Remote Sensing of 3-D Geometry and Surface Moisture of a Peat Production Area Using Hyperspectral Frame Cameras in Visible to Short-Wave Infrared Spectral Ranges Onboard a Small Unmanned Airborne Vehicle (UAV)

摘要

Miniaturized hyperspectral imaging sensors are becomingavailable to small unmanned airborne vehicle (UAV) platforms.Imaging concepts based on frame format offer an attractivealternative to conventional hyperspectral pushbroom scannersbecause they enable enhanced processing and interpretation potentialby allowing for acquisition of the 3-D geometry of theobject and multiple object views together with the hyperspectralreflectance signatures. The objective of this investigation was tostudy the performance of novel visible and near-infrared (VNIR)and short-wave infrared (SWIR) hyperspectral frame camerasbased on a tunable Fabry–Pérot interferometer (FPI) in measuringa 3-D digital surface model and the surface moisture of a peatproduction area. UAV image blocks were captured with groundsample distances (GSDs) of 15, 9.5, and 2.5 cm with the SWIR,VNIR, and consumer RGB cameras, respectively. Georeferencingshowed consistent behavior, with accuracy levels better than GSDfor the FPI cameras. The best accuracy in moisture estimation wasobtained when using the reflectance difference of the SWIR bandat 1246 nm and of the VNIR band at 859 nm, which gave a rootmean square error (rmse) of 5.21 pp (pp is the mass fraction inpercentage points) and a normalized rmse of 7.61%. The resultsare encouraging, indicating that UAV-based remote sensing couldsignificantly improve the efficiency and environmental safety aspectsof peat production.