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Land Surface Monitoring Based on Satellite Imagery
| Land Surface Monitoring Based on Satellite Imagery |
| Autore | Venafra Sara |
| Pubbl/distr/stampa | Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 |
| Descrizione fisica | 1 electronic resource (232 p.) |
| Soggetto topico |
Research & information: general
Environmental economics |
| Soggetto non controllato |
Sentinel-2
spectral bands LAI vegetation indices Sentinel-1 SAR RVI incidence angle crop coefficient leaf area index urban heat island UHI regional impacts non-urban areas remote sensing thermal band UHI intensity remote sensing/GIS spatial dynamics landscape metrics urban–rural gradient urbanization automatic monitoring time series change detection urban planning hyperspectral cacti drone climate change drought water deficit index infrared observations satellite surface temperature air temperature humidity dew point temperature land subsidence DInSAR differential interferograms stacking floods coastal plain of Tabasco crop residue fusion machine learning algorithm reflective and radar bands land-cover change REDD+ Google Earth Engine random forest landsat Togo emissivity evapotranspiration heterogeneity Rao’s Q index spectral variation hypothesis thermal infrared |
| ISBN | 3-0365-5930-2 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910639991903321 |
Venafra Sara
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| Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Machine Learning Techniques Applied to Geoscience Information System and Remote Sensing
| Machine Learning Techniques Applied to Geoscience Information System and Remote Sensing |
| Autore | Lee Saro |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2019 |
| Descrizione fisica | 1 electronic resource (438 p.) |
| Soggetto non controllato |
artificial neural network
model switching sensitivity analysis neural networks logit boost Qaidam Basin land subsidence land use/land cover (LULC) naïve Bayes multilayer perceptron convolutional neural networks single-class data descriptors logistic regression feature selection mapping particulate matter 10 (PM10) Bayes net gray-level co-occurrence matrix multi-scale Logistic Model Trees classification Panax notoginseng large scene coarse particle grayscale aerial image Gaofen-2 environmental variables variable selection spatial predictive models weights of evidence landslide prediction random forest boosted regression tree convolutional network Vietnam model validation colorization data mining techniques spatial predictions SCAI unmanned aerial vehicle high-resolution texture spatial sparse recovery landslide susceptibility map machine learning reproducible research constrained spatial smoothing support vector machine random forest regression model assessment information gain ALS point cloud bagging ensemble one-class classifiers leaf area index (LAI) landslide susceptibility landsat image ionospheric delay constraints spatial spline regression remote sensing image segmentation panchromatic Sentinel-2 remote sensing optical remote sensing materia medica resource GIS precise weighting change detection TRMM traffic CO crop training sample size convergence time object detection gully erosion deep learning classification-based learning transfer learning landslide traffic CO prediction hybrid model winter wheat spatial distribution logistic alternating direction method of multipliers hybrid structure convolutional neural networks geoherb predictive accuracy real-time precise point positioning spectral bands |
| ISBN | 3-03921-216-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910367564103321 |
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Lee Saro
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| MDPI - Multidisciplinary Digital Publishing Institute, 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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