Investigating snow cover duration changes based on a cloud-free snow cover product developed using a spatiotemporal cloud removal method for Northeast China
Optical remote sensing satellites have great potential for detecting long-term and large-scale snow cover properties with minimal manual effort. However, cloud contamination makes it challenging to obtain snow cover extent using optical sensors. To address this issue, we develop a series of spatiote...
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2025-08-01
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| Series: | International Journal of Digital Earth |
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| Online Access: | https://www.tandfonline.com/doi/10.1080/17538947.2025.2497520 |
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| author | Dajiang Yan Yinsheng Zhang |
| author_facet | Dajiang Yan Yinsheng Zhang |
| author_sort | Dajiang Yan |
| collection | DOAJ |
| description | Optical remote sensing satellites have great potential for detecting long-term and large-scale snow cover properties with minimal manual effort. However, cloud contamination makes it challenging to obtain snow cover extent using optical sensors. To address this issue, we develop a series of spatiotemporal cloud-clearing processes to mitigate cloud contamination based on Moderate Resolution Imaging Spectroradiometer (MODIS) snow products. A 21-year daily gap-filled snow cover dataset over Northeast China from the snow years of 2000–2020 is generated and validated against China Meteorological Administration-classified snow depth observations and Landsat images, achieving mean overall accuracies of 92.47% and 90.54%, respectively. The annual snow cover duration (SCD) calculated on the basis of this gap-filled snow cover product revealed an overall decreasing trend, with a rate of decrease of 1.044 days per year. The rate of decrease in the seasonal SCD was most significant in spring, followed by that in winter and autumn. The correlation between changes in SCD and changes in snowfall is stronger than the correlation between SCD changes and air temperature changes, indicating that SCD is more sensitive to changes in snowfall, which could have significant implications for our understanding of climate change and its impact on snow cover. |
| format | Article |
| id | doaj-art-f249fcbc9a894c03b7caa5434dbaaf67 |
| institution | Kabale University |
| issn | 1753-8947 1753-8955 |
| language | English |
| publishDate | 2025-08-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | International Journal of Digital Earth |
| spelling | doaj-art-f249fcbc9a894c03b7caa5434dbaaf672025-08-25T11:31:42ZengTaylor & Francis GroupInternational Journal of Digital Earth1753-89471753-89552025-08-0118110.1080/17538947.2025.2497520Investigating snow cover duration changes based on a cloud-free snow cover product developed using a spatiotemporal cloud removal method for Northeast ChinaDajiang Yan0Yinsheng Zhang1Key Laboratory of Tibetan Environmental Changes and land Surfaces Processes, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, People’s Republic of ChinaKey Laboratory of Tibetan Environmental Changes and land Surfaces Processes, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, People’s Republic of ChinaOptical remote sensing satellites have great potential for detecting long-term and large-scale snow cover properties with minimal manual effort. However, cloud contamination makes it challenging to obtain snow cover extent using optical sensors. To address this issue, we develop a series of spatiotemporal cloud-clearing processes to mitigate cloud contamination based on Moderate Resolution Imaging Spectroradiometer (MODIS) snow products. A 21-year daily gap-filled snow cover dataset over Northeast China from the snow years of 2000–2020 is generated and validated against China Meteorological Administration-classified snow depth observations and Landsat images, achieving mean overall accuracies of 92.47% and 90.54%, respectively. The annual snow cover duration (SCD) calculated on the basis of this gap-filled snow cover product revealed an overall decreasing trend, with a rate of decrease of 1.044 days per year. The rate of decrease in the seasonal SCD was most significant in spring, followed by that in winter and autumn. The correlation between changes in SCD and changes in snowfall is stronger than the correlation between SCD changes and air temperature changes, indicating that SCD is more sensitive to changes in snowfall, which could have significant implications for our understanding of climate change and its impact on snow cover.https://www.tandfonline.com/doi/10.1080/17538947.2025.2497520Snow covercloud removalsnow cover durationmodisnortheast china |
| spellingShingle | Dajiang Yan Yinsheng Zhang Investigating snow cover duration changes based on a cloud-free snow cover product developed using a spatiotemporal cloud removal method for Northeast China International Journal of Digital Earth Snow cover cloud removal snow cover duration modis northeast china |
| title | Investigating snow cover duration changes based on a cloud-free snow cover product developed using a spatiotemporal cloud removal method for Northeast China |
| title_full | Investigating snow cover duration changes based on a cloud-free snow cover product developed using a spatiotemporal cloud removal method for Northeast China |
| title_fullStr | Investigating snow cover duration changes based on a cloud-free snow cover product developed using a spatiotemporal cloud removal method for Northeast China |
| title_full_unstemmed | Investigating snow cover duration changes based on a cloud-free snow cover product developed using a spatiotemporal cloud removal method for Northeast China |
| title_short | Investigating snow cover duration changes based on a cloud-free snow cover product developed using a spatiotemporal cloud removal method for Northeast China |
| title_sort | investigating snow cover duration changes based on a cloud free snow cover product developed using a spatiotemporal cloud removal method for northeast china |
| topic | Snow cover cloud removal snow cover duration modis northeast china |
| url | https://www.tandfonline.com/doi/10.1080/17538947.2025.2497520 |
| work_keys_str_mv | AT dajiangyan investigatingsnowcoverdurationchangesbasedonacloudfreesnowcoverproductdevelopedusingaspatiotemporalcloudremovalmethodfornortheastchina AT yinshengzhang investigatingsnowcoverdurationchangesbasedonacloudfreesnowcoverproductdevelopedusingaspatiotemporalcloudremovalmethodfornortheastchina |