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Remote sensing based on unmanned airborne vehicles (UAVs) is a rapidly developing field of technology. UAVs enable accurate,flexible, low-cost and multiangular measurements of 3D geometric, radiometric, and temporal properties of land and vegetationusing various sensors. In this paper we present a geometric processing chain for multiangular measurement system that is designedfor measuring object directional reflectance characteristics in a wavelength range of 400–900 nm. The technique is based on a novel,lightweight spectral camera designed for UAV use. The multiangular measurement is conducted by collecting vertical and obliquearea-format spectral images. End products of the geometric processing are image exterior orientations, 3D point clouds and digitalsurface models (DSM). This data is needed for the radiometric processing chain that produces reflectance image mosaics andmultiangular bidirectional reflectance factor (BRF) observations. The geometric processing workflow consists of the following threesteps: (1) determining approximate image orientations using Visual Structure from Motion (VisualSFM) software, (2) calculatingimproved orientations and sensor calibration using a method based on self-calibrating bundle block adjustment (standardphotogrammetric software) (this step is optional), and finally (3) creating dense 3D point clouds and DSMs using PhotogrammetricSurface Reconstruction from Imagery (SURE) software that is based on semi-global-matching algorithm and it is capable ofproviding a point density corresponding to the pixel size of the image. We have tested the geometric processing workflow overvarious targets, including test fields, agricultural fields, lakes and complex 3D structures like forests

the international archives of the photogrammetry, remote sensing and spatial information sciences/international archives of the photogrammetry, remote sensing and spatial information sciences

Geometric processing workflow for vertical and oblique hyperspectral frame images collected using UAV