Near Real Time Crop Health Status Monitoring and Mapping using Sentinel Satellite Image in Menjar Shenkora District, Ethiopia

Abstract

Agricultural monitoring systems must provide timely and standardized information on crop production, status, and yield, from sub-regional to national scales. Accurate monitoring and mapping of vegetation condition and health are vital for managing crops, assessing damage, and predicting yields. Crop health monitoring is one of the important items for tracking the general health status of any crop. In this regard, remote sensing and GIS play a crucial role for monitoring crop health, providing current information that traditional methods like field surveys and sampling questionnaires struggle to obtain. Effective cropland mapping techniques are essential for regular crop monitoring. This type of monitoring demands frequents continuous data with high time and space resolution. Near real-time crop monitoring uses technologies like the Sentinel-2 satellite mission, offering a consistent 5-day revisit cycle and freely accessible data. This opens new doors for delivering timely updates and monitoring parcel-based crop health and conditions in real-time. Therefore, this study used satellite images, Global Positioning System (GPS) collected data, and parcel-based socioeconomic data. GPS and socioeconomic data were employed to validate the satellite-based near real-time crop monitoring results. Vegetation Condition Index (VCI) and the Normalized Difference Vegetation Index (NDVI) were used to evaluate crop health at different stages of the growing season and to generate time series data for crop phenology respectively. NDVI time series data was used to generate crop phenology information for four main crops: Teff, wheat, onion, and sorghum. The crop type maps for these crops at the study sites were validated with an overall accuracy of 79.26% and a Kappa value of 0.737. Additionally, the results from the current research and the field-collected data were consistent in providing information about the onset, greening, maturity, and senescence dates of each crop. These findings highlight the effectiveness of the satellite-based system for real-time agricultural crop monitoring using Sentinel-2 observations across various sites and time frames. Moreover, it helps to fill the gaps of traditional crop monitoring methods with those based on satellite technology. This system is particularly valuable for early warning purpose in areas like the current study site, where conventional crop monitoring methods and inputs are limited.