Spatial Downscaling and Gap-Filling of SMAP Soil Moisture to High Resolution Using MODIS Surface Variables and Machine Learning Approaches over ShanDian River Basin, China

Spatial Downscaling and Gap-Filling of SMAP Soil Moisture to High Resolution Using MODIS Surface Variables and Machine Learning Approaches over ShanDian River Basin, China

High-resolution soil moisture (SM) information is essential for regional to global hydrological and agricultural applications. The Soil Moisture Active Passive (SMAP) offers daily global composites of SM at coarse-resolution 9 and 36 km, with data gaps limiting its local application to depict SM dis...

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Bibliographic Details
Main Authors: Adeel Ahmad Nadeem, Yuanyuan Zha, Liangsheng Shi, Shoaib Ali, Xi Wang, Zeeshan Zafar, Zeeshan Afzal, Muhammad Atiq Ur Rehman Tariq
Format: Article
Language:English
Published: MDPI AG 2023-01-01
Series:Remote Sensing
Subjects:
SMAP soil moisture
artificial neural network
random forest
downscaling
gap-filling
ShanDian River Basin
Online Access:https://www.mdpi.com/2072-4292/15/3/812

Internet

https://www.mdpi.com/2072-4292/15/3/812

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