Abstract

The increasing developments in Unmanned Aerial Vehicles (UAVs) platforms and associated sensing technologies have widely promoted UAVs remote sensing application. UAVs, especially low-cost UAVs, limit the sensor payload in weight and dimension. Mostly, cameras on UAVs are panoramic, fisheye lens, small-format CCD planar array camera, unknown intrinsic parameters and lens optical distortion will cause serious image aberrations, even leading a few meters or tens of meters errors in ground per pixel. However, the characteristic of high spatial resolution make accurate geolocation more critical to UAV quantitative remote sensing research. A method for MCC4-12F Multispectral Imager designed to load on UAVs has been developed and implemented. Using multi-image space resection algorithm to assess geometric calibration parameters of random position and different photogrammetric altitudes in 3D test field, which is suitable for multispectral cameras. Both theoretical and practical accuracy assessments were selected. The results of theoretical strategy, resolving object space and image point coordinate differences by space intersection, showed that object space RMSE were 0.2 and 0.14 pixels in X direction and in Y direction, image space RMSE were superior to 0.5 pixels. In order to verify the accuracy and reliability of the calibration parameters,practical study was carried out in Tianjin UAV flight experiments, the corrected accuracy validated by ground checkpoints was less than 0.3m. Typical surface reflectance retrieved on the basis of geo-rectified data was compared with ground ASD measurement resulting 4% discrepancy. Hence, the approach presented here was suitable for UAV multispectral imager.

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