Optimal Selection of Agricultural Lands Using Remote Sensing Techniques in the Analysis of Climate Data, Wasit Province, Iraq

Abstract

     Determining the optimal location for crop cultivation is a challenging task, as agriculture plays a significant role in economic development and efficient land use. Therefore, remote sensing techniques using satellite imagery have proven to be an excellent method for helping researchers make this choice. To achieve the goal of optimal selection, climate data, including temperature and rainfall, for the study area were collected. The city of Kut, located in central Iraq, was identified as a study area due to its geographical importance, distinguished administrative location, and the vast agricultural areas that can be exploited. These data were projected onto high-resolution satellite images obtained by Sentinel-2 (10 m). The spline interpolation technique was applied to a climatic data set to estimate the other missing points. Supervised classification using the support vector machine technique was performed to exclude agricultural areas from urban projects. Some important indices related to plant health and water content were implemented, which help illustrate soil suitability and quality of cultivated plants. These indices include the normalized difference vegetation index (NDVI), which provides a good indication of reach (0.6), and the normalized difference water index (NDWI), which yields a value of 0.34, considered a good value. Slope computation was applied to show the rate of ground gradient. The research results successfully estimate the optimal area for growing various types of crops.