Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

heavily Environmental mathematical models represent one of the key aids for scientists to forecast, create, and evaluate complex scenarios. These models rely on the data collected by direct field observations. However, assembly of a functional and comprehensive dataset for any environmental variable is difficult, mainly because of i) the high cost of the monitoring campaigns and ii) the low reliability of measurements (e.g., due to occurrences of equipment malfunctions and/or issues related to equipment location). The lack of a sufficient amount of Earth science data may induce an inadequate representation of the response’s complexity in any environmental system to any type of input/change, both natural and human-induced. In such a case, before undertaking expensive studies to gather and analyze additional data, it is reasonable to first understand what enhancement in estimates of system performance would result if all the available data could be well exploited. Missing data imputation is an important task in cases where it is crucial to use all available data and not discard records with missing values. Different approaches are available to deal with missing data. Traditional statistical data completion methods are used in different domains to deal with single and multiple imputation problems. More recently, machine learning techniques, such as clustering and classification, have been proposed to complete missing data. This book showcases the body of knowledge that is aimed at improving the capacity to exploit the available data to better represent, understand, predict, and manage the behavior of environmental systems at all practical scales.

geophysical monitoring --- data scarcity --- missing data --- climate extreme indices (CEIs) --- rule extraction --- Dataset Licensedatabase --- data assimilation --- data imputation --- support vector machines --- environmental observations --- multi-class classification --- earth-science data --- remote sensing --- magnetotelluric monitoring --- soil texture calculator --- machine learning --- ClimPACT --- invasive species --- species distribution modeling --- 3D-Var --- ensemble learning --- data quality --- water quality --- microhabitat --- k-Nearest Neighbors --- Expert Team on Climate Change Detection and Indices (ETCCDI) --- decision trees --- processing --- attribute reduction --- Expert Team on Sector-specific Climate Indices (ET-SCI) --- core attribute --- rough set theory --- GLDAS --- arthropod vector --- environmental modeling --- statistical methods

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

This book provides a practical introduction to remote sensing applications for detecting changes in the terrestrial water cycle and understanding the causes and consequences of these changes. Covering a wide range of innovative remote sensing approaches for hydrological study, this book contributes significantly to the knowledge base of hydrology in the Anthropocene, i.e., global change hydrology. It is an excellent reference for students and professionals in the fields of hydrology, climate change, and geography.

Research & information: general --- Geography --- hydrological cycle --- Three-North region --- climate change --- land cover change --- Variable Infiltration Capacity (VIC) model --- evapotranspiration --- runoff --- soil moisture --- three-temperature model --- infrared remote sensing --- urban hedges --- cooling effects --- irrigation mapping --- remote sensing --- random forest --- subhumid region --- dry-wet regime --- vegetation dynamics --- GLDAS --- GIMMS --- Yarlung Zangbo River --- Microwave emissivity difference vegetation index (EDVI) --- evapotranspiration (ET) --- satellite remote sensing --- cloudy sky --- clouds and earth’s radiation energy system (CERES) --- ChinaFLUX --- precipitation classification --- K-nearest neighbor --- Doppler radar --- Tropical Precipitation Measurement Mission (TRMM) --- irrigation signal --- SMAP --- irrigation intensity --- winter wheat --- precipitation --- evaluation --- error analysis --- Fengyun --- quantitative precipitation estimates --- GPM --- IMERG --- deep learning --- Daihai Lake --- Huangqihai Lake --- lake degradation --- weather radar quantitative precipitation estimation --- rain gauge --- radar-rain gauge merging --- leave-one-out cross validation --- verification --- China --- exorheic catchments --- water balance --- GRACE --- terrestrial water storage changes --- reservoir storage --- MODIS --- SRTM --- n/a --- clouds and earth's radiation energy system (CERES)

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Over the last two decades, satellite gravimetry has become a new remote sensing technique that provides a detailed global picture of the physical structure of the Earth. With the CHAMP, GRACE, GOCE and GRACE Follow-On missions, mass distribution and mass transport in the Earth system can be systematically observed and monitored from space. A wide range of Earth science disciplines benefit from these data, enabling improvements in applied models, providing new insights into Earth system processes (e.g., monitoring the global water cycle, ice sheet and glacier melting or sea-level rise) or establishing new operational services. Long time series of mass transport data are needed to disentangle anthropogenic and natural sources of climate change impacts on the Earth system. In order to secure sustained observations on a long-term basis, space agencies and the Earth science community are currently planning future satellite gravimetry mission concepts to enable higher accuracy and better spatial and temporal resolution. This Special Issue provides examples of recent improvements in gravity observation techniques and data processing and analysis, applications in the fields of hydrology, glaciology and solid Earth based on satellite gravimetry data, as well as concepts of future satellite constellations for monitoring mass transport in the Earth system.

Research & information: general --- terrestrial water storage (TWS) --- GRACE --- GLDAS --- TRMM --- drought --- ENSO --- NAO --- Turkey --- Mass balance --- Ice Sheets --- Sea-level Rise --- Antarctica --- CryoSat-2 --- GRACE-Follow On --- GRACE-FO --- downward continuation --- spectral methods --- gravity field recovery --- GRACE Follow-On --- orbit configuration --- synergistic observation --- mass transport in the Earth system --- GRACE and GRACE follow-on mission --- current and future observation concepts and instruments --- GRACE TWSA --- groundwater level anomaly --- downscaling --- machine learning --- boosted regression trees --- glacial sediment --- ice mass --- satellite gravimetry --- Patagonia --- ice mass change --- SLR --- swarm --- normal equation combination --- coseismic gravity gradient changes --- gravity field model --- GOCE --- Earth’s gravity field --- kinematic orbit --- kinematic baseline --- time-variable gravity --- geocenter --- reference frames --- self-attraction and loading --- Level-2 processing --- time-variable gravity field --- mass change monitoring --- next-generation gravity mission --- temporal gravity field --- numerical closed-loop simulation --- satellite mission constellations --- mass transport --- gravity field satellite missions --- GOCE High-Level Processing Facility (HPF), earth gravity field --- geoid --- spectral enhancement method (SEM), GPS/leveling

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

This book provides a practical introduction to remote sensing applications for detecting changes in the terrestrial water cycle and understanding the causes and consequences of these changes. Covering a wide range of innovative remote sensing approaches for hydrological study, this book contributes significantly to the knowledge base of hydrology in the Anthropocene, i.e., global change hydrology. It is an excellent reference for students and professionals in the fields of hydrology, climate change, and geography.

hydrological cycle --- Three-North region --- climate change --- land cover change --- Variable Infiltration Capacity (VIC) model --- evapotranspiration --- runoff --- soil moisture --- three-temperature model --- infrared remote sensing --- urban hedges --- cooling effects --- irrigation mapping --- remote sensing --- random forest --- subhumid region --- dry-wet regime --- vegetation dynamics --- GLDAS --- GIMMS --- Yarlung Zangbo River --- Microwave emissivity difference vegetation index (EDVI) --- evapotranspiration (ET) --- satellite remote sensing --- cloudy sky --- clouds and earth’s radiation energy system (CERES) --- ChinaFLUX --- precipitation classification --- K-nearest neighbor --- Doppler radar --- Tropical Precipitation Measurement Mission (TRMM) --- irrigation signal --- SMAP --- irrigation intensity --- winter wheat --- precipitation --- evaluation --- error analysis --- Fengyun --- quantitative precipitation estimates --- GPM --- IMERG --- deep learning --- Daihai Lake --- Huangqihai Lake --- lake degradation --- weather radar quantitative precipitation estimation --- rain gauge --- radar-rain gauge merging --- leave-one-out cross validation --- verification --- China --- exorheic catchments --- water balance --- GRACE --- terrestrial water storage changes --- reservoir storage --- MODIS --- SRTM --- n/a --- clouds and earth's radiation energy system (CERES)