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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 online resource (352 p.) |
| Soggetto topico |
Environmental economics
Research and information: general |
| Soggetto non controllato |
activity data
bootstrapping boreal forest Bowen ratio C-band canopy height model carbon flux classification compatible equation constrained neighbor interpolation CRFasRNN CUSUM data assessment data fusion deep learning deforestation degradation digital surface model digital terrain model drought dual-FCN8s EBLUP emissions factor error propagation error-in-variable modeling FCN8s field measured LAI forest area change forest cover forest disturbance mapping forest monitoring forest structure change forest type genetic algorithm Germany GF2 improved k-NN inconsistency IPCC good practice guidelines La Rioja land use land cover Landsat leave-one-out cross-validation LiDAR logistic regression machine-learning magnitude multinomial logistic regression multitemporal LiDAR and stand-level estimates n/a near real-time monitoring nonlinear seemingly unrelated regression NRT monitoring ordinary neighbor interpolation Picea crassifolia Kom point cloud density random forest random forests remotely sensed LAI removals factor savanna Sentinel 2 Sentinel-1 Sentinel-2 small area estimation South Africa state space models statistical estimator stereo imagery support vector machine synthetic aperture radar temperate forest temporal dynamics time series satellite data tropical forest tropical peat uncertainty uncertainty evaluation validation windstorm damage |
| 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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Remote Sensing of Hydro-Meteorology
| Remote Sensing of Hydro-Meteorology |
| Autore | Lee Joo-Heon |
| Pubbl/distr/stampa | Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 |
| Descrizione fisica | 1 online resource (154 p.) |
| Soggetto topico |
History of engineering and technology
Technology: general issues |
| Soggetto non controllato |
agricultural drought
Bayesian principal component analysis (BPCA) China El Niño-Southern Oscillation El Niño-Southern Oscillation (ENSO) error propagation extreme precipitation index fuzzy C-means clustering genetic programming Huai River Basin hydrological drought hydrological modeling Indian Ocean Dipole (IOD) Indian Ocean Dipole mode integrated drought monitoring intentional statistical simulation KGE linear trend meteorological drought MODIS chlorophyll-a monsoon-climate watershed multiple polynomial regression mutual information non-stationarity of seasonal precipitation PERSIANN-CDR prediction rainfall variability remote sensing satellite-based precipitation sentinel-2A MSI singular spectrum analysis spatial downscaling statistical model statistical simulation typhoon-induced rainfall |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910566458603321 |
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Lee Joo-Heon
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| Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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