Satellite image analysis for crop health monitoring

Authors: Kim, James

Submitted to: Proceedings for CIGR World Congress Meetings
Publication Type: Abstract Only
Publication Acceptance Date: 3/14/2024
Publication Date: N/A
Citation: N/A

Interpretive Summary: This paper discusses an satellite image-based plant monitoring system to provide a sustainable solution for spatiotemporal field observation and thus help management strategies for crop productivity and protection. Planet Scope imagery from Planet Lab is accessible through NASA-CSDA program for federal researchers and offers global daily satellite imagery in up to 3-m resolution. Imagery is accessed through application program interface based on user-defined parameters such as time of interest, area of interest, and image types. The downloaded imagery in multspectral bands is analyzed for image processing using in-house software to extract vegetation indexes and create a seasonal profile of field map calendar. This monitoring system provides a sustainable solution for crop production and protection and also helps developing new germplasm with enhanced resistance to pests and plant diseases.

Technical Abstract: Satellite imagery is accessed through NASA-CSDA program for crop health monitoring. Landsat 8, Sentinel-2, and Planet Scope 2 imagery from Planet Lab offer global imagery data in various spectrums with up to 3 m resolution and facilitates agricultural assessment for markets and food security. 4-band, 8-band, and 11-band 16-bit imagery are accessed and analyzed by open-source software coded in Python. Application program interface (API) is developed to automate the image queuing, activation, and download based on user-defined time and area of interest and field borders. Analysis is applied in plot level for a crop health alert system that gives an alarm to the farmers when field abnormality is detected so that the farmers can address the issues proactively prior to the widespread. The satellite images are processed to generate various vegetation indexes and create a seasonal profile of crop health conditions and yield estimate in row crop fields such as corn, soybean, and sugarbeet. The satellite image-based high throughput plant monitoring system provides a sustainable solution for spatiotemporal field observation and thus helps developing new germplasm with enhanced resistance to pests and diseases. It offers a significant improvement to in-season crop health assessment, thereby promoting new management strategies for crop productivity and protection.