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ISSN: 2574 -1241

Research ArticleOpen Access

Examining the Spatial and Temporal Variability of Soil Moisture in Kentucky Using Remote Sensing Data

Volume 1 - Issue 7

Bassil El Masri*

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    • Department of Geosciences, Murray State University, USA

    *Corresponding author:Bassil El Masri, Department of Geosciences, Murray State University, Murray, KY, USA, 42071; Email: belmasri@murraystate.edu

Received: December 01, 2017;   Published: December 18, 2017

DOI: 10.26717/BJSTR.2017.01.000604

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Abstract

Soil moisture is a key variable of the climate system and plays an important role in local, regional and global climates. It constrains vegetation photosynthesis, respiration and transpiration in many regions of the world. However, large-scale and long-term observation of soil moisture is sparse. The main objective of the paper is to investigate the spatial and temporal variability in remote sensing soil moisture for the State of Kentucky. The observed trends in satellite soil moisture estimates for different Kentucky biome types are analyzed. To accomplish this task soil moisture data from Advanced Microwave and Scanning Radiometer (AMSR-E) for years 2002-2011 are used. Daily AMSR-E data are averaged to produce monthly estimates. Moderate Resolution Imagining Spectroradiometer (MODIS) Land cover data are used to subset the AMSR-E data for the major Kentucky biomes: Forest and cropland. Results show that the spatial variability of soil moisture is related to vegetation type. AMSR-E soil moisture data shows an apparent decreasing trend in KY soil moisture during the vegetation growing season. This trend is consistent with observed decrease in the precipitation duration during the growing season in KY, particularly from July to September. In conclusion, AMSR-E soil moisture data are capable of detecting the spatial and temporal variability in soil moisture for KY biomes. Evaluating satellite soil moisture products is important for improving our understanding of the spatial variability in vegetation carbon and water cycles.

Abstract| Introduction| Methods Satellite Data| Statistical Analysis| Results and Discussion| References|