Remote Sensing of Above Ground Biomass
Above ground biomass has been listed by the Intergovernmental Panel on Climate Change as one of the five most prominent, visible, and dynamic terrestrial carbon pools. The increased awareness of the impacts of climate change has seen a burgeoning need to consistently assess carbon stocks to combat c...
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| Format: | Online |
| Language: | English |
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MDPI - Multidisciplinary Digital Publishing Institute
2021
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| Online Access: | 42486 |
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| author | Mutanga, Onisimo Kumar, Lalit |
| author_browse | Kumar, Lalit Mutanga, Onisimo |
| author_facet | Mutanga, Onisimo Kumar, Lalit |
| author_sort | Mutanga, Onisimo |
| collection | Directory of Open Access Books |
| description | Above ground biomass has been listed by the Intergovernmental Panel on Climate Change as one of the five most prominent, visible, and dynamic terrestrial carbon pools. The increased awareness of the impacts of climate change has seen a burgeoning need to consistently assess carbon stocks to combat carbon sequestration. An accurate estimation of carbon stocks and an understanding of the carbon sources and sinks can aid the improvement and accuracy of carbon flux models, an important pre-requisite of climate change impact projections. Based on 15 research topics, this book demonstrates the role of remote sensing in quantifying above ground biomass (forest, grass, woodlands) across varying spatial and temporal scales. The innovative application areas of the book include algorithm development and implementation, accuracy assessment, scaling issues (local–regional–global biomass mapping), and the integration of microwaves (i.e. LiDAR), along with optical sensors, forest biomass mapping, rangeland productivity and abundance (grass biomass, density, cover), bush encroachment biomass, and seasonal and long-term biomass monitoring. |
| format | Online |
| id | doab-20.500.12854ir-58170 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2021 |
| publishDateRange | 2021 |
| publishDateSort | 2021 |
| publisher | MDPI - Multidisciplinary Digital Publishing Institute |
| publisherStr | MDPI - Multidisciplinary Digital Publishing Institute |
| record_format | ojs |
| spelling | doab-20.500.12854ir-581702024-04-11T15:10:36Z Remote Sensing of Above Ground Biomass Mutanga, Onisimo Kumar, Lalit TA1-2040 T1-995 TA170-171 NDLMA n/a multi-angle remote sensing TerraSAR-X above ground biomass stem volume regression analysis ground-based remote sensing sensor fusion pasture biomass grazing management livestock mixed forest SPLSR estimation accuracy Bidirectional Reflectance Distribution Factor forage crops Land Surface Phenology climate change vegetation index dry biomass mapping rangeland productivity vegetation indices error analysis broadleaves remote sensing applicability evaluation ultrasonic sensor chlorophyll index alpine meadow grassland forest biomass anthropogenic disturbance fractional vegetation cover alpine grassland conservation carbon mitigation conifer short grass grazing exclusion MODIS time series random forest aboveground biomass NDVI AquaCrop model inversion model wetlands field spectrometry spectral index yield foliage projective cover lidar correlation coefficient Sahel biomass dry matter index Niger Landsat grass biomass particle swarm optimization winter wheat carbon inventory rice forest structure information MODIS light detection and ranging (LiDAR) ALOS2 ecological policies above-ground biomass Wambiana grazing trial food security forest above ground biomass (AGB) Atriplex nummularia regional sustainability CIRed-edge thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology Above ground biomass has been listed by the Intergovernmental Panel on Climate Change as one of the five most prominent, visible, and dynamic terrestrial carbon pools. The increased awareness of the impacts of climate change has seen a burgeoning need to consistently assess carbon stocks to combat carbon sequestration. An accurate estimation of carbon stocks and an understanding of the carbon sources and sinks can aid the improvement and accuracy of carbon flux models, an important pre-requisite of climate change impact projections. Based on 15 research topics, this book demonstrates the role of remote sensing in quantifying above ground biomass (forest, grass, woodlands) across varying spatial and temporal scales. The innovative application areas of the book include algorithm development and implementation, accuracy assessment, scaling issues (local–regional–global biomass mapping), and the integration of microwaves (i.e. LiDAR), along with optical sensors, forest biomass mapping, rangeland productivity and abundance (grass biomass, density, cover), bush encroachment biomass, and seasonal and long-term biomass monitoring. 2021-02-12T01:47:37Z 2021-02-12T01:47:37Z 2019-12-09 11:49:15 2019 book 42486 9783039212101 9783039212095 https://directory.doabooks.org/handle/20.500.12854/58170 eng application/octet-stream Attribution-NonCommercial-NoDerivatives 4.0 International https://mdpi.com/books/pdfview/book/1500 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-03921-210-1 10.3390/books978-3-03921-210-1 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783039212101 9783039212095 264 open access |
| spellingShingle | TA1-2040 T1-995 TA170-171 NDLMA n/a multi-angle remote sensing TerraSAR-X above ground biomass stem volume regression analysis ground-based remote sensing sensor fusion pasture biomass grazing management livestock mixed forest SPLSR estimation accuracy Bidirectional Reflectance Distribution Factor forage crops Land Surface Phenology climate change vegetation index dry biomass mapping rangeland productivity vegetation indices error analysis broadleaves remote sensing applicability evaluation ultrasonic sensor chlorophyll index alpine meadow grassland forest biomass anthropogenic disturbance fractional vegetation cover alpine grassland conservation carbon mitigation conifer short grass grazing exclusion MODIS time series random forest aboveground biomass NDVI AquaCrop model inversion model wetlands field spectrometry spectral index yield foliage projective cover lidar correlation coefficient Sahel biomass dry matter index Niger Landsat grass biomass particle swarm optimization winter wheat carbon inventory rice forest structure information MODIS light detection and ranging (LiDAR) ALOS2 ecological policies above-ground biomass Wambiana grazing trial food security forest above ground biomass (AGB) Atriplex nummularia regional sustainability CIRed-edge thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology Mutanga, Onisimo Kumar, Lalit Remote Sensing of Above Ground Biomass |
| title | Remote Sensing of Above Ground Biomass |
| title_full | Remote Sensing of Above Ground Biomass |
| title_fullStr | Remote Sensing of Above Ground Biomass |
| title_full_unstemmed | Remote Sensing of Above Ground Biomass |
| title_short | Remote Sensing of Above Ground Biomass |
| title_sort | remote sensing of above ground biomass |
| topic | TA1-2040 T1-995 TA170-171 NDLMA n/a multi-angle remote sensing TerraSAR-X above ground biomass stem volume regression analysis ground-based remote sensing sensor fusion pasture biomass grazing management livestock mixed forest SPLSR estimation accuracy Bidirectional Reflectance Distribution Factor forage crops Land Surface Phenology climate change vegetation index dry biomass mapping rangeland productivity vegetation indices error analysis broadleaves remote sensing applicability evaluation ultrasonic sensor chlorophyll index alpine meadow grassland forest biomass anthropogenic disturbance fractional vegetation cover alpine grassland conservation carbon mitigation conifer short grass grazing exclusion MODIS time series random forest aboveground biomass NDVI AquaCrop model inversion model wetlands field spectrometry spectral index yield foliage projective cover lidar correlation coefficient Sahel biomass dry matter index Niger Landsat grass biomass particle swarm optimization winter wheat carbon inventory rice forest structure information MODIS light detection and ranging (LiDAR) ALOS2 ecological policies above-ground biomass Wambiana grazing trial food security forest above ground biomass (AGB) Atriplex nummularia regional sustainability CIRed-edge thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology |
| topic_facet | TA1-2040 T1-995 TA170-171 NDLMA n/a multi-angle remote sensing TerraSAR-X above ground biomass stem volume regression analysis ground-based remote sensing sensor fusion pasture biomass grazing management livestock mixed forest SPLSR estimation accuracy Bidirectional Reflectance Distribution Factor forage crops Land Surface Phenology climate change vegetation index dry biomass mapping rangeland productivity vegetation indices error analysis broadleaves remote sensing applicability evaluation ultrasonic sensor chlorophyll index alpine meadow grassland forest biomass anthropogenic disturbance fractional vegetation cover alpine grassland conservation carbon mitigation conifer short grass grazing exclusion MODIS time series random forest aboveground biomass NDVI AquaCrop model inversion model wetlands field spectrometry spectral index yield foliage projective cover lidar correlation coefficient Sahel biomass dry matter index Niger Landsat grass biomass particle swarm optimization winter wheat carbon inventory rice forest structure information MODIS light detection and ranging (LiDAR) ALOS2 ecological policies above-ground biomass Wambiana grazing trial food security forest above ground biomass (AGB) Atriplex nummularia regional sustainability CIRed-edge thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology |
| url | 42486 |
| work_keys_str_mv | AT mutangaonisimo remotesensingofabovegroundbiomass AT kumarlalit remotesensingofabovegroundbiomass |