Estimation of fractional cover based on NDVI-VISI response space using visible-near infrared satellite imagery
Remote sensing observations of green vegetation (GV), impervious surface (IS), and bare soil (BS) fractional cover are essential for understanding climate change, characterizing ecosystem functions, monitoring urbanization process. As an important indicator of urbanization, the continuous increase o...
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| Format: | Article |
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Elsevier
2025-03-01
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| Series: | International Journal of Applied Earth Observations and Geoinformation |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S1569843225000792 |
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| author | Zhaoyang Han Qingjiu Tian Jia Tian Tianyu Zhao Chenglong Xu Qing Zhou |
| author_facet | Zhaoyang Han Qingjiu Tian Jia Tian Tianyu Zhao Chenglong Xu Qing Zhou |
| author_sort | Zhaoyang Han |
| collection | DOAJ |
| description | Remote sensing observations of green vegetation (GV), impervious surface (IS), and bare soil (BS) fractional cover are essential for understanding climate change, characterizing ecosystem functions, monitoring urbanization process. As an important indicator of urbanization, the continuous increase of impervious surfaces alters the radiative transfer process at the surface, causing a series of environmental problems. Therefore, timely and accurate monitoring of the spatial and temporal changes in impervious surfaces and their impact on the ecological environment is of great significance for a comprehensive understanding of the process of urbanization as well as for the planning and construction of future cities. This study aims to propose a generalized method for the accurate estimation of GV, IS, and BS coverage. In this study, the visible impervious surface index (VISI), (Br-Bg)/(Br+Bg), was developed using measured spectral data of GV, IS, and BS, and analyzing their spectral characteristics to determine the spectral bands where they can be distinguished. Furthermore, the VISI combined with the NDVI was utilized to establish a triangular space for linear unmixing of the satellite image data to estimate the coverage of its GV, IS, and BS. Finally, the generalizability of this method was verified using UAV and satellite image data, with pearson correlation coefficient > 0.69. The results demonstrate that the VISI index proposed in this study is feasible for long-term series of multispectral imagery and large-scale coverage estimation. |
| format | Article |
| id | doaj-art-647e06b9247042749d87bce8fd7d03d5 |
| institution | DOAJ |
| issn | 1569-8432 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Elsevier |
| record_format | Article |
| series | International Journal of Applied Earth Observations and Geoinformation |
| spelling | doaj-art-647e06b9247042749d87bce8fd7d03d52025-08-20T03:05:39ZengElsevierInternational Journal of Applied Earth Observations and Geoinformation1569-84322025-03-0113710443210.1016/j.jag.2025.104432Estimation of fractional cover based on NDVI-VISI response space using visible-near infrared satellite imageryZhaoyang Han0Qingjiu Tian1Jia Tian2Tianyu Zhao3Chenglong Xu4Qing Zhou5International Institute for Earth System Science, Nanjing University, Nanjing 210023, China; Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, Nanjing University, Nanjing 210023, ChinaInternational Institute for Earth System Science, Nanjing University, Nanjing 210023, China; Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, Nanjing University, Nanjing 210023, China; Corresponding authors at: International Institute for Earth System Science, Nanjing University, Nanjing 210023, China (Q. Tian). School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing 100191, China (J. Tian).School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing 100191, China; Corresponding authors at: International Institute for Earth System Science, Nanjing University, Nanjing 210023, China (Q. Tian). School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing 100191, China (J. Tian).School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing 100191, ChinaInternational Institute for Earth System Science, Nanjing University, Nanjing 210023, China; Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, Nanjing University, Nanjing 210023, ChinaInternational Institute for Earth System Science, Nanjing University, Nanjing 210023, China; Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, Nanjing University, Nanjing 210023, ChinaRemote sensing observations of green vegetation (GV), impervious surface (IS), and bare soil (BS) fractional cover are essential for understanding climate change, characterizing ecosystem functions, monitoring urbanization process. As an important indicator of urbanization, the continuous increase of impervious surfaces alters the radiative transfer process at the surface, causing a series of environmental problems. Therefore, timely and accurate monitoring of the spatial and temporal changes in impervious surfaces and their impact on the ecological environment is of great significance for a comprehensive understanding of the process of urbanization as well as for the planning and construction of future cities. This study aims to propose a generalized method for the accurate estimation of GV, IS, and BS coverage. In this study, the visible impervious surface index (VISI), (Br-Bg)/(Br+Bg), was developed using measured spectral data of GV, IS, and BS, and analyzing their spectral characteristics to determine the spectral bands where they can be distinguished. Furthermore, the VISI combined with the NDVI was utilized to establish a triangular space for linear unmixing of the satellite image data to estimate the coverage of its GV, IS, and BS. Finally, the generalizability of this method was verified using UAV and satellite image data, with pearson correlation coefficient > 0.69. The results demonstrate that the VISI index proposed in this study is feasible for long-term series of multispectral imagery and large-scale coverage estimation.http://www.sciencedirect.com/science/article/pii/S1569843225000792Fractional coverImpervious surfacesLinear unmixingVisible impervious surface index (VISI)NDVI-VISI response space |
| spellingShingle | Zhaoyang Han Qingjiu Tian Jia Tian Tianyu Zhao Chenglong Xu Qing Zhou Estimation of fractional cover based on NDVI-VISI response space using visible-near infrared satellite imagery International Journal of Applied Earth Observations and Geoinformation Fractional cover Impervious surfaces Linear unmixing Visible impervious surface index (VISI) NDVI-VISI response space |
| title | Estimation of fractional cover based on NDVI-VISI response space using visible-near infrared satellite imagery |
| title_full | Estimation of fractional cover based on NDVI-VISI response space using visible-near infrared satellite imagery |
| title_fullStr | Estimation of fractional cover based on NDVI-VISI response space using visible-near infrared satellite imagery |
| title_full_unstemmed | Estimation of fractional cover based on NDVI-VISI response space using visible-near infrared satellite imagery |
| title_short | Estimation of fractional cover based on NDVI-VISI response space using visible-near infrared satellite imagery |
| title_sort | estimation of fractional cover based on ndvi visi response space using visible near infrared satellite imagery |
| topic | Fractional cover Impervious surfaces Linear unmixing Visible impervious surface index (VISI) NDVI-VISI response space |
| url | http://www.sciencedirect.com/science/article/pii/S1569843225000792 |
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