Title :
Relationships Between Remote-Sensing-Based Agricultural Drought Indicators and Root Zone Soil Moisture: A Comparative Study of Iowa
Author :
Chunming Peng ; Meixia Deng ; Liping Di
Author_Institution :
George Mason Univ., Fairfax, VA, USA
Abstract :
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).
Keywords :
crops; hydrology; soil; vegetation mapping; Iowa; agricultural drought analysis; agricultural drought monitoring; canopies; corn; drought forecasting; drought indicator; enhanced vegetation index; lagging periods; normalized difference drought index; normalized difference vegetation index; normalized difference water index; remote-sensing-based agricultural drought indicators; root zone soil moisture; soil climate analysis network sites; soil moisture levels; soil moisture memory; soybeans; Agriculture; Indexes; Monitoring; Remote sensing; Soil moisture; Stress; Vegetation mapping; Agriculture; Earth; remote sensing (RS);
Journal_Title :
Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of
DOI :
10.1109/JSTARS.2014.2344115