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      정규화 적설지수의 대기보정 영향 분석: 토지피복별 NDSI 변화 및 적설탐지 특성 = Atmospheric Correction Effects on the NDSI: Snow Detection Characteristics across Land Cover Types

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      https://www.riss.kr/link?id=A109368758

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      The normalized difference snow index (NDSI) is a key indicator used to identify and map snow-covered areas by normalizing the reflectance difference between visible and shortwave infrared bands detected by satellite sensors. This study analyzed the effects of atmospheric correction on NDSI and snow cover detection characteristics according to land cover types. The study used data from the geostationary satellite (GK-2A/AMI) from November 2022 to April 2023. Comparing top-of-atmosphere (TOA) reflectance-based NDSI (NDSITOA) and top-of-canopy (TOC) reflectance-based NDSI (NDSITOC), NDSITOC generally showed higher values. Time series analysis revealed that the difference between the two NDSI values was relatively high when the snow-covered area was extensive. Comparison with S-NPP/VIIRS snow cover showed that NDSITOC-based snow detection had a higher agreement rate than NDSITOA-based snow detection (NDSITOA 72.36%, NDSITOC 75.88%). Analysis by land cover type showed the highest snow cover detection agreement rate in grasslands and croplands, while forest areas showed the lowest agreement rate. These findings emphasize the importance of atmospheric correction in NDSIbased snow cover detection and confirm the need for a customized approach considering land cover characteristics. This study provides a foundation for offering more reliable snow cover information in various fields such as climate change research, water resource management, aviation weather forecasting, and disaster management.
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      The normalized difference snow index (NDSI) is a key indicator used to identify and map snow-covered areas by normalizing the reflectance difference between visible and shortwave infrared bands detected by satellite sensors. This study analyzed the ef...

      The normalized difference snow index (NDSI) is a key indicator used to identify and map snow-covered areas by normalizing the reflectance difference between visible and shortwave infrared bands detected by satellite sensors. This study analyzed the effects of atmospheric correction on NDSI and snow cover detection characteristics according to land cover types. The study used data from the geostationary satellite (GK-2A/AMI) from November 2022 to April 2023. Comparing top-of-atmosphere (TOA) reflectance-based NDSI (NDSITOA) and top-of-canopy (TOC) reflectance-based NDSI (NDSITOC), NDSITOC generally showed higher values. Time series analysis revealed that the difference between the two NDSI values was relatively high when the snow-covered area was extensive. Comparison with S-NPP/VIIRS snow cover showed that NDSITOC-based snow detection had a higher agreement rate than NDSITOA-based snow detection (NDSITOA 72.36%, NDSITOC 75.88%). Analysis by land cover type showed the highest snow cover detection agreement rate in grasslands and croplands, while forest areas showed the lowest agreement rate. These findings emphasize the importance of atmospheric correction in NDSIbased snow cover detection and confirm the need for a customized approach considering land cover characteristics. This study provides a foundation for offering more reliable snow cover information in various fields such as climate change research, water resource management, aviation weather forecasting, and disaster management.

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