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Air Quality Research Using Remote Sensing
| Air Quality Research Using Remote Sensing |
| Autore | Costa Maria João |
| Pubbl/distr/stampa | Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 |
| Descrizione fisica | 1 electronic resource (190 p.) |
| Soggetto topico |
Research & information: general
Meteorology & climatology |
| Soggetto non controllato |
tropospheric NO2 concentrations
nitrogen dioxide OMI spatio-temporal trends DBEST PolyTrend time-series analysis breakpoint detection air pollution TROPOMI COVID nitrogen oxides satellite-based NO2 land use regression exposure assessment carbon monoxide COVID-19 China surface concentration IASI drone UAV gas sensors odour industrial emissions mapping environmental monitoring aerosol optical depth CAMS machine learning MODIS urban form PM2.5 landscape metrics geographically weighted regression Yunnan Plateau biomass burning cross-border transport WRF-Chem formaldehyde trend satellite monitor annual seasonal temperature meteorology AOD Europe open data |
| ISBN | 3-0365-5894-2 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910639989803321 |
Costa Maria João
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| Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Electronics, Close-Range Sensors and Artificial Intelligence in Forestry
| Electronics, Close-Range Sensors and Artificial Intelligence in Forestry |
| Autore | Borz Stelian Alexandru |
| Pubbl/distr/stampa | Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 |
| Descrizione fisica | 1 electronic resource (248 p.) |
| Soggetto topico |
Research & information: general
Biology, life sciences Forestry & related industries |
| Soggetto non controllato |
forest fire detection
deep learning ensemble learning Yolov5 EfficientDet EfficientNet big data automation artificial intelligence multi-modality acceleration classification events performance motor-manual felling willow Romania region detection of forest fire grading of forest fire weakly supervised loss fine segmentation region-refining segmentation lightweight Faster R-CNN ultrasound sensors road scanner terrestrial laser scanning TLS forest road maintenance forest road monitoring crowned road surface digital twinning climate smart LiDAR digitalization forest loss land-cover change machine learning spatial heterogeneity random forest model geographically weighted regression aboveground biomass estimation remote sensing Sentinel-2 Iran multiple regression artificial neural network k-nearest neighbor random forest canopy drone leaf leaves foliar samples sampling Aerial robotics UAS UAV IoT forest ecology accessibility wood diameter length close-range sensing Augmented Reality comparison accuracy effectiveness potential forestry 4.0 wood technology sawmilling productivity prediction long-term tree ring forestry detection resistance sensor micro-drilling resistance method signal processing Signal-to-Noise Ratio (SNR) |
| ISBN | 3-0365-6171-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910639985003321 |
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Borz Stelian Alexandru
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| Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Novel Approaches in Landslide Monitoring and Data Analysis
| Novel Approaches in Landslide Monitoring and Data Analysis |
| Autore | Blahut Jan |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2022 |
| Descrizione fisica | 1 electronic resource (282 p.) |
| Soggetto topico |
Research & information: general
Earth sciences, geography, environment, planning |
| Soggetto non controllato |
landslide susceptibility assessment
geographically weighted regression spatial non-stationary spatial proximity slope unit multitemporal DEM control factors susceptibility assessment LRM historical landslide events unsaturated soil capillary barrier multi-layer slope slope failure coastal landslides mass rock creep coastal cliffs land surface analysis data analysis Conero promontory slow-moving landslide landslide monitoring time-series analysis San Andrés Landslide El Hierro Canary Islands large-scale landslide model experiment soil–water characteristic curve Bayesian updating Markov chain Monte Carlo artificial neural networks object-based image analysis Sentinel-1 Sentinel-2 digital elevation model InSAR landslide landslide-dammed lake river Iceland rockfill ground-based interferometric synthetic aperture radar construction cross-sectional area of equal displacement body landslide warning method data mining landslide detection landslide inventory Typhoon Morakot Global Positioning System (GPS) disaster prevention monitoring disaster mitigation monitoring landslides photogrammetry global positioning system in-hole wire extensometer DInSAR GBSAR landslide susceptibility ranking cross validation prediction model prediction pattern target pattern uncertainty pattern airborne electromagnetics physical-based modeling tropical volcanic environment La Martinique modelling susceptibility |
| ISBN | 3-0365-3788-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910619468903321 |
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Blahut Jan
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| MDPI - Multidisciplinary Digital Publishing Institute, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Remote Sensing of Precipitation: Part II
| Remote Sensing of Precipitation: Part II |
| Autore | Michaelides Silas |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
| Descrizione fisica | 1 electronic resource (594 p.) |
| Soggetto topico | Research & information: general |
| Soggetto non controllato |
Northern China
raindrop size distribution (DSD) microphysical processes quantitative precipitation estimation (QPE) satellite-based precipitation elevation extreme events IMERG-V05B and V06A MSWEP ERA5 SM2RAIN precipitation estimation soil moisture SM2RAIN-CCI SM2RAIN-ASCAT multi-satellite precipitation analysis (TMPA) error decomposition complex topography diverse climate gauge data IMERG TAHMO morphing field displacement TIGGE precipitation numerical weather prediction satellite flood spring 2019 Iran GPM IMERG satellite precipitation spatiotemporal analysis statistical distribution validation Mainland China GSMaP_NRT GSMaP_Gauge_NRT raindrop size distribution radar reflectivity raindrop spectrometer semi-arid area assessment Taiwan data assimilation WRF model high-impact rainfall events GNSS ZTD optimum interpolation geographically weighted regression downscaling Tianshan Mountains satellite precipitation products evaluation daily rainfall hourly rainfall GPM TRMM GNSS GNSS antenna receiver antenna calibration relative calibration Phase Center Variation U-blox goGPS Zenith Tropospheric Delay ZED-F9P GSMaP Nepal cloud radar thunderstorm LDR hydrometeor hydrometeor classification lightning discharge remote sensing SEVIRI ground radar precipitation interpolation geographically and temporally weighted regression time weight function geographically and temporally weighted regression kriging extreme rainfall polarimetric radar signatures quantitative precipitation estimation southern china reanalysis linear trends mainland China EDBF algorithm geospatial predictor spatial pattern weighted precipitation Cyprus bias correction object-based method storm events Thies disdrometer weather circulations convective stratiform rain spectra radar reflectivity-rain rate relationship gridded precipitation products abrupt changes trends statistical indicators agriculture Pakistan rainfall radar extreme precipitation spatial bootstrap Louisiana annual maxima |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Altri titoli varianti | Remote Sensing of Precipitation |
| Record Nr. | UNINA-9910557704903321 |
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Michaelides Silas
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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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Sustainable Real Estate: Management, Assessment and Innovations
| Sustainable Real Estate: Management, Assessment and Innovations |
| Autore | De Paola Pierfrancesco |
| Pubbl/distr/stampa | Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 |
| Descrizione fisica | 1 electronic resource (252 p.) |
| Soggetto topico | Information technology industries |
| Soggetto non controllato |
big data
decision-making feasibility study fuzzy theory high-rise building mixed-use development urban tree canopy (UTC) hedonic price model two-stage spatial model multi-level mixed model varying effect customer gender women tenure choice sustainable housing housing market mass appraisal techniques evaluation model hedonic price method geographically weighted regression evolutionary polynomial regression market value smart building smart energy system renewable energy resources energy storage reserve power system investor motives investment profitability smart readiness indicator discounted cash flow analysis natural landscape views visual perception housing price quantile regression marginal impact wealth inequality growth management sustainable development transit-oriented development contingent valuation method retirement housing downsizing housing consumption housing tenure choice consumption housing wealth effect financial wealth effect multi-step causality ESG real estate companies ratings sustainability energy efficiency sustainable decision-making sustainable social housing management multi-criteria decision-making (MCDM) AHP WASPAS COPRAS social cohesion uncertainty U.S. housing markets local projection method impulse response functions |
| ISBN | 3-0365-5826-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Altri titoli varianti | Sustainable Real Estate |
| Record Nr. | UNINA-9910639996603321 |
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De Paola Pierfrancesco
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| Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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