Digital Soil Mapping Using Spectral and Terrain Parameters and Statistical Modelling Integrated into GIS-Northwestern Coastal Region of Egypt

Abstract

This chapter examines digital soil mapping approach for the production of soil maps by using multinomial logistic regression on soil and terrain information from pilot areas in the northwestern coastal region of Egypt. The aim is to reproduce the original map and predict soil distribution in the adherent landscape. Reference soil maps produced by conventional methods at Omayed and Nagamish areas were used. The logit models of the soil classes as expressed by the spectral and terrain parameters were calculated, and predicted soil classes’ maps were produced. The IDRISI/SAGA/SATISTCA/SPSS platforms were used in this chapter. The terrain and spectral parameters were found to be significantly influential that the selection of the land surface predictors was satisfactory. The McFadden pseudo R-squares ranged from 0.473 to 0.496. The most significant terrain parameters influencing the spatial distribution of the soil classes are found to be elevation, valley depth, multiresolution ridgetop flatness index, multiresolution valley bottom flatness and SAGA wetness index. However, the most influential spectral parameters are the first two principle components of the six Enhanced Thematic Mapper bands. The overall accuracy of the predicted soil maps ranged from 72 to 74% with kappa index ranged from 0.62 to 0.64. The developed probability models were successfully used to predict the spatial distribution of the soil mapping units at pixel resolutions of 28.5 m × 28.5 m and 90 m × 90 m at adjacent unvisited areas at Matrouh and Alamin. The developed methodology could contribute to the allocation and to the digital mapping and management for new expansion sites in the remote desert areas of Egypt.