期刊
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
卷 7, 期 11, 页码 4572-4580出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JSTARS.2014.2344115
关键词
Agriculture; Earth; remote sensing (RS)
类别
资金
- NASA
- NOAA [NA09NES4280007]
Remote-sensing (RS)-based agricultural drought indicators, such as the normalized difference vegetation index (NDVI), normalized difference water index (NDWI), enhanced vegetation index (EVI), and normalized difference drought index (NDDI), have been popularly used in agricultural drought monitoring, analysis and related applications. Understanding the relationships between these indicators and root zone soil moisture under different canopies will help reduce uncertainties and enhance reliability of estimating soil moisture levels over a large area, and thus improve the accuracy in drought monitoring, analysis, and forecasting. This research aims to investigate such relationships and choose a drought indicator that best correlates with soil moisture observed at various depths from the soil climate analysis network (SCAN) sites, with 0-64 days of lagging periods. Results from the study show that the indicators applied to corn led to statistically significant correlations with soil moisture at deeper depths and also the soil moisture memory can be kept for a long period of time (32-48 days), while the indicators applied to soybeans correlated best with soil moisture at shallower depths and the soil moisture memory can only be kept for a short time (concurrent to 16 days).
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