A feasible framework to downscale NPP-VIIRS nighttime light imagery using multi-source spatial variables and geographically weighted regression
The cloud-free monthly composite of global nighttime light (NTL) data of the Suomi National Polar-orbiting Partnership with the Visible Infrared Imaging Radiometer Suite (NPP-VIIRS) day/night band (DNB) provides indispensable indications of human activities and settlements. However, the coarse spati...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2021-12-01
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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/S0303243421002208 |
| _version_ | 1829459202400059392 |
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| author | Yang Ye Linyan Huang Qiming Zheng Chenxin Liang Baiyu Dong Jinsong Deng Xiuzhen Han |
| author_facet | Yang Ye Linyan Huang Qiming Zheng Chenxin Liang Baiyu Dong Jinsong Deng Xiuzhen Han |
| author_sort | Yang Ye |
| collection | DOAJ |
| description | The cloud-free monthly composite of global nighttime light (NTL) data of the Suomi National Polar-orbiting Partnership with the Visible Infrared Imaging Radiometer Suite (NPP-VIIRS) day/night band (DNB) provides indispensable indications of human activities and settlements. However, the coarse spatial resolution (15 arc sec) of NTL imagery greatly restricts its application potential. This study proposes a feasible framework to downscale NPP-VIIRS NTL using muti-source spatial variables and geographically weighted regression (GWR) method. High-resolution auxiliary variables were acquired from the Landsat 8 OLI/ TIRS and social media platforms. GWR-based downscaling procedures were consequently implemented to obtain NTL at a 100-m resolution. The downscaled NTL data were validated against Loujia1-01 imagery based on the coefficient of determination (R2) and root-mean-square error (RMSE). The results suggest that the data quality was suitably improved after downscaling, yielding higher R2 (0.604 vs. 0.568) and lower RMSE (8.828 vs. 9.870 nW/cm2/sr) values than those of the original NTL data. Finally, the NTL was extendedly applied to detect impervious surfaces, and the downscaled NTL had higher accuracy than the original NTL. Therefore, this study facilitates data quality improvement of NPP-VIIRS NTL imagery by downscaling, thus enabling more accurate applications. |
| first_indexed | 2024-12-12T11:15:09Z |
| format | Article |
| id | doaj.art-b216a57224f64f638fc2b1c1e6ad95e3 |
| institution | Directory Open Access Journal |
| issn | 1569-8432 |
| language | English |
| last_indexed | 2024-12-12T11:15:09Z |
| publishDate | 2021-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | International Journal of Applied Earth Observations and Geoinformation |
| spelling | doaj.art-b216a57224f64f638fc2b1c1e6ad95e32022-12-22T00:26:10ZengElsevierInternational Journal of Applied Earth Observations and Geoinformation1569-84322021-12-01104102513A feasible framework to downscale NPP-VIIRS nighttime light imagery using multi-source spatial variables and geographically weighted regressionYang Ye0Linyan Huang1Qiming Zheng2Chenxin Liang3Baiyu Dong4Jinsong Deng5Xiuzhen Han6College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, ChinaBusiness College, Zhejiang University City College, Hangzhou 310015, ChinaCentre for Nature-Based Climate Solutions, Department of Biological Sciences, National University of Singapore, Singapore 117558, SingaporeCollege of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, ChinaCollege of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, ChinaCollege of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China; Correspondence author.National Satellite Meteorological Centre, China Meteorological Administration, Beijing 100081, China; Correspondence author.The cloud-free monthly composite of global nighttime light (NTL) data of the Suomi National Polar-orbiting Partnership with the Visible Infrared Imaging Radiometer Suite (NPP-VIIRS) day/night band (DNB) provides indispensable indications of human activities and settlements. However, the coarse spatial resolution (15 arc sec) of NTL imagery greatly restricts its application potential. This study proposes a feasible framework to downscale NPP-VIIRS NTL using muti-source spatial variables and geographically weighted regression (GWR) method. High-resolution auxiliary variables were acquired from the Landsat 8 OLI/ TIRS and social media platforms. GWR-based downscaling procedures were consequently implemented to obtain NTL at a 100-m resolution. The downscaled NTL data were validated against Loujia1-01 imagery based on the coefficient of determination (R2) and root-mean-square error (RMSE). The results suggest that the data quality was suitably improved after downscaling, yielding higher R2 (0.604 vs. 0.568) and lower RMSE (8.828 vs. 9.870 nW/cm2/sr) values than those of the original NTL data. Finally, the NTL was extendedly applied to detect impervious surfaces, and the downscaled NTL had higher accuracy than the original NTL. Therefore, this study facilitates data quality improvement of NPP-VIIRS NTL imagery by downscaling, thus enabling more accurate applications.http://www.sciencedirect.com/science/article/pii/S0303243421002208Nighttime light (NTL)DownscalingGeographically weighted regression (GWR)Impervious surface detection |
| spellingShingle | Yang Ye Linyan Huang Qiming Zheng Chenxin Liang Baiyu Dong Jinsong Deng Xiuzhen Han A feasible framework to downscale NPP-VIIRS nighttime light imagery using multi-source spatial variables and geographically weighted regression International Journal of Applied Earth Observations and Geoinformation Nighttime light (NTL) Downscaling Geographically weighted regression (GWR) Impervious surface detection |
| title | A feasible framework to downscale NPP-VIIRS nighttime light imagery using multi-source spatial variables and geographically weighted regression |
| title_full | A feasible framework to downscale NPP-VIIRS nighttime light imagery using multi-source spatial variables and geographically weighted regression |
| title_fullStr | A feasible framework to downscale NPP-VIIRS nighttime light imagery using multi-source spatial variables and geographically weighted regression |
| title_full_unstemmed | A feasible framework to downscale NPP-VIIRS nighttime light imagery using multi-source spatial variables and geographically weighted regression |
| title_short | A feasible framework to downscale NPP-VIIRS nighttime light imagery using multi-source spatial variables and geographically weighted regression |
| title_sort | feasible framework to downscale npp viirs nighttime light imagery using multi source spatial variables and geographically weighted regression |
| topic | Nighttime light (NTL) Downscaling Geographically weighted regression (GWR) Impervious surface detection |
| url | http://www.sciencedirect.com/science/article/pii/S0303243421002208 |
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