Environmental Influences on Rabi Crops using GIS and Remote Sensing: A Case Study of Mianwali District

Abstract

Current study aims at to analyze the environmental influence on Rabi crops and to analyze the rainfall pattern with the vegetation pattern. Despite a declining GDP contribution, agriculture remains a fundamental pillar of Pakistan's economy, supporting livelihoods, nutrition, and export earnings. Focused on Mianwali District, the research integrates data from Landsat satellites, MODIS LST, and rainfall records to untangle relationships between environmental factors and Rabi crop productivity. Analysis of the Normalized Difference Vegetation Index (NDVI) provides insights into crop health by revealing variations in vegetation cover. Land Surface Temperature (LST) data offers perspectives on thermal conditions during the Rabi season, crucial for understanding water stress. Rainfall data assists in assessing water availability and its impact on crop yield. Correlation analysis highlights the direct impact of environmental conditions on agricultural productivity. Temporal trends show diversification in crop types, with "High Crops" on an upward trajectory, while the overall crop area in Mianwali District consistently decreases, possibly linked to changing environmental patterns. Land Surface Temperature conditions suggest potential environmental adaptations, supported by a decrease in LST values from 2000 to 2022, indicating improved thermal conditions or adaptive strategies. Rainfall analysis underscores the significance of understanding climatic patterns for sustainable agriculture. The correlation between NDVI and LST emphasizes vegetation sensitivity to thermal conditions, providing valuable insights for ecological studies and precision agriculture. The positive correlation between Rainfall and NDVI highlights the crucial role of water availability in fostering vegetation health and guiding sustainable agricultural practices.