Agricultural Activities and Their Spatial Distribution in Naour District Using GIS
DOI:
https://doi.org/10.33977/0507-000-068-004Keywords:
Naour district, GIS, remote sensing, NDVI, supervised classification, demAbstract
Objectives:
This study aimed to analyze the spatial distribution of agricultural activities in the Naour District of Jordan using Geographic Information Systems (GIS) and remote sensing techniques. It sought to develop a comprehensive agricultural geodatabase to support decision-making, inform planning processes, and promote sustainable agricultural practices.
Methods:
ArcGIS 10.5 and Landsat 8-OLI/TIRS satellite imagery generated climate, elevation, slope, NDVI, and land use maps. A supervised classification was performed using the Maximum Likelihood Classifier (MLC). Data from the Naour Agriculture Directorate and field surveys were integrated into a spatial database.
Results:
NDVI analysis for three seasonal periods (January, June, and October 2022) revealed vegetation cover variation. Supervised classification identified forests (6.25 km²), bare soil (64.52 km²), crops (22.67 km²), irrigated lands near Husban stream (13.08 km²), urban areas (52.16 km²), and fruit plantations (42.14 km²), with an overall classification accuracy of 82.4% and a Kappa coefficient of 0.77.
Conclusions:
The study demonstrates the value of GIS and remote sensing in mapping and managing agricultural activities. The generated maps and geo-database provide a strategic tool for resource allocation, agricultural development, and environmental planning in Naour District.
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