Geospatial Mapping of Soil Morphological Properties in Irrigated Farmlands of Jahun LGA, Jigawa State, Nigeria
Abstract
Soil morphological properties are important indicators of soil health, agricultural productivity, and sustainable land management. In semi-arid regions such as northern Nigeria, these properties are influenced by climatic conditions, irrigation practices, and land-use activities, affecting soil quality and crop performance. This study employed an integrated geospatial approach to assess and map soil morphological properties within irrigated farmlands of the Habazaya Irrigation Area in Jahun Local Government Area, Jigawa State, Nigeria. Sentinel-2 imagery, Digital Elevation Model (DEM) data, Geographic Information Systems (GIS), and field-based soil survey techniques were combined to examine spatial variability in soil conditions. Field sampling was conducted at 10 locations where soil samples were collected from 0-30 cm depth and analyzed for pH, bulk density, structure, consistency, and texture. Spectral indices, including the Bare Soil Index (BSI) and Normalized Difference Moisture Index (NDMI), were derived from Sentinel-2 imagery and integrated with field observations for spatial and statistical analysis. Ordinary Least Squares (OLS) regression was used to evaluate relationships between soil properties and remotely sensed variables. The findings revealed that sandy loam (29.62%) and sandy clay (21.33%) were the dominant soil textural classes. Approximately 76.38% of the study area exhibited low to very low moisture conditions, while 94.99% of the irrigation area was classified as well-drained. Soil pH ranged from 5.0 to 7.0, whereas bulk density ranged from 1.08 to 1.40 g/cm 3 . Predictive modeling showed weak performance for pH (R 2 = 0.145) but stronger predictive potential for bulk density (R 2 = 0.744). Loose soil structure dominated 80% of sampled locations, while slightly sticky consistency accounted for 40%. The study demonstrates the value of integrating remote sensing, GIS, and field observations for improved soil characterization and sustainable irrigation management.