Journal of Remote Sensing & GIS

Joseph Essamuah–Quansah

Publications

• Research Article
  Estimation of Soil Moisture Percentage Using LANDSAT-based Moisture Stress Index
  Author(s): Pauline Welikhe, Joseph Essamuah–Quansah, Souleymane Fall and Wendell McElhenney Pauline Welikhe, Joseph Essamuah–Quansah, Souleymane Fall and Wendell McElhenney
  
  The global agronomy community needs quick and frequent information on soil moisture variability and spatial trends in order to maximize crop production to meet growing food demands in a changing climate. However, in situ soil moisture measurement is expensive and labor intensive. Remote sensing based biophysical and predictive regression modeling approach have the potential for efficiently estimating soil moisture content over large areas. The study investigates the use of Moisture Stress Index (MSI) to estimate soil moisture variability in Alabama. In situ data were obtained from Soil Climate Analysis Network (SCAN) sites in Alabama and MSI developed from LANDSAT 8 OLI and LANDSAT 5 TM data. Pearson product moment correlation analysis showed that MSI strongly correlates with 16-day average growing season soil moisture measurements, with negative correlations of -0.519, -0.482 and -0... View More»
  DOI: 10.4172/2469-4134.1000200

  Abstract PDF