Korean Journal of Soil Science and Fertilizer · 2016 · 11 citations · 11 references
AgricultureAgronomyCrop SciencesCrop EcologyCrop SensingRemote SensingAgricultural ApplicationsRemote Sensing ImageryVegetation IndicesVegetation MonitoringAerial Crop MonitoringCrop Condition MonitoringCrop MonitoringCrop ReflectanceImage-based Crop MonitoringReflectance CalculationUnmanned Aerial Vehicle Crop MonitoringUnmanned Aerial Vehicle Sensing
Recent technological advance in UAV (Unmanned Aerial Vehicle) technology offers new opportunities for assessing crop situation using UAV imagery. The objective of this study was to assess if reflectance and NDVI derived from consumer-grade cameras mounted on UAVs are useful for crop condition monitoring. This study was conducted using a fixed-wing UAV(Ebee) with Cannon S110 camera from March 2015 to March 2016 in the experiment field of National Institute of Agricultural Sciences. Results were compared with ground-based recordings obtained from consumer-grade cameras and ground multi-spectral sensors. The relationship between raw digital numbers (DNs) of UAV images and measured calibration tarp reflectance was quadratic. Surface (lawn grass, stairs, and soybean cultivation area) reflectance obtained from UAV images was not similar to reflectance measured by ground-based sensors. But NDVI based on UAV imagery was similar to NDVI calculated by ground-based sensors. Change of NDVI in lawn grass and soybean cultivation area depending on method of reflectance calculation using UAV images.
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A change detection experiment using vegetation indices.
John G. Lyon, Ding Yuan, Ross S. Lunetta et al. · 1998 · 462 citations