Listing 1 - 2 of 2 |
Sort by
|
Choose an application
Dear 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.
normalized difference vegetation index (NDVI) --- SRTMGL1 --- SPOT-6 --- urban ecology --- terrestrial laser scanner --- Lantana camara --- terrestrial laser scanning --- harvester --- product recovery --- imputation --- optimization --- multi-spectral --- function --- ZiYuan-3 stereo images --- spatial noise --- 3D remote sensing --- tree measurement --- diameter at breast height (DBH) --- DSM --- metabolic scale theory --- municipal forestry --- digital photogrammetry --- Norway spruce --- missing observations --- interrater agreement --- measurement error --- stump height --- Fractional cover analysis --- google earth engine --- high-voltage power transmission lines --- habitat fragmentation --- codispersion coefficient --- forest fire --- tree height --- nu SVR --- RapidEye --- uneven-aged mountainous --- random Hough transform --- kriging --- street trees --- ground validation --- Google Street View --- laser --- species identification --- composition --- maximum forest heights --- mountainous areas --- landscape fragmentation --- Landsat 8 --- forest canopy height --- allometric scaling and resource limitation model --- urban forestry --- point cloud --- GSV --- stump diameter --- structure --- 3D --- codispersion map --- forest ecology --- polarimetery --- crowdsourced data
Choose an application
Monitoring of vegetation structure and functioning is critical to modeling terrestrial ecosystems and energy cycles. In particular, leaf area index (LAI) is an important structural property of vegetation used in many land surface vegetation, climate, and crop production models. Canopy structure (LAI, fCover, plant height, and biomass) and biochemical parameters (leaf pigmentation and water content) directly influence the radiative transfer process of sunlight in vegetation, determining the amount of radiation measured by passive sensors in the visible and infrared portions of the electromagnetic spectrum. Optical remote sensing (RS) methods build relationships exploiting in situ measurements and/or as outputs of physical canopy radiative transfer models. The increased availability of passive (radar and LiDAR) RS data has fostered their use in many applications for the analysis of land surface properties and processes, thanks also to their insensitivity to weather conditions and the capability to exploit rich structural and textural information. Data fusion and multi-sensor integration techniques are pressing topics to fully exploit the information conveyed by both optical and microwave bands.
artificial neural network --- downscaling --- simulation --- 3D point cloud --- European beech --- consistency --- adaptive threshold --- evaluation --- photosynthesis --- geographic information system --- P-band PolInSAR --- validation --- density-based clustering --- structure from motion (SfM) --- EPIC --- Tanzania --- signal attenuation --- trunk --- canopy closure --- REDD+ --- unmanned aerial vehicle (UAV) --- forest --- recursive feature elimination --- Fraction of Photosynthetically Active Radiation absorbed by vegetation (FPAR) --- aboveground biomass --- random forest --- uncertainty --- household survey --- spectral information --- forests biomass --- root biomass --- biomass --- unmanned aerial vehicle --- Brazilian Amazon --- VIIRS --- global positioning system --- LAI --- photochemical reflectance index (PRI) --- allometric scaling and resource limitation --- R690/R630 --- modelling aboveground biomass --- leaf area index --- forest degradation --- spectral analyses --- terrestrial laser scanning --- BAAPA --- leaf area index (LAI) --- stem volume estimation --- tomographic profiles --- polarization coherence tomography (PCT) --- canopy gap fraction --- automated classification --- HemiView --- remote sensing --- multisource remote sensing --- Pléiades imagery --- photogrammetric point cloud --- farm types --- terrestrial LiDAR --- altitude --- RapidEye --- forest aboveground biomass --- recovery --- southern U.S. forests --- NDVI --- machine-learning --- conifer forest --- satellite --- chlorophyll fluorescence (ChlF) --- tree heights --- phenology --- point cloud --- local maxima --- clumping index --- MODIS --- digital aerial photograph --- Mediterranean --- hemispherical sky-oriented photo --- managed temperate coniferous forests --- fixed tree window size --- drought --- GLAS --- smartphone-based method --- forest above ground biomass (AGB) --- forest inventory --- over and understory cover --- sampling design
Listing 1 - 2 of 2 |
Sort by
|