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3D Remote Sensing Applications in Forest Ecology: Composition, Structure and Function

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ISBN: 9783039217823 9783039217830 Year: Pages: 188 DOI: 10.3390/books978-3-03921-783-0 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Science (General) --- Biology --- Ecology
Added to DOAB on : 2019-12-09 11:49:16
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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.

Remote Sensing Technology Applications in Forestry and REDD+

Authors: --- --- ---
ISBN: 9783039284702 9783039284719 Year: Pages: 244 DOI: 10.3390/books978-3-03928-471-9 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- Environmental Technology
Added to DOAB on : 2020-04-07 23:07:09
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Advances in close-range and remote sensing technologies are driving innovations in forest resource assessments and monitoring on varying scales. Data acquired with airborne and spaceborne platforms provide high(er) spatial resolution, more frequent coverage, and more spectral information. Recent developments in ground-based sensors have advanced 3D measurements, low-cost permanent systems, and community-based monitoring of forests. The UNFCCC REDD+ mechanism has advanced the remote sensing community and the development of forest geospatial products that can be used by countries for the international reporting and national forest monitoring. However, an urgent need remains to better understand the options and limitations of remote and close-range sensing techniques in the field of forest degradation and forest change. Therefore, we invite scientists working on remote sensing technologies, close-range sensing, and field data to contribute to this Special Issue. Topics of interest include: (1) novel remote sensing applications that can meet the needs of forest resource information and REDD+ MRV, (2) case studies of applying remote sensing data for REDD+ MRV, (3) timeseries algorithms and methodologies for forest resource assessment on different spatial scales varying from the tree to the national level, and (4) novel close-range sensing applications that can support sustainable forestry and REDD+ MRV. We particularly welcome submissions on data fusion.

Keywords

sentinel imagery --- above-ground biomass --- predictive mapping --- machine learning --- geographically weighted regression --- canopy cover (CC) --- spectral --- texture --- digital hemispherical photograph (DHP) --- random forest (RF) --- gray level co-occurrence matrix (GLCM) --- forest inventory --- LiDAR --- tall trees --- overstory trees --- tree mapping --- crown delineation --- aboveground biomass --- Landsat --- random forest --- topography --- human activity --- aboveground biomass estimation --- remote sensing --- crown density --- low-accuracy estimation --- model comparison --- old-growth forest --- multispectral satellite imagery --- random forest --- forest classification --- remote sensing --- forestry --- phenology --- silviculture --- forest growing stock volume (GSV) --- full polarimetric SAR --- subtropical forest --- topographic effects --- environment effects --- geographic information system --- support vector machine --- random forest --- ensemble model --- hazard mapping --- 3D tree modelling --- aboveground biomass estimation --- destructive sampling --- Guyana --- LiDAR --- local tree allometry --- model evaluation --- quantitative structural model --- Pinus massoniana --- specific leaf area --- leaf area --- terrestrial laser scanning --- voxelization --- forest canopy --- REDD+ --- Cameroon --- reference level --- deforestation --- agriculture --- forest baseline --- airborne laser scanning --- terrestrial laser scanning --- remote sensing --- REDD+ --- forestry

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2020 (1)

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