Nothing Special   »   [go: up one dir, main page]

You seem to have javascript disabled. Please note that many of the page functionalities won't work as expected without javascript enabled.
 
 
Sign in to use this feature.

Years

Between: -

Subjects

remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline

Journals

Article Types

Countries / Regions

Search Results (25)

Search Parameters:
Keywords = Dunhuang site

Order results
Result details
Results per page
Select all
Export citation of selected articles as:
21 pages, 10990 KiB  
Article
Radiometric Cross-Calibration of HJ-2A/CCD3 Using the Random Forest Algorithm and a Spectral Interpolation Convolution Method with Sentinel-2/MSI
by Xiang Zhou, Yidan Chen, Yong Xie, Jie Han and Wen Shao
Remote Sens. 2024, 16(22), 4337; https://doi.org/10.3390/rs16224337 - 20 Nov 2024
Viewed by 249
Abstract
In the process of radiometric calibration, the corrections for bidirectional reflectance distribution functions (BRDFs) and spectral band adjustment factors (SBAFs) are crucial. Time-series MODIS images are commonly used to construct BRDFs by using the Ross–Li model in current research. However, the Ross–Li BRDF [...] Read more.
In the process of radiometric calibration, the corrections for bidirectional reflectance distribution functions (BRDFs) and spectral band adjustment factors (SBAFs) are crucial. Time-series MODIS images are commonly used to construct BRDFs by using the Ross–Li model in current research. However, the Ross–Li BRDF model is based on the linear relationship between the kernel models and is unable to take into account the nonlinear relationship between them. Furthermore, when using SBAF to account for spectral difference, a radiative transfer model is often used, but it requires many parameters to be set, which may introduce more errors and reduce the calibration accuracy. To address these issues, the random forest algorithm and a spectral interpolation convolution method using the Sentinel-2/multispectral instrument (MSI) are proposed in this study, in which the HuanJing-2A (HJ-2A)/charge-coupled device (CCD3) sensor is taken as an example, and the Dunhuang radiometric calibration site (DRCS) is used as a radiometric delivery platform. Firstly, a BRDF model by using the random forest algorithm of the DRCS is constructed using time-series MODIS images, which corrects the viewing geometry difference. Secondly, the BRDF correction coefficients, MSI reflectance, and relative spectral responses (RSRs) of CCD3 are used to correct the spectral differences. Finally, with the validation results, the maximum relative error between the calibration results of the proposed method and the official calibration coefficients (OCCs) published by the China Centre for Resources Satellite Data and Application (CRESDA) is 3.38%. When tested using the Baotou sandy site, the proposed method is better than the OCCs of the average relative errors calculated for all the bands except for the near-infrared (NIR) band, which has a larger error. Additionally, the effects of the light-matching method and the radiative transfer method, different approaches to constructing the BRDF model using SBAF to account for spectral differences, different BRDF models, as well as the precise viewing geometrical parameters, spectral interpolation method, and geometric positioning error, on the calibration results are analyzed. Results indicate that the cross-calibration coefficients obtained using the random forest algorithm and the proposed spectral interpolation method are more applicable to the CCD3; thus, they also account for the nonlinear relationships between the kernel models and reduce the error due to the radiative transfer model. The total uncertainty of the proposed method in all bands is less than 5.16%. Full article
Show Figures

Figure 1

Figure 1
<p>RSRs of CCD3 and MSI.</p>
Full article ">Figure 2
<p>DRCS from CCD3 image on 9 May 2022.</p>
Full article ">Figure 3
<p>Baotou sandy site from MSI image on 2 March 2022.</p>
Full article ">Figure 4
<p>The geometry information of time-series MODIS images in 2022.</p>
Full article ">Figure 5
<p>Flowchart of the experiment.</p>
Full article ">Figure 6
<p>Fitting of cross-calibration coefficients for each band of the CCD3.</p>
Full article ">Figure 7
<p>Average relative error of the ICRs with reflectance calculated based on OCCs and FCCs.</p>
Full article ">Figure 8
<p>Average relative error of ICRs with reflectance calculated by OCCs and other cross-calibration coefficients after fitting.</p>
Full article ">Figure 9
<p>Continuous spectral curves after cubic polynomial interpolation for MOD09GA on calibration days.</p>
Full article ">Figure 10
<p>The reflectance information of time-series MSI images in 2022.</p>
Full article ">
19 pages, 4700 KiB  
Article
Radiometric Cross-Calibration of GF6-PMS and WFV Sensors with Sentinel 2-MSI and Landsat 9-OLI2
by Hengyang Wang, Zhaoning He, Shuang Wang, Yachao Zhang and Hongzhao Tang
Remote Sens. 2024, 16(11), 1949; https://doi.org/10.3390/rs16111949 - 29 May 2024
Viewed by 777
Abstract
A panchromatic and multispectral sensor (PMS) and a wide-field-of-view (WFV) sensor were fitted aboard the Gaofen6 (GF6) satellite, which was launched on 2 June 2018. This study used the Landsat9-Operational Land Imager 2 and Sentinel2-Multispectral Instrument as reference sensors to perform radiometric cross-calibration [...] Read more.
A panchromatic and multispectral sensor (PMS) and a wide-field-of-view (WFV) sensor were fitted aboard the Gaofen6 (GF6) satellite, which was launched on 2 June 2018. This study used the Landsat9-Operational Land Imager 2 and Sentinel2-Multispectral Instrument as reference sensors to perform radiometric cross-calibration on GF6-PMS and WFV data at the Dunhuang calibration site. The four selected sensor images were all acquired on the same day. The results indicate that: the calibration results between different reference sensors can be controlled within 3%, with the maximum difference from the official coefficients being 8.78%. A significant difference was observed between the coefficients obtained by different reference sensors when spectral band adjustment factor (SBAF) correction was not performed; from the two sets of validation results, the maximum mean relative difference in the near-infrared band was 9.46%, with the WFV sensor showing better validation results. The validation of calibration coefficients based on synchronous ground observation data and the analysis of the impact of different SBAF methods on the calibration results indicated that Landsat9 is more suitable as a reference sensor for radiometric cross-calibration of GF6-PMS and WFV. Full article
(This article belongs to the Special Issue Remote Sensing Satellites Calibration and Validation)
Show Figures

Figure 1

Figure 1
<p>Dunhuang calibration site.</p>
Full article ">Figure 2
<p>Spectral response functions of Landsat9-OLI2, Sentinel2-MSI, GF6-PMS, and GF6-WFV.</p>
Full article ">Figure 3
<p>Ground reflectance of the Dunhuang calibration site.</p>
Full article ">Figure 4
<p>Radiometric cross-calibration process diagram.</p>
Full article ">Figure 5
<p>Calculation process diagram for SBAF.</p>
Full article ">Figure 6
<p>Comparison of radiance between Landsat9-OLI2 and Sentinel2-MSI pre-and post-SBAF correction (MD and MR are the mean relative difference and mean ratio, respectively).</p>
Full article ">Figure 7
<p>Linear fitting results of radiometric cross-calibration for GF6-PMS.</p>
Full article ">Figure 8
<p>Linear fitting results of radiometric cross-calibration for GF6-WFV.</p>
Full article ">Figure 9
<p>Evaluation and validation of radiance results for GF6-PMS simulated using Sentinel2-MSI versus calculated using radiometric cross-calibration coefficients (MD and MR are the mean relative difference and mean ratio, respectively).</p>
Full article ">Figure 10
<p>Evaluation and validation of radiance results for GF6-WFV simulated using Sentinel2-MSI versus calculated using radiometric cross-calibration coefficients (MD and MR are the mean relative difference and mean ratio, respectively).</p>
Full article ">Figure 11
<p>Evaluation and validation of radiance results for GF6-PMS simulated using Landsat9-OLI2 versus calculated using radiometric cross-calibration coefficients (MD and MR are the mean relative difference and mean ratio, respectively).</p>
Full article ">Figure 12
<p>Evaluation and validation of radiance results for GF6-WFV simulated using Landsat9-OLI2 versus calculated using radiometric cross-calibration coefficients (MD and MR are the mean relative difference and mean ratio, respectively).</p>
Full article ">Figure 13
<p>Surface reflectance from ground synchronous observation at the Dunhuang calibration site on 25 November 2022.</p>
Full article ">
34 pages, 32984 KiB  
Article
Vision and Site: Revisiting a Pure Land Cave of Dunhuang
by Zhenru Zhou and Luke Li
Religions 2024, 15(3), 329; https://doi.org/10.3390/rel15030329 - 8 Mar 2024
Cited by 1 | Viewed by 3391
Abstract
Buddhist Utopian vision shaped the art of Pure Land; so did many other factors, including the actual locale. Taking Mogao Cave 172 as the main case study, this article deciphers a visual paradigm of a Pure Land painting and cave in Dunhuang (Gansu, [...] Read more.
Buddhist Utopian vision shaped the art of Pure Land; so did many other factors, including the actual locale. Taking Mogao Cave 172 as the main case study, this article deciphers a visual paradigm of a Pure Land painting and cave in Dunhuang (Gansu, China) from the high Tang period (710–780 CE). By analyzing the visual contents and compositions, the painting medium, the cave spaces, and the cliff site, this study investigates the ways in which the architectural images and spaces in Cave 172 helped to convey the invitation to Pure Land. A close reading of the Western Pure Land painting in Cave 172 reveals the spatial construct of the Buddhist paradise that encouraged a transformative viewing experience. A situated visual analysis of Cave 172 with its auxiliary cave and neighboring caves illustrates the historical procedure in which Pure Land imageries were further integrated with the architectural spaces of caves and cave suites. As this study demonstrates, strategies of spatial layering, self-symmetry and scaling, and plastic and multimedia practices of cave-making enhanced the situatedness of the utopian vision. Full article
(This article belongs to the Special Issue Space for Worship in East Asia)
Show Figures

Figure 1

Figure 1
<p>Representative pictorial compositions of the Pure Land transformation tableaux in Dunhuang between the sixth and twelfth centuries. Line drawings. (<b>a</b>) Western Pure Land, west wall, Mogao Cave 393, Sui period; (<b>b</b>) Western Pure Land, north wall, Mogao Cave 205, the early Tang period; (<b>c</b>) Eastern Pure Land, north wall, Mogao Cave 361, mid-Tang period; (<b>d</b>) Eastern Pure Land, north wall, Mogao Cave 146, Five Dynasties period. After <a href="#B28-religions-15-00329" class="html-bibr">Shi</a> (<a href="#B28-religions-15-00329" class="html-bibr">1999, p. 20</a>); <a href="#B46-religions-15-00329" class="html-bibr">Xiao</a> (<a href="#B46-religions-15-00329" class="html-bibr">1989, pp. 65, 73, 77, figs. 28, 36, 40</a>).</p>
Full article ">Figure 2
<p><span class="html-italic">Meditation Sūtra</span> transformation tableau. North wall of Mogao Cave 172. High Tang period. Mural painting. 400 (w) × 270 (h) cm. Photo Courtesy of Dunhuang Academy.</p>
Full article ">Figure 3
<p>A trace-copy line drawing of the architectural setting in <a href="#religions-15-00329-f002" class="html-fig">Figure 2</a>. Drawing by Zhenru Zhou in AutoCAD.</p>
Full article ">Figure 4
<p>The pictorial composition of figural images in <a href="#religions-15-00329-f002" class="html-fig">Figure 2</a>. (<b>a</b>) Isolated deity figures; (<b>b</b>) the locations and relationships between several figures. Digital photo collage and diagram by Zhenru Zhou in Adobe Photoshop.</p>
Full article ">Figure 5
<p>The pictorial composition of architectural images in <a href="#religions-15-00329-f002" class="html-fig">Figure 2</a>. Digital photo collage and diagram by Zhenru Zhou in Adobe Photoshop.</p>
Full article ">Figure 6
<p>Details in <a href="#religions-15-00329-f003" class="html-fig">Figure 3</a>. (<b>a</b>) a corner pavilion represented in a frontal perspective; (<b>b</b>) the bracket sets and rafters of the main hall seen from below; (<b>c</b>) a terrace seen from above. Drawing by Zhenru Zhou in AutoCAD.</p>
Full article ">Figure 7
<p>A bird’s-eye view of the Western Pure Land: Zhenru Zhou’s reconstruction design based on <a href="#religions-15-00329-f002" class="html-fig">Figure 2</a>. Digital photo collage by Zhenru Zhou in Sketchup and Adobe Photoshop software.</p>
Full article ">Figure 8
<p>A one-point perspective of the Western Pure Land from a standpoint on the bridge looking toward the main terrace: Zhenru Zhou’s reconstruction design based on <a href="#religions-15-00329-f002" class="html-fig">Figure 2</a>. Digital photo collage by Zhenru Zhou in Sketchup and Adobe Photoshop software.</p>
Full article ">Figure 9
<p>The herringbone-like construct of multiple “vanishing points” in <a href="#religions-15-00329-f002" class="html-fig">Figure 2</a>, with the architectural image completed. Diagram by Zhenru Zhou.</p>
Full article ">Figure 10
<p>Sixteen meditations: <span class="html-italic">Meditation Sūtra</span> transformation tableau. North wall of Mogao Cave 172. High Tang period. Mural painting. <a href="#B8-religions-15-00329" class="html-bibr">Feng</a> (<a href="#B8-religions-15-00329" class="html-bibr">2018, pp. 2–121, Figure 3–30</a>).</p>
Full article ">Figure 11
<p>Sixteen steps of contemplating the pictorial space in <a href="#religions-15-00329-f002" class="html-fig">Figure 2</a>. Horizontal line is the level of the viewpoint of the imaginary traveler. Diagonal lines in a circle or semicircle are lines that are parallel in the pictorial space and represented as conjoining at the center of the circle (i.e., the “vanishing point”). Sets of diagonal lines mirrored along the vertical axis are in the direction of parallel projection. Diagram by Zhenru Zhou.</p>
Full article ">Figure 12
<p>Isometric view of Mogao Cave 172 showing the dimensions of the main chamber wall and the ear-chamber wall. Drawing by Zhenru Zhou, texture after Sun Ruxian’s rendering in Sun and Sun, <span class="html-italic">Shiku jianzhu juan</span>, 225.</p>
Full article ">Figure 13
<p>Cave 173, late Tang period, statues remade in the Qing period. Photo courtesy of the Dunhuang Academy.</p>
Full article ">Figure 14
<p>The timber-framed façade and exterior mural of Mogao Cave 431 showing three-step bracket sets, a three-bay façade, and an overhanging roof. Dated by inscription to 980 CE; 486 cm (w) × 142 cm (d) × 320 cm (h). Wood, mud brick, polychromic pigments. Photo by Zhenru Zhou, 20 January 2022.</p>
Full article ">Figure 15
<p>Potential viewing angles of the Pure Land paintings in Cave 172 (figure’s height: 1.70 m). Drawing by Zhenru Zhou, texture after Sun Ruxian’s water-color renderings in Sun and Sun, <span class="html-italic">Shiku jianzhu juan</span>, 225.</p>
Full article ">Figure 16
<p>Isometric view of the main chamber of Cave 171 showing the subject matter of the images along the niche-entrance dimension. Drawing by Zhenru Zhou.</p>
Full article ">Figure 17
<p>Distribution of cave suites at the Mogao Caves. Base map by Sun Ruxian. Annotation by Zhenru Zhou.</p>
Full article ">Figure 18
<p>The building prototype and the methods of scaling and positioning for generating the architectural complex in <a href="#religions-15-00329-f002" class="html-fig">Figure 2</a>. Diagram by Zhenru Zhou.</p>
Full article ">Figure 19
<p>Open-air mural above Cave 170. (<b>a</b>) Location of the mural (in red rectangular frame next to gray shade of a hypothetical façade added by Zhenru Zhou) in Oldenburg’s 1914–15 rendering (<a href="#B11-religions-15-00329" class="html-bibr">Ėrmitazh and Shanghai 1997–2005, v5, pl. 1</a>); (<b>b</b>) a recent photograph. Photo by Zhenru Zhou, August 2019.</p>
Full article ">Figure 20
<p>A detail of a <span class="html-italic">Meditation Sūtra</span> painting showing a two-level pavilion as the backdrop of a Buddha preaching scene. Silk painting, ninth or tenth century. Discovered in Mogao Cave 17. In the collection of the Guimet Museum (MG 17673). Digitized and made available by the International Dunhuang Project, <a href="https://idp.bl.uk/collection/F67D8E2A42102A44A2CC0D37DD4C6271/?return=%2Fcollection%2F%3Fterm%3D17673" target="_blank">https://idp.bl.uk/collection/F67D8E2A42102A44A2CC0D37DD4C6271/?return=%2Fcollection%2F%3Fterm%3D17673</a> (accessed on 26 February 2024).</p>
Full article ">Figure 21
<p>A stripe of open-air mural remaining above the antechambers of Mogao Caves 181–85. Photo by Oldenburg expedition team, 1914–15. After Gosudarstvennyĭ Ėrmitazh, <span class="html-italic">Eluosi guo li Ai’ermitashi bo wu guan cang Dunhuang yi shu pin</span>, 3:13.</p>
Full article ">Figure A1
<p>The sequential viewing of the Pure Land painting (<b>left</b>) paired with scenes from a walk-through experience (<b>right</b>).</p>
Full article ">Figure A1 Cont.
<p>The sequential viewing of the Pure Land painting (<b>left</b>) paired with scenes from a walk-through experience (<b>right</b>).</p>
Full article ">Figure A1 Cont.
<p>The sequential viewing of the Pure Land painting (<b>left</b>) paired with scenes from a walk-through experience (<b>right</b>).</p>
Full article ">Figure A1 Cont.
<p>The sequential viewing of the Pure Land painting (<b>left</b>) paired with scenes from a walk-through experience (<b>right</b>).</p>
Full article ">
17 pages, 607 KiB  
Article
The Impact of Emotional Experience on Tourists’ Cultural Identity and Behavior in the Cultural Heritage Tourism Context: An Empirical Study on Dunhuang Mogao Grottoes
by Yang Yang, Zhengyun Wang, Han Shen and Naipeng Jiang
Sustainability 2023, 15(11), 8823; https://doi.org/10.3390/su15118823 - 30 May 2023
Cited by 6 | Viewed by 6160
Abstract
The emotions perceived by tourists and their effects in the tourism context are increasingly highlighted in tourism studies. In the cultural heritage tourism context, tourists’ emotional experience comes from their cognitive evaluation of the natural environment and the humanistic environment and triggers deep [...] Read more.
The emotions perceived by tourists and their effects in the tourism context are increasingly highlighted in tourism studies. In the cultural heritage tourism context, tourists’ emotional experience comes from their cognitive evaluation of the natural environment and the humanistic environment and triggers deep cognitive processing and prosocial behavior, further building tourists’ identity with culture and enhancing their awareness and heritage conservation behavior. Based on the theory of emotional evaluation and positive emotional expansion and construction, this study constructed the research model of emotional arousal—positive emotional experience—tourists’ cultural identity—heritage protection behavior. Three hundred and ninety-seven tourists’ data were empirically tested using the World Heritage Site, the Dunhuang Mogao Grottoes, as a case site. The study found that in the cultural heritage tourism context, the cognitive evaluation of the natural and humanistic environment has the effect of inducing positive emotional experience among tourists; positive emotional experience positively influences tourists’ cultural identity and heritage conservation behavior; and they are part of the mediating variables of tourists’ emotion elicitation and cultural identity. The results of this study will further enrich the theoretical research on emotions in the cultural heritage tourism context and also help the relevant departments of cultural heritage tourism further enhance tourists’ cultural identity and heritage conservation behaviors from the perspective of tourists’ emotional experience. The future research could focus on investigating the emotional triggers’ impact on tourists’ cultural identity and heritage conservation behavior in relation to a particular cultural experience activity. Full article
(This article belongs to the Special Issue Tourism, Sustainable Development, and Cultural Heritage)
Show Figures

Figure 1

Figure 1
<p>Theoretical model.</p>
Full article ">
32 pages, 8554 KiB  
Article
Vicarious Radiometric Calibration of the Multispectral Imager Onboard SDGSAT-1 over the Dunhuang Calibration Site, China
by Zhenzhen Cui, Chao Ma, Hao Zhang, Yonghong Hu, Lin Yan, Changyong Dou and Xiao-Ming Li
Remote Sens. 2023, 15(10), 2578; https://doi.org/10.3390/rs15102578 - 15 May 2023
Cited by 12 | Viewed by 2115
Abstract
The multispectral imager (MII), onboard the Sustainable Development Science Satellite 1 (SDGSAT-1), performs detailed terrestrial change detection and coastal monitoring. SDGSAT-1 was launched at 2:19 UTC on 5 November 2021, as the world’s first Earth science satellite to serve the United Nations 2030 [...] Read more.
The multispectral imager (MII), onboard the Sustainable Development Science Satellite 1 (SDGSAT-1), performs detailed terrestrial change detection and coastal monitoring. SDGSAT-1 was launched at 2:19 UTC on 5 November 2021, as the world’s first Earth science satellite to serve the United Nations 2030 Sustainable Development Agenda. A vicarious radiometric calibration experiment was conducted at the Dunhuang calibration site (Gobi Desert, China) on 14 December 2021. In-situ measurements of ground reflectance, aerosol optical depth (AOD), total columnar water vapor, radiosonde data, and diffuse-to-global irradiance (DG) ratio were performed to predict the top-of-atmosphere radiance by the reflectance-, irradiance-, and improved irradiance-based methods using the moderate resolution atmospheric transmission model. The MII calibration coefficients were calculated by dividing the top-of-atmosphere radiance by the average digital number value of the image. The radiometric calibration coefficients calculated by the three calibration methods were reliable (average relative differences: 2.20% (reflectance-based vs. irradiance-based method) and 1.43% (reflectance-based vs. improved irradiance-based method)). The total calibration uncertainties of the reflectance-, irradiance-, and improved irradiance-based methods were 2.77–5.23%, 3.62–5.79%, and 3.50–5.23%, respectively. The extra DG ratio measurements in the latter two methods did not improve the calibration accuracy for AODs ≤ 0.1. The calibrated MII images were verified using Landsat-8 Operational Land Imager (OLI) and Sentinel-2A MultiSpectral Instrument (MSI) images. The retrieved ground reflectances of the MII over different surface types were cross-compared with those of OLI and MSI using the FAST Line-of-sight Atmospheric Analysis of Hypercubes software. The MII retrievals differed by <0.0075 (7.13%) from OLI retrievals and <0.0084 (7.47%) from MSI retrievals for calibration coefficients from the reflectance-based method; <0.0089 (7.57%) from OLI retrievals and <0.0111 (8.65%) from MSI retrievals for the irradiance-based method; and <0.0082 (7.33%) from OLI retrievals and <0.0101 (8.59%) from MSI retrievals for the improved irradiance-based method. Thus, our findings support the application of SDGSAT-1 data. Full article
(This article belongs to the Special Issue Accuracy and Quality Control of Remote Sensing Data)
Show Figures

Figure 1

Figure 1
<p>Relative spectral response function of the SDGSAT-1 MII.</p>
Full article ">Figure 2
<p>Sentinel-2A/MSI image of the Dunhuang calibration site acquired on 17 December 2021.</p>
Full article ">Figure 3
<p>(<b>a</b>) Photograph of the in-situ ground reflectance measurement at Dunhuang calibration site. (<b>b</b>) Scheme of the ground surface measurement route.</p>
Full article ">Figure 4
<p>Simultaneous ground reflectance measurements performed over the Dunhuang calibration site on 14 December 2021, using FieldSpec-4 ASD spectroradiometer.</p>
Full article ">Figure 5
<p>The 550 nm AOD and CWV retrieved from the CE318 sun photometer on 14 December 2021.</p>
Full article ">Figure 6
<p>Measured DG ratios (<b>a</b>) at 550 nm on the date of the SDGSAT-1 overpass and (<b>b</b>) the entire spectrum at the time of the SDGSAT-1 overpass.</p>
Full article ">Figure 7
<p>Atmospheric vertical profiles of (<b>a</b>) pressure, (<b>b</b>) temperature, and (<b>c</b>) relative humidity obtained by the radiosonde balloon released on 14 December 2021.</p>
Full article ">Figure 8
<p>Scatter plot of <math display="inline"><semantics> <mrow> <mi>l</mi> <mi>n</mi> <mrow> <mo>(</mo> <mrow> <mn>1</mn> <mo>−</mo> <msub> <mi>α</mi> <mi>s</mi> </msub> </mrow> <mo>)</mo> </mrow> </mrow> </semantics></math> versus <span class="html-italic">m</span> at 550 nm.</p>
Full article ">Figure 9
<p>Goodness-of-fit statistics for DG ratio measurements according to Equation (11).</p>
Full article ">Figure 10
<p>DG ratios in solar and viewing directions during the SDGSAT-1 overpass.</p>
Full article ">Figure 11
<p>The column mean value of dark current acquired by imaging the ocean at night on 14 December 2021.</p>
Full article ">Figure 12
<p>MODTRAN-simulated TOA spectral radiances for the SDGSAT-1 MII calculated by the reflectance-, irradiance-, and improved irradiance-based methods.</p>
Full article ">Figure 13
<p>Calibration uncertainty caused by the assumption of different aerosol types for SDGSAT-1 MII calibration on 24 December 2021, utilizing the (<b>a</b>) reflectance-, (<b>b</b>) irradiance-, and (<b>c</b>) improved irradiance-based methods.</p>
Full article ">Figure 14
<p>Relative differences between the (<b>a</b>) rural and desert aerosol types, (<b>b</b>) rural and urban aerosol types, and (<b>c</b>) rural and maritime aerosol types for the reflectance-, irradiance-, and improved irradiance-based methods under different AOD conditions (AOD = 0.05, 0.1, 0.2, 0.3, 0.4, and 0.5).</p>
Full article ">Figure 15
<p>Calibration uncertainty caused by atmospheric profile measurements for SDGSAT-1 MII calibration on 24 December 2021, utilizing the (<b>a</b>) reflectance-, (<b>b</b>) irradiance-, and (<b>c</b>) improved irradiance-based methods.</p>
Full article ">Figure 16
<p>Calibration uncertainty caused by AOD retrieval for SDGSAT-1 MII calibration on 24 December 2021, utilizing the (<b>a</b>) reflectance-, (<b>b</b>) irradiance-, and (<b>c</b>) improved irradiance-based methods.</p>
Full article ">Figure 17
<p>Changes in direct and diffuse transmittances for both downward and upward directions under different 550 nm AOD.</p>
Full article ">Figure 18
<p>Changes in direct transmittance and transmittances under different 550 nm AOD conditions, including direct and diffuse transmittances in (<b>a</b>) downward and (<b>b</b>) upward directions.</p>
Full article ">Figure 19
<p>Calibration uncertainty caused by CWV retrieval for SDGSAT-1 MII calibration on 24 December 2021, utilizing the (<b>a</b>) reflectance-, (<b>b</b>) irradiance-, and (<b>c</b>) improved irradiance-based methods.</p>
Full article ">Figure 20
<p>Calibration uncertainty caused by viewing geometry errors for SDGSAT-1 MII calibration on 24 December 2021, utilizing the (<b>a</b>) reflectance-, (<b>b</b>) irradiance-, and (<b>c</b>) improved irradiance-based methods.</p>
Full article ">Figure 21
<p>Relative spectral responses of corresponding bands for SDGSAT-1 MII, Landsat-8 OLI, and Sentinel-2A MSI.</p>
Full article ">Figure 22
<p>Different surface types selected for validation.</p>
Full article ">Figure 23
<p>Comparison of retrieved ground reflectances obtained by the indicated sensors according to the (<b>a</b>) reflectance-, (<b>b</b>) irradiance-, and (<b>c</b>) improved irradiance-based methods.</p>
Full article ">
14 pages, 6196 KiB  
Article
Gaining Instead of Losing: The Image of Dunhuang as a Religious Heritage in a WeChat Mini-Programme
by Zhuyun Song
Religions 2023, 14(5), 634; https://doi.org/10.3390/rel14050634 - 9 May 2023
Cited by 1 | Viewed by 2956
Abstract
In 2020, a WeChat mini-programme called the Dunhuang E-Tour (云游敦煌) was launched during the COVID-19 pandemic to showcase one of China’s most important religious heritage sites, the Dunhuang Mogao Grottoes (also known as the Dunhuang Caves), and it attracted a considerable number of [...] Read more.
In 2020, a WeChat mini-programme called the Dunhuang E-Tour (云游敦煌) was launched during the COVID-19 pandemic to showcase one of China’s most important religious heritage sites, the Dunhuang Mogao Grottoes (also known as the Dunhuang Caves), and it attracted a considerable number of online tourists. Unlike the colonial image of Dunhuang in Chinese public discourse, the mini-programme does not focus on Dunhuang’s history; rather, it provides a dynamic and interactive representation of Dunhuang’s religious murals, painted sculptures and cave architecture. To reflect the impact of the mini-programme’s digital mechanisms on users’ experience, this study adopts an analytical framework that combines the walkthrough method and religious tourist perspectives to explore the image of the digital Dunhuang and how it was shaped. The analysis finds that the functions of the Dunhuang E-Tour create a culturally rich image of Dunhuang, which subverts its decades-long Dunhuang image as a site of loss in Chinese public discourse. This difference in images mirrors the potential impact of China’s recent cultural policy of ‘cultural confidence’ in relation to its cultural and creative industries. Full article
(This article belongs to the Section Religions and Humanities/Philosophies)
Show Figures

Figure 1

Figure 1
<p>The Menu and Functions of Dunhuang E-Tour: (<b>a</b>) The Menu of Dunhuang E-Tour; (<b>b</b>) The Functions of Dunhuang E-Tour.</p>
Full article ">Figure 2
<p>The cultural conservation projects page and the donation page to the project.</p>
Full article ">Figure 3
<p>The page of Mission Centre in the Mine section.</p>
Full article ">Figure 4
<p>The pages of the Dunhuang Animations: (<b>a</b>) Dunhuang Animations in the New Cultural Creation section; (<b>b</b>) A description of the animation feature; (<b>c</b>) The selection page.</p>
Full article ">Figure 5
<p>The pages of <span class="html-italic">Princes Sailing for the Pearl</span>: (<b>a</b>) The voiceover participation page; (<b>b</b>) The character selection page; (<b>c</b>) The poster page.</p>
Full article ">Figure 6
<p>The pages of the Buddha with “oriental smile”: (<b>a</b>) The page of the iconic Buddha statue; (<b>b</b>) The two options’ page; (<b>c</b>) The page of the Share Card.</p>
Full article ">Figure 7
<p>A table of the User’s Experience of Dunhuang E-Tour.</p>
Full article ">
18 pages, 10365 KiB  
Article
Radiometric Calibration of GF5-02 Advanced Hyperspectral Imager Based on RadCalNet Baotou Site
by Hongzhao Tang, Chenchao Xiao, Kun Shang, Taixia Wu and Qi Li
Remote Sens. 2023, 15(9), 2233; https://doi.org/10.3390/rs15092233 - 23 Apr 2023
Cited by 5 | Viewed by 1805
Abstract
In this study, an on-orbit radiometric calibration campaign of the GF5-02 AHSI was performed at the RadCalNet Baotou site, based on the automated observation of reflectance and atmospheric parameters of a 300 m × 300 m homogeneous desert area. The consistency of the [...] Read more.
In this study, an on-orbit radiometric calibration campaign of the GF5-02 AHSI was performed at the RadCalNet Baotou site, based on the automated observation of reflectance and atmospheric parameters of a 300 m × 300 m homogeneous desert area. The consistency of the radiometric calibration coefficients was validated both at the Dunhuang calibration site and the Baotou site. The average relative difference between the calibrated top-of-atmospheric (TOA) radiance and the predicted TOA radiance were less than 7%. The R2 of these two TOA radiances were all higher than 0.99. These results showed that the accuracy of calibration coefficients could meet the requirements of hyperspectral quantification applications. The uncertainty of GF5-02 AHSI radiometric calibration was 6.18%. This study also demonstrated that automated observation data of the Baotou site were reliable for high-frequency radiometric calibration and radiometric performance monitoring of GF5-02 AHSI. Full article
(This article belongs to the Special Issue Hyperspectral Remote Sensing Data Calibration and Validation)
Show Figures

Figure 1

Figure 1
<p>GF5-02 Advanced Hyperspectral Imager.</p>
Full article ">Figure 2
<p>Normalized SRF of GF5-02 AHSI Band 1 from laboratory spectral calibration.</p>
Full article ">Figure 3
<p>Normalized SRF of GF5-02 AHSI Band 84 to Band 91.</p>
Full article ">Figure 4
<p>The flowchart of the on-orbit reflectance-based radiometric calibration method of GF5-02 AHSI.</p>
Full article ">Figure 5
<p>Homogeneous desert area and automatic observation system at the RadCalNet Baotou site.</p>
Full article ">Figure 6
<p>The AHSI hyperspectral imagery of the RadCalNet Baotou site on 23 May.</p>
Full article ">Figure 7
<p>The AHSI hyperspectral imagery of the RadCalNet Baotou site on 2 April.</p>
Full article ">Figure 8
<p>The AHSI hyperspectral imagery of the RadCalNet Baotou site on 2 September.</p>
Full article ">Figure 9
<p>The mean reflectance measurements of homogeneous sand at the GF5-02 satellite overpass on 2 April, 23 May, and 2 September.</p>
Full article ">Figure 10
<p>BRDF measuring instrument.</p>
Full article ">Figure 11
<p>Synchronous measurement of atmospheric parameters at the RadCalNet Baotou site (23 May 2022). (<b>a</b>) Synchronous measurement of AOD. (<b>b</b>) Synchronous measurement of CWV.</p>
Full article ">Figure 12
<p>TOA radiance of GF5-02 AHSI predicted by Modtran6.0.</p>
Full article ">Figure 13
<p>DN from GF5-02 AHSI hyperspectral imagery.</p>
Full article ">Figure 14
<p>On-orbit calibration coefficient of the GF5-02 AHSI.</p>
Full article ">Figure 15
<p>Homogeneous natural features at the RadCalNet Baotou site. (<b>a</b>) 200 m × 200 m bare soil. (<b>b</b>) 200 m × 200 m grassland.</p>
Full article ">Figure 16
<p>Spectral reflectance measurement results of sand, bare soil, and grassland.</p>
Full article ">Figure 17
<p>The predicted TOA radiance and the calibrated TOA radiance at the RadCalNet Baotou site. (<b>a</b>) homogeneous sand at Baotou site. (<b>b</b>) bare soil at Baotou site. (<b>c</b>) grassland at Baotou site.</p>
Full article ">Figure 18
<p>The Gobi Desert in Dunhuang calibration site of GF5-02 AHSI imagery.</p>
Full article ">Figure 19
<p>Mean and standard deviation of surface reflectance of the Gobi Desert at Dunhuang site.</p>
Full article ">Figure 20
<p>The predicted TOA radiance and the calibrated TOA radiance of the Gobi Desert at Dunhuang site.</p>
Full article ">
17 pages, 11287 KiB  
Article
Network Construction for Overall Protection and Utilization of Cultural Heritage Space in Dunhuang City, China
by Bin Feng and Yongchi Ma
Sustainability 2023, 15(5), 4579; https://doi.org/10.3390/su15054579 - 3 Mar 2023
Cited by 7 | Viewed by 2127
Abstract
An important recent issue in research is the effective protection and rational utilization of cultural heritage. In particular, the regional protection and utilization network of heritage space is the overall requirement for promoting cultural protection and high-quality development of its industry. Using Dunhuang [...] Read more.
An important recent issue in research is the effective protection and rational utilization of cultural heritage. In particular, the regional protection and utilization network of heritage space is the overall requirement for promoting cultural protection and high-quality development of its industry. Using Dunhuang city, Gansu Province, China, as a case study, it is argued here that the cultural heritage space is a living unit that is composed of not only cultural heritage but also its overall environment. By identifying the key historical factors of Dunhuang’s regional cultural heritage space, this paper explores the conservation factors and utilization factors. The suitability of the conservation factors and utilization factors is assessed through a two-way index of conservation and utilization. In addition, using a field strength model that considered various factors, the suitability characteristics of conservation and utilization were summarized. It was found that the conservation and utilization space of Dunhuang’s cultural heritage had three network features: same level overlap, primary and secondary combination, and significant differentiation. At the same time, these formed an organization network of “patch collage and corridor concatenation” and the network of “mine field pattern and branch extension”. From this, the sustainable development of the Dunhuang cultural space network can be realized through the combinations of site protection and ecological protection and environmental utilization and ecological restoration. Full article
(This article belongs to the Section Tourism, Culture, and Heritage)
Show Figures

Figure 1

Figure 1
<p>Distribution of Dunhuang cultural heritage and its overall environmental factors. Source: drawn by the author (2022).</p>
Full article ">Figure 2
<p>Method and technical route. Source: drawn by the author (2022).</p>
Full article ">Figure 3
<p>Yumenguan Site, one of the elements of military defense communication. Source: authors’ photographs (2021).</p>
Full article ">Figure 4
<p>Mogao Grottoes, one of the artistic factors of grottoes. Source: authors’ photographs (2022).</p>
Full article ">Figure 5
<p>Evaluation of the factors of conservation and utilization of cultural heritage space. Source: drawn by the author (2022).</p>
Full article ">Figure 6
<p>Overall protection evaluation and classification. Source: drawn by the author (2022).</p>
Full article ">Figure 7
<p>Overall utilization evaluation grading. Source: drawn by the author (2022).</p>
Full article ">Figure 8
<p>Network concept diagram of conservation and utilization in the cultural heritage space of Dunhuang city. Source: drawn by the author (2022).</p>
Full article ">
19 pages, 8422 KiB  
Article
Monitoring of Atmospheric Carbon Dioxide over a Desert Site Using Airborne and Ground Measurements
by Qin Wang, Farhan Mustafa, Lingbing Bu, Juxin Yang, Chuncan Fan, Jiqiao Liu and Weibiao Chen
Remote Sens. 2022, 14(20), 5224; https://doi.org/10.3390/rs14205224 - 19 Oct 2022
Cited by 6 | Viewed by 2880
Abstract
Accurate monitoring of atmospheric carbon dioxide (CO2) is of great significance for studying the carbon cycle. Compared to ground observational sites, airborne observations cover a wider area, which help in effectively monitoring the distribution of CO2 sources and sinks. In [...] Read more.
Accurate monitoring of atmospheric carbon dioxide (CO2) is of great significance for studying the carbon cycle. Compared to ground observational sites, airborne observations cover a wider area, which help in effectively monitoring the distribution of CO2 sources and sinks. In this study, an airborne campaign was carried out in June and July 2021 to measure the atmospheric CO2 concentration over a desert site, Dunhuang, located in western China. The dry-air column-averaged CO2 mole fraction (XCO2) inversion results obtained from the Atmospheric Carbon Dioxide Lidar (ACDL) system were compared with the Orbiting Carbon Observatory 2 (OCO-2) retrievals, portable Fourier Transform Spectrometer (EM27/SUN) measurement results, and with the XCO2 estimates derived using the airborne Ultraportable Greenhouse Gas Analyzer (UGGA) and the Copernicus Atmosphere Monitoring Service (CAMS) model measurements. Moreover, the vertical CO2 profiles obtained from the OCO-2 and the CAMS datasets were also compared with the airborne UGGA measurements. OCO-2 and CAMS CO2 measurements showed a vertical distribution pattern similar to that of the aircraft-based measurements of atmospheric CO2. In addition, the relationship of atmospheric CO2 with the aerosol optical depth (AOD) was also determined and the results showed a strong and positive correlation between the two variables. Full article
Show Figures

Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Pictures of the aircraft Instrumentation. (<b>a</b>) The ACDL system. (<b>b</b>) The control interfaces of some instruments. (<b>c</b>) The Ultraportable Greenhouse Gas Analyzer (UGGA).</p>
Full article ">Figure 2
<p>Ground station layout. The solid pink line is the flight route on 19 July 2021. It is worth noting that the Chinese Radiometric Calibration Site (CRCS) (40.17°N, 94.25°E, ~1230 m a.s.l. (above sea level)) is located in the Gobi Desert and approximately 20 km west of Dunhuang city in west China (© Google Earth Pro).</p>
Full article ">Figure 3
<p>The flight routes between 11 and 19 July 2021. (© Google Earth Pro).</p>
Full article ">Figure 4
<p>U- shaped flight pattern (<b>a</b>) and spiral descent flight pattern (<b>b</b>). The black asterisk represents the CRCS ground station.</p>
Full article ">Figure 5
<p>Diurnal variation of XCO<sub>2</sub> measured by EM27/SUN at CRCS ground station.</p>
Full article ">Figure 6
<p>Diurnal variation of CO<sub>2</sub> concentration measured by UGGA at CRCS ground station.</p>
Full article ">Figure 7
<p>The concentrations of CO<sub>2</sub> measured by the UGGA before calibration (<b>a</b>) and the concentrations of CO<sub>2</sub> measured by the UGGA after calibration (<b>b</b>). The black straight line is the concentration value of the standard gas.</p>
Full article ">Figure 8
<p>The CO<sub>2</sub> concentration distribution measured by airborne UGGA in July 2021 (<b>a</b>) and the CO<sub>2</sub> concentration vertical structure (<b>b</b>). In <a href="#remotesensing-14-05224-f008" class="html-fig">Figure 8</a>a, the time period when the aircraft’s flight altitude is decreasing is marked by orange shading. The time when the aircraft’s flight height is increasing is marked with light blue shading. In <a href="#remotesensing-14-05224-f008" class="html-fig">Figure 8</a>b, the gray scatters represent the results at different heights for all CO<sub>2</sub> concentrations marked with shading in <a href="#remotesensing-14-05224-f008" class="html-fig">Figure 8</a>a. The blue scatter points represent the average of all grey scatter points at different heights.</p>
Full article ">Figure 9
<p>The distribution of OCO-2 satellite orbits in the flight area (<b>a</b>) and the CO<sub>2</sub> concentration vertical structure measured by the OCO-2 (<b>b</b>). In <a href="#remotesensing-14-05224-f009" class="html-fig">Figure 9</a>a, there are two satellite orbits on 16 July and 18 July 2021 within the flight zone. The solid green line is the satellite orbit. The solid red line is the flight route of the plane on 16 July 2021. The green scatters represent the locations where the OCO-2 satellite data was sampled. In <a href="#remotesensing-14-05224-f009" class="html-fig">Figure 9</a>b, the cyan solid lines represent the results at different heights for all CO<sub>2</sub> concentrations marked with green scatters in <a href="#remotesensing-14-05224-f009" class="html-fig">Figure 9</a>a. The blue scatter points represent the average of all cyan solid lines at different heights (© Google Earth Pro).</p>
Full article ">Figure 10
<p>Distribution of the CAMS model data points in the flight area (<b>a</b>) and the CO<sub>2</sub> concentration vertical structure calculated by the CAMS model (<b>b</b>). In <a href="#remotesensing-14-05224-f010" class="html-fig">Figure 10</a>a, the green points represent the locations of the CAMS mode grid data. The solid pink line is the flight route of the plane on 19 July 2021. In <a href="#remotesensing-14-05224-f010" class="html-fig">Figure 10</a>b, the gray scatters represent the results at different heights for all CO<sub>2</sub> concentrations of point 1 in the figure, and each gray profile represents the calculation results at different times at point 1. The blue scatters represent the average of all grey scatter points at different heights (© Google Earth Pro).</p>
Full article ">Figure 11
<p>Comparison of vertical structures of CO<sub>2</sub> concentrations measured by airborne UGGA, OCO-2 satellite, and CAMS model (<b>a</b>) and the CO<sub>2</sub> concentration lapse rate of the airborne UGGA, OCO-2 satellite, and CAMS model (<b>b</b>). The green scatter is the measurement result of the airborne UGGA. The solid blue line is the measurement result of the OCO-2 satellite. The pink solid line is the calculation result of the CAMS model.</p>
Full article ">Figure 12
<p>Measurement results of XCO<sub>2</sub> and AOD at the CRCS ground station on 11 July 2021 (<b>a</b>). The red dots represent the XCO<sub>2</sub> results measured by EM27/SUN, and the black scatter points represent the AOD results measured by CE318. (<b>b</b>) The correlation analysis result of XCO<sub>2</sub> and AOD.</p>
Full article ">Figure 13
<p>Measurement results of XCO<sub>2</sub> and AOD at the CRCS ground station on 12 July 2021 (<b>a</b>). The red dots represent the XCO<sub>2</sub> results measured by EM27/SUN, and the black scatter points represent the AOD results measured by CE318. (<b>b</b>) The correlation analysis result of XCO<sub>2</sub> and AOD.</p>
Full article ">Figure 14
<p>Measurement results of XCO<sub>2</sub> and AOD at the CRCS ground station on 16 July 2021 (<b>a</b>). The red dots represent the XCO<sub>2</sub> results measured by EM27/SUN, and the black scatter points represent the AOD results measured by CE318. (<b>b</b>) The correlation analysis result of XCO<sub>2</sub> and AOD.</p>
Full article ">Figure 15
<p>Measurement results of XCO<sub>2</sub> and AOD at the CRCS ground station on 18 July 2021 (<b>a</b>). The red dots represent the XCO<sub>2</sub> results measured by EM27/SUN, and the black scatter points represent the AOD results measured by CE318. (<b>b</b>) The correlation analysis result of XCO<sub>2</sub> and AOD.</p>
Full article ">Figure 16
<p>Aerosol backscatter coefficient and XCO<sub>2</sub> results measured by the airborne ACDL system on 14 March 2019. The flight altitude of the aircraft is represented by a solid white line, and the green scattered points are the inversion results of XCO<sub>2</sub>. The flight process is divided into ABCD four parts, corresponding to different surface types. The purple vertical line is the dividing line between different surface types.</p>
Full article ">Figure 17
<p>Comparison of AOD and XCO<sub>2</sub> measured by the airborne ACDL system in marine and urban areas on 14 March 2019. The blue scatters represent XCO<sub>2</sub> and the black scatters represent AOD. The pink vertical line is the dividing line between the marine area and the urban area.</p>
Full article ">Figure 18
<p>Atmospheric CO<sub>2</sub> concentration measured by airborne UGGA during the plane’s horizontal flight at an altitude of 4.05 km on 19 July 2021. The carbon dioxide emission sources on the flight track are marked with black upper triangle symbols.</p>
Full article ">
17 pages, 4503 KiB  
Article
Occurrence and Discrepancy of Surface and Column Mole Fractions of CO2 and CH4 at a Desert Site in Dunhuang, Western China
by Chong Wei, Zheng Lyu, Lingbing Bu and Jiqiao Liu
Atmosphere 2022, 13(4), 571; https://doi.org/10.3390/atmos13040571 - 1 Apr 2022
Cited by 3 | Viewed by 2453
Abstract
Carbon dioxide (CO2) and methane (CH4) are the two major radiative forcing factors of greenhouse gases. In this study, surface and column mole fractions of CO2 and CH4 were first measured at a desert site in Dunhuang, [...] Read more.
Carbon dioxide (CO2) and methane (CH4) are the two major radiative forcing factors of greenhouse gases. In this study, surface and column mole fractions of CO2 and CH4 were first measured at a desert site in Dunhuang, west China. The average column mole fractions of CO2 (XCO2) and CH4 (XCH4) were 413.00 ± 1.09 ppm and 1876 ± 6 ppb, respectively, which were 0.90 ppm and 72 ppb lower than their surface values. Diurnal XCO2 showed a sinusoidal mode, while XCH4 appeared as a unimodal distribution. Ground observed XCO2 and XCH4 were compared with international satellites, such as GOSAT, GOSAT-2, OCO-2, OCO-3, and Sentinel-5P. The differences between satellites and EM27/SUN observations were 0.26% for XCO2 and −0.38% for XCH4, suggesting a good consistency between different satellites and ground observations in desert regions in China. Hourly XCO2 was close to surface CO2 mole fractions, but XCH4 appeared to have a large gap with CH4, probably because of the additional chemical removals of CH4 in the upper atmosphere. It is necessary to carry out a long-term observation of column mole fractions of greenhouse gases in the future to obtain their temporal distributions as well as the differences between satellites and ground observations. Full article
(This article belongs to the Special Issue Novel Techniques for Measuring Greenhouse Gases)
Show Figures

Figure 1

Figure 1
<p>Location of the CRCS observation site in the Gobi Desert in Dunhuang, western China. The subfigure (<b>B</b>–<b>D</b>) are the enlarged area in the red box of subfigures (<b>A</b>–<b>C</b>) respectively. The base map was obtained from Geoq, and the base figures were obtained from Google Earth, Image Landsat/Copernicus, Image 2021 © CNES/Airbus; Image © 2021 Maxar Technologies.</p>
Full article ">Figure 2
<p>Daily and hourly average mole fractions of surface CO<sub>2</sub> (<b>A</b>,<b>B</b>) and CH<sub>4</sub> (<b>C</b>,<b>D</b>), as well as hourly average column mole fractions of CO<sub>2</sub> (<b>A</b>) and CH<sub>4</sub> (<b>C</b>), observed at CRCS in Dunhuang, China.</p>
Full article ">Figure 3
<p>Diurnal variation in EM27/SUN observed XCO<sub>2</sub> (<b>A</b>), XCH<sub>4</sub> (<b>B</b>), XCO (<b>C</b>), XCO<sub>2</sub>/XCH<sub>4</sub> (<b>D</b>), XCO<sub>2</sub>/XCO (<b>E</b>), and XCH<sub>4</sub>/XCO (<b>F</b>) on different days. The format of the date is mm-dd on the top of the Figure.</p>
Full article ">Figure 4
<p>Comparison of XCO<sub>2</sub> (<b>A</b>) and XCH<sub>4</sub> (<b>B</b>) observed from EM27/SUN and satellites (OCO-2, OCO-3, GOSAT, GOSAT-2, and S5-P) at CRCS in Dunhuang, western China.</p>
Full article ">Figure 5
<p>Footprints of XCO<sub>2</sub> observations from OCO-2, OCO-3, and GOSAT near the EM27/SUN observation site from 26 June to 19 July 2021. The observation data from different satellites were selected as a region spanning 5° latitude and 10° longitude of the center of the EM27/SUN site.</p>
Full article ">Figure 6
<p>Diurnal variation in hourly XCO<sub>2</sub> (<b>A</b>) and XCH<sub>4</sub> (<b>B</b>) mole fractions and their ratio (<b>C</b>), as well as the comparison with the corresponding greenhouse gas mole fractions and the ratio in the Gobi Desert in Dunhuang, China. The data were averaged from the hourly data on 11, 12, 14, and 16 July 2021.</p>
Full article ">Figure 7
<p>Boxplots of hourly average CO<sub>2</sub> (<b>A</b>), CH<sub>4</sub> (<b>B</b>), XCO<sub>2</sub> (<b>C</b>), and XCH<sub>4</sub> (<b>D</b>) mole fractions against wind speed. GHG mole fractions were binned by wind speed with an interval of 1 m s<sup>−1</sup>.</p>
Full article ">Figure 8
<p>Bivariate polar plots for hourly CO<sub>2</sub> and CH<sub>4</sub> mole fraction and their ratio between 26 June and 19 July 2021 in Dunhuang, west China.</p>
Full article ">
18 pages, 7606 KiB  
Article
On-Orbit Radiometric Performance of GF-7 Satellite Multispectral Imagery
by Hongzhao Tang, Junfeng Xie, Xinming Tang, Wei Chen and Qi Li
Remote Sens. 2022, 14(4), 886; https://doi.org/10.3390/rs14040886 - 12 Feb 2022
Cited by 10 | Viewed by 2964
Abstract
China’s first civilian, sub-meter, high-resolution stereo mapping satellite, GF-7, launched on 3 November 2019. Radiometric characterization of GF-7 multispectral imagery has been performed in this study. A relative radiometric accuracy evaluation of the GF-7 multispectral imagery was performed using several large uniform scenes, [...] Read more.
China’s first civilian, sub-meter, high-resolution stereo mapping satellite, GF-7, launched on 3 November 2019. Radiometric characterization of GF-7 multispectral imagery has been performed in this study. A relative radiometric accuracy evaluation of the GF-7 multispectral imagery was performed using several large uniform scenes, and the results showed that the accuracy is better than 2%. The absolute radiometric evaluation of the GF-7 satellite sensor was conducted at the Baotou and Dunhuang calibration sites, using the reflectance-based vicarious approach. The synchronous measurements of surface reflectance and atmospheric parameters were collected as the input for the radiative transfer model. The official radiometrically calibrated coefficient of the GF-7 multispectral imagery was evaluated with the predicted top-of-atmosphere (TOA) radiance from the radiative transfer model. The results indicated that the absolute radiometric accuracy of GF-7 multispectral imagery is better than 5%. In order to monitor the radiometric stability of the GF-7 satellite multispectral sensor, a relative and absolute radiometric accuracy assessment campaign should be performed several times a year. Full article
(This article belongs to the Special Issue Accuracy and Quality Control of Remote Sensing Data)
Show Figures

Figure 1

Figure 1
<p>The DLC (forward-looking and backward-looking cameras) of the GF7 satellite.</p>
Full article ">Figure 2
<p>Normalized spectral response function of the GF-7 backward-looking camera.</p>
Full article ">Figure 3
<p>The three CCD arrays of the GF-7 satellite multispectral sensor.</p>
Full article ">Figure 4
<p>GF-7 BWD-MUX blue band imagery of the uniform Libya 4 PICs (8 August 2020).</p>
Full article ">Figure 5
<p>The normalized DN in the along-track direction of the uniform Libya 4 PICs.</p>
Full article ">Figure 6
<p>Detailed flow chart of the reflectance-based approach.</p>
Full article ">Figure 7
<p>The gray-scale permanent artificial targets at the Baotou site of GF-7 BWD imagery (15 September 2020).</p>
Full article ">Figure 8
<p>Spectral reflectance measurement data of gray-scale permanent targets.</p>
Full article ">Figure 9
<p>The BRDF measurement instrument.</p>
Full article ">Figure 10
<p>The ANIF values of gray target from BRDF measurement.</p>
Full article ">Figure 11
<p>Synchronous measurement of the atmospheric parameters of the Baotou site on 23 July 2020.</p>
Full article ">Figure 12
<p>The GF-7 satellite Baotou site acquisition geometry.</p>
Full article ">Figure 13
<p>The Dunhuang calibration site.</p>
Full article ">Figure 14
<p>Surface reflectance and standard deviation of the Gobi Desert at the Dunhuang test site.</p>
Full article ">Figure 15
<p>The GF-7 satellite Dunhuang test site acquisition geometry.</p>
Full article ">
11 pages, 4310 KiB  
Communication
Calibration of Automatic Sun Photometer with Temperature Correction in Field Environment
by Shuyu Chen, Yuan Li, Fengmei Cao and Yuxiang Zhang
Remote Sens. 2022, 14(1), 66; https://doi.org/10.3390/rs14010066 - 24 Dec 2021
Cited by 1 | Viewed by 2406
Abstract
Aerosol optical depth (AOD) is an important atmospheric correction parameter in remote sensing. In order to obtain AOD accurately, the surface-based automatic sun photometer needs to carry out calibration regularly. The normally used Langley method can be effective only when the AOD and [...] Read more.
Aerosol optical depth (AOD) is an important atmospheric correction parameter in remote sensing. In order to obtain AOD accurately, the surface-based automatic sun photometer needs to carry out calibration regularly. The normally used Langley method can be effective only when the AOD and the calibration coefficients of the instrument remain unchanged throughout the day. However, when observing the AOD with CE318 sun photometer in field environment, it was found that the AOD of silicon (Si) detector at 1020 nm and indium gallium arsenide (InGaAs) detector at 1639 nm was strongly influenced by temperature due to the large temperature difference at the Dunhuang site. Based on the corresponding relationship between AOD and wavelength, the model of the calibration coefficients varying with temperature was established by nonlinear regression method in field environment. By comparing the AOD before and after temperature correction with the theoretical one, the ratio of data with relative error (RE) less than 5% increased from 0.195 and 0.14 to 0.894 and 0.355, respectively. By this method, calibration can be carried out without the limit of constant AOD. In addition, it is simpler, more convenient, and less costly to perform temperature correction in a field environment than in a laboratory. Full article
(This article belongs to the Section Atmospheric Remote Sensing)
Show Figures

Figure 1

Figure 1
<p>Sun photometer (CE318-T593) at the Dunhuang site.</p>
Full article ">Figure 2
<p>The calibration coefficients changing with temperature (°C) for a whole year: (<b>a</b>) 1020 nm; (<b>b</b>) 1639 nm.</p>
Full article ">Figure 3
<p>Results of before and after temperature correction on 30 January 2020: (<b>a</b>) AOD varying with temperature (°C); (<b>b</b>) normalized AOD varying with temperature (°C).</p>
Full article ">Figure 4
<p>RE and AE of the estimated AOD and the theoretical AOD varying with temperature (°C) on 30 January 2020: (<b>a</b>) 1020 nm; (<b>b</b>) 1639 nm.</p>
Full article ">Figure 5
<p>The estimated AOD before and after calibration changing with the theoretical AOD. There are 8969 points: (<b>a</b>) 1020 nm; (<b>b</b>) 1639 nm.</p>
Full article ">Figure 6
<p>Distribution of RE of the estimated AOD and the theoretical AOD: (<b>a</b>) 1020 nm before correction; (<b>b</b>) 1639 nm before correction; (<b>c</b>) 1020 nm after correction; (<b>d</b>) 1639 nm after correction.</p>
Full article ">Figure 6 Cont.
<p>Distribution of RE of the estimated AOD and the theoretical AOD: (<b>a</b>) 1020 nm before correction; (<b>b</b>) 1639 nm before correction; (<b>c</b>) 1020 nm after correction; (<b>d</b>) 1639 nm after correction.</p>
Full article ">
19 pages, 3685 KiB  
Article
Aging Characteristics of Asphalt Binder under Strong Ultraviolet Irradiation in Northwest China
by Ling Zou, Yan Zhang and Bangyi Liu
Sustainability 2021, 13(19), 10753; https://doi.org/10.3390/su131910753 - 28 Sep 2021
Cited by 14 | Viewed by 1967
Abstract
Asphalt pavement is significantly affected by ultraviolet (UV) aging. Therefore, the establishment of an asphalt UV aging evaluation system is desirable for highway construction in areas which experience strong UV radiation. In this study, Dunhuang City in Gansu Province (northwest China) was used [...] Read more.
Asphalt pavement is significantly affected by ultraviolet (UV) aging. Therefore, the establishment of an asphalt UV aging evaluation system is desirable for highway construction in areas which experience strong UV radiation. In this study, Dunhuang City in Gansu Province (northwest China) was used as the research site. Base and SBS modified asphalts were selected, and their performance changes before and after UV aging were studied. An asphalt UV aging evaluation system was established, including the conditions for an indoor, accelerated UV aging test as well as evaluation indicators. The results showed that the adverse effect of UV aging on asphalt performance was greater than that of RTFOT and PAV, and that the low-temperature performance of asphalt degraded most rapidly. SBS modified asphalt was more resistant to UV aging than base asphalt, while 60/80 pen grade base asphalt was found to be unsuitable for use on pavements which are exposed to strong UV radiation. The residual penetration, penetration attenuation index at 25 °C, and residual ductility of the asphalt were used as indicators to characterize the aging of asphalt, while the fracture energy method was used as a supplementary evaluation method. Full article
Show Figures

Figure 1

Figure 1
<p>Straight tube high pressure mercury lamp used in testing.</p>
Full article ">Figure 2
<p>Indoor accelerated UV aging environment chamber.</p>
Full article ">Figure 3
<p>(<b>a</b>) Sample container; (<b>b</b>) asphalt sample used for the indoor accelerated UV aging test.</p>
Full article ">Figure 4
<p>Penetration of asphalt at 25 °C under different aging methods.</p>
Full article ">Figure 5
<p>Ductility of asphalt under different aging methods.</p>
Full article ">Figure 6
<p>The softening point of asphalt under different aging methods.</p>
Full article ">Figure 7
<p>DSR test results of 90-1 base asphalt under different aging conditions: (<b>a</b>) complex modulus; (<b>b</b>) phase angle.</p>
Full article ">Figure 8
<p>DSR test results of SBS-2 modified asphalt under different aging conditions: (<b>a</b>) complex modulus; (<b>b</b>) phase angle.</p>
Full article ">Figure 9
<p>BBR test results of asphalts under different aging conditions.</p>
Full article ">Figure 10
<p>The true stress-true strain curves of asphalts under different aging methods: (<b>a</b>) 90-1 base asphalt, (<b>b</b>) SBS-2 modified asphalt.</p>
Full article ">Figure 11
<p>The fracture energy density of asphalt under different aging methods.</p>
Full article ">Figure 12
<p>The estimated value of penetration after UV aging.</p>
Full article ">Figure 13
<p>Estimated values of ductility after UV aging.</p>
Full article ">
21 pages, 13319 KiB  
Article
Colour-Balanced Edge-Guided Digital Inpainting: Applications on Artworks
by Irina-Mihaela Ciortan, Sony George and Jon Yngve Hardeberg
Sensors 2021, 21(6), 2091; https://doi.org/10.3390/s21062091 - 17 Mar 2021
Cited by 14 | Viewed by 2865
Abstract
The virtual inpainting of artworks provides a nondestructive mode of hypothesis visualization, and it is especially attractive when physical restoration raises too many methodological and ethical concerns. At the same time, in Cultural Heritage applications, the level of details in virtual reconstruction and [...] Read more.
The virtual inpainting of artworks provides a nondestructive mode of hypothesis visualization, and it is especially attractive when physical restoration raises too many methodological and ethical concerns. At the same time, in Cultural Heritage applications, the level of details in virtual reconstruction and their accuracy are crucial. We propose an inpainting algorithm that is based on generative adversarial network, with two generators: one for edges and another one for colors. The color generator rebalances chromatically the result by enforcing a loss in the discretized gamut space of the dataset. This way, our method follows the modus operandi of an artist: edges first, then color palette, and, at last, color tones. Moreover, we simulate the stochasticity of the lacunae in artworks with morphological variations of a random walk mask that recreate various degradations, including craquelure. We showcase the performance of our model on a dataset of digital images of wall paintings from the Dunhuang UNESCO heritage site. Our proposals of restored images are visually satisfactory and they are quantitatively comparable to state-of-the-art approaches. Full article
(This article belongs to the Section Intelligent Sensors)
Show Figures

Figure 1

Figure 1
<p><b>Left</b>: Dunhuang dataset visualized in a two dimensional space with Barnes-Hut Stochastic Neighbour Embedding (BH-SNE) [<a href="#B8-sensors-21-02091" class="html-bibr">8</a>]. The clustering is done based on the activations of the first fully connected layer of the pretrained VGG19 network [<a href="#B9-sensors-21-02091" class="html-bibr">9</a>] that outputs a vector of 4096 features (color, size, semantics, etc.) for each image. Images are displayed exactly at their embedded location in the two-dimensional (2D) projection space. <b>Right</b>: color gamut of the Dunhuang dataset. The L*a*b* coordinates are rendered with the corresponding RGB colour.</p>
Full article ">Figure 2
<p>Our model converts the RGB images to L*a*b* color. The edge generator receives as input only the monochrome luminance channel and the binary masks of missing pixels (that follow variations of a random walk pattern). Subsequently, color rarity weights are computed on the a* and b* channels and then used in the loss function of the color generator. The edge map, the multichannel L*a*b* image and the priors are fed to the color generator.</p>
Full article ">Figure 3
<p>Both color and edge generators have the same underlying convolutional architecture, composed of encoder–decoder blocks and eight residual blocks with dilated convolution in between. Different from [<a href="#B17-sensors-21-02091" class="html-bibr">17</a>], we introduce the <math display="inline"><semantics> <msub> <mi>L</mi> <mrow> <mi>a</mi> <mo>∗</mo> <mi>b</mi> <mo>∗</mo> </mrow> </msub> </semantics></math> loss for the color generator to lower the bias towards mean values of the dataset’s gamut.</p>
Full article ">Figure 4
<p>Random walk (RW) mask (leftmost) with three morphological variations: skeletonization (RW + SK), medial axis transform (RW + MAT) and dilation (RW + DIL). Besides covering different areas of missing pixels, these masks simulate various patterns characteristic to artwork degradation: moist and pest formation, craquelure, and mechanical damage.</p>
Full article ">Figure 5
<p>Intermediate results generated for a subset of random six images from the validation set (original size of the images is 256 × 256, scaled to fit in the page). For each of the six instances, five images are shown, in order from left to right: ground-truth; ground-truth with deterioration; edge map in the missing region; output inpainted image with both edge and color information as generated by the network; and, output of the model merged with the non-masked input pixels.</p>
Full article ">Figure 6
<p>Ground-truth images selected for discussion. (<b>a</b>) First image (697 × 701 pixels) was chosen because it contains a face, that we consider a challenging case for inpainting. (<b>b</b>) Second image (681 × 674) is very color diverse. (<b>c</b>) Third image (828 × 800) is a homogenous colour, where it will be easy to check for color artifacts in the inpainted result. (<b>d</b>) Fourth image (582 × 841) is a scene with decorating motifs, where edges reconstruction can be inspected.</p>
Full article ">Figure 7
<p>Inpainting results for random walk deterioration with different coverage of the same scene (ground-truth is <a href="#sensors-21-02091-f006" class="html-fig">Figure 6</a>a). The inpainted images were generated at full resolution, however they are shrinked for display purposes here. Even though, in the first deteriorated example, the face of the character is mostly covered, the inpainted version manages to reconstruct some structural details with good accuracy, such as the aura, the lips and the left eye.</p>
Full article ">Figure 8
<p>Pairs of inpainting results for morphological variations of random walk masks with different coverage of the same scene (ground-truth is <a href="#sensors-21-02091-f006" class="html-fig">Figure 6</a>b). The colors are well preserved in the restored version. In the second pair (top third and fourth images), where dilated random walk deterioration is used, we can notice more blurriness.</p>
Full article ">Figure 9
<p>Inpainting result for <a href="#sensors-21-02091-f006" class="html-fig">Figure 6</a>c. The restoration does not disrupt the color homogeneity with respect to the non-corrupted part of the image.</p>
Full article ">Figure 10
<p>Inpainting result for <a href="#sensors-21-02091-f006" class="html-fig">Figure 6</a>d. The beige structure in the middle of the image remains color coherent in the infilled image. Similarly, the two leftward black poles. However, the reconstruction is more blurry in the top left corner, which corresponds to a bigger and more contiguous lacuna.</p>
Full article ">Figure 11
<p>The columns represent in order, from left to right: original image, deteriorated image with RW mask, inpainted image with our approach, inpainted image with the approach of [<a href="#B17-sensors-21-02091" class="html-bibr">17</a>]. In the highlighted regions of interest, our approach outputs more color coherent and sharper results.</p>
Full article ">Figure 12
<p>Contour plots showing the isolines of difference in <math display="inline"><semantics> <mo>Δ</mo> </semantics></math>E error between images inpainted with the proposed method minus the method in [<a href="#B17-sensors-21-02091" class="html-bibr">17</a>]. For each method, <math display="inline"><semantics> <mo>Δ</mo> </semantics></math>E was computed with the S-CIELAB distance metric, where the reference was the original, undamaged image. A positive value (yellow) for the contour plots show areas where our proposed method is more color coherent with the original, whereas negative values (blue) represent regions where the other algorithm performs better.</p>
Full article ">Figure 13
<p>Bar plots showing the overall performance of three CNN-based mage quality metrics (IQMs) for groups of damage. These metrics measure the similarity of the feature maps given by the activations of AlexNet (pretrained on ImageNet) for the ground-truth test images and images inpainted by our approach and [<a href="#B17-sensors-21-02091" class="html-bibr">17</a>]. The overall metrics are aggregated as the geometric mean of the result at each convolutional layer.</p>
Full article ">Figure 13 Cont.
<p>Bar plots showing the overall performance of three CNN-based mage quality metrics (IQMs) for groups of damage. These metrics measure the similarity of the feature maps given by the activations of AlexNet (pretrained on ImageNet) for the ground-truth test images and images inpainted by our approach and [<a href="#B17-sensors-21-02091" class="html-bibr">17</a>]. The overall metrics are aggregated as the geometric mean of the result at each convolutional layer.</p>
Full article ">Figure 14
<p>Bar plots showing the performance of three CNN-based IQMs for each convolutional layer. These metrics measure the similarity of the feature maps given by the activations of AlexNet (pretrained on ImageNet) for the ground-truth test images and images inpainted by our approach and [<a href="#B17-sensors-21-02091" class="html-bibr">17</a>]. Top for each pair: the results for RW damage. Bottom for each pair: results for RW+DIL damage.</p>
Full article ">
18 pages, 7907 KiB  
Article
Vicarious Radiometric Calibration of Ocean Color Bands for FY-3D/MERSI-II at Lake Qinghai, China
by Shengli Chen, Xiaobing Zheng, Xin Li, Wei Wei, Shenda Du and Fuxiang Guo
Sensors 2021, 21(1), 139; https://doi.org/10.3390/s21010139 - 28 Dec 2020
Cited by 10 | Viewed by 2589
Abstract
To calibrate the low signal response of the ocean color (OC) bands and test the stability of the Fengyun-3D (FY-3D)/Medium Resolution Spectral Imager II (MERSI-II), an absolute radiometric calibration field test of FY-3D/MERSI-II at the Lake Qinghai Radiometric Calibration Site (RCS) was carried [...] Read more.
To calibrate the low signal response of the ocean color (OC) bands and test the stability of the Fengyun-3D (FY-3D)/Medium Resolution Spectral Imager II (MERSI-II), an absolute radiometric calibration field test of FY-3D/MERSI-II at the Lake Qinghai Radiometric Calibration Site (RCS) was carried out in August 2018. The lake surface and atmospheric parameters were mainly measured by advanced observation instruments, and the MODerate spectral resolution atmospheric TRANsmittance algorithm and computer model (MODTRAN4.0) was used to simulate the multiple scattering radiance value at the altitude of the sensor. The results showed that the relative deviations between bands 9 and 12 are within 5.0%, while the relative deviations of bands 8, and 13 are 17.1%, and 12.0%, respectively. The precision of the calibration method was verified by calibrating the Aqua/Moderate-resolution Imaging Spectroradiometer (MODIS) and National Polar-orbiting Partnership (NPP)/Visible Infrared Imaging Radiometer (VIIRS), and the deviation of the calibration results was evaluated with the results of the Dunhuang RCS calibration and lunar calibration. The results showed that the relative deviations of NPP/VIIRS were within 7.0%, and the relative deviations of Aqua/MODIS were within 4.1% from 400 nm to 600 nm. The comparisons of three on-orbit calibration methods indicated that band 8 exhibited a large attenuation after launch and the calibration results had good consistency at the other bands except for band 13. The uncertainty value of the whole calibration system was approximately 6.3%, and the uncertainty brought by the field surface measurement reached 5.4%, which might be the main reason for the relatively large deviation of band 13. This study verifies the feasibility of the vicarious calibration method at the Lake Qinghai RCS and provides the basis and reference for the subsequent on-orbit calibration of FY-3D/MERSI-II. Full article
(This article belongs to the Special Issue Marine Sensors: Recent Advances and Challenges)
Show Figures

Figure 1

Figure 1
<p>Spectral response function of the FY-3D/MERSI-II.</p>
Full article ">Figure 2
<p>Flowchart of vicarious calibration method.</p>
Full article ">Figure 3
<p>The geometric diagram of the above method.</p>
Full article ">Figure 4
<p>Synchronous observation points at Lake Qinghai.</p>
Full article ">Figure 5
<p>Observation equipment used in the experiment: (<b>a</b>–<b>c</b>) an ASD FieldSpec4 spectrometer for acquiring water surface parameters; (<b>d</b>) a CE-318 automated sun photometer for measuring atmospheric parameters; (<b>e</b>) a GPS radiosonde for obtaining PTU.</p>
Full article ">Figure 6
<p>(<b>a</b>) Water-leaving radiance; (<b>b</b>) remote sensing reflectance.</p>
Full article ">Figure 7
<p>AOD (<b>a</b>) at 14:38 (UTC + 08:00), 18 August 2018; (<b>b</b>) at 14:43 (UTC + 08:00), 23 August 2018.</p>
Full article ">Figure 8
<p>Whitecap radiance.</p>
Full article ">Figure 9
<p>The curve of atmospheric PTU.</p>
Full article ">Figure 10
<p>(<b>a</b>) Atmospheric transmittance at 14:38 (UTC + 08:00), 18 August 2018; (<b>b</b>) atmospheric transmittance at 14:43 (UTC + 08:00), 23 August 2018; (<b>c</b>) multiple scattering radiance and normalized water-leaving radiance at 14:38 (UTC + 08:00), 18 August 2018; (<b>d</b>) multiple scattering radiance and normalized water-leaving radiance at 14:43 (UTC + 08:00), 23 August 2018.</p>
Full article ">Figure 11
<p>Satellite images: (<b>a</b>) 14:38 (UTC + 08:00), 18 August 2018; (<b>b</b>) 14:43 (UTC + 08:00), 23 August 2018.</p>
Full article ">Figure 12
<p>Calibration coefficients of three methods.</p>
Full article ">
Back to TopTop