374-6 Comparison of Modified Camera, Multispectral Camera and Active Optical Sensor in Estimating in-Season Biomass and Grain Yield in Winter Wheat.
See more from this Division: ASA Section: Climatology and Modeling
See more from this Session: Agricultural Remote Sensing Oral
Wednesday, November 9, 2016: 9:20 AM
Phoenix Convention Center North, Room 228 A
Abstract:
Accurate and timely estimates of crop biomass and grain yield across a field are key objectives of many agronomists and farmers alike. Remotely sensed spectral measurements acquired by earth orbiting satellites have been used for decades with varying degrees of success for classifying crop types and predicting yields. Their limitations are associated with low spatial resolution and unfavorable revisit time in precision agriculture. High spatial resolution images taken by low altitude remote sensing (LARS) platform or small unmanned aircraft system (sUAS) could fill this gap. Crop field active optical sensor (AOS) has been used to compute Normalized Difference Vegetation Index (NDVI)-type vegetation indices (VIs) to assess factors such as crop vigor, leaf nitrogen status and potential yields. This study was conducted to test the ability of three sensors (a Canon T4i® modified color infrared (CIR) camera, a Micasense RedEdge® multispectral camera and a Holland Scientific® RapidScan CS-45® hand-held AOS) to estimate in-season biomass and grain yield using NDVI-type VIs in winter wheat across ten Feekes growth stages (F4, F6, F7, F10, F10.2, F10.5, F10.5.2, F10.5.4, F11.1, F11.3) managed under four rates of nitrogen application (0, 50, 100 and 150 lb/ac). The results showed the VIs derive from the Canon T4i CIR camera and the RedEdge multispectral camera were highly correlated and can equally estimate winter wheat in-season biomass between F4 and F11.1 (0.72<R2<0.94, all P<0.001). The highest R2 was found at F10.2. The RapidScan AOS only showed moderate ability to estimate in-season biomass at F10.2 (0.36<R2<0.55, 0.001<P<0.05). The ability of estimating grain yield for all three sensors was weaker when compared to estimation of in-season biomass.
Keywords: color infrared (CIR), multispectral, Active Optical Sensor (AOS), Normalized Difference Vegetation Index (NDVI), in-season biomass, grain yield
See more from this Division: ASA Section: Climatology and Modeling
See more from this Session: Agricultural Remote Sensing Oral