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Advances in Remote Sensing for Global Forest Monitoring
| Advances in Remote Sensing for Global Forest Monitoring |
| Autore | Tomppo Erkki |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
| Descrizione fisica | 1 electronic resource (352 p.) |
| Soggetto topico |
Research & information: general
Environmental economics |
| Soggetto non controllato |
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 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557338103321 |
Tomppo Erkki
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| Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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ALOS-2/PALSAR-2 Calibration, Validation, Science and Applications
| ALOS-2/PALSAR-2 Calibration, Validation, Science and Applications |
| Autore | Tadono Takeo |
| Pubbl/distr/stampa | Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 |
| Descrizione fisica | 1 electronic resource (240 p.) |
| Soggetto topico |
Technology: general issues
History of engineering & technology Environmental science, engineering & technology |
| Soggetto non controllato |
Sentinel-1
ALOS/PALSAR-2 land subsidence accuracy assessment Alexandria City Egypt local climate zone random forest feature importance land surface temperature grid cells Sentinel-2 PALSAR-2 ASTER soil moisture ALOS-2 GA-BP water cloud model L-band SAR backscattering soil moisture content LAI HH and HV polarization flood NoBADI Florida Hurricane Irma synthetic aperture radar polarimetric radar co-polarized phase difference radar scattering vegetation radar applications agriculture leaf area index leave-one-out cross-validation oil palm radar vegetation index vegetation descriptors ecosystem carbon cycle L-band SAR vegetation index random forest regression plantation permafrost InSAR Qinghai-Tibet Plateau ALOS thermal melting collapse Sentinel-1A SBAS-InSAR heavy forest area potential landslide identification SAR-based landslide detection Growing Split-Based Approach (GSBA) Hokkaido landslide Putanpunas landslide SAR polarimetry model-free 3-component decomposition for full polarimetric data (MF3CF) radar polarimetry calibration Faraday rotation |
| ISBN | 3-0365-6105-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910639994803321 |
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Tadono Takeo
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| Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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