Advancing Precision Agriculture: Integrating Satellite Remote Sensing For Crop Health Monitoring And Assessment

Abstract

This study presents an integrated remote sensing approach for monitoring and assessing the health and development of wheat crops in Allahabad district, Uttar Pradesh, an important wheat-producing region in India. Satellite images from Landsat 7 and Landsat 8, acquired on five key dates during the 2015–2016 growing season (December 24, 2015; January 24, 2016; February 10, 2016; March 21, 2016; and April 14, 2016), were utilized to derive the Normalized Difference Vegetation Index (NDVI) across 110 contiguous wheat fields spanning the all eight tehsils of the district. The temporal NDVI analysis revealed a clear phenological evolution, with mean values progressing from 0.07 during the crop establishment phase in December to a peak of 0.47 in February, followed by a decline to 0.31 in March and reaching a low of 0.13 by April, marking the onset of senescence and harvest-readiness. Further, spatial assessments of NDVI revealed variability in crop health within and among the selected fields, with higher heterogeneity apparent during early and peak growth phases indicating localized stress factors such as moisture deficits or nutrient imbalances. The later uniformity in NDVI across fields, while indicative of synchronized senescence, also raised concerns for areas that consistently underperformed during peak growth.

Overall, the findings of the present study underscore the efficacy of satellite remote sensing as a cost-effective and scalable solution for monitoring and assessing crop health. Moreover, this technology underpins precision agriculture by enabling timely, targeted interventions that optimize crop management and sustain yield potential.