Python Driven Pathways for Wheat Cultivation Incorporating Physico-Climatic Parameters of Growth

Agriculture has a pivotal role in the provision of food, fabric and income. Agricultural sector is backbone of Pakistan’s economy, which is strongly dependent on agriculture. Pakistan is renowned globally for its wheat crop. However, wheat production has suffered due to lack of modern farming techniques, inadequate water availability, and relevant soil parameters. The main objective of this study was to monitor stages of wheat growth using Landsat ۸ thermal datasets through temperature-based site maps. This study delineates suitable areas for sustainable wheat growth using Multi-Criteria Evaluation (MCE) and GIS. The total area under investigation was ۵,۶۹۷ km۲ and the area under wheat cultivation was ۲,۲۷۶.۶۳ km۲, out of which ۱,۶۸۴.۲۶ km۲ (۷۴%) was found highly suitable, ۶۸.۳۳۷۶ km۲ (۳%) was moderately suitable, ۶۱.۶۶۷۸ km۲ (۲.۷%) was least suitable, and ۴۶۲.۳۵۵ km۲ (۲۰.۳۰%) was found not suitable for wheat crop cultivation. The results interoperated that the area with temperature range of ۱۰–۱۸◦C, and pH ranging between ۶.۲ and ۶.۵, clay loom soil texture, and ۰.۸۵ and ۱.۱ drainage level indicate highly suitable land for wheat production. This study highlights the local farming techniques, suitable land for wheat production, and patterns of crop harvesting.

Keywords:

Analytic Hierarchy Technique (AHP) , Inverse Distance Weighted (IDW) , Land suitability , Multicriteria Evaluation (MCE).