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Livelihood and Landscape Change in Africa: Future Trajectories for Improved Well-Being under a Changing Climate

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ISBN: 9783039214693 9783039214709 Year: Pages: 246 DOI: 10.3390/books978-3-03921-470-9 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Science (General) --- Biology --- Agriculture (General)
Added to DOAB on : 2019-12-09 11:49:15
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This book is based on a Special Issue of the journal LAND that draws together a collection of 11 diverse articles at the nexus of climate change, landscapes, and livelihoods in rural Africa; all explore the links between livelihood and landscape change, including shifts in farming practices and natural resource use and management. The articles, which are all place-based case studies across nine African countries, cover three not necessarily mutually exclusive thematic areas, namely: smallholder farming livelihoods under new climate risk (five articles); long-term dynamics of livelihoods and landscape change and future trajectories (two articles); and natural resource management and governance under a changing climate, spanning forests, woodlands, and rangelands (four articles). The commonalities, key messages, and research gaps across the 11 articles are presented in a synthesis article. All the case studies pointed to the need for an integrated and in-depth understanding of the multiple drivers of landscape and livelihood change and how these interact with local histories, knowledge systems, cultures, complexities, and lived realities. Moreover, where there are interventions (such as new governance systems, REDD+ or climate smart agriculture), it is critical to interrogate what is required to ensure a fair and equitable distribution of emerging benefits.

Statistical Analysis and Stochastic Modelling of Hydrological Extremes

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ISBN: 9783039216642 9783039216659 Year: Pages: 294 DOI: 10.3390/books978-3-03921-665-9 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Science (General) --- Meteorology and Climatology
Added to DOAB on : 2019-12-09 16:10:12
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Hydrological extremes have become a major concern because of their devastating consequences and their increased risk as a result of climate change and the growing concentration of people and infrastructure in high-risk zones. The analysis of hydrological extremes is challenging due to their rarity and small sample size, and the interconnections between different types of extremes and becomes further complicated by the untrustworthy representation of meso-scale processes involved in extreme events by coarse spatial and temporal scale models as well as biased or missing observations due to technical difficulties during extreme conditions. The complexity of analyzing hydrological extremes calls for robust statistical methods for the treatment of such events. This Special Issue is motivated by the need to apply and develop innovative stochastic and statistical approaches to analyze hydrological extremes under current and future climate conditions. The papers of this Special Issue focus on six topics associated with hydrological extremes: Historical changes in hydrological extremes; Projected changes in hydrological extremes; Downscaling of hydrological extremes; Early warning and forecasting systems for drought and flood; Interconnections of hydrological extremes; Applicability of satellite data for hydrological studies.

Keywords

rainfall --- monsoon --- high resolution --- TRMM --- drought prediction --- APCC Multi-Model Ensemble --- seasonal climate forecast --- machine learning --- sparse monitoring network --- Fiji --- drought analysis --- ANN model --- drought indices --- meteorological drought --- SIAP --- SWSI --- hydrological drought --- discrete wavelet --- global warming --- statistical downscaling --- HBV model --- flow regime --- uncertainty --- reservoir inflow forecasting --- artificial neural network --- wavelet artificial neural network --- weighted mean analogue --- variation analogue --- streamflow --- artificial neural network --- simulation --- forecasting --- support vector machine --- evolutionary strategy --- heavy storm --- hyetograph --- temperature --- clausius-clapeyron scaling --- climate change --- the Cauca River --- climate variability --- ENSO --- extreme rainfall --- trends --- statistical downscaling --- random forest --- least square support vector regression --- extreme rainfall --- polynomial normal transform --- multivariate modeling --- sampling errors --- non-normality --- extreme rainfall analysis --- statistical analysis --- hydrological extremes --- stretched Gaussian distribution --- Hurst exponent --- INDC pledge --- precipitation --- extreme events --- extreme precipitation exposure --- non-stationary --- extreme value theory --- uncertainty --- flood regime --- flood management --- Kabul river basin --- Pakistan --- extreme events --- innovative methods --- downscaling --- forecasting --- compound events --- satellite data

Climate Variability and Climate Change Impacts on Land Surface, Hydrological Processes and Water Management

Authors: --- ---
ISBN: 9783039215072 9783039215089 Year: Pages: 460 DOI: 10.3390/books978-3-03921-508-9 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Science (General) --- Environmental Sciences
Added to DOAB on : 2019-12-09 11:49:15
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During the last several decades, Earth´s climate has undergone significant changes due to anthropogenic global warming, and feedbacks to the water cycle. Therefore, persistent efforts are required to improve our understanding of hydrological processes and to engage in efficient water management strategies that explicitly consider changing environmental conditions. The twenty-four contributions in this book have broadly addressed topics across four major research areas: (1) Climate and land-use change impacts on hydrological processes, (2) hydrological trends and causality analysis faced in hydrology, (3) hydrological model simulations and predictions, and (4) reviews on water prices and climate extremes. The broad spectrum of international contributions to the Special Issue indicates that climate change impacts on water resources analysis attracts global attention. We hope that the collection of articles presented here can provide scientists, policymakers and stakeholders alike with insights that support sustainable decision-making in the face of climate change and increasingly scarce environmental resources.

Keywords

hydrological drought --- Three Gorges Dam --- GRACE --- compound extremes --- climate change --- multivariate distribution --- quantile regression --- indicator --- PUB --- rainfall-runoff experiments --- distributed hydrological model --- Hydro-Informatic Modelling System (HIMS) --- freshwater availability --- runoff --- simulated rainfall --- plot scale --- litter layer --- topsoil --- karst --- Yellow River Delta --- estuarine wetlands --- spatiotemporal change analysis --- remote sensing --- intra-annual climate change --- variation in percentage of flood-season precipitation --- natural streamflow variation --- contribution and sensitivity analysis --- Yellow River --- highland agricultural field area --- diffuse pollutant discharge --- multiple regression model --- climate change --- jackknife validation --- water security --- water pricing --- sustainable water management --- trends and patterns --- economics --- precipitation --- air temperature --- river discharge --- Mann-Kendall test --- Selenga river basin --- Lake Baikal basin --- Mongolia --- snowfall to precipitation ratio --- WRF model --- arid region --- Xinjiang --- water resources management --- climate change --- LULCC --- Budyko equation --- streamflow --- drought --- climate variability --- land surface change --- runoff --- Budyko framework --- elasticity coefficient --- Weihe River Basin --- flood --- streamflow --- CMIP5 --- climate change --- HEC-RAS --- trend analysis --- precipitation --- temperature --- eco-region --- Ethiopia --- Three Gorges Project --- dam --- runoff changes --- flood control --- Yangtze River --- benefits --- evapotranspiration --- Pan evaporation --- TFPW-MK --- Haihe River Basin --- hydrological simulation --- quantitative analysis --- SWAT model --- land use/cover change --- climate change --- scenario simulation --- Climate variability --- Large-scale climate indices --- Reservoir inflow forecasting --- Ensemble empirical mode decomposition --- Time series model --- Artificial intelligence model --- grid-based --- HRU-based --- SHM --- SWAT --- large scale basin --- climate change --- human activities --- power operations --- cascade joint operation chart --- inter-basin water transfer project --- climate change --- MATOPIBA agricultural frontier --- water security --- hydroclimatic analysis --- water conflicts --- average annual runoff --- runoff map --- hydrological model --- GIS --- DPR Korea --- streamflow reduction --- climate change --- coal mining --- SWCM --- coal mining concentrated watershed --- the Loess Plateau --- hydrology --- land cover --- land use and climate change --- water resources management --- macro scale modeling --- climate variability --- climate change --- land use change --- hydrological processes --- trends --- water management --- model --- predictions

Solar Radiation, Modelling and Remote Sensing

Authors: ---
ISBN: 9783039210046 9783039210053 Year: Pages: 230 DOI: 10.3390/books978-3-03921-005-3 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Science (General) --- Physics (General)
Added to DOAB on : 2019-06-26 08:44:06
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Accurate solar radiation knowledge and its characterization on the Earth’s surface are of high interest in many aspects of environmental and engineering sciences. Modeling of solar irradiance from satellite imagery has become the most widely used method for retrieving solar irradiance information under total sky conditions, particularly in the solar energy community. Solar radiation modeling, forecasting, and characterization continue to be broad areas of study, research, and development in the scientific community. This Special Issue contains a small sample of the current activities in this field. Both the environmental and climatology community, as the solar energy world, share a great interest in improving modeling tools and capabilities for obtaining more reliable and accurate knowledge of solar irradiance components worldwide. The work presented in this Special Issue also remarks on the significant role that remote sensing technologies play in retrieving and forecasting solar radiation information.

Keywords

Himawari-8/Advanced Meteorological Imager (Himawari-8/AHI) --- Geostationary Korea Multi-Purse Satellite/Advanced Meteorological Imager (GK-2A/AMI) --- broadband albedo at the top of the atmosphere (TOA albedo) --- reflected shortwave radiation at the top of the atmosphere (RSR) --- Clouds and the Earth Radiant Energy System (CERES) --- surface solar radiation --- remote sensing --- validation --- India --- solar radiation trends --- Solis scheme --- clear sky --- radiation model --- radiative transfer --- high turbidity --- water vapor --- solar radiation --- understory light condition --- forest canopy --- subcanopy light regime --- PAR --- shortwave radiation --- light attenuation --- remote sensing --- solar irradiance --- nowcasting --- AMESIS --- MSG --- SEVIRI --- radiance --- brightness temperature --- motion vector field --- photosynthetically active radiation --- global horizontal irradiance --- clustering analysis --- Kato bands --- solar irradiance --- MSG --- SEVIRI --- HRV --- AMESIS --- solar radiation --- global horizontal irradiance --- satellite-derived dataset --- validation --- solar energy --- aerosol impact --- earth observation --- clear sky index --- solar irradiance --- downward shortwave radiation --- global horizontal irradiance --- solar variability --- cloud categories --- GOES satellites --- evapotranspiration --- insolation --- surface energy balance --- data fusion --- water resource management --- California Delta --- solar radiation --- radiative transfer --- solar energy systems --- solar radiation forecasting

Carbon, Nitrogen and Phosphorus Cycling in Forest Soils

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ISBN: 9783038976820 9783038976837 Year: Pages: 238 DOI: 10.3390/books978-3-03897-683-7 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Science (General) --- Biology --- Forestry
Added to DOAB on : 2019-06-26 08:44:06
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The majority of carbon stored in the soils of the world is stored in forests. The refractory nature of some portions of forest soil organic matter also provides the slow, gradual release of organic nitrogen and phosphorus to sustain long term forest productivity. Contemporary and future disturbances, such as climatic warming, deforestation, short rotation sylviculture, the invasion of exotic species, and fire, all place strains on the integrity of this homeostatic system of C, N, and P cycling. On the other hand, the CO2 fertilization effect may partially offset losses of soil organic matter, but many have questioned the ability of N and P stocks to sustain the CO2 fertilization effect.

Keywords

carbon distribution index --- moisture gradient --- soil organic matter fraction --- soil degradation --- soil available nitrogen --- soil available phosphorus --- temperature --- stand density --- charcoal --- forest soil --- carbon mineralization --- microbial activity --- nitrification --- polyphenols --- temperature --- soil microbial communities --- PLFA --- seasons --- nitrogen dynamics --- gross nitrogen transformations --- Daxing’an Mountains --- climatic factors --- soil nutrients --- forest types --- principal component analyses --- soil structure --- soil pH --- Oxisol --- variable-charge soils --- aluminum accumulator --- seasonal trends --- beech forests --- soil enzymes --- organic matter --- multilevel models --- near natural forest management --- Pinus massoniana plantation --- Cunninghamia lanceolata plantation --- soil greenhouse gas flux --- biolability --- tree-DOM --- dissolved organic matter (DOM) --- carbon --- dissolved organic carbon (DOC) --- stemflow --- throughfall --- alpine forest --- ammonia-oxidizing bacteria --- ammonia-oxidizing archaea --- ammonium --- nitrate --- revegetation --- microbial biomass --- chloroform fumigation extraction --- enzyme activities --- stoichiometric homeostasis --- the Three Gorges Reservoir --- Eucalyptus sp. --- wood volume --- second production cycle --- annual increment average --- soil fertility --- nutrient cycling --- Chamaecyparis forest --- humic substances --- 31P nuclear magnetic resonance spectroscopy (31P NMR) --- P species --- topography --- net primary productivity --- climate zone --- climate --- soil N --- litter N --- climate change --- manuring --- manure pelleting --- northern temperate --- pyrolysis --- information review --- leaf N:P ratio --- P resorption efficiency --- soil P fractions --- P stock --- stand age

Efficiency of Bank Filtration and Post-Treatment

Authors: ---
ISBN: 9783039213054 9783039213061 Year: Pages: 352 DOI: 10.3390/books978-3-03921-306-1 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
Added to DOAB on : 2019-12-09 11:49:15
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Riverbank filtration (RBF) schemes for the production of drinking water are increasingly challenged by new constituents of concern, such as organic micropollutants and pathogens in the source water and hydrological flow variations due to weather extremes. RBF and new technology components are integrated and monitoring and operating regimes are adopted to further optimize water treatment in bank filtration schemes for these new requirements. This Special Issue presents results from the EU project AquaNES “Demonstrating synergies in combined natural and engineered processes for water treatment systems” (www.aquanes.eu). Additionally, papers from other research groups cover the efficiency of bank filtration and post-treatment, advantages and limitations of combining natural and engineered processes, parameter-specific assessment of removal rates during bank filtration, and the design and operation of RBF wells. The feasibility, design, and operation of RBF schemes under specific site conditions are highlighted for sites in the US, India, and South Korea

Keywords

riverbank filtration --- removal efficacy --- dissolved organic carbon (DOC) --- pesticides --- pharmaceutical residues --- riverbank filtration --- organic matter degradation --- manganese --- riverbed --- climate change --- floods --- droughts --- column experiments --- PHREEQC --- decentralized capillary nanofiltration --- anoxic --- suboxic --- organic micropollutants --- bank filtrate --- groundwater --- sulphate --- dissolved organic matter --- high temperature --- sub-oxic conditions --- organic matter composition --- PARAFAC-EEM --- LC-OCD --- redox sensitivity --- micropollutants --- oxypurinol --- gabapentin --- river bank filtration --- hydrological trends --- sustainable water production --- well structure remodeling --- point-bar alluvial setting --- riverbank filtration --- site investigation --- hydrochemistry --- subsurface geology --- riverbank filtration --- organic micropollutants --- water quality --- environmental monitoring --- riverbank filtration --- collector wells --- performance --- entrance velocity --- river bank filtration --- attenuation --- organic micropollutants --- pharmaceuticals --- riverbank filtration --- small communities --- disinfection by-products --- trihalomethanes --- riverbank filtration (RBF) --- Krishna River --- southern India --- water treatment --- water quality --- salinity --- river bank filtration --- ultrafiltration --- surface water treatment --- energy efficiency --- out/in membrane comparison --- inline electrolysis --- bank filtration --- biofilm --- clogging --- filter cake --- pathogen barrier --- pressure loss --- slow sand filtration --- electro-chlorination --- smart villages --- disinfection --- river bank filtration --- rural water supply, online monitoring --- dissolved organic matter --- fluorescence excitation-emission matrix --- LC-OCD --- Nakdong River --- riverbank filtration --- bank filtration --- drinking water treatment --- inorganic chemicals --- organic micropollutants --- Ganga --- Yamuna --- Damodar --- riverbank filtration --- water quality --- organic carbon --- nitrate --- heavy metals --- microorganisms --- riverbank filtration --- riverside water source --- analytical method --- mirror-image method --- optimization --- riverbank filtration --- water quality --- bank filtrate portion --- iron --- manganese --- microorganisms --- system costs --- water supply --- storage tank --- drinking water hydropower --- turbine --- energy generation --- renewable energy

Knowledge Manageation and Big Data: Implications for Sustainability, Policy Making and Competitiveness

Authors: ---
ISBN: 9783039280087 9783039280094 Year: Pages: 416 DOI: 10.3390/books978-3-03928-009-4 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Social Sciences --- Education
Added to DOAB on : 2020-01-07 09:21:22
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The evolution of knowledge management theory and the special emphasis on human and social capital sets new challenges for knowledge-driven and technology-enabled innovation. Emerging technologies including big data and analytics have significant implications for sustainability, policy making, and competitiveness. This edited volume promotes scientific research into the potential contributions knowledge management can make to the new era of innovation and social inclusive economic growth. We are grateful to all the contributors of this edition for their intellectual work. The organization of the relevant debate is aligned around three pillars: SECTION A. DATA, KNOWLEDGE, HUMAN AND SOCIAL CAPITAL FOR INNOVATION: We elaborate on the new era of knowledge types and the emerging forms of social capital and their impact on technology-driven innovation. Topics include: Social Networks; Smart Education; Social Capital; Corporate Innovation; Disruptive Innovation; Knowledge integration; Enhanced Decision-Making. SECTION B. KNOWLEDGE MANAGEMENT & BIG DATA ENABLED INNOVATION: In this section, knowledge management and big data applications and systems are presented. Selective topic include: Crowdsourcing Analysis; Natural Language Processing; Data Governance; Knowledge Extraction; Ontology Design Semantic Modeling SECTION C. SUSTAINABLE DEVELOPMENT: In the section, the debate on the impact of knowledge management and big data research to sustainability is promoted with integrative discussion of complementary social and technological factors including: Big Social Networks on Sustainable Economic Development; Business Intelligence

Keywords

innovation capability --- social capital --- knowledge creation --- human capital investment --- training --- education --- communication --- six sigma --- structural equation model --- leadership --- innovation performance --- knowledge sharing --- social capital --- project-based organization --- citizen-scientist --- climate change --- crowdsourcing --- MTurk --- social networks --- Twitter --- social networks --- big data --- big data analysis --- sustainable development --- text mining --- NLP --- technological information --- patent analysis --- text structure --- top management team --- strategic decision-making --- risk perception --- knowledge creation process --- process innovation capability --- product innovation capability --- sustainable competitive advantage --- data governance --- cloud computing --- cloud data governance --- taxonomy --- systematic review --- holistic --- text feature extraction --- patent analysis --- hybrid neural networks --- mechanical patent classification --- international technological collaboration --- IC manufacturing --- patent association analysis --- social network analysis --- collaboration network --- corporate sustainability --- business intelligence --- multi-dimensional data model --- key performance indicators --- knowledge assets --- knowledge embeddedness --- knowledge specificity --- disruptive innovation --- personalized business mode --- technology acceptance model --- user acceptance --- data analysis --- ontology design --- knowledge management --- heterogeneous architectures --- Big Data --- transformational training programs-TTP --- quality orientation of employees-QOE --- employee loyalty-EL --- universities --- Jordan --- administrative file --- administrative procedure --- sustainability --- open data --- linked data --- provenance --- RDF --- PROV-O --- P-PLAN --- big data --- visualizing --- intellectual structure --- big data environment --- co-citation network --- collaboration network --- sustainability --- bibliometric --- knowledge management --- keywords analysis --- intellectual structure --- emerging trends --- knowledge mapping --- new ventures --- internal social networks --- absorptive capacity --- innovation --- big data --- competitive advantage --- disruptive innovation --- human capital --- innovation --- knowledge management --- sustainability --- smart education --- social networks --- social media --- conceptual maturity model --- technology-enhanced learning process

Google Earth Engine Applications

Authors: ---
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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