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Cosmic Ray Neutron Sensing: Estimation of Agricultural Crop Biomass Water Equivalent

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ISBN: 9783319695389 9783319695396 Year: Pages: 33 DOI: https://doi.org/10.1007/978-3-319-69539-6 Language: English
Publisher: Springer Nature Grant: International Atomic Energy Agency (IAEA)
Subject: Agriculture (General)
Added to DOAB on : 2018-06-22 16:37:01
License: CC BY IGO 3.0

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This open access book provides methods for the estimation of Biomass Water Equivalent (BEW), an essential step for improving the accuracy of area-wide soil moisture by cosmic-ray neutron sensors (CRNS). Three techniques are explained in detail: (i) traditional in-situ destructive sampling, (ii) satellite based remote sensing of plant surfaces, and (iii) biomass estimation via the use of the CRNS itself. The advantages and disadvantages of each method are discussed along with step by step instructions on proper procedures and implementation.

Applications of Photogrammetry for Environmental Research

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ISBN: 9783039281800 9783039281817 Year: Pages: 154 DOI: 10.3390/books978-3-03928-181-7 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Science (General)
Added to DOAB on : 2020-01-30 16:39:46
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The book presents a collection of papers focused on recent progress in key areas of photogrammetry for environmental research. Applications oriented to the understanding of natural phenomena and quantitative processes using dataset from photogrammetry (from satellite to unmanned aerial vehicle images) and terrestrial laser scanning, also by a diachronic approach, are reported. The book covers topics of interest of many disciplines from geography, geomorphology, engineering geology, geotechnology, including landscape description and coastal studies. Mains issues faced by the book are related to applications on coastal monitoring, using multitemporal aerial images, and investigations on geomorphological hazard by the joint use of proximal photogrammetry, terrestrial and aerial laser scanning aimed to the reconstruction of detailed surface topography and successive 2D/3D numerical simulations for rock slope stability analyses. Results reported in the book bring into evidence the fundamental role of multitemporal surveys and reliable reconstruction of morphologies from photogrammetry and laser scanning as support to environmental researches.

Earth Observation, Remote Sensing and Geoscientific Ground Investigations for Archaeological and Heritage Research

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ISBN: 9783039211937 9783039211944 Year: Pages: 304 DOI: 10.3390/books978-3-03921-194-4 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Science (General)
Added to DOAB on : 2019-08-28 11:21:27
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This book collects 15 papers written by renowned scholars from across the globe that showcase the forefront research in Earth observation (EO), remote sensing (RS), and geoscientific ground investigations to study archaeological records and cultural heritage.Archaeologists, anthropologists, geographers, remote sensing, and archaeometry experts share their methodologies relying on a wealth of techniques and data including, but not limited to: very high resolution satellite images from optical and radar space-borne sensors, air-borne surveys, geographic information systems (GIS), archaeological fieldwork, and historical maps.A couple of the contributions highlight the value of noninvasive and nondestructive laboratory analyses (e.g., neutron diffraction) to reconstruct ancient manufacturing technologies, and of geological ground investigations to corroborate hypotheses of historical events that shaped cultural landscapes.Case studies encompass famous UNESCO World Heritage Sites (e.g., the Nasca Lines in Peru), remote and yet-to-discover archaeological areas in tropical forests in central America, European countries, south Asian changing landscapes, and environments which are arid nowadays but were probably full of woody vegetation in the past.Finally, the reader can learn about the state-of-the-art of education initiatives to train site managers in the use of space technologies in support of their activities, and can understand the legal aspects involved in the application of EO and RS to address current challenges of African heritage preservation.

Keywords

analytic hierarchy process (AHP) --- archaeology --- predictive model --- tumuli --- remote sensing --- multi-criteria --- Saharan Morocco --- airborne laser scanning --- orthophotographs --- archaeological survey --- field reconnaissance --- Arran --- national archaeological mapping programme --- synthetic aperture radar --- subsurface imaging --- microwave penetration --- archaeology --- arid environments --- remote sensing --- Oman --- e-learning --- Earth observation --- education --- capacity development --- cultural and natural heritage --- UNESCO --- photogrammetry --- RPAS --- UAV --- Peru --- geoglyph Pista --- mapping --- drones --- remote sensing --- free satellite imagery --- GoogleEarth --- Bing Maps --- archaeological fieldwork --- arid environments --- basalt desert --- landscape accessibility --- Harra --- Jordan --- archaeological landscapes --- settlements --- historical maps --- Survey of India --- Archaeological Survey of India --- heritage --- colonial studies --- remote sensing --- historical landscapes --- landscape archaeology --- settlements --- colonial studies --- river morphology --- Indus --- floods --- remote sensing --- satellite --- Sentinel-2 --- surface survey --- Roman archaeology --- Sumerian pottery --- neutron techniques --- neutron diffraction --- chemometric analysis --- Mega El Niño --- pampa of Nazca --- Cuenca Pisco --- Rio Grande de Nazca --- grain-size --- volcaniclastic layer --- stratigraphy --- petrography --- Lidar --- GIS --- Mesoamerica --- Archaeology --- Caves --- Landscape --- Ritual --- Visualization --- Maya --- Belize --- Sacred --- automated detection --- OBIA --- LiDAR --- Difference Map --- field monument --- Burial Mound --- Motte-and-Bailey castle --- Ridge and Furrow --- space law --- disaster and conservation management --- Geographic Information System (GIS) --- international boundaries --- Africa --- Cameroon-Nigeria Mixed Commission --- satellite imagery --- Boundary Demarcation --- international law --- relict boundaries --- Earth Observation --- remote sensing --- optical --- SAR --- drone --- airborne LiDAR --- GIS --- OBIA --- neutron diffraction --- archaeological prospection --- pattern recognition --- archaeometry --- geological mapping

Earth Observation Data Cubes

Authors: --- --- ---
ISBN: 9783039280926 9783039280933 Year: Pages: 302 DOI: 10.3390/books978-3-03928-093-3 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Science (General) --- Geography
Added to DOAB on : 2020-04-07 23:07:09
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Satellite Earth observation (EO) data have already exceeded the petabyte scale and are increasingly freely and openly available from different data providers. This poses a number of issues in terms of volume (e.g., data volumes have increased 10

Keywords

topology based map algebra --- data cubes --- big data --- map algebra --- earth oberservation --- GRASS GIS --- earth observations --- satellite imagery --- R --- data cubes --- Sentinel-2 --- Sentinel-1 --- SAR --- analysis ready data --- ARD --- interoperability --- data cube --- Earth observation --- pyroSAR --- data cube --- image cube --- image data cube --- imagery --- Landsat --- Sentinel --- earth observation --- GIS --- web services --- web application --- analysis --- GIS --- Open Data Cube --- Earth Observations --- interoperability --- visualization --- Sentinel --- Analysis Ready Data --- Sentinel-1 --- Synthetic Aperture Radar --- Data Cube --- dual-polarimetric decomposition --- interferometric coherence --- Digital Earth Australia --- remote sensing --- big Earth data --- big EO data --- information extraction --- semantic enrichment --- time-series --- Open Data Cube --- remote sensing --- geospatial standards --- landsat --- sentinel --- analysis ready data --- dynamic data citation --- subset --- data curation --- persistent identifier --- data provenance --- metadata --- versioning --- query store --- data sharing --- FAIR principles --- big earth data --- sustainable development goals --- swiss DC --- Armenian DC --- Landsat --- sentinel --- analysis ready data --- data discovery --- metadata --- knowledge base --- graph data --- intelligent semantic agents --- data cube --- optical remote sensing --- snow cover --- Gran Paradiso National Park --- climate change --- land cover classification --- change --- Digital Earth Australia --- open data cube --- Landsat --- Australia --- Open Data Cube --- UN 2030 Agenda for Sustainable Development --- UN System of Environmental Economic Accounting --- Earth observation data --- open science --- reproducibility --- earth observations --- data cube --- analysis ready data --- remote sensing --- satellite imagery

Remote Sensing Technology Applications in Forestry and REDD+

Authors: --- --- ---
ISBN: 9783039284702 9783039284719 Year: Pages: 244 DOI: 10.3390/books978-3-03928-471-9 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- Environmental Technology
Added to DOAB on : 2020-04-07 23:07:09
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Advances in close-range and remote sensing technologies are driving innovations in forest resource assessments and monitoring on varying scales. Data acquired with airborne and spaceborne platforms provide high(er) spatial resolution, more frequent coverage, and more spectral information. Recent developments in ground-based sensors have advanced 3D measurements, low-cost permanent systems, and community-based monitoring of forests. The UNFCCC REDD+ mechanism has advanced the remote sensing community and the development of forest geospatial products that can be used by countries for the international reporting and national forest monitoring. However, an urgent need remains to better understand the options and limitations of remote and close-range sensing techniques in the field of forest degradation and forest change. Therefore, we invite scientists working on remote sensing technologies, close-range sensing, and field data to contribute to this Special Issue. Topics of interest include: (1) novel remote sensing applications that can meet the needs of forest resource information and REDD+ MRV, (2) case studies of applying remote sensing data for REDD+ MRV, (3) timeseries algorithms and methodologies for forest resource assessment on different spatial scales varying from the tree to the national level, and (4) novel close-range sensing applications that can support sustainable forestry and REDD+ MRV. We particularly welcome submissions on data fusion.

Keywords

sentinel imagery --- above-ground biomass --- predictive mapping --- machine learning --- geographically weighted regression --- canopy cover (CC) --- spectral --- texture --- digital hemispherical photograph (DHP) --- random forest (RF) --- gray level co-occurrence matrix (GLCM) --- forest inventory --- LiDAR --- tall trees --- overstory trees --- tree mapping --- crown delineation --- aboveground biomass --- Landsat --- random forest --- topography --- human activity --- aboveground biomass estimation --- remote sensing --- crown density --- low-accuracy estimation --- model comparison --- old-growth forest --- multispectral satellite imagery --- random forest --- forest classification --- remote sensing --- forestry --- phenology --- silviculture --- forest growing stock volume (GSV) --- full polarimetric SAR --- subtropical forest --- topographic effects --- environment effects --- geographic information system --- support vector machine --- random forest --- ensemble model --- hazard mapping --- 3D tree modelling --- aboveground biomass estimation --- destructive sampling --- Guyana --- LiDAR --- local tree allometry --- model evaluation --- quantitative structural model --- Pinus massoniana --- specific leaf area --- leaf area --- terrestrial laser scanning --- voxelization --- forest canopy --- REDD+ --- Cameroon --- reference level --- deforestation --- agriculture --- forest baseline --- airborne laser scanning --- terrestrial laser scanning --- remote sensing --- REDD+ --- forestry

Marine Geomorphometry

Authors: --- ---
ISBN: 9783038979548 9783038979555 Year: Pages: 400 DOI: 10.3390/books978-3-03897-955-5 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
Added to DOAB on : 2019-06-26 08:44:07
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Geomorphometry is the science of quantitative terrain characterization and analysis, and has traditionally focused on the investigation of terrestrial and planetary landscapes. However, applications of marine geomorphometry have now moved beyond the simple adoption of techniques developed for terrestrial studies, driven by the rise in the acquisition of high-resolution seafloor data and by the availability of user-friendly spatial analytical tools. Considering that the seafloor represents 71% of the surface of our planet, this is an important step towards understanding the Earth in its entirety.This volume is the first one dedicated to marine applications of geomorphometry. It showcases studies addressing the five steps of geomorphometry: sampling a surface (e.g., the seafloor), generating a Digital Terrain Model (DTM) from samples, preprocessing the DTM for subsequent analyses (e.g., correcting for errors and artifacts), deriving terrain attributes and/or extracting terrain features from the DTM, and using and explaining those terrain attributes and features in a given context. Throughout these studies, authors address a range of challenges and issues associated with applying geomorphometric techniques to the complex marine environment, including issues related to spatial scale, data quality, and linking seafloor topography with physical, geological, biological, and ecological processes. As marine geomorphometry becomes increasingly recognized as a sub-discipline of geomorphometry, this volume brings together a collection of research articles that reflect the types of studies that are helping to chart the course for the future of marine geomorphometry.

Keywords

bedforms --- forage fish --- Pacific sand lance --- sediment habitats --- bathymetry --- currents --- seabed mapping --- marine geology --- submarine topography --- marine geomorphology --- terrain analysis --- multibeam echosounder --- bathymetry --- DEM --- satellite imagery --- multi beam echosounder --- filter --- geomorphology --- coral reefs --- Acoustic applications --- object segmentation --- seafloor --- underwater acoustics --- Cretaceous --- Cenomanian–Turonian --- paleobathymetry --- paleoclimate --- paleoceanography --- reconstruction --- simulation --- shelf-slope-rise --- geomorphometry --- GIS --- spatial scale --- spatial analysis --- terrain analysis --- seafloor geomorphometry --- domes --- volcanoes --- digital elevation models (DEMs) --- Canary Basin --- Atlantic Ocean --- cold-water coral --- carbonate mound --- habitat mapping --- spatial prediction --- image segmentation --- geographic object-based image analysis --- random forest --- accuracy --- confidence --- global bathymetry --- Seabed 2030 --- Nippon Foundation/GEBCO --- seafloor mapping technologies --- seafloor mapping standards and protocols --- benthic habitats --- shelf morphology --- eastern Brazilian shelf --- geomorphometry --- terrain analysis --- bathymetry --- surface roughness --- benthic habitat mapping --- python --- geomorphology --- submerged glacial bedforms --- deglaciation --- sedimentation --- multibeam --- acoustic-seismic profiling --- swath geometry --- multibeam spatial resolution --- integration artefacts --- Multibeam bathymetry --- benthic habitat mapping --- multiscale --- Random Forests --- pockmarks --- automated-mapping --- ArcGIS --- Glaciated Margin --- North Sea --- Malin Basin --- Barents Sea --- bathymetry --- thalwegs --- canyons --- Alaska --- Bering Sea --- multibeam sonar --- carbonate banks --- semi-automated mapping --- polychaete --- Northwestern Australia --- Oceanic Shoals Australian Marine Park --- Bonaparte Basin --- Timor Sea --- bathymetry --- digital terrain analysis --- geomorphometry --- geomorphology --- habitat mapping --- marine remote sensing

Very High Resolution (VHR) Satellite Imagery: Processing and Applications

Authors: ---
ISBN: 9783039217564 9783039217571 Year: Pages: 262 DOI: 10.3390/books978-3-03921-757-1 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering --- Environmental Engineering
Added to DOAB on : 2019-12-09 11:49:16
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Recently, growing interest in the use of remote sensing imagery has appeared to provide synoptic maps of water quality parameters in coastal and inner water ecosystems;, monitoring of complex land ecosystems for biodiversity conservation; precision agriculture for the management of soils, crops, and pests; urban planning; disaster monitoring, etc. However, for these maps to achieve their full potential, it is important to engage in periodic monitoring and analysis of multi-temporal changes. In this context, very high resolution (VHR) satellite-based optical, infrared, and radar imaging instruments provide reliable information to implement spatially-based conservation actions. Moreover, they enable observations of parameters of our environment at greater broader spatial and finer temporal scales than those allowed through field observation alone. In this sense, recent very high resolution satellite technologies and image processing algorithms present the opportunity to develop quantitative techniques that have the potential to improve upon traditional techniques in terms of cost, mapping fidelity, and objectivity. Typical applications include multi-temporal classification, recognition and tracking of specific patterns, multisensor data fusion, analysis of land/marine ecosystem processes and environment monitoring, etc. This book aims to collect new developments, methodologies, and applications of very high resolution satellite data for remote sensing. The works selected provide to the research community the most recent advances on all aspects of VHR satellite remote sensing.

Keywords

road extraction --- very high-resolution image --- fast marching method --- semiautomatic --- edge constraint --- beaver mimicry --- beaver dam analogue --- QuickBird --- riparian --- stream restoration --- Worldview --- benthic mapping --- seagrass --- airborne hypespectral imagery --- Worldview-2 --- atmospheric correction --- sunglint correction --- water column correction --- dimensionality reduction techniques --- SVM classification --- linear unmixing --- building detection --- built-up areas extraction --- local feature points --- saliency index --- morphological building index --- Deformable CNN --- Faster R-CNN --- data augmentation --- occluded object detection --- very high-resolution Pléiades imagery --- canopy height model --- acquisition geometry --- forested mountain --- accuracy assessment --- remote sensing imagery --- super-resolution --- ultra-dense connection --- feature distillation --- video satellite --- compensation unit --- urban water mapping --- water index --- shadow detection --- threshold stability --- agriculture parcel segmentation --- superpixels --- consensus --- texture analysis --- multi-resolution segmentation (MRS) --- greenhouse extraction --- over-segmentation index (OSI) --- under-segmentation index (USI) --- error index of total area (ETA) --- composite error index (CEI) --- GaoFen-2 (GF-2) --- synthetic aperture radar --- landslide monitoring --- sub-pixel offset tracking --- Slumgullion landslide --- natural hazards --- large displacements --- remote sensing --- scene classification --- CNN --- capsule --- PrimaryCaps --- CapsNet --- High-resolution satellite imagery --- submesoscale --- spiral eddy --- cyanobacteria --- surface convergence --- western Baltic Sea

Remote Sensing Applications for Agriculture and Crop Modelling

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ISBN: 9783039282265 9783039282272 Year: Pages: 308 DOI: 10.3390/books978-3-03928-227-2 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Science (General) --- Geography
Added to DOAB on : 2020-04-07 23:07:08
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Crop models and remote sensing techniques have been combined and applied in agriculture and crop estimation on local and regional scales, or worldwide, based on the simultaneous development of crop models and remote sensing. The literature shows that many new remote sensing sensors and valuable methods have been developed for the retrieval of canopy state variables and soil properties from remote sensing data for assimilating the retrieved variables into crop models. At the same time, remote sensing has been used in a staggering number of applications for agriculture. This book sets the context for remote sensing and modelling for agricultural systems as a mean to minimize the environmental impact, while increasing production and productivity. The eighteen papers published in this Special Issue, although not representative of all the work carried out in the field of Remote Sensing for agriculture and crop modeling,

Keywords

crop residue management --- remote sensing --- satellite images --- hyperspectral sensor --- vegetation index --- yield monitoring --- remote sensing --- proximal sensing --- crop modeling --- soil --- plant --- management zone --- spatial variability --- temporal variability --- precision agriculture --- Á Trous algorithm --- conservation agriculture --- crop inventory --- remote sensing --- spectral-weight variations in fused images --- soil stoichiometry --- land use change --- soil organic carbon --- nitrogen --- Tarim Basin --- SPAD --- leaf nitrogen concentration --- nitrogen nutrition index --- grain yield --- dynamic model --- wheat --- disease --- yield --- septoria tritici blotch --- leaf area index --- crop modelling --- decision support system for agrotechnology transfer (DSSAT) --- Cropsim-CERES Wheat --- sorghum biomass --- prediction modeling --- machine learning --- fAPAR --- Sentinel-2 satellite imagery --- big data technology --- remote sensing --- UAV --- vegetation indices --- relative frequencies --- yield --- precision agriculture --- cultivars --- crop growth model --- data assimilation --- Leaf Area Index --- Sentinel-2 --- EPIC model --- yield estimation --- NDVI --- remote sensing --- GIS --- precision farming --- variable rate technology --- yield mapping --- protein content --- wheat --- canopy temperature depression --- NDVI --- RGB images --- grain yield --- ?13C --- UAV chemical application --- droplet drift --- flat-fan atomizer --- simulation analysis --- control variables --- agricultural land-cover --- multi-spectral --- generalized model --- machine learning --- crop type mapping --- Integrated Administration and Control System --- remote sensing --- hydroponic --- vegetable monitoring --- crop production --- spectral simulation --- hyperspectral data --- n/a --- fractional cover --- irrigation --- satellite --- crop simulation model --- AquaCrop --- yield mapping --- remote sensing --- durum wheat --- precision agriculture --- large cardamom --- remote sensing --- species modelling --- habitat assessment --- climate change

Google Earth Engine Applications

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ISBN: 9783038978848 9783038978855 Year: Pages: 420 DOI: 10.3390/books978-3-03897-885-5 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- Environmental Technology
Added to DOAB on : 2019-04-25 16:37:17
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In a rapidly changing world, there is an ever-increasing need to monitor the Earth’s resources and manage it sustainably for future generations. Earth observation from satellites is critical to provide information required for informed and timely decision making in this regard. Satellite-based earth observation has advanced rapidly over the last 50 years, and there is a plethora of satellite sensors imaging the Earth at finer spatial and spectral resolutions as well as high temporal resolutions. The amount of data available for any single location on the Earth is now at the petabyte-scale. An ever-increasing capacity and computing power is needed to handle such large datasets. The Google Earth Engine (GEE) is a cloud-based computing platform that was established by Google to support such data processing. This facility allows for the storage, processing and analysis of spatial data using centralized high-power computing resources, allowing scientists, researchers, hobbyists and anyone else interested in such fields to mine this data and understand the changes occurring on the Earth’s surface. This book presents research that applies the Google Earth Engine in mining, storing, retrieving and processing spatial data for a variety of applications that include vegetation monitoring, cropland mapping, ecosystem assessment, and gross primary productivity, among others. Datasets used range from coarse spatial resolution data, such as MODIS, to medium resolution datasets (Worldview -2), and the studies cover the entire globe at varying spatial and temporal scales.

Keywords

Google Earth Engine --- NDVI --- vegetation index --- Landsat --- remote sensing --- phenology --- surface reflectance --- cropland mapping --- cropland areas --- 30-m --- Landsat-8 --- Sentinel-2 --- Random Forest --- Support Vector Machines --- segmentation --- RHSeg --- Google Earth Engine --- Africa --- remote sensing --- semi-arid --- ecosystem assessment --- land use change --- image classification --- seasonal vegetation --- carbon cycle --- Google Earth Engine --- crop yield --- gross primary productivity (GPP) --- data fusion --- Landsat --- MODIS --- MODIS --- Random Forest --- pasture mapping --- Brazilian pasturelands dynamics --- Google Earth Engine --- crop classification --- multi-classifier --- cloud computing --- time series --- high spatial resolution --- BACI --- Enhanced Vegetation Index --- Google Earth Engine --- cloud-based geo-processing --- satellite-derived bathymetry --- image composition --- pseudo-invariant features --- sun glint correction --- empirical --- spatial error --- Google Earth Engine --- low cost in situ --- Sentinel-2 --- Mediterranean --- burn severity --- change detection --- Landsat --- dNBR --- RdNBR --- RBR --- composite burn index (CBI) --- MTBS --- lower mekong basin --- landsat collection --- suspended sediment concentration --- online application --- google earth engine --- Landsat --- Google Earth Engine --- protected area --- forest and land use mapping --- machine learning classification --- China --- temporal compositing --- image time series --- multitemporal analysis --- change detection --- cloud masking --- Landsat-8 --- Google Earth Engine (GEE) --- Google Earth Engine --- LAI --- FVC --- FAPAR --- CWC --- plant traits --- random forests --- PROSAIL --- small-scale mining --- industrial mining --- google engine --- image classification --- land-use cover change --- seagrass --- habitat mapping --- image composition --- machine learning --- support vector machines --- Google Earth Engine --- Sentinel-2 --- Aegean --- Ionian --- global scale --- soil moisture --- Soil Moisture Ocean Salinity --- Soil Moisture Active Passive --- Google Earth Engine --- drought --- cloud computing --- remote sensing --- snow hydrology --- water resources --- Google Earth Engine --- user assessment --- MODIS --- snow cover --- flood --- disaster prevention --- emergency response --- decision making --- Google Earth Engine --- land cover --- deforestation --- Brazilian Amazon --- Bayesian statistics --- BULC-U --- Mato Grosso --- spatial resolution --- Landsat --- GlobCover --- SDG --- surface urban heat island --- Geo Big Data --- Google Earth Engine --- global monitoring service --- Google Earth Engine --- web portal --- satellite imagery --- trends --- earth observation --- wetland --- Google Earth Engine --- Sentinel-1 --- Sentinel-2 --- random forest --- cloud computing --- geo-big data --- cloud computing --- big data analytics --- long term monitoring --- data archival --- early warning systems

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