Operationalization of Remote Sensing Solutions for Sustainable Forest Management
The great potential of remote sensing technologies for operational use in sustainable forest management is addressed in this book, which is the reprint of papers published in the Remote Sensing Special Issue “Operationalization of Remote Sensing Solutions for Sustainable Forest Management”. The stud...
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| Médium: | Online |
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| Jazyk: | angličtina |
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MDPI - Multidisciplinary Digital Publishing Institute
2022
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| On-line přístup: | ONIX_20220111_9783036509822_100 |
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| _version_ | 1869529875351601152 |
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| collection | Directory of Open Access Books |
| description | The great potential of remote sensing technologies for operational use in sustainable forest management is addressed in this book, which is the reprint of papers published in the Remote Sensing Special Issue “Operationalization of Remote Sensing Solutions for Sustainable Forest Management”. The studies come from three continents and cover multiple remote sensing systems (including terrestrial mobile laser scanning, unmanned aerial vehicles, airborne laser scanning, and satellite data acquisition) and a diversity of data processing algorithms, with a focus on machine learning approaches. The focus of the studies ranges from identification and characterization of individual trees to deriving national- or even continental-level forest attributes and maps. There are studies carefully describing exercises on the case study level, and there are also studies introducing new methodologies for transdisciplinary remote sensing applications. Even though most of the authors look forward to continuing their research, nearly all studies introduced are ready for operational use or have already been implemented in practical forestry. |
| format | Online |
| id | doab-20.500.12854ir-76364 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2022 |
| publishDateRange | 2022 |
| publishDateSort | 2022 |
| publisher | MDPI - Multidisciplinary Digital Publishing Institute |
| publisherStr | MDPI - Multidisciplinary Digital Publishing Institute |
| record_format | ojs |
| spelling | doab-20.500.12854ir-763642024-03-28T03:32:18Z Operationalization of Remote Sensing Solutions for Sustainable Forest Management Mozgeris, Gintautas Balenović, Ivan forest road inventory total station global navigation satellite system point cloud precision density positional accuracy efficiency mangrove sustainability deforestation depletion anthropogenic natural water balance Southeast Asia Phoracantha spp. unmanned aerial vehicle (UAV) multispectral imagery vegetation index thresholding analysis Large Scale Mean-Shift Segmentation (LSMS) Random Forest (RF) forest mask validation probability sampling remote sensing earth observations forestry accuracy assessment forest classification forested catchment hydrological modeling SWAT model DEM airborne laser scanning deep learning Landsat national forest inventory stand volume bark beetle Ips typographus L. pest change detection forest damage spruce Sentinel-2 damage mapping multi-temporal regression mangrove replanting restoration analytic hierarchy process UAV DJI drone machine learning forest canopy canopy gaps canopy openings percentage satellite indices Elastic Net beech–fir forests pixel-based supervised classification random forest support vector machine gray level cooccurrence matrix (GLCM) principal component analysis (PCA) WorldView-3 wildfires MaxENT risk modeling GIS multi-scale analysis Yakutia Artic Siberia phenology modelling forest disturbance forest monitoring bark beetle infestation forest management time series analysis satellite imagery landsat time series growing stock volume forest inventory harmonic regression n/a thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general The great potential of remote sensing technologies for operational use in sustainable forest management is addressed in this book, which is the reprint of papers published in the Remote Sensing Special Issue “Operationalization of Remote Sensing Solutions for Sustainable Forest Management”. The studies come from three continents and cover multiple remote sensing systems (including terrestrial mobile laser scanning, unmanned aerial vehicles, airborne laser scanning, and satellite data acquisition) and a diversity of data processing algorithms, with a focus on machine learning approaches. The focus of the studies ranges from identification and characterization of individual trees to deriving national- or even continental-level forest attributes and maps. There are studies carefully describing exercises on the case study level, and there are also studies introducing new methodologies for transdisciplinary remote sensing applications. Even though most of the authors look forward to continuing their research, nearly all studies introduced are ready for operational use or have already been implemented in practical forestry. 2022-01-11T13:29:58Z 2022-01-11T13:29:58Z 2021 book ONIX_20220111_9783036509822_100 9783036509822 9783036509839 https://directory.doabooks.org/handle/20.500.12854/76364 eng image/jpeg Attribution 4.0 International https://mdpi.com/books/pdfview/book/3789 https://mdpi.com/books/pdfview/book/3789 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-0365-0983-9 10.3390/books978-3-0365-0983-9 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783036509822 9783036509839 296 Basel, Switzerland open access |
| spellingShingle | forest road inventory total station global navigation satellite system point cloud precision density positional accuracy efficiency mangrove sustainability deforestation depletion anthropogenic natural water balance Southeast Asia Phoracantha spp. unmanned aerial vehicle (UAV) multispectral imagery vegetation index thresholding analysis Large Scale Mean-Shift Segmentation (LSMS) Random Forest (RF) forest mask validation probability sampling remote sensing earth observations forestry accuracy assessment forest classification forested catchment hydrological modeling SWAT model DEM airborne laser scanning deep learning Landsat national forest inventory stand volume bark beetle Ips typographus L. pest change detection forest damage spruce Sentinel-2 damage mapping multi-temporal regression mangrove replanting restoration analytic hierarchy process UAV DJI drone machine learning forest canopy canopy gaps canopy openings percentage satellite indices Elastic Net beech–fir forests pixel-based supervised classification random forest support vector machine gray level cooccurrence matrix (GLCM) principal component analysis (PCA) WorldView-3 wildfires MaxENT risk modeling GIS multi-scale analysis Yakutia Artic Siberia phenology modelling forest disturbance forest monitoring bark beetle infestation forest management time series analysis satellite imagery landsat time series growing stock volume forest inventory harmonic regression n/a thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general Operationalization of Remote Sensing Solutions for Sustainable Forest Management |
| title | Operationalization of Remote Sensing Solutions for Sustainable Forest Management |
| title_full | Operationalization of Remote Sensing Solutions for Sustainable Forest Management |
| title_fullStr | Operationalization of Remote Sensing Solutions for Sustainable Forest Management |
| title_full_unstemmed | Operationalization of Remote Sensing Solutions for Sustainable Forest Management |
| title_short | Operationalization of Remote Sensing Solutions for Sustainable Forest Management |
| title_sort | operationalization of remote sensing solutions for sustainable forest management |
| topic | forest road inventory total station global navigation satellite system point cloud precision density positional accuracy efficiency mangrove sustainability deforestation depletion anthropogenic natural water balance Southeast Asia Phoracantha spp. unmanned aerial vehicle (UAV) multispectral imagery vegetation index thresholding analysis Large Scale Mean-Shift Segmentation (LSMS) Random Forest (RF) forest mask validation probability sampling remote sensing earth observations forestry accuracy assessment forest classification forested catchment hydrological modeling SWAT model DEM airborne laser scanning deep learning Landsat national forest inventory stand volume bark beetle Ips typographus L. pest change detection forest damage spruce Sentinel-2 damage mapping multi-temporal regression mangrove replanting restoration analytic hierarchy process UAV DJI drone machine learning forest canopy canopy gaps canopy openings percentage satellite indices Elastic Net beech–fir forests pixel-based supervised classification random forest support vector machine gray level cooccurrence matrix (GLCM) principal component analysis (PCA) WorldView-3 wildfires MaxENT risk modeling GIS multi-scale analysis Yakutia Artic Siberia phenology modelling forest disturbance forest monitoring bark beetle infestation forest management time series analysis satellite imagery landsat time series growing stock volume forest inventory harmonic regression n/a thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general |
| topic_facet | forest road inventory total station global navigation satellite system point cloud precision density positional accuracy efficiency mangrove sustainability deforestation depletion anthropogenic natural water balance Southeast Asia Phoracantha spp. unmanned aerial vehicle (UAV) multispectral imagery vegetation index thresholding analysis Large Scale Mean-Shift Segmentation (LSMS) Random Forest (RF) forest mask validation probability sampling remote sensing earth observations forestry accuracy assessment forest classification forested catchment hydrological modeling SWAT model DEM airborne laser scanning deep learning Landsat national forest inventory stand volume bark beetle Ips typographus L. pest change detection forest damage spruce Sentinel-2 damage mapping multi-temporal regression mangrove replanting restoration analytic hierarchy process UAV DJI drone machine learning forest canopy canopy gaps canopy openings percentage satellite indices Elastic Net beech–fir forests pixel-based supervised classification random forest support vector machine gray level cooccurrence matrix (GLCM) principal component analysis (PCA) WorldView-3 wildfires MaxENT risk modeling GIS multi-scale analysis Yakutia Artic Siberia phenology modelling forest disturbance forest monitoring bark beetle infestation forest management time series analysis satellite imagery landsat time series growing stock volume forest inventory harmonic regression n/a thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general |
| url | ONIX_20220111_9783036509822_100 |