Advances in Remote Sensing for Global Forest Monitoring
The topics of the book cover forest parameter estimation, methods to assess land cover and change, forest disturbances and degradation, and forest soil drought estimations. Airborne laser scanner data, aerial images, as well as data from passive and active sensors of different spatial, spectral and...
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| 格式: | Online |
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| 語言: | 英语 |
| 出版: |
MDPI - Multidisciplinary Digital Publishing Institute
2022
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| 在線閱讀: | ONIX_20220111_9783036512525_459 |
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| _version_ | 1869524497516724224 |
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| collection | Directory of Open Access Books |
| description | The topics of the book cover forest parameter estimation, methods to assess land cover and change, forest disturbances and degradation, and forest soil drought estimations. Airborne laser scanner data, aerial images, as well as data from passive and active sensors of different spatial, spectral and temporal resolutions have been utilized. Parametric and non-parametric methods including machine and deep learning methods have been employed. Uncertainty estimation is a key topic in each study. In total, 15 articles are included, of which one is a review article dealing with methods employed in remote sensing aided greenhouse gas inventories, and one is the Editorial summary presenting a short review of each article. |
| format | Online |
| id | doab-20.500.12854ir-76724 |
| 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-767242024-03-28T03:31:14Z Advances in Remote Sensing for Global Forest Monitoring Tomppo, Erkki Praks, Jaan Wang, Guangxing Waser, Lars T. forest structure change EBLUP small area estimation multitemporal LiDAR and stand-level estimates forest cover Sentinel-1 Sentinel-2 data fusion machine-learning Germany South Africa temperate forest savanna classification Sentinel 2 land use land cover improved k-NN logistic regression random forest support vector machine statistical estimator IPCC good practice guidelines activity data emissions factor removals factor Picea crassifolia Kom compatible equation nonlinear seemingly unrelated regression error-in-variable modeling leave-one-out cross-validation digital surface model digital terrain model canopy height model constrained neighbor interpolation ordinary neighbor interpolation point cloud density stereo imagery remotely sensed LAI field measured LAI validation magnitude uncertainty temporal dynamics state space models forest disturbance mapping near real-time monitoring CUSUM NRT monitoring deforestation degradation tropical forest tropical peat forest type deep learning FCN8s CRFasRNN GF2 dual-FCN8s random forests error propagation bootstrapping Landsat LiDAR La Rioja forest area change data assessment uncertainty evaluation inconsistency forest monitoring drought time series satellite data Bowen ratio carbon flux boreal forest windstorm damage synthetic aperture radar C-band genetic algorithm multinomial logistic regression n/a thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general thema EDItEUR::K Economics, Finance, Business and Management::KC Economics::KCV Economics of specific sectors::KCVG Environmental economics The topics of the book cover forest parameter estimation, methods to assess land cover and change, forest disturbances and degradation, and forest soil drought estimations. Airborne laser scanner data, aerial images, as well as data from passive and active sensors of different spatial, spectral and temporal resolutions have been utilized. Parametric and non-parametric methods including machine and deep learning methods have been employed. Uncertainty estimation is a key topic in each study. In total, 15 articles are included, of which one is a review article dealing with methods employed in remote sensing aided greenhouse gas inventories, and one is the Editorial summary presenting a short review of each article. 2022-01-11T13:40:11Z 2022-01-11T13:40:11Z 2021 book ONIX_20220111_9783036512525_459 9783036512525 9783036512532 https://directory.doabooks.org/handle/20.500.12854/76724 eng image/jpeg Attribution 4.0 International https://mdpi.com/books/pdfview/book/4173 https://mdpi.com/books/pdfview/book/4173 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-0365-1253-2 10.3390/books978-3-0365-1253-2 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783036512525 9783036512532 352 Basel, Switzerland open access |
| spellingShingle | forest structure change EBLUP small area estimation multitemporal LiDAR and stand-level estimates forest cover Sentinel-1 Sentinel-2 data fusion machine-learning Germany South Africa temperate forest savanna classification Sentinel 2 land use land cover improved k-NN logistic regression random forest support vector machine statistical estimator IPCC good practice guidelines activity data emissions factor removals factor Picea crassifolia Kom compatible equation nonlinear seemingly unrelated regression error-in-variable modeling leave-one-out cross-validation digital surface model digital terrain model canopy height model constrained neighbor interpolation ordinary neighbor interpolation point cloud density stereo imagery remotely sensed LAI field measured LAI validation magnitude uncertainty temporal dynamics state space models forest disturbance mapping near real-time monitoring CUSUM NRT monitoring deforestation degradation tropical forest tropical peat forest type deep learning FCN8s CRFasRNN GF2 dual-FCN8s random forests error propagation bootstrapping Landsat LiDAR La Rioja forest area change data assessment uncertainty evaluation inconsistency forest monitoring drought time series satellite data Bowen ratio carbon flux boreal forest windstorm damage synthetic aperture radar C-band genetic algorithm multinomial logistic regression n/a thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general thema EDItEUR::K Economics, Finance, Business and Management::KC Economics::KCV Economics of specific sectors::KCVG Environmental economics Advances in Remote Sensing for Global Forest Monitoring |
| title | Advances in Remote Sensing for Global Forest Monitoring |
| title_full | Advances in Remote Sensing for Global Forest Monitoring |
| title_fullStr | Advances in Remote Sensing for Global Forest Monitoring |
| title_full_unstemmed | Advances in Remote Sensing for Global Forest Monitoring |
| title_short | Advances in Remote Sensing for Global Forest Monitoring |
| title_sort | advances in remote sensing for global forest monitoring |
| topic | forest structure change EBLUP small area estimation multitemporal LiDAR and stand-level estimates forest cover Sentinel-1 Sentinel-2 data fusion machine-learning Germany South Africa temperate forest savanna classification Sentinel 2 land use land cover improved k-NN logistic regression random forest support vector machine statistical estimator IPCC good practice guidelines activity data emissions factor removals factor Picea crassifolia Kom compatible equation nonlinear seemingly unrelated regression error-in-variable modeling leave-one-out cross-validation digital surface model digital terrain model canopy height model constrained neighbor interpolation ordinary neighbor interpolation point cloud density stereo imagery remotely sensed LAI field measured LAI validation magnitude uncertainty temporal dynamics state space models forest disturbance mapping near real-time monitoring CUSUM NRT monitoring deforestation degradation tropical forest tropical peat forest type deep learning FCN8s CRFasRNN GF2 dual-FCN8s random forests error propagation bootstrapping Landsat LiDAR La Rioja forest area change data assessment uncertainty evaluation inconsistency forest monitoring drought time series satellite data Bowen ratio carbon flux boreal forest windstorm damage synthetic aperture radar C-band genetic algorithm multinomial logistic regression n/a thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general thema EDItEUR::K Economics, Finance, Business and Management::KC Economics::KCV Economics of specific sectors::KCVG Environmental economics |
| topic_facet | forest structure change EBLUP small area estimation multitemporal LiDAR and stand-level estimates forest cover Sentinel-1 Sentinel-2 data fusion machine-learning Germany South Africa temperate forest savanna classification Sentinel 2 land use land cover improved k-NN logistic regression random forest support vector machine statistical estimator IPCC good practice guidelines activity data emissions factor removals factor Picea crassifolia Kom compatible equation nonlinear seemingly unrelated regression error-in-variable modeling leave-one-out cross-validation digital surface model digital terrain model canopy height model constrained neighbor interpolation ordinary neighbor interpolation point cloud density stereo imagery remotely sensed LAI field measured LAI validation magnitude uncertainty temporal dynamics state space models forest disturbance mapping near real-time monitoring CUSUM NRT monitoring deforestation degradation tropical forest tropical peat forest type deep learning FCN8s CRFasRNN GF2 dual-FCN8s random forests error propagation bootstrapping Landsat LiDAR La Rioja forest area change data assessment uncertainty evaluation inconsistency forest monitoring drought time series satellite data Bowen ratio carbon flux boreal forest windstorm damage synthetic aperture radar C-band genetic algorithm multinomial logistic regression n/a thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general thema EDItEUR::K Economics, Finance, Business and Management::KC Economics::KCV Economics of specific sectors::KCVG Environmental economics |
| url | ONIX_20220111_9783036512525_459 |