Search Results (8,929)

Global climate change is closely tied to CO₂ emissions, and implementing conservation-agricultural systems can help mitigate emissions in the Amazon. By maintaining forest cover and integrating sustainable agricultural practices in pasture, these systems help mitigate climate change and preserve the carbon stocks in Amazon forest soils. In addition, these systems improve soil health, microclimate regulation, and promote sustainable agricultural practices in the Amazon region. This study aimed to evaluate the CO₂ emission dynamics and its relationship with soil attributes under different uses in the Amazon. The experiment consisted of four treatments (Degraded Pasture—DP; Managed Pasture—MP; Native Forest—NF; and Livestock Forest Integration—LF), with 25 replications. Soil CO₂ emission (FCO₂), soil temperature, and soil moisture were evaluated over a period of 114 days, and the chemical, physical, and biological attributes of the soil were measured at the end of this period. The mean FCO₂ reached values of 4.44, 3.88, 3.80, and 3.14 µmol m⁻² s⁻¹ in DP, MP, NF, and LF, respectively. In addition to the direct relationship between soil CO₂ emissions and soil temperature for all land uses, soil bulk density indirectly influenced emissions in NF. The amount of humic acid induced the highest emission in DP. Soil organic carbon and carbon stock were higher in MP and LF. These values demonstrate that FCO₂ was influenced by the Amazon land uses and highlight LF as a low CO₂ emission system with a higher potential for carbon stock in the soil. Full article

With the advancement of polarimetric synthetic aperture radar (PolSAR) imaging technology and the growing demand for image interpretation, extracting meaningful land cover information from PolSAR images has become a key research focus. To address the segmentation challenge, we propose an innovative method. First, features from co-polarization and cross-polarization channels are separately used as dual inputs, and a cross-attention mechanism effectively fuses these features to capture correlations between different polarization information. Second, a diffusion framework is employed to jointly model target features and class probabilities, aiming to improve segmentation accuracy by learning and fitting the probabilistic distribution of target labels. Finally, experimental results demonstrate that the proposed method achieves superior performance in PolSAR image segmentation, effectively managing complex polarization relationships while offering robustness and broad application potential. Full article

High-altitude mountainous regions are highly vulnerable to climate and environmental shifts, with the current global climate change exerting a profound influence on the ecological landscape of the Tianshan Mountains in China. This study assesses the ecological security quality in the Tianshan Mountains of China from 2001 to 2020 by employing various remote sensing techniques such as the Remote Sensing Ecological Index (RSEI) for evaluation, Normalized Difference Vegetation Index (NDVI) for fractional vegetation cover (FVC) analysis, the CASA model for estimating vegetation primary productivity (NPP), and a carbon source/sink model for calculating the net ecosystem productivity (NEP) of vegetation. The research also delves into the evolutionary trends and impact mechanisms on the ecological environment using land use and meteorological data. The findings reveal that the RSEI’s principal component (PC1) exhibits significant explanatory power, showing a notable increase of 5.90% from 2001 to 2020. Despite relatively stable changes in the RSEI over the past two decades covering 61.37% of the study area, there is a prevalent anti-persistence pattern at 72.39%. Notably, NDVI, FVC, and NPP display upward trends in vegetation characteristics. While most areas in the Tianshan Mountains continue to emit carbon, there is a marked increase in NEP, signifying an enhanced carbon absorption capacity. The partial correlation coefficients between the RSEI and temperature, as well as precipitation, demonstrate statistically significant relationships (p < 0.05), encompassing 6.36% and 1.55% of the study area, respectively. Temperature displays a predominantly negative correlation in 98.71% of the significantly correlated zones, while precipitation exhibits a prevalent positive correlation. An in-depth analysis of how climate change affects the quality of the ecological environment provides crucial insights for strategic interventions to enhance regional environmental protection and promote ecological sustainability. Full article

Mountains support many kinds of ecosystem services (ESs) for human beings, emphasizing the need to understand the characteristics and drivers of ES changes in mountainous regions. In this study, Nanling, the most significant mountains of southern China, was selected as a case study. Utilizing the GlobeLand30 dataset, we employed InVEST, Geodetector and MGWR to identify the spatio-temporal characteristics and drivers of ES changes, investigate trade-offs and synergies between ESs, and examine the relationship between ESs and the landscape ecological risk index (LERI) to provide a new perspective for ecosystem management in vulnerable mountain regions. The results showed that carbon storage (CS) and habitat quality (HQ) slightly decreased, while the water yield (WY) increased slightly. Soil conservation (SC) significantly decreased, but the total ES (TES) slightly increased. All ES bundles demonstrated a synergistic relationship, but most of the synergies exhibited a decreasing trend. The ESs in the study area were mainly affected by climate factors, and anthropogenic factors also had a significant impact on ESs. LERI exhibited a negative correlation with the provision of ESs and demonstrated a high explanatory power for ES changes, especially for CS, HQ and TES, suggesting that areas with more stable landscape patterns are likely to harbor greater levels of ESs. The results provide insights into the analysis of the characteristics of ES change in vulnerable mountainous areas, also providing the practical implications for introducing LERI as a driver for ES change. Full article

The frequent occurrence of floods puts additional pressure on people to change their activities and alter land use practices, consequently making exposed lands more vulnerable to floods. It is thus crucial to investigate dynamic changes in flood exposures and conduct quantitative evaluations of flood risk-reduction strategies to minimize damage to exposed items. This study quantitatively assessed dynamics of flood exposure and flood risk, and evaluated the effectiveness of flood control measures in the Bengawan Solo River basin, Indonesia. The Water and Energy Budget-Based Rainfall–Runoff–Inundation Model was employed for flood simulation for different return periods, and then dynamics of flood exposures and flood risk were assessed. After that, the effectiveness of flood control measures was quantitively evaluated. The results show that settlement/built-up areas and population are increasing in flood-prone areas. The flood-exposed paddy field and settlement areas for 100-year flood were estimated to be more than 950 and 212.58 km², respectively. The results also show that the dam operation for flood control in the study area reduces the flood damage to buildings, contents, and agriculture by approximately 21.2%, 20.9%, and 25.1%, respectively. The river channel improvements were also found effective to reduce flood damage in the study area. The flood damage can be reduced by more than 60% by implementing a combination of a flood control dam and river channel improvements. The findings can be useful for planning and implementing effective flood risk reduction measures. Full article

Desertification presents major environmental challenges in Central Asia, driven by climatic and anthropogenic factors. The present study quantifies desertification risk through an integrated approach using Bayesian networks and the ESAS model, offering a holistic perspective on desertification dynamics. Four key variables—vegetation cover, precipitation, land-use intensity, and soil quality—were incorporated into a Bayesian model to evaluate their influence on desertification. A probabilistic model was developed to gauge desertification intensity, with simulations conducted at 200 geospatial points. Hazard maps for 2030–2050 were produced under climate scenarios SSP245 and SSP585, incorporating projected land-use changes. All procedures for desertification risk assessment, land-use mapping, and climate downscaling were performed using the Google Earth Engine platform. The findings suggest a 4% increase in desertification risk under SSP245 and an 11% increase under SSP585 by 2050, with the greatest threats observed in western regions such as Kazakhstan, Uzbekistan, and Turkmenistan. Sensitivity analysis indicated that vegetation quality exerts the strongest influence on desertification, reflected by a Vegetation Quality Index (VQI) ranging from 1.582 (low in Turkmenistan) to 1.692 (very low in Kazakhstan). A comparison of the Bayesian and ESAS models revealed robust alignment, evidenced by an R² value of 0.82, a Pearson correlation coefficient of 0.76, and an RMSE of 0.18. These results highlight the utility of Bayesian networks as an effective tool for desertification assessment and scenario analysis, underscoring the urgency of targeted land management and proactive climate adaptation. Although reclaimed land presents opportunities for afforestation and sustainable agriculture, carefully considering potential trade-offs with biodiversity and ecosystem services remains essential. Full article

Erosion is a significant environmental challenge in Serbia, shaped by natural and human factors. Pronounced relief, fragile geological substrate, a developed hydrographic network, and a climate characterized by an uneven distribution of precipitation throughout the year make this area prone to activating erosion processes and flash floods whenever there is a significant disruption in ecological balance, whether due to the removal of vegetation cover or inadequate land use. Researchers have recorded approximately 11,500 torrents in Serbia, most of which were activated during the 19th century, a period of significant social and political change, as well as intensive deforestation and the irrational exploitation of natural resources. By the mid-19th century, the effects of land degradation were impossible to ignore. As the adequate assessment of soil erosion intensity is the initial step in developing a prevention and protection strategy and the type and scope of anti-erosion works and measures, this article presents the path that the anti-erosion field in Serbia has taken from the initial observations of erosion processes through the first attempts to create the Barren Land Cadastre and Torrent Cadastre to the creation of the Erosion Potential Method (EPM) and its modification by Dr. Lazarević that resulted in the creation of the first Erosion Map of SR Serbia in 1971 (published in 1983). In 2020, a new Erosion Map of Serbia was created with the application of Geographic Information System (GIS) technologies and based on the original method by Professor Slobodan Gavrilović—the EPM—without the modifications introduced by Lazarević. We compared the 1983 and 2020 erosion maps in a GIS environment, where the change in soil erosion categories was analyzed using a confusion matrix. The updated erosion maps mirror the shift in methodology from a traditional approach (Lazarević’s modification) to the modern GIS-based method (Gavrilović’s original EPM) and reflect technological improvements and changes in land use, conservation practices, and environmental awareness. Full article

In the context of rapid urbanization and extreme climate change globally, balancing ecological resources and economic development for land spatial planning has become one of the pressing issues that need to be addressed. This study proposes a composite model to construct a spatial ecological security pattern. It identifies restoration areas with different risk levels based on the spatial distribution of land use, offering suggestions for optimizing spatial configuration. Focusing on the central Shaanxi region of the Yellow River Basin in China, ecological sources are identified by integrating ecological factors, and ecological corridors and restoration zones are extracted using the minimum cumulative resistance difference and circuit theory. The results indicate significant improvements in ecological quality and desertification in the study area from 2000 to 2020. Currently, the core area covers 51,649.71 km², accounting for 62.18% of all landscape types; the total ecological source area covers 31,304.88 km², representing 18.84% of the entire area. These ecological source areas are mainly distributed in the northern Loess Plateau and the southern mountainous regions. The area has 26 important ecological corridors, identifying 16 ecological pinch points and 12 ecological barriers, presenting an ecological security pattern characterized by a grid-like structure in the northern region and a dispersed pattern in the southern region. Additionally, 273.72 km² of ecological restoration priority areas and 197.98 square kilometers of ecological restoration encouragement areas are proposed as key planning regions for ecological environmental protection. This study provides references for optimizing spatial configuration to promote the sustainable development of urban and rural living environments in the Yellow River Basin. Full article

Accurate knowledge of surface and subsurface soil moisture (SM) is essential for hydrologic modeling, weather forecasting, and agricultural water management. NASA’s Soil Moisture Active Passive (SMAP) satellite (level 3) provides ‘surface’ SM with 2–3 days temporal resolution, hence lacks daily and subsurface SM information. This study developed a convolutional neural network–long short-term memory (ConvLSTM) deep learning model to produce ‘daily’ surface (5 cm) and subsurface (25 cm) SM products (9 km) by integrating SMAP level 3 ancillary data, North American Land Data Assimilation System (NLDAS-2; 12 km) SM, and Soil Landscapes of the United States (SOLUS100) digital maps across the contiguous U.S. Two input scenarios were evaluated: scenario 1 used only SMAP ancillary data, while scenario 2 included both SMAP ancillary data and SOLUS100 soil maps. Model evaluation with in situ SM data showed higher accuracy for scenario 2, indicating the importance of soil properties (texture and bulk density) in SM estimation. Coarse-textured soils showed the highest estimation accuracy, followed by medium- and fine-textured soils. The model also performed in estimating subsurface SM than surface SM for most land-cover types. Incorporating SMAP ancillary data and SOLUS100 digital soil maps into the ConvLSTM improved the spatial and temporal estimation of surface and subsurface SM. The results highlight the potential of deep learning for integrating multi-source multi-scale observations for improving SM estimation at large scale. Full article

The relocation of residents from high-risk areas is a critical measure to address safety and development issues in the floodplain regions of Henan Province in China. Whether the old villages can be reclaimed as farmland after demolition concerns Henan Province’s ability to maintain its farmland red line. This paper integrated multiple remote sensing indices and proposed a remote sensing identification method for monitoring the progress status of village relocation and reclamation that adapted to data characteristics and application scenarios. Firstly, it addressed the issue of missing target bands in GF-2 (GaoFen-2) by employing a band downscaling method; secondly, it combined building and vegetation indices to identify changes in land cover in the old villages within the floodplain, analyzing the implementation effects of the relocation and reclamation policies. Results showed that using a Random Forest regression model to generate a 4 m resolution shortwave infrared band not only retains the original target band information of Landsat-8 but also enhances the spatial detail of the images. Based on the optimal thresholds of multiple remote sensing indices, combined with human footprint data and POI (Points of Interest) identified village boundaries, the overall accuracy of identifying the progress status of resident relocation and reclamation reached 93.5%. In the floodplain region of Henan, the implementation effect of resident relocation was relatively good, with an old village demolition rate of 77%, yet the farmland reclamation rate was only 23%, indicating significant challenges in land conversion, lagging well behind the pilot program schedule requirements. Overall, this study made two primary contributions. First, to distinguish between rural construction and bare soil, thereby improving the accuracy of construction land extraction, an Enhanced Artifical Surface Index (EASI) was proposed. Second, the monitoring results of land use changes were transformed from pixel-level to village-level, and this framework can be extended to other specific land use change monitoring scenarios, demonstrating broad application potential. Full article

Economic pressure on agricultural land is generating major changes in affected territorial systems. The development of methodologies to analyze the pressure on agricultural land is one of the main concerns regarding food security and how to provide fresh produce to large cities. The methodology used uses the Corine Land Cover database, provided by Copernicus Land Monitoring Services (CLMS), from 1990–2018. Data processing and analysis was performed using the open-source software package QGIS, a process that started by reprojecting the data into the national coordinate reference system Pulkovo 1942(58)/Stereo 70, EPSG: 3844. The methodology used was able to highlight the transformations that have taken place in land use, highlighting when and how the land was transformed. Our results show that quantitative and land-use changes due to the socio-economic pressures generated by the transition to a different type of economy can be highlighted. Urban sprawl has led to dramatic changes in land use, with agricultural land being the category that has seen the largest reductions in area. Full article

The expanding use of civilian unmanned aerial vehicles (UAVs) has brought forth a crucial need to address the safety risks they pose in the event of failure, especially when flying in populated areas. This paper reviews recent advancements in recovery systems designed for the emergency landing of civilian UAVs. It covers a wide range of recovery methods, categorizing them based on different recovery approaches and UAV types, including multirotor and fixed-wing. The study highlights the diversity of recovery strategies, ranging from parachute and airbag systems to software-based methods and hybrid solutions. It emphasizes the importance of considering UAV-specific characteristics and operational environments when selecting appropriate safety systems. Furthermore, by comparing various emergency landing systems, this study reveals that integrating multiple approaches based on the UAV type and mission requirements can achieve broader cover of emergency situations compared to using a single system for a specific scenario. Examples of UAVs that utilize emergency landing systems are also provided. For each recovery system, three key parameters of operating altitude, flight speed and added weight are presented. Researchers and UAV developers can utilize this information to identify a suitable emergency landing method tailored to their mission requirements and available UAVs. Based on the key trends and challenges found in the literature, this review concludes by proposing specific, actionable recommendations. These recommendations are directed towards researchers, UAV developers, and regulatory bodies, and focus on enhancing the safety of civilian UAV operations through the improvement of emergency landing systems. Full article

To investigate the influence of factors such as tourism, agriculture, and population density on the presence of microplastic (MP) content in aquatic environments and their associated ecological risks, Jingpo Lake, a remote high-mountain lake situated away from urban areas, was selected as the research subject. This study examined the abundance, types, sizes, colors, and polymer compositions of MPs within the water body, fish, and sediments. By considering variables, including fishing practices, agricultural activities, population dynamics, and vegetation cover, an analysis was conducted to unravel the spatial and temporal distribution of MPs concerning human activities, ultimately leading to an assessment of the ecological risks posed by MP pollution. The findings revealed that the average abundance of MPs in the lake’s surface water was recorded as (304.8 ± 170.5) n/m³, while in the sediments, it averaged (162.0 ± 57.45) n/kg. Inside the digestive tracts of fish, the MP abundance was measured at 11.4 ± 5.4 n/ind. The contamination of MPs within the aquatic environment of Jingpo Lake was found to be relatively minimal. Variations in MP loads across time and space were observed, with MPs predominantly falling within the size range of small planktonic organisms (50–1000 μm). Additionally, the prevalent colors of MPs in the water samples were white or transparent, constituting approximately 55.65% of the entire MP composition. Subsequently, they were black, red, and blue. This colors distribution were consistent across MPs extracted from fish and sediment samples. The chemical compositions of the MPs predominantly comprised PE (31.83%) and PS (25.48%), followed by PP (17.56%), PA (11.84%), PET (6.71%), EVA (4.56%), and PC (2.03%). Regarding the seasonal aspect, MP concentrations were highest during summer (46.68%), followed by spring (36.75%) and autumn (16.56%). The spatial distribution of MPs within Jingpo Lake’s water body, fish, and sediments was notably influenced by human activities, as confirmed by Pearson correlation coefficients. A strong association was observed between MP levels and water quality indicators such as ammonium nitrogen (NH₄-N), total phosphorus (TP), and chlorophyll-a (Chla), suggesting that human-related pollution contributed significantly to MP contamination. The diversity assessment of MP pollutants exhibited the highest variability in chemical composition (1.23 to 1.79) using the Shannon–Wiener Index. Subsequently, the diversity of colors ranged from 0.59 to 1.54, shape diversity from 0.78 to 1.30, seasonal diversity from 0.83 to 1.10, and size diversity from 0.44 to 1.01. The assessment results of ecological risk highlighted that the risk categories for MPs within the surface water, fish, and sediments of Jingpo Lake were categorized as I for the PHI and PLI and as “Minor” for the PERI. These relatively low-risk values were attributed to the predominantly low toxicity of the distributed MPs within the Jingpo Lake basin. Moreover, the results of the risk assessment were found to be interconnected with the distribution of the local population and agricultural activities around the sampling sections. Usage patterns of coastal land and population density were recognized as influential factors affecting MP loads within the water body, sediments, fish, and other components of the lake ecosystem. Full article

Human activities and climate change have accelerated land use and land cover change (LUCC) globally, diminishing the ecosystem service value (ESV) in ecologically fragile areas such as highly mountainous canyons and disrupting the human–nature balance. However, existing research lacks analysis on the impact of land use changes on ecosystem service value in typical counties with highly mountainous canyon regions. Therefore, we aim to address this gap by analyzing land use changes and their driving factors in Chayu County using multi-year land use data, calculating the ecosystem service value (ESV) for different periods, and estimating its spatial correlation and stability. The results showed the following: (1) Forestland and grassland were the predominant land-use types, with notable conversions between grassland and water bodies, grassland and unused land, and water bodies and unused land. (2) The total ESV increased steadily from 2003 to 2023, with higher values in the north and west and lower values in the central east. Forestland and water areas were the primary contributors to ESV changes, and ESV sensitivity to LUCC steadily increased from 0.46% to 2.49%. (3) Moran’s I ESV shows an overall increase, with a heightened correlation and enhanced stability. Spatially, the ESV exhibited a general high–high and low–low clustering pattern, with localized high–low and low–high clusters. These changes, driven by natural resource endowments and climate change, provide essential support for ecological protection and sustainable development in highly mountainous canyons and similar regions. Full article

The Qinghai Plateau has a complex geographical environment and vast amounts of land with a sparse population, dispersed settlements, and a low traffic density. In the face of major disasters, the rational layout of emergency material reserve warehouses is crucial for reducing disaster losses, ensuring regional stability, and quickly restoring production and life. This paper starts by considering the rationality and timeliness of the location selection of provincial emergency material reserve warehouses, considering the distance costs of emergency material transportation on the Qinghai Plateau. By using a traffic accessibility analysis model combined with a location–allocation model and an L-A maximum coverage model, this study optimizes the location selection of emergency material reserve warehouses on the Qinghai Plateau. The research results show the following: (1) On the basis of the existing Golmud Depot and Chengxi Depot in Qinghai Province, it is necessary to add four more depots, i.e., the Yushu Depot, Gande Depot, Ping’an Depot, and Tongde Depot, to achieve the timely and efficient supply of emergency materials. (2) After the optimization, the layout of the six provincial emergency material reserve warehouses can achieve full coverage of Qinghai Province within 8 h in the event of major disasters, increasing the coverage by 20% compared to the original layout; the new plan allows for emergency material transportation to cover 87% of Qinghai Province within 4 h, an increase of 28% compared to before. (3) The optimized location selection plan for emergency material reserve warehouses saves 139 min of time costs, and the transportation efficiency is increased by 46% compared to the previous plan. The optimized location selection plan for emergency material reserve warehouses is instructive for the construction of emergency material reserve warehouses on the Qinghai–Tibet Plateau. Full article