Enhancing spatial resolution of drought monitoring through a novel random forest-based GRACE drought index: a case study in Central Yunnan

The original coarse spatial resolution of Gravity Recovery and Climate Experiment (GRACE) data limits its application in small and medium-scale areas. The study proposes a novel random forest-based GRACE drought index (NRFGDI) to enhance the spatial resolution of drought monitoring, which is applied...

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Main Authors: Xia Wang, Wei Zheng, Wenjie Yin, Keke Xu, Hebing Zhang, Weiwei Lei
Format: Article
Language:English
Published: Taylor & Francis Group 2024-01-01
Series:Geocarto International
Subjects:
Online Access:https://www.tandfonline.com/doi/10.1080/10106049.2024.2387784
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author Xia Wang
Wei Zheng
Wenjie Yin
Keke Xu
Hebing Zhang
Weiwei Lei
author_facet Xia Wang
Wei Zheng
Wenjie Yin
Keke Xu
Hebing Zhang
Weiwei Lei
author_sort Xia Wang
collection DOAJ
description The original coarse spatial resolution of Gravity Recovery and Climate Experiment (GRACE) data limits its application in small and medium-scale areas. The study proposes a novel random forest-based GRACE drought index (NRFGDI) to enhance the spatial resolution of drought monitoring, which is applied to central Yunnan. We first employed the random forest (RF) algorithm to improve the spatial resolution of GRACE-derived terrestrial water storage anomaly (TWSA) to 0.1°, then established the NRFGDI based on the downscaled TWSA. Subsequently, the NRFGDI was verified using traditional drought indexes, including the standardized precipitation evapotranspiration index (SPEI) and the self-calibrating Palmer drought severity index (sc-PDSI), along with the 2009/2010 Bulletin of Flood and Drought Disasters in China. The NRFGDI not only captures drought characteristics, but also offers finer spatial resolution. The study provides an effective means for medium to small-scale drought monitoring, thereby making valuable contributions to decision-making processes concerning droughts in central Yunnan.
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institution OA Journals
issn 1010-6049
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language English
publishDate 2024-01-01
publisher Taylor & Francis Group
record_format Article
series Geocarto International
spelling doaj-art-e1cb4fdce81d4d30b2ea3034c3cbeb3c2025-08-20T02:38:26ZengTaylor & Francis GroupGeocarto International1010-60491752-07622024-01-0139110.1080/10106049.2024.2387784Enhancing spatial resolution of drought monitoring through a novel random forest-based GRACE drought index: a case study in Central YunnanXia Wang0Wei Zheng1Wenjie Yin2Keke Xu3Hebing Zhang4Weiwei Lei5School of Surveying and Landing Information Engineering, Henan Polytechnic University, Jiaozuo, ChinaSchool of Surveying and Landing Information Engineering, Henan Polytechnic University, Jiaozuo, ChinaMinistry of Ecology and Environment Center for Satellite Application on Ecology and Environment, Beijing, ChinaSchool of Surveying and Landing Information Engineering, Henan Polytechnic University, Jiaozuo, ChinaSchool of Surveying and Landing Information Engineering, Henan Polytechnic University, Jiaozuo, ChinaSchool of Surveying and Landing Information Engineering, Henan Polytechnic University, Jiaozuo, ChinaThe original coarse spatial resolution of Gravity Recovery and Climate Experiment (GRACE) data limits its application in small and medium-scale areas. The study proposes a novel random forest-based GRACE drought index (NRFGDI) to enhance the spatial resolution of drought monitoring, which is applied to central Yunnan. We first employed the random forest (RF) algorithm to improve the spatial resolution of GRACE-derived terrestrial water storage anomaly (TWSA) to 0.1°, then established the NRFGDI based on the downscaled TWSA. Subsequently, the NRFGDI was verified using traditional drought indexes, including the standardized precipitation evapotranspiration index (SPEI) and the self-calibrating Palmer drought severity index (sc-PDSI), along with the 2009/2010 Bulletin of Flood and Drought Disasters in China. The NRFGDI not only captures drought characteristics, but also offers finer spatial resolution. The study provides an effective means for medium to small-scale drought monitoring, thereby making valuable contributions to decision-making processes concerning droughts in central Yunnan.https://www.tandfonline.com/doi/10.1080/10106049.2024.2387784Novel random forest-based GRACE drought indexterrestrial water storage anomalyspatial resolution enhancementsoil moisturedrought monitoring
spellingShingle Xia Wang
Wei Zheng
Wenjie Yin
Keke Xu
Hebing Zhang
Weiwei Lei
Enhancing spatial resolution of drought monitoring through a novel random forest-based GRACE drought index: a case study in Central Yunnan
Geocarto International
Novel random forest-based GRACE drought index
terrestrial water storage anomaly
spatial resolution enhancement
soil moisture
drought monitoring
title Enhancing spatial resolution of drought monitoring through a novel random forest-based GRACE drought index: a case study in Central Yunnan
title_full Enhancing spatial resolution of drought monitoring through a novel random forest-based GRACE drought index: a case study in Central Yunnan
title_fullStr Enhancing spatial resolution of drought monitoring through a novel random forest-based GRACE drought index: a case study in Central Yunnan
title_full_unstemmed Enhancing spatial resolution of drought monitoring through a novel random forest-based GRACE drought index: a case study in Central Yunnan
title_short Enhancing spatial resolution of drought monitoring through a novel random forest-based GRACE drought index: a case study in Central Yunnan
title_sort enhancing spatial resolution of drought monitoring through a novel random forest based grace drought index a case study in central yunnan
topic Novel random forest-based GRACE drought index
terrestrial water storage anomaly
spatial resolution enhancement
soil moisture
drought monitoring
url https://www.tandfonline.com/doi/10.1080/10106049.2024.2387784
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