LEADER 05209nam 2201093z- 450 001 9910557781303321 005 20231214133548.0 035 $a(CKB)5400000000045576 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/76575 035 $a(EXLCZ)995400000000045576 100 $a20202201d2021 |y 0 101 0 $aeng 135 $aurmn|---annan 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aUAV Photogrammetry and Remote Sensing 210 $aBasel, Switzerland$cMDPI - Multidisciplinary Digital Publishing Institute$d2021 215 $a1 electronic resource (257 p.) 311 $a3-0365-1454-6 311 $a3-0365-1453-8 330 $aThe concept of remote sensing as a way of capturing information from an object without making contact with it has, until recently, been exclusively focused on the use of Earth observation satellites.The emergence of unmanned aerial vehicles (UAV) with Global Navigation Satellite System (GNSS) controlled navigation and sensor-carrying capabilities has increased the number of publications related to new remote sensing from much closer distances. Previous knowledge about the behavior of the Earth's surface under the incidence different wavelengths of energy has been successfully applied to a large amount of data recorded from UAVs, thereby increasing the special and temporal resolution of the products obtained.More specifically, the ability of UAVs to be positioned in the air at pre-programmed coordinate points; to track flight paths; and in any case, to record the coordinates of the sensor position at the time of the shot and at the pitch, yaw, and roll angles have opened an interesting field of applications for low-altitude aerial photogrammetry, known as UAV photogrammetry. In addition, photogrammetric data processing has been improved thanks to the combination of new algorithms, e.g., structure from motion (SfM), which solves the collinearity equations without the need for any control point, producing a cloud of points referenced to an arbitrary coordinate system and a full camera calibration, and the multi-view stereopsis (MVS) algorithm, which applies an expanding procedure of sparse set of matched keypoints in order to obtain a dense point cloud. The set of technical advances described above allows for geometric modeling of terrain surfaces with high accuracy, minimizing the need for topographic campaigns for georeferencing of such products.This Special Issue aims to compile some applications realized thanks to the synergies established between new remote sensing from close distances and UAV photogrammetry. 606 $aTechnology: general issues$2bicssc 610 $aunmanned aerial vehicle 610 $aurban LULC 610 $aGEOBIA 610 $amultiscale classification 610 $aunmanned aircraft system (UAS) 610 $adeep learning 610 $asuper-resolution (SR) 610 $aconvolutional neural network (CNN) 610 $agenerative adversarial network (GAN) 610 $astructure-from-motion 610 $aphotogrammetry 610 $aremote sensing 610 $aUAV 610 $a3D-model 610 $asurveying 610 $avertical wall 610 $asnow 610 $aremotely piloted aircraft systems 610 $astructure from motion 610 $alidar 610 $aforests 610 $aorthophotography 610 $aconstruction planning 610 $asustainable construction 610 $aurbanism 610 $aBIM 610 $abuilding maintenance 610 $aunmanned aerial vehicle (UAV) 610 $astructure-from-motion (SfM) 610 $aground control points (GCP) 610 $aaccuracy assessment 610 $apoint clouds 610 $acorridor mapping 610 $aUAV photogrammetry 610 $aterrain modeling 610 $avegetation removal 610 $aunmanned aerial vehicles 610 $apower lines 610 $aimage-based reconstruction 610 $a3D reconstruction 610 $aunmanned aerial systems 610 $atime series 610 $aaccuracy 610 $areproducibility 610 $aorthomosaic 610 $avalidation 610 $adrone 610 $aGNSS RTK 610 $aprecision 610 $aelevation 610 $amultispectral imaging 610 $avegetation indices 610 $anutritional analysis 610 $acorrelation 610 $aoptimal harvest time 610 $aUAV images 610 $amonoscopic mapping 610 $astereoscopic plotting 610 $aimage overlap 610 $aoptimal image selection 615 7$aTechnology: general issues 700 $aCarvajal-Rami?rez$b Fernando$4edt$01278701 702 $aAgu?era-Vega$b Francisco$4edt 702 $aMarti?nez-Carricondo$b Patricio$4edt 702 $aCarvajal-Rami?rez$b Fernando$4oth 702 $aAgu?era-Vega$b Francisco$4oth 702 $aMarti?nez-Carricondo$b Patricio$4oth 906 $aBOOK 912 $a9910557781303321 996 $aUAV Photogrammetry and Remote Sensing$93013751 997 $aUNINA