Registration Information System Operational Success: Empirical Evidence from Ethiopia
by Shewakena Aytenfisu Abab, Feyera Senbeta Wakjira and Tamirat Tefera Negash
Land 2021, 10(12), 1394; https://doi.org/10.3390/land10121394 - 16 Dec 2021
Cited by 9 | Viewed by 6055
Abstract
Ethiopia has embarked on one of the largest digitalization programs for rural land registration in Africa. The program is called the national rural land administration information system (NRLAIS). Over the past couple of years, NRLAIS was rolled-out and made operational in over 180 [...] Read more.
Ethiopia has embarked on one of the largest digitalization programs for rural land registration in Africa. The program is called the national rural land administration information system (NRLAIS). Over the past couple of years, NRLAIS was rolled-out and made operational in over 180 woredas (districts). There is, however, limited empirical evidence on whether and to what extent NRLAIS has been successful. This study explores the factors that influence the acceptance and actual use of NRLAIS to gauge its operational success in Ethiopia. Data were collected both from primary and secondary sources using surveys, key informant interviews, and a literature review. Survey data were collected from 201 staff of 50 woreda land administration offices in three regional states (Amhara, Oromia, and SNNP) and analyzed using a structural equation model. The results revealed that system quality, information quality, service quality, and perceived usefulness of NRLAIS have positively and significantly influenced the acceptance and actual use of the system. However, perceived ease of use has an insignificant influence. The predictive relevance of the research model is significant and indicates substantial operational success of NRLAIS. The quick acceptance and use of NRLAIS will likely improve service delivery, promote data integration, and strengthen informed decision-making. The study recommends strengthening behavioral changes of the land administration experts through two enhanced service quality measures—technical and operational capacity to a robust and sustainable digitalization. Policymakers could leverage operational success to upgrade the NRLAIS into a unified national land registration information system that bridges the urban–rural land governance divide. Full article
(This article belongs to the Special Issue Land Perspectives: People, Tenure, Planning, Tools, Space, and Health)
►▼ Show Figures

Figure 1

Figure 1
<p>Research model with latent variables and hypotheses construct adapted from information system success model and technology acceptance model.</p> Full article ">Figure 2
<p>Study Site Map. Data Source: Ministry of Agriculture, November 2021.</p> Full article ">Figure 3
<p>Sex and age distribution of respondents.</p> Full article ">Figure 4
<p>Experience of the respondents’ actual usage of the NRLAIS in their daily official business discharge.</p> Full article ">Figure 5
<p>Time spent to process land transaction management and service delivery using NRLAIS.</p> Full article ">Figure 6
<p>Users’ specific assigned role of respondents.</p> Full article ">Figure 7
<p>Measurement and structure equation model results of the research model.</p> Full article ">
19 pages, 2577 KiB  
Article
The Alien Plants That Threaten South Africa’s Mountain Ecosystems
by Kim Canavan, Susan Canavan, Vincent Ralph Clark, Onalenna Gwate, David Mark Richardson, Guy Frederick Sutton and Grant Douglas Martin
Land 2021, 10(12), 1393; https://doi.org/10.3390/land10121393 - 16 Dec 2021
Cited by 9 | Viewed by 4933
Abstract
The six major mountain ranges in South Africa support critically important ecosystem services—notably water production—and are rich in biodiversity and endemism. These mountains are threatened by detrimental land uses, unsustainable use of natural resources, climate change, and invasive alien plants. Invasive alien plants [...] Read more.
The six major mountain ranges in South Africa support critically important ecosystem services—notably water production—and are rich in biodiversity and endemism. These mountains are threatened by detrimental land uses, unsustainable use of natural resources, climate change, and invasive alien plants. Invasive alien plants pose substantial and rapidly increasing problems in mountainous areas worldwide. However, little is known about the extent of plant invasions in the mountains of South Africa. This study assessed the status of alien plants in South African mountains by determining sampling efforts, species compositions and abundances across the six ranges in lower-and higher-elevation areas. Species occurrence records were obtained from three databases that used various approaches (roadside surveys, citizen science observations, focused botanical surveys). Most mountain ranges were found to be undersampled, and species composition assessments were only possible for two ranges. The majority of abundant alien plants in both the lower- and higher-elevation areas were species with broad ecological tolerances and characterised by long distance seed dispersal. These prevalent species were mostly woody plants—particularly tree species in the genera Acacia, Pinus, and Prosopis—that are contributing to the trend of woody plant encroachment across South African mountains. We suggest improved mountain-specific surveys to create a database which could be used to develop management strategies appropriate for each mountain range. Full article
(This article belongs to the Special Issue Mountains under Pressure)
►▼ Show Figures

Figure 1

Figure 1
<p>The top five most abundant alien plants recorded in each range in South Africa using SAPIA, iNaturalist and Great Escarpment Data (GED) databases. The high-elevation areas represent the upper 20th percentile elevational area in each range from the highest point recorded in the databases. The maximum elevation (highest peak) and high-elevation delineation for each range was—WGE: 1719 m, 1469 m; TC: 1868 m, 1528 m; EGE: 3446 m, 1651 m; SGE: 1784 m, 1451 m; CGM: 1605 m, 1355 m and CFM: 2064 m, 1667m. The lower elevational area reflect the entire mountain range below the designated high-elevation area. Figure created using BioRender (<a href="https://biorender.com/" target="_blank">https://biorender.com/</a>, accessed on 10 October 2021).</p> Full article ">Figure 2
<p>The six major mountain ranges in South Africa (adapted from Canavan et al. [<a href="#B13-land-10-01393" class="html-bibr">13</a>]), showing sampling effort across the six mountain ranges. The occurrence points for each alien plant record for all three databases is shown: SAPIA—the Southern African Plant Invaders Atlas, iNat—iNaturalist and the GED—the Great Escarpment Data.</p> Full article ">Figure 3
<p>(<b>A</b>). The elevational gradient (metres) across the mountains of South Africa. (<b>B</b>). The vegetation types within South African mountains: EGE—438; TC—30; CGM—7; SGE—17; WGE—36, CFM—139 vegetation types according to Rutherford et al. [<a href="#B32-land-10-01393" class="html-bibr">32</a>] (see <a href="#app1-land-10-01393" class="html-app">Table S2 and Figure S1</a> for vegetation type information).</p> Full article ">Figure 4
<p>The native range distributions of the alien plants present within the six mountain ranges of South Africa (<a href="#app1-land-10-01393" class="html-app">Table S3</a>).</p> Full article ">Figure 5
<p>Species accumulation curves showing the number of records over time and the cumulative number of unique species recorded for iNaturalist and SAPIA databases for each mountain range across South Africa.</p> Full article ">Figure 6
<p>(<b>A</b>) The number of unique species recorded in each plant family across the three databases—Great Escarpment Data (GED), iNaturalist (iNat), South African Plant Invaders Atlas (SAPIA) (see <a href="#app1-land-10-01393" class="html-app">Table S4</a> for all species recorded). Families are ordered by highest species richness from left to right. (<b>B</b>) Species accumulation curves showing the number of records over time and the cumulative number of unique species recorded for the GED, iNat and SAPIA. All records for each database are within the geographical range of the GED surveys (see <a href="#land-10-01393-f003" class="html-fig">Figure 3</a> for geographical area).</p> Full article ">
15 pages, 1114 KiB  
Article
Biochar Enriched with Buffalo Slurry Improved Soil Nitrogen and Carbon Dynamics, Nutrient Uptake and Growth Attributes of Wheat by Reducing Leaching Losses of Nutrients
by Hafiz Muhammad Rashad Javeed, Mazhar Ali, Imtiaz Ahmed, Xiukang Wang, Ibrahim Al-Ashkar, Rafi Qamar, Abdullah Ibrahim, Muhammad Habib-Ur-Rahman, Allah Ditta and Ayman EL Sabagh
Land 2021, 10(12), 1392; https://doi.org/10.3390/land10121392 - 16 Dec 2021
Cited by 12 | Viewed by 3229
Abstract
The present investigation was conducted to understand the role of enriched biochar on soil nitrogen and carbon dynamics, leaching losses of nutrients, and growth attributes of wheat. Buffalo slurry (BS) was used to enrich the biochar for 24 h and 2% biochar (SB) [...] Read more.
The present investigation was conducted to understand the role of enriched biochar on soil nitrogen and carbon dynamics, leaching losses of nutrients, and growth attributes of wheat. Buffalo slurry (BS) was used to enrich the biochar for 24 h and 2% biochar (SB) or enriched biochar (SEB) was used. Enrichment of biochar with BS as SEB improved the C and N contents of biochar by 33–310% and 41–286% respectively. The application of biochar (SB) and enriched biochar (SEB) reduced the net nitrification by 81% and 94%, ammonification by 48% and 74%, and carbon dioxide by 50% and 92% respectively as compared to control. The leaching losses minerals i.e., C (by 30%), N (by 125%), P (by 50%), K (by 82%), Na (by 9%), Ca (by 24%), and Mg (by 12%) was decreased in SEB treatments compared to control. The soil enzyme activities, microbial biomass (MBC and MBN), wheat agronomy, soil bulk density and soil pore density, mineral uptake from the soil, and mineral contents in the plant body were improved in the SEB as compared to SB and control treatments. Our results revealed that the biochar enrichment process could improve the C and N storage in the soil reservoir and lower the environmental risks to soil and water. Full article
(This article belongs to the Special Issue Biochar-Complemented Compost: Production, Characterization, and Application)
►▼ Show Figures

Figure 1

Figure 1
<p>Influence of biochar amendments on soil ammonium and nitrate (KCl extractable). The measurement of NH<sub>4</sub> and NO<sub>3</sub> was done on days 1, 5, 10, 20, 28, 35, 42, 49, 60, and was statistically different at a 5% probability level. The abbreviations of treatment are S, soil; SF, soil + feedstock; SB, soil + 2% biochar; SEB, soil + 2% enriched biochar (n = 4).</p> Full article ">Figure 2
<p>The influence of biochar amendments on net ammonification (NH<sub>4</sub>-N), net nitrification (NO<sub>3</sub>-N), and net mineralization was measured by following the method of Robertson et al. [<a href="#B17-land-10-01392" class="html-bibr">17</a>]. The different letters on the bars are indicated the significant difference among the treatments at 5% probability levels. The abbreviations of treatment are S, soil; SF, soil + feedstock; SB, soil + 2% biochar; SEB, soil + 2% enriched biochar (n = 4).</p> Full article ">Figure 3
<p>Influence of biochar amendments on CO<sub>2</sub> flux. The measurement of NH<sub>4</sub> and NO<sub>3</sub> was done on days 1, 5, 10, 20, 28, 35, 42, 49, 60, and was statistically different at a 5% probability level. The abbreviations of treatment are S, soil; SF, soil + feedstock; SB, soil + 2% biochar; SEB, soil + 2% enriched biochar (n = 4).</p> Full article ">Figure 4
<p>Influence of biochar amendments on apparent nitrogen recovery (ANR; %) and phosphorus use efficiency (PU; %). Values shows mean ± SD (n = 4). Bars sharing the same letters are statistically at par with each other at the significance level of 5% (<span class="html-italic">p</span> ≤ 0.05). The abbreviations of treatment are S, soil; SF, soil + feedstock; SB, soil + 2% biochar; SEB, soil + 2% enriched biochar (n = 4).</p> Full article ">
21 pages, 845 KiB  
Article
The Assessment of Density Bonus in Building Renovation Interventions. The Case of the City of Florence in Italy
by Fabrizio Battisti and Orazio Campo
Land 2021, 10(12), 1391; https://doi.org/10.3390/land10121391 - 15 Dec 2021
Cited by 9 | Viewed by 2918 | Correction
Abstract
The European Green Deal indicates the renovation of both public and private buildings as a key element for the improvement of energy efficiency in the building stock, in order to reach the goals of the document itself. New incentives, also including density bonus, [...] Read more.
The European Green Deal indicates the renovation of both public and private buildings as a key element for the improvement of energy efficiency in the building stock, in order to reach the goals of the document itself. New incentives, also including density bonus, can significantly contribute to foster diffuse actions. In Italy, the density bonus is under testing: the current framework has produced profitability for regeneration in some areas and unprofitability in others. This has led to a non-diffuse renewal, widening differences in richness and quality throughout territories subjected to the same reward measure. A territory is characterized by a high degree of typological and qualitative fragmentation and dissimilarity. Thus, the aim of the present work is the construction of a model that allows for identifying the entity of the reward measure in terms of density bonus. Density bonus can determine the feasibility of renovation interventions—in economic-financial terms and in relation to urban impact—taking into account the characteristics of the context (or micro-context) where they are performed. The research model is based on a Balance Sheet Model and is applied to the city of Florence. The model suggests an innovative approach where urban, landscape and environmental impacts produced by the density bonus are evaluated according to the economic amount needed for their mitigation. The expected results in the application of the model consist in the definition of an iso-bonus map organized by areas. Full article
(This article belongs to the Special Issue Land Management in Territorial Planning: Analysis, Appraisal, Strategies for Sustainability Ⅱ)
►▼ Show Figures

Figure 1

Figure 1
<p>Geo-references of results.</p> Full article ">
19 pages, 3165 KiB  
Article
Identification of Regional Drought Processes in North China Using MCI Analysis
by Xiuhua Cai, Wenqian Zhang, Xiaoyi Fang, Qiang Zhang, Cunjie Zhang, Dong Chen, Chen Cheng, Wenjie Fan and Ying Yu
Land 2021, 10(12), 1390; https://doi.org/10.3390/land10121390 - 15 Dec 2021
Cited by 9 | Viewed by 4424
Abstract
Comprehensive identification of drought events is of great significance for monitoring and evaluating drought processes. Based on the date of daily precipitation, temperature and drought-affected area of 403 meteorological stations in North China from 1960 to 2019, the Comprehensive Drought Process Intensity Index [...] Read more.
Comprehensive identification of drought events is of great significance for monitoring and evaluating drought processes. Based on the date of daily precipitation, temperature and drought-affected area of 403 meteorological stations in North China from 1960 to 2019, the Comprehensive Drought Process Intensity Index (CDPII) has been developed by using the Meteorological-drought Composite Index (MCI) and regional drought process identification method, as well as the EIDR theory method. The regional drought processes in the past 60 years in North China, including Beijing, Tianjin, Hebei, Shanxi and Middle Inner Mongolia, were analyzed and identified. The result shows that the distribution characteristic of droughts with different intensities is as follows: The number of days of all annual-average mild droughts, moderate droughts and severe droughts was highest in Tianjin and that of extreme droughts was highest in Shanxi. The number of days of mild droughts was highest in May and lowest in January. The number of days of moderate droughts was highest in June. The number of days with mild and moderate drought showed an overall increasing trend, while the number of days with severe drought and above showed an overall decreasing trend (through a 95% significance test). The number of drought days was the highest in the 1990s. The annual frequency of drought is between 66.7% and 86.7%; the drought frequency in Hebei is the highest at 86.7%, followed by Beijing at 80%. There were 75 regional drought processes in North China from 1960 to 2019, and the correlation coefficient between process intensity and the drought-affected area was 0.55, which passed the 99% significance test. The comprehensive intensity of drought process from 27 April to 1 September 1972 was the strongest. From 18 May to 31 October 1965, the drought lasted 167 days. The overall drought intensity had a slight weakening trend in the past 60 years. A total of 75 regional drought processes occurred in North China, and the process intensity showed a trend of wavy decline with a determination coefficient (R2) of 0.079 (95% significance test). Overall, the regional drought process identification method and strength assessment result tally with the drought disaster, which can better identify the regional drought process. Furthermore, including the last days, the average intensity, average scope comprehensive strength, there are many angles to monitor and evaluate the drought and drought process. These provide a reference for drought control and decision-making. Full article
►▼ Show Figures

Figure 1

Figure 1
<p>Land use distribution (<b>a</b>) and meteorological station distribution (<b>b</b>) in North China in 2020.</p> Full article ">Figure 2
<p>Variation of annual average precipitation (<b>a</b>) and average temperature (<b>b</b>) in North China from 1960 to 2019.</p> Full article ">Figure 3
<p>Flow chart for calculating the drought index and the intensity of the drought process.</p> Full article ">Figure 4
<p>Spatial distribution of the days of mild drought (<b>a</b>), moderate drought (<b>b</b>), heavy drought (<b>c</b>) and extreme drought (<b>d</b>) in North China from 1960 to 2019.</p> Full article ">Figure 5
<p>Characteristics of monthly changes from mild drought (<b>a</b>), moderate drought (<b>b</b>), heavy drought (<b>c</b>) and extreme drought (<b>d</b>) in North China from 1960 to 2019.</p> Full article ">Figure 6
<p>Interannual variation and linear trend from mild drought to extreme drought in North China (<b>a</b>), Beijing (<b>b</b>), Tianjin (<b>c</b>), Hebei (<b>d</b>), Shanxi (<b>e</b>) and Inner Mongolia (<b>f</b>) from 1960 to 2019.</p> Full article ">Figure 7
<p>Frequency distribution of regional drought processes in North China from 1960 to 2019.</p> Full article ">Figure 8
<p>Variation of duration (<b>a</b>), comprehensive intensity (<b>b</b>) of regional drought processes in North China from 1960 to 2019.</p> Full article ">Figure 9
<p>Variations of average annual drought process intensity and annual drought disaster area in North China from 1971 to 2019.</p> Full article ">
27 pages, 4988 KiB  
Article
Prediction of Crop Yield for New Mexico Based on Climate and Remote Sensing Data for the 1920–2019 Period
by Kamini Yadav and Hatim M. E. Geli
Land 2021, 10(12), 1389; https://doi.org/10.3390/land10121389 - 15 Dec 2021
Cited by 9 | Viewed by 3918
Abstract
Agricultural production systems in New Mexico (NM) are under increased pressure due to climate change, drought, increased temperature, and variable precipitation, which can affect crop yields, feeds, and livestock grazing. Developing more sustainable production systems requires long-term measurements and assessment of climate change [...] Read more.
Agricultural production systems in New Mexico (NM) are under increased pressure due to climate change, drought, increased temperature, and variable precipitation, which can affect crop yields, feeds, and livestock grazing. Developing more sustainable production systems requires long-term measurements and assessment of climate change impacts on yields, especially over such a vulnerable region. Providing accurate yield predictions plays a key role in addressing a critical sustainability gap. The goal of this study is the development of effective crop yield predictions to allow for a better-informed cropland management and future production potential, and to develop climate-smart adaptation strategies for increased food security. The objectives were to (1) identify the most important climate variables that significantly influence and can be used to effectively predict yield, (2) evaluate the advantage of using remotely sensed data alone and in combination with climate variables for yield prediction, and (3) determine the significance of using short compared to long historical data records for yield prediction. This study focused on yield prediction for corn, sorghum, alfalfa, and wheat using climate and remotely sensed data for the 1920–2019 period. The results indicated that the use of normalized difference vegetation index (NDVI) alone is less accurate in predicting crop yields. The combination of climate and NDVI variables provided better predictions compared to the use of NDVI only to predict wheat, sorghum, and corn yields. However, the use of a climate only model performed better in predicting alfalfa yield. Yield predictions can be more accurate with the use of shorter data periods that are based on region-specific trends. The identification of the most important climate variables and accurate yield prediction pertaining to New Mexico’s agricultural systems can aid the state in developing climate change mitigation and adaptation strategies to enhance the sustainability of these systems. Full article
(This article belongs to the Special Issue Advances in Remote Sensing for Crop Monitoring and Yield Estimation)
►▼ Show Figures

Figure 1

Figure 1
<p>The map of New Mexico counties in the United States, including the share of harvested areas in acres for sorghum, wheat, alfalfa, and corn within the total harvested cropland areas in 2017 [<a href="#B54-land-10-01389" class="html-bibr">54</a>].</p> Full article ">Figure 2
<p>Historical climate variables (annual precipitation (P), annual water year precipitation (P<sub>wy</sub>), average min (T<sub>min</sub>), max (T<sub>max</sub>), and mean (T<sub>mean</sub>) temperature) from 1920 to 2019 [<a href="#B55-land-10-01389" class="html-bibr">55</a>].</p> Full article ">Figure 3
<p>Historical crop yields of corn, wheat, sorghum, and alfalfa from 1920 to 2019 (USDA-NASS).</p> Full article ">Figure 4
<p>Correlation analysis of (<b>a</b>) climate variables and (<b>b</b>) NDVI with crop yields for corn, alfalfa, sorghum, and wheat. The highlighted large size markers represent the high correlation coefficient of climate variables with crop yield (<b>a</b>) and monthly NDVI with crop yield (<b>b</b>).</p> Full article ">Figure 5
<p>A summary of the correlation matrix for all 13 variables initially evaluated to predict (<b>a</b>) corn, (<b>b</b>) sorghum, (<b>c</b>) wheat, and (<b>d</b>) alfalfa yields. The matrices show the values of the Pearson’s correlation coefficient (R) with the direction and strength of correlation between all climate variables, with the positive values in blue, negative in red, −0.25 to 0.25 in light shades of color. The correlation coefficients range from −1 to 1, whereby −1 means a perfect negative linear relationship between climate variables, 1 indicates a perfect positive linear relationship between variables, and 0 indicates that there is no relationship between climate variables. Color intensity is proportional to correlation coefficients. The variables on the top of each matrix were ordered using the first principal component (PC1) from high to low scores, indicated from left to right. For example, in panel c for wheat, T<sub>min</sub> had the highest score, while P<sub>wy</sub> had the lowest score in PC1.</p> Full article ">Figure 6
<p>The comparison of observed corn, sorghum, wheat, and alfalfa yields with their respective predicted yields resulting from the best models using 100 years and segmented data period scales.</p> Full article ">Figure 6 Cont.
<p>The comparison of observed corn, sorghum, wheat, and alfalfa yields with their respective predicted yields resulting from the best models using 100 years and segmented data period scales.</p> Full article ">Figure 7
<p>The scatter plot of observed and predicted corn, sorghum, wheat, and alfalfa yields resulting from the best models in segmented time scales.</p> Full article ">Figure 8
<p>The scatter plot of observed and predicted corn, sorghum, wheat, and alfalfa yields resulting from the best models in long data period from 1920 to 2019.</p> Full article ">Figure 9
<p>The comparison of observed and predicted corn, sorghum, and wheat yields resulting from best climate only and climate and NDVI models from 1984 to 2016.</p> Full article ">Figure 10
<p>The scatter plot of observed and predicted corn, sorghum, and wheat yields resulting from the best climate only, climate and NDVI, and NDVI only models (1984 to 2016).</p> Full article ">
16 pages, 44826 KiB  
Article
The Effects of a Megafire on Ecosystem Services and the Pace of Landscape Recovery
by Diana Mancilla-Ruiz, Francisco de la Barrera, Sergio González and Ana Huaico
Land 2021, 10(12), 1388; https://doi.org/10.3390/land10121388 - 15 Dec 2021
Cited by 4 | Viewed by 4425
Abstract
(1) Background: Megafires have affected several regions in the world (e.g., Australia, California), including, in 2017, the central and south-central zones of Chile. These areas represent real laboratories to monitor the impacts on the sustainability of landscapes and their recovery after fires. The [...] Read more.
(1) Background: Megafires have affected several regions in the world (e.g., Australia, California), including, in 2017, the central and south-central zones of Chile. These areas represent real laboratories to monitor the impacts on the sustainability of landscapes and their recovery after fires. The present research examines the modification of dynamics and the provision of ecosystem services by a megafire in a Mediterranean landscape in central Chile, combining remote sensing technologies and ecosystem service assessments. (2) Methods: Land cover and spectral indices (NBRI, BAIS-2, NDVI, and EVI) were measured using Sentinel-2 imagery, while the provision of ecosystem services was evaluated using an expert-based matrix. (3) Results: The megafire affected forest plantations, formerly the dominant land cover, as well as other ecosystems, e.g., native forests. After five years, the landscape is dominated by exotic shrublands and grasslands. (4) Conclusions: The megafire caused a loss of 50% of the landscape’s capacity to supply ecosystem services. Given that native forests are the best provider of ecosystem services in this landscape, restoration is a key to recovering landscape sustainability. Full article
►▼ Show Figures

Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Empedrado watershed located in the core of the Empedrado municipality (Maule Region).</p> Full article ">Figure 2
<p>Matrix or integrated table for ecosystem service valuation including formulas. This matrix includes the area of each ecosystem in each year studied, the assessment of the capacity to provide ecosystem services, and estimated values for the provision of each ecosystem service, and a combination of all ecosystem services. Based on Echeverría et al., 2018.</p> Full article ">Figure 3
<p>Fire severity index ΔNBRI (spatialized) and its main changes after the 2017 megafire.</p> Full article ">Figure 4
<p>Vegetation vigor calculated using (<b>a</b>) NDVI and (<b>b</b>) EVI indices, both spatialized, and its main changes before and after the 2017 megafire by season.</p> Full article ">Figure 5
<p>Annual average and S.D. values for NBRI and BAIS-2, and monthly averages for NDVI. The months without data had cloud cover greater than 20%.</p> Full article ">Figure 6
<p>Land cover as structure of the landscape between years 2016 and 2021.</p> Full article ">Figure 7
<p>Dominant vegetation after the megafire: (<b>a</b>) regrowth of <span class="html-italic">Pinus radiata</span>, (<b>b</b>) <span class="html-italic">Teline monspessulana</span>.</p> Full article ">Figure 8
<p>The matrix or integrated table with the evaluation of the provision of ecosystem services in the study area. IL (irrigated land), WB (water bodies), GR (grasslands) IS (impervious surface), SH (shrublands), NF (native forest), FP (forest plantations), HB (high-intensity burned areas), LB (low-intensity burned areas), LV (land with little or no vegetation).</p> Full article ">Figure 9
<p>Variation in the provision of ecosystem services pre- and post-fire in an ordinal range from 0 to 5, where 0 means zero capacity and 5 is the highest capacity for the provision of ecosystem services.</p> Full article ">Figure 10
<p>Map of the potential provision of all ecosystem services, provisioning services, regulation services, cultural services, and services most demanded by the population of the Maule Region.</p> Full article ">
25 pages, 11216 KiB  
Article
Sub-Watershed Parameter Transplantation Method for Non-Point Source Pollution Estimation in Complex Underlying Surface Environment
by Xuekai Chen, Guojian He, Xiaobo Liu, Bogen Li, Wenqi Peng, Fei Dong, Aiping Huang, Weijie Wang and Qiuyue Lian
Land 2021, 10(12), 1387; https://doi.org/10.3390/land10121387 - 14 Dec 2021
Cited by 7 | Viewed by 2762
Abstract
The prevention and control of non-point source pollution is an important link in managing basin water quality and is an important factor governing the environmental protection of watershed water in China over the next few decades. The control of non-point source pollution relies [...] Read more.
The prevention and control of non-point source pollution is an important link in managing basin water quality and is an important factor governing the environmental protection of watershed water in China over the next few decades. The control of non-point source pollution relies on the recognition of the amount, location, and influencing factors. The watershed nonpoint source pollution mechanism model is an effective method to address the issue. However, due to the complexity and randomness of non-point source pollution, both the development and application of the watershed water environment model have always focused on the accuracy and rationality of model parameters. In this pursuit, the present study envisaged the temporal and spatial heterogeneity of non-point source pollution caused by the complex underlying surface conditions of the watershed, and the insufficient coverage of hydrological and water quality monitoring stations. A refined watershed non-point source pollution simulation method, combining the Monte Carlo analytic hierarchy process (MCAHP) and the sub-watershed parameter transplantation method (SWPT), was established on the basis of the migration and transformation theory of the non-point source pollution, considering the index selection, watershed division, sub-watershed simulation, and parameter migration. Taking the Erhai Lake, a typical plateau lake in China, as the representative research object, the MCAHP method effectively reduced the uncertainty of the weights of the watershed division indexes compared to the traditional AHP method. Furthermore, compared to the traditional all watershed parameter simulation (AWPS) approach, the simulation accuracy was improved by 40% using the SWPT method, which is important for the prevention and control of non-point source pollution in large-scale watersheds with significant differences in climatic and topographic conditions. Based on the simulation results, the key factors affecting the load of the non-point source pollution in the Erhai watershed were identified. The results showed that the agricultural land in Erhai Lake contributed a majority of the load for several reasons, including the application of nitro phosphor complex fertilizer. Among the different soil types, paddy soil was responsible for the largest pollution load of total nitrogen and total phosphorus discharge into the lake. The zones with slopes of 0–18° were found to be the appropriate area for farming. Our study presents technical methods for the assessment, prevention, and control of non-point source pollution load in complex watersheds. Full article
(This article belongs to the Special Issue Understanding Watershed Connectivity in a Changing Planet)
►▼ Show Figures

Figure 1

Figure 1
<p>Elevation (<b>a</b>), precipitation (<b>b</b>), slope (<b>c</b>), vegetation coverage (<b>d</b>), and sub-watershed (<b>e</b>) of the Lake Erhai watershed.</p> Full article ">Figure 2
<p>Study framework.</p> Full article ">Figure 3
<p><span class="html-italic">CR</span> calculation results of MCAHP.</p> Full article ">Figure 4
<p>Determination of weight of dividing index: Probability density distribution of index weight (<b>a</b>), 95% confidence intervals for index weights (<b>b</b>).</p> Full article ">Figure 5
<p>Watershed division and selection of sub-watersheds. Basin division of the Erhai Lake (<b>a</b>), the watershed upstream of the LC station of the MJ (<b>b</b>), YX, BS, and MC watershed in the west region (<b>c</b>), BL watershed in the south region (<b>d</b>), and YL watershed in the east region (<b>e</b>).</p> Full article ">Figure 6
<p>Calibration and validation of runoff, nitrate, and TP in typical sub-watersheds.</p> Full article ">Figure 6 Cont.
<p>Calibration and validation of runoff, nitrate, and TP in typical sub-watersheds.</p> Full article ">Figure 7
<p>Comparison between simulated and observed values of lake inflow and pollution load in Lake Erhai watershed.</p> Full article ">Figure 8
<p>Rationality analysis of SWPT: YX watershed (<b>a</b>) and BL watershed (<b>b</b>).</p> Full article ">Figure 9
<p>Pollution load intensity of different land use types in Lake Erhai watershed.</p> Full article ">Figure 10
<p>Pollution load intensity of different soil types in Lake Erhai watershed.</p> Full article ">Figure 11
<p>TN (<b>a</b>) and TP (<b>b</b>) pollution load intensity of different slope in Lake Erhai watershed.</p> Full article ">Figure 12
<p>The distribution characteristics of the pollution load intensities of the same land use types with different slopes: TN for farmland (<b>a</b>), forest (<b>c</b>) and grassland (<b>e</b>), TP for farmland (<b>b</b>), forest (<b>d</b>) and grassland (<b>f</b>).</p> Full article ">Figure 12 Cont.
<p>The distribution characteristics of the pollution load intensities of the same land use types with different slopes: TN for farmland (<b>a</b>), forest (<b>c</b>) and grassland (<b>e</b>), TP for farmland (<b>b</b>), forest (<b>d</b>) and grassland (<b>f</b>).</p> Full article ">Figure 13
<p>Intensity of TN (<b>a</b>) and TP (<b>b</b>) pollution load at different elevations in Lake Erhai watershed.</p> Full article ">Figure 14
<p>Variation characteristics of pollution load intensity at different elevations under a single land use type: TN for farmland (<b>a</b>), forest (<b>c</b>) and grassland (<b>e</b>), TP for farmland (<b>b</b>), forest (<b>d</b>) and grassland (<b>f</b>).</p> Full article ">
30 pages, 2725 KiB  
Review
A Framework for Reviewing Silvopastoralism: A New Zealand Hill Country Case Study
by Thomas H. Mackay-Smith, Lucy Burkitt, Janet Reid, Ignacio F. López and Chris Phillips
Land 2021, 10(12), 1386; https://doi.org/10.3390/land10121386 - 14 Dec 2021
Cited by 13 | Viewed by 4342 | Correction
Abstract
Silvopastoral systems can be innovative solutions to agricultural environmental degradation, especially in hilly and mountainous regions. A framework that expresses the holistic nature of silvopastoral systems is required so research directions can be unbiased and informed. This paper presents a novel framework that [...] Read more.
Silvopastoral systems can be innovative solutions to agricultural environmental degradation, especially in hilly and mountainous regions. A framework that expresses the holistic nature of silvopastoral systems is required so research directions can be unbiased and informed. This paper presents a novel framework that relates the full range of known silvopastoral outcomes to bio-physical tree attributes, and uses it to generate research priorities for a New Zealand hill country case study. Current research is reviewed and compared for poplar (Populus spp.), the most commonly planted silvopastoral tree in New Zealand hill country, and kānuka (Kunzea spp.), a novel and potentially promising native alternative. The framework highlights the many potential benefits of kānuka, many of which are underappreciated hill country silvopastoral outcomes, and draws attention to the specific outcome research gaps for poplar, despite their widespread use. The framework provides a formalised tool for reviewing and generating research priorities for silvopastoral trees, and provides a clear example of how it can be used to inform research directions in silvopastoral systems, globally. Full article
(This article belongs to the Special Issue Mountains under Pressure)
►▼ Show Figures

Figure 1

Figure 1
<p>A framework of the interactions within a silvopastoral system between tree attributes and silvopastoral outcomes.</p> Full article ">Figure 2
<p>A typical North Island New Zealand hill country landscape 25 km north east of Dannevirke, in the Manawatū-Whanganui region. Willows can be seen space-planted in pastures at the bottom of the slope directly beneath the photographer. The photograph was taken by the lead author.</p> Full article ">Figure 3
<p>A high-density mānuka-kānuka shrubland study site for the leaf fall study by Lambie and Dando [<a href="#B75-land-10-01386" class="html-bibr">75</a>] (pp. 612).</p> Full article ">
21 pages, 4330 KiB  
Article
Collective and Social Representations on Nature and Environment: Social Psychology Investigation in Rural Areas
by Iulian Dincă, Dragoș Dărăbăneanu and Ionuț Mihai Oprea
Land 2021, 10(12), 1385; https://doi.org/10.3390/land10121385 - 14 Dec 2021
Cited by 2 | Viewed by 3934
Abstract
This is a qualitative research based on a phenomenological perspective of understanding, that aim to captures the way in which the population of rural areas from the western part of Romania understands the terms of nature and environment. Starting from valuable scientific studies [...] Read more.
This is a qualitative research based on a phenomenological perspective of understanding, that aim to captures the way in which the population of rural areas from the western part of Romania understands the terms of nature and environment. Starting from valuable scientific studies related to the relationship between man and nature, we propose an original interdisciplinary approach that combines social methodology with a geographical, ecological and land use perspective. This study aims to identify the forms in which social representations about nature and environment are outlined on the level of rural areas people perceptions. As Romania is a European Union member state, its rural areas have seen transformations and changes in detail that reflect in the environmental-geographical ambience typical of the three main relief types (mountains, hills and plains), the mixed geomorphological type, its residents’ basic aspirations and conscious attitudinal and behavioral levels. The two study benchmarks are the notions of nature and environment, raising perception sensitivities and everyday concerns belonging to the residents of the rural areas surveyed. The administrative unit of Bihor County, belonging to the northern half of the Crișana Province and comprised of rural communities in 97 villages, was selected as the study’s target area. These villages were selected in such a way that they had to meet the requirements of balance and diversity of local environmental conditions, land use and the result of changing their land cover and the socio-geodemographic conditions of the population. A series of 1576 questionnaires were administered to subjects who are over 18 years old and are aware of the reality of their places. The results of the applied tests (Levene’s test) show that the concrete factors of daily activities are very good predictors of the relationship between man and nature. Full article
►▼ Show Figures

Figure 1

Figure 1
<p>Geographical placement of villages on relief types where the surveyed subjects live. Inset, the position of the studied villages within Romania.</p> Full article ">Figure 2
<p>Diagram of the research stages.</p> Full article ">Figure 3
<p>Social and collective representation of nature in the case of Bihor County residents.</p> Full article ">Figure 4
<p>Representing nature as “a place around us” but also as a “place of harmony” between purely natural and anthropic elements: (<b>a</b>) Village of Săucani; (<b>b</b>) Village of Finiş; (<b>c</b>) Village of Meziad; (<b>d</b>) Village of Paleu.</p> Full article ">Figure 5
<p>People’s perception of the term of environment.</p> Full article ">Figure 6
<p>Exemplifying various types of environment in the studied area by showing the pervasive outlook and also the environment as a provider of human and animal life favorable conditions: (<b>a</b>) plains in the village of Mădăras; (<b>b</b>) mixed hills-plains in the village of Răbăgani; (<b>c</b>) mixed hills-mountains in the village of Meziad; (<b>d</b>) mountain plateau in the village of Șinteu.</p> Full article ">
18 pages, 14982 KiB  
Article
Crop Intensity Mapping Using Dynamic Time Warping and Machine Learning from Multi-Temporal PlanetScope Data
by Raihan Rafif, Sandiaga Swahyu Kusuma, Siti Saringatin, Giara Iman Nanda, Pramaditya Wicaksono and Sanjiwana Arjasakusuma
Land 2021, 10(12), 1384; https://doi.org/10.3390/land10121384 - 14 Dec 2021
Cited by 13 | Viewed by 3577
Abstract
Crop intensity information describes the productivity and the sustainability of agricultural land. This information can be used to determine which agricultural lands should be prioritized for intensification or protection. Time-series data from remote sensing can be used to derive the crop intensity information; [...] Read more.
Crop intensity information describes the productivity and the sustainability of agricultural land. This information can be used to determine which agricultural lands should be prioritized for intensification or protection. Time-series data from remote sensing can be used to derive the crop intensity information; however, this application is limited when using medium to coarse resolution data. This study aims to use 3.7 m-PlanetScope™ Dove constellation data, which provides daily observations, to map crop intensity information for agricultural land in Magelang District, Indonesia. Two-stage histogram matching, before and after the monthly median composites, is used to normalize the PlanetScope data and to generate monthly data to map crop intensity information. Several methods including Time-Weighted Dynamic Time Warping (TWDTW) and the machine-learning algorithms: Random Forest (RF), Extremely Randomized Trees (ET), and Extreme Gradient Boosting (XGB) are employed in this study, and the results are validated using field survey data. Our results show that XGB generated the highest overall accuracy (OA) (95 ± 4%), followed by RF (92 ± 5%), ET (87 ± 6%), and TWDTW (81 ± 8%), for mapping four-classes of cropping intensity, with the near-infrared (NIR) band being the most important variable for identifying cropping intensity. This study demonstrates the potential of PlanetScope data for the production of cropping intensity maps at detailed resolutions. Full article
(This article belongs to the Special Issue Advances in Remote Sensing for Crop Monitoring and Yield Estimation)
►▼ Show Figures

Figure 1

Figure 1
<p>Study area observed in this research, the red polygon represents the paddy fields derived from another study by Kusuma, et al. [<a href="#B22-land-10-01384" class="html-bibr">22</a>].</p> Full article ">Figure 2
<p>The workflow of the method used.</p> Full article ">Figure 3
<p>K-means clustering in the study area used to define the fieldwork campaign.</p> Full article ">Figure 4
<p>Training samples distribution map. The yellow polygons represent the paddy fields; this information was derived from a study by Kusuma et al. [<a href="#B22-land-10-01384" class="html-bibr">22</a>].</p> Full article ">Figure 5
<p>Distribution map of validation samples. The yellow polygons represent paddy fields, and were derived from a study by Kusuma, Arjasakusuma, Rafif, Saringatin, Wicaksono, and Aziz [<a href="#B24-land-10-01384" class="html-bibr">24</a>].</p> Full article ">Figure 6
<p>The samples of time-series values from unchanged objects using median composite before the second histogram matching (<b>a</b>,<b>c</b>,<b>e</b>), and after the second histogram matching (<b>b</b>,<b>d</b>,<b>f</b>).</p> Full article ">Figure 6 Cont.
<p>The samples of time-series values from unchanged objects using median composite before the second histogram matching (<b>a</b>,<b>c</b>,<b>e</b>), and after the second histogram matching (<b>b</b>,<b>d</b>,<b>f</b>).</p> Full article ">Figure 7
<p>The average reflectance temporal patterns from different cropping intensities identified in the study areas. (<b>a</b>) Average Reflectance in Blue Band; (<b>b</b>) Average Reflectance in Green Band; (<b>c</b>) Average Reflectance in Green Band; (<b>d</b>) Average Reflectance in NIR Band.</p> Full article ">Figure 7 Cont.
<p>The average reflectance temporal patterns from different cropping intensities identified in the study areas. (<b>a</b>) Average Reflectance in Blue Band; (<b>b</b>) Average Reflectance in Green Band; (<b>c</b>) Average Reflectance in Green Band; (<b>d</b>) Average Reflectance in NIR Band.</p> Full article ">Figure 8
<p>The classification results using tested algorithms in this study, for instance, (<b>a</b>) TWDTW, (<b>b</b>) XGB, (<b>c</b>) RF, and (<b>d</b>) ET.</p> Full article ">Figure 8 Cont.
<p>The classification results using tested algorithms in this study, for instance, (<b>a</b>) TWDTW, (<b>b</b>) XGB, (<b>c</b>) RF, and (<b>d</b>) ET.</p> Full article ">Figure 9
<p>The identified important variables (top 15) in the machine learning models of (<b>a</b>) ET, (<b>b</b>) RF, and (<b>c</b>) XGB.</p> Full article ">Figure 9 Cont.
<p>The identified important variables (top 15) in the machine learning models of (<b>a</b>) ET, (<b>b</b>) RF, and (<b>c</b>) XGB.</p> Full article ">
12 pages, 9330 KiB  
Article
Estimation of the Rational Range of Ecological Compensation to Address Land Degradation in the Poverty Belt around Beijing and Tianjin, China
by Haiming Yan, Wei Li, Huicai Yang, Xiaonan Guo, Xingran Liu and Wenru Jia
Land 2021, 10(12), 1383; https://doi.org/10.3390/land10121383 - 14 Dec 2021
Cited by 6 | Viewed by 2494
Abstract
Ecological compensation provides innovative ecological solutions for addressing land degradation and guaranteeing the sustainable provision of essential ecosystem services. This study estimated the ecosystem service value and the opportunity cost of land use in the Poverty Belt of China—around Beijing and Tianjin—from 1980 [...] Read more.
Ecological compensation provides innovative ecological solutions for addressing land degradation and guaranteeing the sustainable provision of essential ecosystem services. This study estimated the ecosystem service value and the opportunity cost of land use in the Poverty Belt of China—around Beijing and Tianjin—from 1980 to 2015 on the small watershed scale, and thereafter estimated the rational range of ecological compensation in this ecologically fragile zone. Results showed that the total ecosystem service value in the study area gradually decreased from CNY 54.198 billion in 1980 to CNY 53.912 billion in 2015. Moreover, the annual total ecological compensation of the whole study area ranged between CNY 2.67 billion and 2.83 billion. More specifically, areas with higher ecological compensation standards are mainly concentrated in the northwestern and northern parts of the study area, with a lower economic development level, while areas with lower ecological compensation standards are mainly located in areas with a relatively high level of economic development, e.g., the southern and southeastern parts of the study area. These results can provide valuable decision-support information for the design and optimization of ecological compensation to address land degradation along with rapid urbanization in the Beijing–Tianjin–Hebei region. Full article
(This article belongs to the Special Issue Advances in Characterizing and Addressing Land Degradation and Associated Ecosystem Responses)
►▼ Show Figures

Figure 1

Figure 1
<p>Location of the Poverty Belt around Beijing and Tianjin.</p> Full article ">Figure 2
<p>The total ecosystem service value in the Poverty Belt around Beijing and Tianjin from 1980 to 2015 (unit: CNY 100 million).</p> Full article ">Figure 3
<p>Ecological compensation standards based on the (<b>a</b>) ecosystem service value and (<b>b</b>) opportunity cost in the study area.</p> Full article ">Figure 4
<p>The total ecological compensation value based on the (<b>a</b>) ecosystem service value and (<b>b</b>) opportunity cost on the small watershed scale in the study area (unit: CNY 10,000).</p> Full article ">Figure 5
<p>Ecological compensation priority levels in the Poverty Belt around Beijing and Tianjin.</p> Full article ">
24 pages, 5031 KiB  
Article
Impacts of Future Sea-Level Rise under Global Warming Assessed from Tide Gauge Records: A Case Study of the East Coast Economic Region of Peninsular Malaysia
by Milad Bagheri, Zelina Z. Ibrahim, Mohd Fadzil Akhir, Bahareh Oryani, Shahabaldin Rezania, Isabelle D. Wolf, Amin Beiranvand Pour and Wan Izatul Asma Wan Talaat
Land 2021, 10(12), 1382; https://doi.org/10.3390/land10121382 - 14 Dec 2021
Cited by 10 | Viewed by 5287
Abstract
The effects of global warming are putting the world’s coasts at risk. Coastal planners need relatively accurate projections of the rate of sea-level rise and its possible consequences, such as extreme sea-level changes, flooding, and coastal erosion. The east coast of Peninsular Malaysia [...] Read more.
The effects of global warming are putting the world’s coasts at risk. Coastal planners need relatively accurate projections of the rate of sea-level rise and its possible consequences, such as extreme sea-level changes, flooding, and coastal erosion. The east coast of Peninsular Malaysia is vulnerable to sea-level change. The purpose of this study is to present an Artificial Neural Network (ANN) model to analyse sea-level change based on observed data of tide gauge, rainfall, sea level pressure, sea surface temperature, and wind. A Feed-forward Neural Network (FNN) approach was used on observed data from 1991 to 2012 to simulate and predict the sea level change until 2020 from five tide gauge stations in Kuala Terengganu along the East Coast of Malaysia. From 1991 to 2020, predictions estimate that sea level would increase at a pace of roughly 4.60 mm/year on average, with a rate of 2.05 ± 7.16 mm on the East Coast of Peninsular Malaysia. This study shows that Peninsular Malaysia’s East Coast is vulnerable to sea-level rise, particularly at Kula Terengganu, Terengganu state, with a rate of 1.38 ± 7.59 mm/year, and Tanjung Gelang, Pahang state, with a rate of 1.87 ± 7.33 mm/year. As a result, strategies and planning for long-term adaptation are needed to control potential consequences. Our research provides crucial information for decision-makers seeking to protect coastal cities from the risks of rising sea levels. Full article
(This article belongs to the Special Issue Time Series Analysis by Focusing on Climate-Land Interactions Variables)
►▼ Show Figures

Figure 1

Figure 1
<p>Schematic of a tide gauge measurement system and locations and details of stations based in Terengganu, along the East Coast of Peninsular Malaysia. Source: the pictures from <a href="https://www.sutron.com/product/tide-stations/" target="_blank">https://www.sutron.com/product/tide-stations/</a>, accessed on 1 December 2021, and <a href="https://www.unavco.org/instrumentation/geophysical/tide-gauges/tide-gauges.html" target="_blank">https://www.unavco.org/instrumentation/geophysical/tide-gauges/tide-gauges.html</a>, accessed on 1 December 2021.</p> Full article ">Figure 2
<p>Tidal stations were selected for this study of sea-level rise in Terengganu, along the East Coast of Malaysia.</p> Full article ">Figure 3
<p>FNN framework for tide gauge analysis.</p> Full article ">Figure 4
<p>(<b>a</b>) Monthly tidal gauge data from five tide gauge stations between 1991 and (<b>b</b>) From 1991 to 2012, sea level residuals at five tide gauge stations along Peninsular Malaysia’s East Coast.</p> Full article ">Figure 5
<p>Sea-level residuals compared between the lowest and highest El Niño and La Niño year, 1985 to 2012, of Cendering station: +a High Sea Level Residual (HSLR); −a Low Sea Level Residual (LSLR); +b High Sea Level Pressure (HSLP); −b Low Sea Level Pressure (LSLP); +c High Sea Surface Temperature (HSST), and −c Low Sea Surface Temperature (HSST).</p> Full article ">Figure 6
<p>Flowchart of sea-level rise simulation and prediction using a Feed-Forward Neural Network model.</p> Full article ">Figure 7
<p>The architecture of the FNN model.</p> Full article ">Figure 8
<p>(<b>a</b>) The model performances and (<b>b</b>) simulation validation trend from 1991 to 2012.</p> Full article ">Figure 8 Cont.
<p>(<b>a</b>) The model performances and (<b>b</b>) simulation validation trend from 1991 to 2012.</p> Full article ">Figure 9
<p>The model performances (<b>a</b>) and prediction validation trend (<b>b</b>) from 2013 to 2020.</p> Full article ">Figure 9 Cont.
<p>The model performances (<b>a</b>) and prediction validation trend (<b>b</b>) from 2013 to 2020.</p> Full article ">Figure 10
<p>Sea level simulation and prediction for five tide gauge stations (1991 to 2020) located in Terengganu, along the East Coast of Malaysia.</p> Full article ">
16 pages, 2548 KiB  
Article
Threat Ranking to Improve Conservation Planning: An Example from the Gediz Delta, Turkey
by Dilara Arslan, Kerim Çiçek, Ömer Döndüren and Lisa Ernoul
Land 2021, 10(12), 1381; https://doi.org/10.3390/land10121381 - 14 Dec 2021
Cited by 3 | Viewed by 3729
Abstract
Mediterranean wetlands are among the most threatened natural areas. The needs and demands of an increasing human population are modifying land use and converting natural habitats into artificial areas. In order to combat these trends, effective conservation planning needs to provide clear, systematic [...] Read more.
Mediterranean wetlands are among the most threatened natural areas. The needs and demands of an increasing human population are modifying land use and converting natural habitats into artificial areas. In order to combat these trends, effective conservation planning needs to provide clear, systematic identification of threats to find sustainable conservation strategies. In this case study, we evaluated current threats in the Gediz Delta (Turkey) using a multi-method approach. First, we did a comprehensive literature review and stakeholder interviews to identify existing threats. We then did a complete survey of the Delta through intensive fieldwork. The threats were coded and ranked using the conservation standards. We used the threat ranking and field survey to map the most vulnerable areas of the Delta. The most commonly observed threats in the field were pollution and agriculture and aquaculture activities. According to the threat ranking, the most important threats are climate change and residential and commercial development. The habitats that are most at risk are agricultural grassland habitats. The results indicate a need to extend conservation actions in the inner part of the Delta. In addition, the multi-method threat ranking approach could serve as a model to improve conservation planning in other sites worldwide. Full article
(This article belongs to the Special Issue Land: 10th Anniversary)
►▼ Show Figures

Figure 1

Figure 1
<p>Location and principal ecosystems of the Gediz Delta in Turkey (adapted from Guelmami, 2021 unpublished data).</p> Full article ">Figure 2
<p>Classification of the major threats in the Gediz Delta based on the IUCN threats classification system using a systematic literature review (n = 233 sources).</p> Full article ">Figure 3
<p>Frequency of direct threats identified by governmental and non-governmental stakeholders in the Gediz Delta based on the IUCN threat classification system (30 ind).</p> Full article ">Figure 4
<p>Global threat heat map of the Gediz Delta with green representing the lowest threat rankings and red representing highest threat rankings.</p> Full article ">Figure A1
<p>The maps show the grids where the four major the threats were identified through the field survey. Yellow colour represents where the threat was observed.</p> Full article ">
23 pages, 5710 KiB  
Article
The Prediction of Carbon Emission Information in Yangtze River Economic Zone by Deep Learning
by Huafang Huang, Xiaomao Wu and Xianfu Cheng
Land 2021, 10(12), 1380; https://doi.org/10.3390/land10121380 - 13 Dec 2021
Cited by 28 | Viewed by 4223
Abstract
This study aimed to respond to the national “carbon peak” mid-and long-term policy plan, comprehensively promote energy conservation and emission reduction, and accurately manage and predict carbon emissions. Firstly, the proposed method analyzes the Yangtze River Economic Belt as well as its “carbon [...] Read more.
This study aimed to respond to the national “carbon peak” mid-and long-term policy plan, comprehensively promote energy conservation and emission reduction, and accurately manage and predict carbon emissions. Firstly, the proposed method analyzes the Yangtze River Economic Belt as well as its “carbon peak” and carbon emissions. Secondly, a support vector regression (SVR) machine prediction model is proposed for the carbon emission information prediction of the Yangtze River Economic Zone. This experiment uses a long short-term memory neural network (LSTM) to train the model and realize the experiment’s prediction of carbon emissions. Finally, this study obtained the fitting results of the prediction model and the training model, as well as the prediction results of the prediction model. Information indicators such as the scale of industry investment, labor efficiency output, and carbon emission intensity that affect carbon emissions in the “Yangtze River Economic Belt” basin can be used to accurately predict the carbon emissions information under this model. Therefore, the experiment shows that the SVR model for solving complex nonlinear problems can achieve a relatively excellent prediction effect under the training of LSTM. The deep learning model adopted herein realized the accurate prediction of carbon emission information in the Yangtze River Economic Zone and expanded the application space of deep learning. It provides a reference for the model in related fields of carbon emission information prediction, which has certain reference significance. Full article
(This article belongs to the Special Issue Socio-Economic Impacts of Carbon Sequestration on Livelihoods and Future Climate)
►▼ Show Figures

Figure 1

Figure 1
<p>Sketch map of the geographic regions of provinces and cities in the Yangtze River Economic Belt.</p> Full article ">Figure 2
<p>Diagram of the warming effects and life cycles of some greenhouse gases.</p> Full article ">Figure 3
<p>Schematic diagram of the classification of “carbon sources”.</p> Full article ">Figure 4
<p>Expanded schematic diagram of an RNN network structure.</p> Full article ">Figure 5
<p>Schematic diagram of an LSTM neural network structure.</p> Full article ">Figure 6
<p>Schematic diagram of SVR.</p> Full article ">Figure 7
<p>Schematic diagram of kernel function names and characteristic parameters.</p> Full article ">Figure 8
<p>LSTM-SVR hybrid model framework diagram.</p> Full article ">Figure 9
<p>Schematic diagram of linear kernel function fitting results.</p> Full article ">Figure 10
<p>Schematic diagram of the Gaussian kernel function fitting results.</p> Full article ">Figure 11
<p>Schematic diagram of the sigmoid kernel function fitting results.</p> Full article ">Figure 12
<p>Schematic diagram of the polynomial kernel function fitting results.</p> Full article ">Figure 13
<p>Comparison of the model performance of four types of kernel functions.</p> Full article ">Figure 14
<p>Comparison of the training and testing losses for multiple iterations of LSTM.</p> Full article ">Figure 15
<p>Schematic diagram of the fitting trend results after LSTM training.</p> Full article ">Figure 16
<p>Schematic diagram of the comparison between the industry investment scale information and “Yangtze River Economic Belt” carbon emission information prediction and the actual comparison.</p> Full article ">Figure 17
<p>Schematic diagram of the comparison between the labor efficiency output information and carbon emission information prediction and the actual comparison of the “Yangtze River Economic Belt”.</p> Full article ">Figure 18
<p>A schematic diagram of the comparison between the scale of carbon emissions information and the carbon emissions information prediction and the actual comparison of the “Yangtze River Economic Belt”.</p> Full article ">
19 pages, 353 KiB  
Article
Challenges and Opportunities for Public Participation in Urban and Regional Planning during the COVID-19 Pandemic—Lessons Learned for the Future
by Marijana Pantić, Juaneé Cilliers, Guido Cimadomo, Fernando Montaño, Olusola Olufemi, Sally Torres Mallma and Johan van den Berg
Land 2021, 10(12), 1379; https://doi.org/10.3390/land10121379 - 13 Dec 2021
Cited by 39 | Viewed by 6499
Abstract
The COVID-19 pandemic has spurred significant changes in the fields of economic development, social issues, everyday life, etc. Activities that used to depend on face-to-face communication were firstly suspended and then shifted to new forms of communication. This includes the public participation process [...] Read more.
The COVID-19 pandemic has spurred significant changes in the fields of economic development, social issues, everyday life, etc. Activities that used to depend on face-to-face communication were firstly suspended and then shifted to new forms of communication. This includes the public participation process in urban and spatial planning. Therefore, this study explores the new domain developed in urban and spatial planning with regard to public participation and surmises future realms in the post-pandemic era. On the occasion of the virtual collaboration platform Cyber Agora organized by the ISOCARP (International Society of City and Regional Planners), chosen participants got together virtually to share, discuss, and compare their practical knowledge in public participation before and during COVID-19. In addition, they addressed the potential benefits of shifting from traditional to virtual participation and potential benefits in the post-COVID-19 era. Considering the collected data and understanding them in the light of the available literature, this study concludes that the application of a combined approach (using both traditional and virtual modes of participation) is recommended because it would enable a larger number and higher diversity of participants. The study also elaborates particular modes of virtual participation with the pros and cons of their use in a particular context. Full article
(This article belongs to the Special Issue Reflecting on the Future of the Built Environment)
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-128
Previous Issue
Next Issue
Back to TopTop