Land Surface Monitoring Based on Satellite Imagery

This book focuses attention on significant novel approaches developed to monitor land surface by exploiting satellite data in the infrared and visible ranges. Unlike in situ measurements, satellite data provide global coverage and higher temporal resolution, with very accurate retrievals of land par...

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Bibliographic Details
Other Authors: Venafra, Sara (Editor), Serio, Carmine (Editor), Masiello, Guido (Editor)
Format: Electronic Book Chapter
Language:English
Published: Basel MDPI - Multidisciplinary Digital Publishing Institute 2022
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Online Access:DOAB: download the publication
DOAB: description of the publication
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245 1 0 |a Land Surface Monitoring Based on Satellite Imagery 
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520 |a This book focuses attention on significant novel approaches developed to monitor land surface by exploiting satellite data in the infrared and visible ranges. Unlike in situ measurements, satellite data provide global coverage and higher temporal resolution, with very accurate retrievals of land parameters. This is fundamental in the study of climate change and global warming. The authors offer an overview of different methodologies to retrieve land surface parameters- evapotranspiration, emissivity contrast and water deficit indices, land subsidence, leaf area index, vegetation height, and crop coefficient-all of which play a significant role in the study of land cover, land use, monitoring of vegetation and soil water stress, as well as early warning and detection of forest fires and drought. 
540 |a Creative Commons  |f https://creativecommons.org/licenses/by/4.0/  |2 cc  |4 https://creativecommons.org/licenses/by/4.0/ 
546 |a English 
650 7 |a Research & information: general  |2 bicssc 
650 7 |a Environmental economics  |2 bicssc 
653 |a Sentinel-2 
653 |a spectral bands 
653 |a LAI 
653 |a vegetation indices 
653 |a Sentinel-1 
653 |a SAR 
653 |a RVI 
653 |a incidence angle 
653 |a crop coefficient 
653 |a leaf area index 
653 |a urban heat island 
653 |a UHI regional impacts 
653 |a non-urban areas 
653 |a remote sensing 
653 |a thermal band 
653 |a UHI intensity 
653 |a remote sensing/GIS 
653 |a spatial dynamics 
653 |a landscape metrics 
653 |a urban-rural gradient 
653 |a urbanization 
653 |a automatic monitoring 
653 |a time series 
653 |a change detection 
653 |a urban planning 
653 |a hyperspectral 
653 |a cacti 
653 |a drone 
653 |a climate change 
653 |a drought 
653 |a water deficit index 
653 |a infrared observations 
653 |a satellite 
653 |a surface temperature 
653 |a air temperature 
653 |a humidity 
653 |a dew point temperature 
653 |a land subsidence 
653 |a DInSAR 
653 |a differential interferograms stacking 
653 |a floods 
653 |a coastal plain of Tabasco 
653 |a crop residue 
653 |a fusion 
653 |a machine learning algorithm 
653 |a reflective and radar bands 
653 |a land-cover change 
653 |a REDD+ 
653 |a Google Earth Engine 
653 |a random forest 
653 |a landsat 
653 |a Togo 
653 |a emissivity 
653 |a evapotranspiration 
653 |a heterogeneity 
653 |a Rao's Q index 
653 |a spectral variation hypothesis 
653 |a thermal infrared 
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856 4 0 |a www.oapen.org  |u https://directory.doabooks.org/handle/20.500.12854/95777  |7 0  |z DOAB: description of the publication