Soil salinity characteristics using moderate resolution imaging spectroradiometer (MODIS) images and statistical analysis

Abstract

Remote sensing is currently a tremendous asset in controlling and monitoring soil salinity. Moderate resolution imaging spectroradiometer (MODIS) images can be obtained daily, are free, offer more opportunities to acquire cloud-free images and may be preferred over high-resolution spatial data. The main objective of this study was to evaluate the capability of MODIS imagery to assess soil properties when coupled with field soil sampling. The study area was ∼95,000 ha, located in the south-east of Fars Province, Iran. In total, 240 soil samples were selected from 60 georeferenced soil pits, following a stratified random sampling approach. Sixteen spectral indices were calculated from a nadir-viewed MODIS scene to establish statistical correlation models between measured soil properties and MODIS band values. A precise map of the soil properties was produced using geostatistical techniques. A paired-sample t-test indicates that there are no significant differences between values estimated using MODIS data statistical modeling and laboratory-measured soil properties of samples collected through fieldwork. The results also indicate that image transformation (salinity index (SI) to radiance) reduces estimation errors and increases both model efficiency and the R ² of the models. The results also indicate that MODIS imagery provides useful information on soil properties.

Keywords:

• MODIS
• statistical models
• soil salinity
• Iran