Precision Agriculture: A Web-GIS Framework for Health and Stress Assessment Using Multi-Source Remote Sensing Data

Abstract. Climate change has an immense impact on many fields, especially in the agricultural sector the reduction in crop yield, pre-maturation of crops, and water scarcity that may lead to drought, and scarcity of food in India. Agriculture plays a significant role in India where approximately 60% of the population works in the agricultural sector, contributing 20.2% to India’s Gross Domestic Product (GDP). India has one of the largest populations 1.2 billion in the whole world (Census 2011), Precision Agriculture (PA) techniques with the utilization of Unmanned Ariel Vehicles (UAV), equipped with multi-sensor along with satellite imagery providing more spectral and temporal resolution. The primary objective of this research is to create a model within the Google Earth Engine (GEE) framework, a WebGIS platform that enables its users to access analyses and visualize geospatial data for a wide range of applications. This model will enable researchers to calculate several indices for crop health and stress assessment mentioned in this research in their respective Areas of Interest (AOI) whether using either a UAV or satellite dataset. These indices help in evaluating water stress, disease detection, biomass and nitrogen estimation, and soil moisture estimation in crops, various tools and techniques will be employed for data processing, comparing, and analysis to acquire the optimal precision, additionally, ground truthing measures were also utilized to validate the accuracy of the outcomes. This research will help in supporting PA practices and promoting sustainable development in the agricultural sector.