Info
- Utilizzare la checkbox di selezione a fianco di ciascun documento per attivare le funzionalità di stampa, invio email, download nei formati disponibili del (i) record.
Geo-Informatics in Resource Management
| Geo-Informatics in Resource Management |
| Autore | Mesas Carrascosa Francisco Javier |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020 |
| Descrizione fisica | 1 electronic resource (206 p.) |
| Soggetto topico | Research & information: general |
| Soggetto non controllato |
secondary succession monitoring
Natura 2000 threats tree detection archival photographs spectro-textural classification granulometric analysis GLCM alpine grassland fractional vegetation cover ground survey precision evaluation multi-scale LAI product validation PROSAIL model EBK crop growth period adaptive K-means algorithm heavy industry heat sources NPP-VIIRS active fire data night-time light data spatial autocorrelation spatial pattern spatial relationship natural wetlands changes associated influencing factors mainland China farmland abandonment mapping textural segmentation aerial imagery land use Poznań agent based modeling disaster management resource allocation high severity level first come first serve geographical information system bearing capacity analytic hierarchy process geographical survey of national conditions hotspot analysis topsis algorithm automatic identification system data 21st Century Maritime Silk Road region oil flow analysis maritime oil chokepoint Middle East Respiratory Syndrome seismic parameters GIS seismicity spatial analysis b-value earthquake catalog future scenarios prelude dynamic of land use Spatial Decision Support System, CORINE Land Cover remote sensing geographic information system |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557296603321 |
Mesas Carrascosa Francisco Javier
|
||
| Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Remote Sensing of Natural Hazards
| Remote Sensing of Natural Hazards |
| Autore | Ahmed Bayes |
| Pubbl/distr/stampa | Basel, : MDPI Books, 2022 |
| Descrizione fisica | 1 electronic resource (314 p.) |
| Soggetto topico |
Research & information: general
Geography |
| Soggetto non controllato |
sequential estimation
InSAR time series groundwater land subsidence and rebound earthquake rapid mapping damage assessment deep learning convolutional neural networks ordinal regression aerial image landslide machine learning models remote sensing ensemble models validation ice storm forest ecosystems disaster impact post-disaster recovery ice jam snowmelt flood mapping monitoring and prediction VIIRS ABI NUAE flash flood BRT CART naive Bayes tree geohydrological model landslide susceptibility Bangladesh digital elevation model random forest modified frequency ratio logistic regression automatic landslide detection OBIA PBA random forests supervised classification landslides uncertainty K-Nearest Neighbor Multi-Layer Perceptron Random Forest Support Vector Machine agriculture drought NDVI MODIS landslide deformation InSAR reservoir water level Sentinel-1 Three Gorges Reservoir area (China) peri-urbanization urban growth boundary demarcation climate change climate migrants natural hazards flooding land use and land cover night-time light data Dhaka |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910595070103321 |
|
Ahmed Bayes
|
||
| Basel, : MDPI Books, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||