Open-Source Software for Satellite-Based Crop Health Monitoring

Abstract Purpose Timely information on agricultural crops is essential to support informed crop management decisions. Satellite remote sensing technology offers a new paradigm for monitoring agricultural crops at large scale. Daily access to satellite imagery from Planet Scope allows opportunities to continuously monitor the Earth’s surface in 3-m resolution with various spectrums. However, satellites on agricultural applications are still in less information to agriculture producers due to the limited access to analytic software. The paper aims to fill the gap between the satellite resources and the agricultural users, specifically to develop satellite image analytic software publicly available for agricultural crop health monitoring. Methods Open-source software, iCalendar, was developed for high-throughput image analysis and visualization of a vegetation index (VI) and a time-series crop growth. Application programing interface (API) was used to automate the image queuing, activation, and download based on user-defined time and area of interest. Results The API was refined to filter unusable data such as multiples of clipped images and duplicates of tile images. iCalendar resulted in the seamless data processing and automated user-friendly visualization of a seasonal VI profile and a corresponding field map calendar, that are key sources of crop production cycle. Machine learning-based segmentation algorithm and radiometric calibration showed the detection and correction of abnormalities in the image. Conclusion The satellite image-based plant monitoring system through open-source software iCalendar provided a significant improvement to spatiotemporal field observation and allows growers and researchers in-season crop health assessment, thereby promoting new management strategies for crop productivity and protection.