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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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"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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This book focuses on the characterization of the physical properties of the Earth’s ionosphere, contributing to unveiling the nature of several processes responsible for a plethora of space weather-related phenomena taking place in a wide range of spatial and temporal scales. This is made possible by the exploitation of a huge amount of high-quality data derived from both remote sensing and in situ facilities such as ionosondes, radars, satellites and Global Navigation Satellite Systems receivers.

Research & information: general --- Geography --- electron temperature --- topside ionosphere --- ESA Swarm satellites --- International Reference Ionosphere model --- Langmuir Probes in-situ data --- Incoherent Scatter Radar data --- GNSS --- GBAS --- ionospheric gradient anomaly --- one class support vector machine --- earthquake --- pre-earthquake anomalies --- swarm satellites --- ionospheric plasma --- deep learning --- physical mechanisms --- τ --- geomagnetic equator --- magnetic storm --- ionosphere --- vertical pulse sounding --- ionosonde --- ionogram --- software-defined radio --- radar imaging --- aspect angle --- field-aligned plasma irregularities --- mid-latitude E region --- norm-constrained Capon --- VHF radar --- plasma turbulence --- ionospheric irregularities --- ionosphere F region --- high latitude --- pressure-gradient current --- diamagnetic current --- swarm measurements --- oblique ionogram --- automatic inversion --- electron density profile --- quasi-parabolic segments --- the sporadic E layer --- internal fine structure --- high-resolution ionosphere imaging --- frequency domain interferometry technique --- auroral ionosphere --- E × B plasma motion --- ionospheric scintillation --- GNSS-R --- CYGNSS --- earthquakes --- polar ionosphere --- VIPIR --- Dynasonde --- Jang Bogo Station (JBS) --- Antarctica --- solar eclipse --- precise point positioning --- total electron content --- rate of total electron content index --- Swarm satellite measurements --- electron density --- main ionospheric trough --- high latitude trough --- ring ionospheric trough --- low latitude trough --- auroral diffuse precipitation --- n/a