SOIL MOISTURE PREDICTION WITH MULTISPECTRAL VISIBLE AND NIR REMOTE SENSING

Abstract

Water is a valuable resource and an understanding of soil moisture dynamics is critical in many land management, agricultural and engineering applications. Satellite and UAV remote sensing platforms present an opportunity for rapid, cost-efficient data collection; however, soil moisture remote sensing presents unique challenges. Specifically, spectral bands near 1400nm and 1900nm associated with water are typically avoided in remote sensing data products due to strong interference by atmospheric moisture. Using soil reflectance data collected in the lab, this paper presents a number of linear equations which maybe be applied to predict soil moisture content from Landsat 5 MSS, 7 TM and 9 data, as well as other NIR sensors collecting data at 1720, 1782, 2140 and 2240nm.