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This book is a reprint of the Special Issue entitled "Statistical and Machine Learning Models for Remote Sensing Data Mining - Recent Advancements" that was published in Remote Sensing, MDPI. It provides insights into both core technical challenges and some selected critical applications of satellite remote sensing image analytics.

Research & information: general --- Environmental economics --- scene classification --- teacher-student --- noisy labels --- knowledge distillation --- remote sensing images --- LightGBM --- spatiotemporal weight interpolation --- AOD recovery --- East Asia --- polarized SAR --- optical image --- random forest --- conditional random fields --- feature-level fusion --- Dirichlet process --- infinite mixture models --- Gamma distribution --- variational inference --- online setting --- oil spill detection --- synthetic aperture radar images --- GNSS-R --- CYGNSS --- high wind speed inversion --- SVR --- PCA-SVR --- CNN --- scene classification --- teacher-student --- noisy labels --- knowledge distillation --- remote sensing images --- LightGBM --- spatiotemporal weight interpolation --- AOD recovery --- East Asia --- polarized SAR --- optical image --- random forest --- conditional random fields --- feature-level fusion --- Dirichlet process --- infinite mixture models --- Gamma distribution --- variational inference --- online setting --- oil spill detection --- synthetic aperture radar images --- GNSS-R --- CYGNSS --- high wind speed inversion --- SVR --- PCA-SVR --- CNN

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As climate-change- and human-induced floods inflict increasing costs upon the planet, both in terms of lives and environmental damage, flood monitoring tools derived from remote sensing platforms have undergone improvements in their performance and capabilities in terms of spectral, spatial and temporal extents and resolutions. Such improvements raise new challenges connected to data analysis and interpretation, in terms of, e.g., effectively discerning the presence of floodwaters in different land-cover types and environmental conditions or refining the accuracy of detection algorithms. In this sense, high expectations are placed on new methods that integrate information obtained from multiple techniques, platforms, sensors, bands and acquisition times. Moreover, the assessment of such techniques strongly benefits from collaboration with hydrological and/or hydraulic modeling of the evolution of flood events. The aim of this Special Issue is to provide an overview of recent advancements in the state of the art of flood monitoring methods and techniques derived from remotely sensed data.

mobile mapping system --- RRI model --- high-water marks --- inundation --- Northern Kyushu floods --- point clouds --- flood mapping --- temporary flooded vegetation (TFV) --- Sentinel-1 --- time series data --- Synthetic Aperture Radar (SAR) --- sentinel-1 --- SAR --- flood --- image classification --- clustering --- monsoon --- Philippines --- LiDAR --- geometric parameters --- levee stability --- overtopping --- Pearl River Delta --- CYGNSS --- flood detection --- Sistan and Baluchestan --- GNSS-R --- flood monitoring --- ALOS 2 --- multi-sensor integration --- multi-temporal inundation analysis --- Zambesi-Shire river basin --- image processing --- hydrology --- synthetic aperture radar --- n/a

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"Earth Observations for Addressing Global Challenges" presents the results of cutting-edge research related to innovative techniques and approaches based on satellite remote sensing data, the acquisition of earth observations, and their applications in the contemporary practice of sustainable development. Addressing the urgent tasks of adaptation to climate change is one of the biggest global challenges for humanity. As His Excellency António Guterres, Secretary-General of the United Nations, said, "Climate change is the defining issue of our time—and we are at a defining moment. We face a direct existential threat." For many years, scientists from around the world have been conducting research on earth observations collecting vital data about the state of the earth environment. Evidence of the rapidly changing climate is alarming: according to the World Meteorological Organization, the past two decades included 18 of the warmest years since 1850, when records began. Thus, Group on Earth Observations (GEO) has launched initiatives across multiple societal benefit areas (agriculture, biodiversity, climate, disasters, ecosystems, energy, health, water, and weather), such as the Global Forest Observations Initiative, the GEO Carbon and GHG Initiative, the GEO Biodiversity Observation Network, and the GEO Blue Planet, among others. The results of research that addressed strategic priorities of these important initiatives are presented in the monograph.

Research & information: general --- Environmental economics --- snow albedo radiative forcing --- snow albedo feedback --- radiative kernel --- remote sensing --- cloud fraction --- integrated liquid water --- integrated water vapour --- diurnal cycle --- microwave radiometer --- classification --- self-learning --- training data --- crop --- leaf area index --- comparison --- MODIS --- uncertainty --- China --- EVI --- climatic factor --- driving force --- grey relational analysis (GRA) --- Inner Mongolia Autonomous Region (IMAR) --- Earth Observation (EO) --- satellite --- sensors --- platform --- SAR --- GNSS-R --- optical sensors --- polar --- weather --- ice --- marine --- land surface temperature --- urban heat island --- surface urban heat island --- land use --- land management unit --- Earth observation --- radiometer --- VIS/NIR imager --- terrestrial ecosystem --- MODIS GPP product --- calibration --- arid region --- oasis-desert ecosystem --- Land use and land cover (LULC) --- cloud-to-ground (CG) lightning --- particulate matter (PM10) --- sulfur dioxide (SO2) --- El Niño 2015-16 --- trace gases --- Upper Troposphere Lower Stratosphere --- snow albedo radiative forcing --- snow albedo feedback --- radiative kernel --- remote sensing --- cloud fraction --- integrated liquid water --- integrated water vapour --- diurnal cycle --- microwave radiometer --- classification --- self-learning --- training data --- crop --- leaf area index --- comparison --- MODIS --- uncertainty --- China --- EVI --- climatic factor --- driving force --- grey relational analysis (GRA) --- Inner Mongolia Autonomous Region (IMAR) --- Earth Observation (EO) --- satellite --- sensors --- platform --- SAR --- GNSS-R --- optical sensors --- polar --- weather --- ice --- marine --- land surface temperature --- urban heat island --- surface urban heat island --- land use --- land management unit --- Earth observation --- radiometer --- VIS/NIR imager --- terrestrial ecosystem --- MODIS GPP product --- calibration --- arid region --- oasis-desert ecosystem --- Land use and land cover (LULC) --- cloud-to-ground (CG) lightning --- particulate matter (PM10) --- sulfur dioxide (SO2) --- El Niño 2015-16 --- trace gases --- Upper Troposphere Lower Stratosphere

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"Earth Observations for Addressing Global Challenges" presents the results of cutting-edge research related to innovative techniques and approaches based on satellite remote sensing data, the acquisition of earth observations, and their applications in the contemporary practice of sustainable development. Addressing the urgent tasks of adaptation to climate change is one of the biggest global challenges for humanity. As His Excellency António Guterres, Secretary-General of the United Nations, said, "Climate change is the defining issue of our time—and we are at a defining moment. We face a direct existential threat." For many years, scientists from around the world have been conducting research on earth observations collecting vital data about the state of the earth environment. Evidence of the rapidly changing climate is alarming: according to the World Meteorological Organization, the past two decades included 18 of the warmest years since 1850, when records began. Thus, Group on Earth Observations (GEO) has launched initiatives across multiple societal benefit areas (agriculture, biodiversity, climate, disasters, ecosystems, energy, health, water, and weather), such as the Global Forest Observations Initiative, the GEO Carbon and GHG Initiative, the GEO Biodiversity Observation Network, and the GEO Blue Planet, among others. The results of research that addressed strategic priorities of these important initiatives are presented in the monograph.

snow albedo radiative forcing --- snow albedo feedback --- radiative kernel --- remote sensing --- cloud fraction --- integrated liquid water --- integrated water vapour --- diurnal cycle --- microwave radiometer --- classification --- self-learning --- training data --- crop --- leaf area index --- comparison --- MODIS --- uncertainty --- China --- EVI --- climatic factor --- driving force --- grey relational analysis (GRA) --- Inner Mongolia Autonomous Region (IMAR) --- Earth Observation (EO) --- satellite --- sensors --- platform --- SAR --- GNSS-R --- optical sensors --- polar --- weather --- ice --- marine --- land surface temperature --- urban heat island --- surface urban heat island --- land use --- land management unit --- Earth observation --- radiometer --- VIS/NIR imager --- terrestrial ecosystem --- MODIS GPP product --- calibration --- arid region --- oasis-desert ecosystem --- Land use and land cover (LULC) --- cloud-to-ground (CG) lightning --- particulate matter (PM10) --- sulfur dioxide (SO2) --- El Niño 2015–16 --- trace gases --- Upper Troposphere Lower Stratosphere --- n/a --- El Niño 2015-16

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Ocean satellite remote sensing plays important roles in the observations of physical, biological and biogeochemical features in inland, coastal, and global ocean waters, with high temporal and spatial resolution. The satellite-measured ocean products are used for near-real-time ocean monitoring and climate data records to understand short-/long-term variabilities in marine environments and ecosystems as well as for decision making tools to manage social, economic, and environmental benefits. Validation/evaluation including a combination of field measurements and inter-satellite comparison is an essential step in providing more accurate satellite-derived ocean products. In this Special Issue, 14 papers have been published and include research on validation/evaluation, retrieval algorithms of ocean geophysical and biogeochemical parameters, and application of the satellite ocean products in the regional and global ocean. Subjects treated include: Sea Surface Temperature; Sea Ice Surface Temperature from VIIRS thermal infrared sensor; Sea Ice Detection from Spectroradiometer; Sea Surface Winds from HY-2A Scatterometer and GNSS—Reflectometry; Wave Height from Sentinel-3A SAR; Retrievals of Sea Surface Salinity, Chlorophyll-a, Particulate Organic Carbon, Particulate Backscattering, Marine Fishery resource, and Submesoscale Eddies from multiple Ocean Colour sensors.

Research & information: general --- sea ice --- ice surface temperature --- Suomi NPP --- JPSS --- remote sensing --- leads --- MODIS --- ocean color --- algorithm --- chlorophyll --- HPLC --- fluorometry --- particulate organic carbon --- southern ocean --- ocean colour --- satellite-derived chlorophyll-a concentration --- algorithm evaluation --- Northwest Atlantic --- Northeast Pacific --- Japanese common squid --- Todarodes pacificus --- habitat suitability index (HSI) --- the Yellow Sea --- the South Sea of South Korea --- spaceborne GNSS-R --- DDM --- ocean surface wind speed --- GMF --- CYGNSS --- HY-2A --- scatterometer --- sea surface wind field --- evaluation --- satellite altimetry --- significant wave height --- SAR --- wave buoy observations --- validation --- southwest England --- coastal altimetry --- Sentinel-3A --- SRAL --- particulate optical backscattering --- Raman scattering --- QAA algorithm --- ESA OC-CCI --- steric height --- sea level variability --- interferometric altimeter validation --- high-frequency radar --- MODIS ocean color patterns --- submesoscale eddies --- sea surface salinity estimation --- Changjiang diluted water --- neural network --- GOCI application --- sea surface temperature --- global gridded dataset --- Yellow Sea --- bias correction --- chlorophyll-a --- phytoplankton --- East/Japan Sea --- sea ice --- ice surface temperature --- Suomi NPP --- JPSS --- remote sensing --- leads --- MODIS --- ocean color --- algorithm --- chlorophyll --- HPLC --- fluorometry --- particulate organic carbon --- southern ocean --- ocean colour --- satellite-derived chlorophyll-a concentration --- algorithm evaluation --- Northwest Atlantic --- Northeast Pacific --- Japanese common squid --- Todarodes pacificus --- habitat suitability index (HSI) --- the Yellow Sea --- the South Sea of South Korea --- spaceborne GNSS-R --- DDM --- ocean surface wind speed --- GMF --- CYGNSS --- HY-2A --- scatterometer --- sea surface wind field --- evaluation --- satellite altimetry --- significant wave height --- SAR --- wave buoy observations --- validation --- southwest England --- coastal altimetry --- Sentinel-3A --- SRAL --- particulate optical backscattering --- Raman scattering --- QAA algorithm --- ESA OC-CCI --- steric height --- sea level variability --- interferometric altimeter validation --- high-frequency radar --- MODIS ocean color patterns --- submesoscale eddies --- sea surface salinity estimation --- Changjiang diluted water --- neural network --- GOCI application --- sea surface temperature --- global gridded dataset --- Yellow Sea --- bias correction --- chlorophyll-a --- phytoplankton --- East/Japan Sea