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Combination of multi-sensor remote sensing data for drought monitoring over Southwest China.

, , and . Int. J. Appl. Earth Obs. Geoinformation, (2015)

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Deep Learning for Monitoring Agricultural Drought in South Asia Using Remote Sensing Data., , , , , , , , , and . Remote. Sens., 13 (9): 1715 (2021)Evaluation of Temperature Vegetation Dryness Index on Drought Monitoring Over Eurasia., , , and . IEEE Access, (2020)Regional Assessment of Climate Potential Productivity of Terrestrial Ecosystems and Its Responses to Climate Change Over China From 1980-2018., , , , , , , , and . IEEE Access, (2020)Crop Area Identification Based on Time Series EVI2 and Sparse Representation Approach: A Case Study in Shandong Province, China., , , , and . IEEE Access, (2019)The response and sensitivity of global vegetation to water stress: A comparison of different satellite-based NDVI products., , , , , , , and . Int. J. Appl. Earth Obs. Geoinformation, (June 2023)MODIS Satellite Data Coupled with a Vegetation Process Model for Mapping Maize Yield in the Northeast China., and . GRMSE (2), volume 399 of Communications in Computer and Information Science, page 214-222. Springer, (2013)Genetic Programming Guided Mapping of Forest Canopy Height by Combining LiDAR Satellites with Sentinel-1/2, Terrain, and Climate Data., , , , , and . Remote. Sens., 16 (1): 110 (January 2024)Combination of multi-sensor remote sensing data for drought monitoring over Southwest China., , and . Int. J. Appl. Earth Obs. Geoinformation, (2015)Mapping cotton cultivated area combining remote sensing with a fused representation-based classification algorithm., , , , , and . Comput. Electron. Agric., (2021)The Impact of Seasonality and Response Period on Qualifying the Relationship between Ecosystem Productivity and Climatic Factors over the Eurasian Steppe., , , , , and . Remote. Sens., 13 (16): 3159 (2021)