Monitoring crop condition, health and seasonal progress are key to providing an in depth agricultural intelligence product. Crop acreage, outside of extreme events, remains relatively stable throughout the growing season. Crop health and seasonal progress are the most dynamic crop attributes and are critical in determination of yield forecasts. These attributes are early indicators of crop yield, crop risk and ultimately the degree of crop success or failure. 

Industry standards for determining crop health and progress rely on surveys and field level sampling. While this is an important step in the process, consider the likelihood that sampling a 3ft. by 3ft. sample plot within a 100 acre field will provide a good indication of the health of the entire field or all fields within a county. GDA relies on daily historical and current time series satellite imagery for direct observation and analysis of crop health and progress. GDA provides detailed analysis of crop conditions during the current growing season and a comparison of the current season to previous years at sub-national and national levels. Uniquely,utilizing ancillary data such as soil condition, weather and crop phenology in conjunction with daily direct measurements, GDA's analysis includes prediction of crop progress for the remaining part of the growing season.  The prediction of seasonal metrics, such as end of season, can aid in crop risk assessment, such as risk of late season frost as well as providing guidance for crop harvest times for use in logistics planning for transportation and processing.

MODIS NDVI Imagery (South Africa) over Time (Images courtesy NASA/LPDAAC)

Crop health and seasonal progress are analyzed using direct measurements of the normalized difference vegetation index (NDVI) and the normalized difference water index (NDWI). NDVI indicates crop condition by monitoring changes in the photosynthetic capacity, while  NDWI indicates vegetation water content and drought risk by analyzing changes in the plant water content, leaf internal structure and leaf dry matter content. Combined with GDA’s proprietary algorithms and databases, crop progress analysis enables both real time monitoring and end of season predictions of crop progress and crop health.

NDVI has been used in the research and analysis of agricultural crops since 1969. While initially a research tool the improvements made in the resolution and processing of satellite imagery, the availability of higher resolution imagery and research and studies that have been made on the correlations between NDVI and agricultural crops, have made the use of NDVI for commercial applications a reality. 

The graphic below represents a typical NDVI curve one would expect to see for a specific crop throughout and entire season. The different points along the curve from left to right represent different points within a plants phenology (life cycle).Using industry leading algorithms and methodologies GDA utilizes the NDVI data in conjunction with ancillary data and our proprietary database to not only monitor but predict crop health and progress throughout a growing season. Our extensive data base allows users to compare current seasonal metrics with historical averages, most similar historical season, highest yielding historical seasons etc. This provides our customers the information they need to make sound judgments relating the current growing season. 

                   NDVI Model for Seasonal Metrics

The image below shows a typical NDVI time-series curve that is available as part of our crop condition product. This particular view demonstrates the comparison of current season versus the average NDVI curve for previous seasons of the same location. As this particular view was taken in March 1, 2009, the curve shown in yellow and the seasonal metrics such as Mid senescence are predictions made by GDA's analysis software. 

NDVI Imagery Aggregated into NDVI Time-Series data

The statistics of crop conditions are presented in tabular, graphic, and map forms and relate current season to the previous year, average/typical season, and other historical seasons. Absolute and relative (% difference from previous year and historical average) values as well as historical trend and 5-year average values are provided. Furthermore, crop maps can be requested in a GIS format.

Sample GIS Maps showing Start of Season parameter both as date values and percentage increase/decrease from previous year