Author
Yang, Ching Pa | |
Anderson, Gerald |
Submitted to: Precision Agriculture
Publication Type: Peer Reviewed Journal Publication Acceptance Date: 9/1/2000 Publication Date: 9/1/2000 Citation: Yang, C., Anderson, G.L. 2000. MAPPING GRAIN SORGHUM YEILD VARIABILITY USING AIRBORNE DIGITAL VIDEOGRAPHY. Precision Agriculture. 2(1): 7-23. Interpretive Summary: Mapping crop yield variability is one important aspect of precision agriculture. This study was designed to assess airborne digital videography as a tool for mapping grain sorghum yields for precision farming. Color-infrared (CIR) imagery was acquired with a three- camera digital video imaging system from two grain sorghum field in south Texas over the 1995 and 1996 growing seasons. The multispectral video data obtained during the bloom to soft dough stages of plant development were related to hand-harvested grain yields at sampling sites determined from unsupervised image classification maps of the two fields. Significant correlations were found between grain yield and the red band, the green band, and the normalized difference vegetation index (NDVI). Regression equations were developed to describe the relations between grain yield and each of the three significant spectral variables using an exponential model and two segmented models. Multiple linear regression equations were also determined to relate grain yields to the three bands and NDVI. These equations were then used to estimate grain yields at each video image pixel within each field and to generate grain yield maps. The equations developed or one field in a given year may not apply to the same field in any other year, the practical value of these relationships is for mapping within-field grain yield variations. The results from this study showed that airborne digital videography, combined with ground sampling, regression analysis, and image processing, could be a useful approach for mapping spatial crop yield variability within fields. Technical Abstract: Mapping crop yield variability is one important aspect of precision agriculture. This study was designed to assess airborne digital videography as a tool for mapping grain sorghum yields for precision farming. Color-infrared (CIR) imagery was acquired with a three- camera digital video imaging system from two grain sorghum field in south Texas over the 1995 and 1996 growing seasons. The multispectral video data obtained during the bloom to soft dough stages of plant development were related to hand-harvested grain yields at sampling sites determined from unsupervised image classification maps of the two fields. Significant correlations were found between grain yield and the red band, the green band, and the normalized difference vegetation index (NDVI). Regression equations were developed to describe the relations between grain yield and each of the three significant spectral variables using an exponential model and two segmented models. Multiple linear regression equations were also determined to relate grain yields to the three bands and NDVI. These equations were then used to estimate grain yields at each video image pixel within each field and to generate grain yield maps. The equations developed or one field in a given year may not apply to the same field in any other year, the practical value of these relationships is for mapping within-field grain yield variations. The results from this study showed that airborne digital videography, combined with ground sampling, regression analysis, and image processing, could be a useful approach for mapping spatial crop yield variability within fields. |