RELATIONSHIPS BETWEEN YIELD MONITOR DATA AND AIRBORNE MULTISPECTRAL DIGITAL IMAGERY

Authors: YANG, CHENGHAI - TX A&M EXP STN-WESLACO,TX; Everitt, James

Submitted to: International Conference on Precision Agriculture Abstracts & Proceedings
Publication Type: Proceedings
Publication Acceptance Date: 6/15/2000
Publication Date: N/A
Citation: N/A

Interpretive Summary: Aerial digital images obtained during the growing season can be a very important data source for precision agriculture. This study was intended to evaluate the relationships between grain sorghum yield and aircraft-based digital image data. Digital images were acquired from two grain sorghum fields on five different dates over a 55-day period during the 1998 growing gseason. Yield data were also collected from these fields using a grain yield monitor. These images clearly show plant growth patterns over the season. Statistical analyses showed there existed significant correlations between grain yield data and image data for each of the five dates. There also exists a distinct temporal progression in relations between yield and image data. The relations reached the strongest around the peak growth, indicating imagery taken during this period (approximately one month) could be a better indicator of yield for grain sorghum. The yield maps generated dfrom the images agreed well with those from the yield monitor data. These results show that airborne digital imagery obtained during the growing season provides valuable crop growth and yield information and can be used in conjunction with other data for yield forecasting.

Technical Abstract: Remote sensing imagery taken during a growing season not only provides spatial and temporal information about crop growth conditions, but also is indicative of crop yield. This study aimed to evaluate the relationships between yield monitor data and airborne multispectral digital imagery for grain sorghum. Color-infrared (CIR) digital images were acquired from two grain sorghum fields on five different dates during the 1998 growing season. Yield data were also collected from these fields using a yield monitor. The digital images and the yield data were georeferenced to a common UTM coordinate system. The image data for the green, red, and near-infrared (NIR) bands and the four vegetation indices derived from the image data were aggregated to generate reduced-resolution images with cell sizes equivalent to the combine's effective cutting width. Correlation analyses showed that grain yield was significantly related to the digital image data for the three bands and the four vegetation indices. Multiple regression equations were determined to relate grain yield to all the three bands and to all the three bands together with the four indices for the five dates. The images taken around peak growth produced the best relationships with yield for both fields. Yield maps generated from the image data using the regression equations agreed well with those from the yield monitor data. These results demonstrated that airborne digital imagery can be a very useful tool for determining yield patterns before harvest for precision agriculture.