Hyperspectral Remote Sensing of Saline Soils in Arid and Semi-Arid Environments

Remote sensing of saline soils has been an active area of research in the past few decades. This is particularly so as soil salinity is a major environmental geo-hazard in both agricultural lands and arid and semi-arid regions. Saline soil adversely affect soil and play a major role in soil erosion, dispersion and degradation. Furthermore, saline soils in arid and semi-arid regions lead, in certain situations, to land subsidence, and ground upheaval. In agricultural lands saline soils lead to reduced agricultural productivity, interference with plant nutrition and soil erosion.

Mapping saline soils is carried out using various techniques and procedures ranging from direct field observations and sampling to space based remote sensing techniques. Traditional methods of measuring soil salinity are time-consuming and labor intensive, making remote sensing techniques an attractive alternative. Remote sensing provides a less costly procedure due to the large global spatial coverage, continuous repetitive coverage and high-quality earth observations. Most of the remote sensing of saline soils previous research have focused on the broad band remote sensing part with primary focus on the spectral ranges in the near infra-red and the short-wave infra-red. However, higher levels of detection accuracy has not been widely achieved.

In comparison to broad band remote sensing data, hyperspectral remotely sensed data provides an alternative approach that is much more accurate in detection levels of saline soils and their spatial distribution. This research employed a hand-held hyperspectral sensor specifically the SVC-XHR-1024i to collect reflectance data over various samples of soils collected in western United Arab Emirates. The collected data were then processed to derive spectral indices that are sensitive to soil salinity. Laboratory measurements of electrical conductivity (EC) of soil water extracts were carried out for the corresponding soil samples. The study established a statistical relationship between measured soil hyperspectral reflectance and EC salinity values. The study findings indicate that the spectral ranges in the shortwave infrared (SWIR) and near-infrared (NIR) are crucial and optimal in detecting soil salinity, in comparison to any other spectral ranges. An accuracy of 71% in detecting saline soils, including salt flats, was achieved through the use of narrow band hyperspectral data at the SWIR and NIR ranges. This by far exceeds accuracy levels that were previously achieved using broad band remote sensing data. The study also, highlights the potential of hyperspectral remote sensing as a cost-effective and efficient tool for monitoring soil salinity and identifying areas at risk of salinization, which can inform land management strategies for sustainable agriculture and future land development.