GIS Modeling Incorporated with Python Programming Language to Determinate Land Productivity Index

Abstract

In order to assess the soil productivity in the Northern section of Sohag Governorate, Egypt, a thorough soil survey conducted. For this, Thirty-four profiles, including old-cultivated, new-cultivated, and barren soils, represented three different agricultural land uses. The profiles selected, and samples taken from each horizon and examined for their physical and chemical characteristics. The Land Productivity Index (LPI) utilized to assess soil productivity. The index individually calculated by each of the earlier studies. However, this procedure takes a long time and is challenging, especially when there are many soil samples. After that, using a weighted overlay tool, create a final map of the productivity index overlay. In order to automate soil productivity, a Python program developed and used in conjunction with the Designed Land Productivity Spatial Model (DLPSM). Such a programme could managed, improved, and transferred by many users and authorities in the current Era of distinctive advancement in information technology.