LEADER 04560nam 2201081z- 450 001 9910367744003321 005 20210211 010 $a3-03921-783-6 035 $a(CKB)4100000010106277 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/39900 035 $a(oapen)doab39900 035 $a(EXLCZ)994100000010106277 100 $a20202102d2019 |y 0 101 0 $aeng 135 $aurmn|---annan 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$a3D Remote Sensing Applications in Forest Ecology: Composition, Structure and Function 210 $cMDPI - Multidisciplinary Digital Publishing Institute$d2019 215 $a1 online resource (188 p.) 311 08$a3-03921-782-8 330 $aDear Colleagues, The composition, structure and function of forest ecosystems are the key features characterizing their ecological properties, and can thus be crucially shaped and changed by various biotic and abiotic factors on multiple spatial scales. The magnitude and extent of these changes in recent decades calls for enhanced mitigation and adaption measures. Remote sensing data and methods are the main complementary sources of up-to-date synoptic and objective information of forest ecology. Due to the inherent 3D nature of forest ecosystems, the analysis of 3D sources of remote sensing data is considered to be most appropriate for recreating the forest's compositional, structural and functional dynamics. In this Special Issue of Forests, we published a set of state-of-the-art scientific works including experimental studies, methodological developments and model validations, all dealing with the general topic of 3D remote sensing-assisted applications in forest ecology. We showed applications in forest ecology from a broad collection of method and sensor combinations, including fusion schemes. All in all, the studies and their focuses are as broad as a forest's ecology or the field of remote sensing and, thus, reflect the very diverse usages and directions toward which future research and practice will be directed. 517 $a3D Remote Sensing Applications in Forest Ecology 606 $aBiology, life sciences$2bicssc 610 $a3D 610 $a3D remote sensing 610 $aallometric scaling and resource limitation model 610 $acodispersion coefficient 610 $acodispersion map 610 $acomposition 610 $acrowdsourced data 610 $adiameter at breast height (DBH) 610 $adigital photogrammetry 610 $aDSM 610 $aforest canopy height 610 $aforest ecology 610 $aforest fire 610 $aFractional cover analysis 610 $afunction 610 $agoogle earth engine 610 $aGoogle Street View 610 $aground validation 610 $aGSV 610 $ahabitat fragmentation 610 $aharvester 610 $ahigh-voltage power transmission lines 610 $aimputation 610 $ainterrater agreement 610 $akriging 610 $aLandsat 8 610 $alandscape fragmentation 610 $aLantana camara 610 $alaser 610 $amaximum forest heights 610 $ameasurement error 610 $ametabolic scale theory 610 $amissing observations 610 $amountainous areas 610 $amulti-spectral 610 $amunicipal forestry 610 $anormalized difference vegetation index (NDVI) 610 $aNorway spruce 610 $anu SVR 610 $aoptimization 610 $apoint cloud 610 $apolarimetery 610 $aproduct recovery 610 $arandom Hough transform 610 $aRapidEye 610 $aspatial noise 610 $aspecies identification 610 $aSPOT-6 610 $aSRTMGL1 610 $astreet trees 610 $astructure 610 $astump diameter 610 $astump height 610 $aterrestrial laser scanner 610 $aterrestrial laser scanning 610 $atree height 610 $atree measurement 610 $auneven-aged mountainous 610 $aurban ecology 610 $aurban forestry 610 $aZiYuan-3 stereo images 615 7$aBiology, life sciences 700 $aLatifi$b Hooman$4auth$01290160 702 $aValbuena$b Ruben$4auth 906 $aBOOK 912 $a9910367744003321 996 $a3D Remote Sensing Applications in Forest Ecology: Composition, Structure and Function$93021368 997 $aUNINA