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Different types of pressures, such as nutrients, micropollutants, microbes, nanoparticles, microplastics, or antibiotic-resistant genes, endanger the quality of water bodies. Evidence-based pollution control needs to be built on the three basic elements of water governance: Monitoring, modeling, and management. Monitoring sets the empirical basis by providing space- and time-dependent information on substance concentrations and loads, as well as driving boundary conditions for assessing water quality trends, water quality statuses, and providing necessary information for the calibration and validation of models. Modeling needs proper system understanding and helps to derive information for times and locations where no monitoring is done or possible. Possible applications are risk assessments for exceedance of quality standards, assessment of regionalized relevance of sources and pathways of pollution, effectiveness of measures, bundles of measures or policies, and assessment of future developments as scenarios or forecasts. Management relies on this information and translates it in a socioeconomic context into specific plans for implementation. Evaluation of success of management plans again includes well-defined monitoring strategies. This book provides an important overview in this context.

diffuse pollution --- field mapping --- storm drains --- Bayesian statistics --- distributed modelling --- PhosFate --- water quality --- analysis method --- chromaticity measurement --- surface fitting --- concentration of dissolved matter --- Copernicus Programme --- ACOLITE --- flooding --- quasi-real time monitoring --- inundation mapping --- suspended matter --- Spain --- cyanobacteria --- Microcystis aeruginosa --- water --- monitoring --- spectrophotometry --- derivative absorbance --- model evaluation --- nitrogen --- nutrient retention --- phosphorus --- sediment --- constructed wetland --- water resources management --- eutrophication --- unmanned surface vehicle --- water monitoring --- ensemble learning --- dynamic power management --- observational process ontology --- water quality monitoring --- water pollution alert --- semantic discovery --- water quality status --- sources and pathways --- land cover --- digital elevation model --- urban river --- ArcGIS --- modeling --- CSO --- urban drainage --- sewer system --- trace pollutants --- urban runoff --- concentration duration frequency curve --- MONERIS --- diffuse nutrient emission --- empirical modeling --- river basin management plan of Hungary --- effectiveness of measures --- scenarios and forecasts --- socioeconomic context --- sources and pathways of water pollution --- system understanding --- water governance --- water quality statuses and trends --- water pollution control

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Ocean color measured by satellite-mounted optical sensors is an essential climate variable that is routinely used as a central element for assessing the health and productivity of marine ecosystems and the role of oceans in the global carbon cycle. For satellite ocean color to be reliable and used in these and other important environmental applications, the data must be trustworthy and high quality. Pre-flight and on-board calibration of satellite ocean color sensors is conducted; however, once in orbit, the data quality can only be fully assessed via independent calibration and validation activities using surface measurements. These measurements therefore need to be at least as high quality as the satellite data, which necessitates SI traceability and a full uncertainty budget. This is the basis for fiducial reference measurements (FRMs) and the FRM4SOC project, which was an European Space Agency (ESA) initiative to establish and maintain SI-traceable ground-based FRM for satellite ocean color, thus providing a fundamental contribution to the European system for monitoring the Earth (Copernicus). This Special Issue of MDPI Remote Sensing is designed to showcase this essential Earth observation work through the publication of the project’s main achievements and results accompanied by other select relevant articles.

VIIRS --- SNPP --- NOAA-20 --- DINEOF --- ocean color data --- data merging --- gap-filling --- ocean color radiometers --- radiometric calibration --- indoor intercomparison measurement --- agreement between sensors --- measurement uncertainty --- field intercomparison measurement --- Hyperspectral reflectance --- validation --- autonomous measurements --- ground-truth data --- system design --- downwelling irradiance --- satellite validation --- Fiducial Reference Measurements --- water reflectance --- satellite --- calibration --- solar diffusor --- SDSM --- desert trend --- lunar calibration --- RVS --- MODIS --- Aqua --- ocean color --- water-leaving radiance --- atmospheric correction --- Sentinel-3 OLCI --- Copernicus --- ocean colour --- system vicarious calibration --- fiducial reference measurement --- Lampedusa --- MOBY --- MarONet --- radiometry --- research infrastructure --- uncertainty budget --- satellite ocean colour --- fiducial reference measurements (FRM) --- calibration and validation --- SI traceability and uncertainty --- European Space Agency (ESA) --- Committee for Earth Observation Satellites (CEOS) --- fiducial reference measurements --- SI-traceability --- Mediterranean Sea --- BOUSSOLE --- MSEA --- hyper-temporal dataset --- optical radiometry --- coastal environment --- observation geometry --- remote sensing reflectance --- ocean colour radiometers --- TriOS RAMSES --- Seabird HyperSAS --- field intercomparison --- AERONET-OC --- Acqua Alta Oceanographic Tower --- remote sensing --- spectral irradiance comparison --- spectral radiance sources comparison

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This book is a collection of recent developments, methodologies, calibration and validation techniques, and applications of thermal remote sensing data and derived products from UAV-based, aerial, and satellite remote sensing. A set of 15 papers written by a total of 70 authors was selected for this book. The published papers cover a wide range of topics, which can be classified in five groups: algorithms, calibration and validation techniques, improvements in long-term consistency in satellite LST, downscaling of LST, and LST applications and land surface emissivity research.

Land Surface Temperature (LST) --- satellite retrievals of LST --- LST from GOES satellites --- land surface temperature --- drones --- unmanned aerial vehicles --- thermal remote sensing --- MODIS --- Bayesian Maximum Entropy --- interpolation --- Himalaya --- air temperature --- topography --- Landsat --- split window algorithm --- TIRS --- thermal --- Landsat 8 --- stray light correction --- split-window algorithm --- single-channel algorithm --- AMSR2 --- annual cycle parameters --- random forest --- cloudy sky LST --- evapotranspiration --- data fusion --- field-scale --- machine-learning --- physical model --- Sentinel-2 --- Sentinel-3 --- Downscaling --- thermal infrared --- disaggregation --- Copernicus --- hyperspectral thermal infrared --- spectral smoothness --- temperature-emissivity separation --- sensitivity analysis --- noise --- land surface temperature (LST) --- daytime LST --- nighttime LST --- validation --- land surface emissivity (LSE) --- single channel algorithm --- radiative transfer equation --- mono window algorithm --- SURFRAD data --- GK2A --- split-window method --- BSRN --- LST --- downscaling --- LSA-SAF --- Sentinel 2 --- DEM --- spatial averaging biases --- land surface emissivity --- measurement uncertainties --- emissivity box method --- Fourier transform infrared spectrometer --- portable spectrometer --- n/a

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This book focuses on remote sensing for urban deformation monitoring. In particular, it highlights how deformation monitoring in urban areas can be carried out using Persistent Scatterer Interferometry (PSI) and Synthetic Aperture Radar (SAR) Tomography (TomoSAR). Several contributions show the capabilities of Interferometric SAR (InSAR) and PSI techniques for urban deformation monitoring. Some of them show the advantages of TomoSAR in un-mixing multiple scatterers for urban mapping and monitoring. This book is dedicated to the technical and scientific community interested in urban applications. It is useful for choosing the appropriate technique and gaining an assessment of the expected performance. The book will also be useful to researchers, as it provides information on the state-of-the-art and new trends in this field

surface subsidence --- PS --- permanent scatterers --- land subsidence --- PS-InSAR --- thermal dilation --- SBAS-InSAR --- Sepulveda Transit Corridor --- deformation --- differential SAR interferometry --- reclaimed land --- Istanbul --- deformation monitoring --- skyscrapers --- generalized likelihood ratio test --- validation --- uplift --- displacement monitoring --- pursuit monostatic --- radar interferometry --- Sentinel-1A --- urbanization --- synthetic aperture radar --- Turkey --- terraSAR-X --- geological and geomorphological mapping --- London --- differential compaction --- expansive soils --- health monitoring --- Copernicus Sentinel-1 --- displacement mapping --- PALSAR --- land reclamation --- tomography --- Venetian-Friulian Plain --- ALOS PALSAR --- multi-temporal DInSAR --- SAR interferometry --- InSAR --- persistent scatterers --- carbonate karstification --- ENVISAT ASAR --- multiple PS detection --- sparse signals --- urban subsidence --- time series InSAR analysis --- time series analysis --- Persistent Scatterer Interferometry (PSI) --- engineering construction --- Rome --- persistent scatterer interferometry --- subsidence --- persistent scatterer interferometry (PSI) --- SNAP-StaMPS --- Lingang New City --- dewatering --- atmospheric component --- urban deformation monitoring --- Sentinel-1 --- differential interferometry --- Late-Quaternary deposits --- modelling --- Generalized Likelihood Ratio Test --- Persistent Scatterer Interferometry --- synthetic aperture radar (SAR) --- Capon estimation --- differential tomography --- deformation time series --- groundwater level variation --- radar detection --- multi-look SAR tomography --- spaceborne SAR --- SAR --- ERS-1/-2 --- reclamation settlements --- Wuhan --- subsidence monitoring --- water level changes --- polarimetry --- asymmetric subsidence --- urban monitoring --- urban areas --- landslide --- SAR tomography --- Urayasu City --- risk --- Los Angeles --- PALSAR-2

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Agriculture, as the main source of alimentation and the most important economic activity globally, is being affected by the impacts of climate change. To maintain and increase our global food system production, to reduce biodiversity loss and preserve our natural ecosystem, new practices and technologies are required. This book focuses on the latest advances in remote sensing technology and agricultural engineering leading to the sustainable agriculture practices. Earth observation data, in situ and proxy-remote sensing data are the main source of information for monitoring and analyzing agriculture activities. Particular attention is given to earth observation satellites and the Internet of Things for data collection, to multispectral and hyperspectral data analysis using machine learning and deep learning, to WebGIS and the Internet of Things for sharing and publishing the results, among others.

Research & information: general --- Geography --- geographic information system (GIS) --- pocket beaches --- coastal management --- Interreg --- climate change --- remote sensing --- drone --- Sicily --- Malta --- Gozo --- Comino --- systematic literature review --- anomaly intrusion detection --- deep learning --- IoT --- resource constraint --- IDS --- evapotranspiration --- penman-monteith equation --- artificial neural network --- canopy conductance --- Ziz basin --- water quality --- satellite image analysis --- modeling approach --- nitrate --- dissolved oxygen --- chlorophyll a --- time series analysis --- environmental monitoring --- water extraction --- modified normalized difference water index (MNDWI) --- machine learning algorithm --- hyperspectral --- proximal sensing --- panicle initiation --- normalized difference vegetation index (NDVI) --- green ring --- internode-elongation --- Sentinel 1 and 2 --- Copernicus Sentinels --- crop classification --- food security --- agricultural monitoring --- data analysis --- SAR --- random forest --- 3D bale wrapping method --- equal bale dimensions --- mathematical model --- minimal film consumption --- optimal bale dimensions --- round bales --- Sentinel-2 --- SVM --- RF --- Boufakrane River watershed --- irrigation requirements --- water resources --- sustainable land use --- agriculture --- invasive plants --- precision agriculture --- rice farming --- site-specific weed management --- nitrogen prediction --- 1D convolution neural networks --- cucumber --- crop yield improvement --- mango leaf --- CCA --- vein pattern --- leaf disease --- cubic SVM --- chlorophyll-a concentration --- transfer learning --- overfitting --- data augmentation --- guava disease --- plant disease detection --- crops diseases --- entropy --- features fusion --- machine learning --- object-based classification --- density estimation --- histogram --- land use --- crop fields --- soil tillage --- data fusion --- multispectral --- sensor --- probe --- temperature profile --- forest roads --- simulation --- autonomous robots --- smart agriculture --- environmental protection --- photogrammetry --- path planning --- internet of things --- modeling --- convolutional neural networks --- machine vision --- computer vision --- modular robot --- selective spraying --- vision-based crop and weed detection --- Faster R-CNN --- YOLOv5 --- band selection --- CNN --- NDVI --- hyperspectral imaging --- crops --- urban flood --- Sentinel-1a --- Synthetic Aperture Radar (SAR) --- 3D Convolutional Neural Network --- multi-temporal data --- land use classification --- GIS --- Coatzacoalcos --- algorithms --- clustering --- pest control --- site-specific --- virtual pests --- rice plant --- weed --- hyperspectral imagery --- sustainable agriculture --- green technologies --- Internet of Things --- natural resources --- sustainable environment --- IoT ecosystem --- hyperspectral remoting sensing --- crop mapping --- image classification --- deep transfer learning --- hyperparameter optimization --- metaheuristic --- soil attribute --- ordinary Kriging --- rational sampling numbers --- spatial heterogeneity --- sampling --- soil pH --- spatial variation --- ordinary kriging --- Land Use/Land Cover --- LISS-III --- Landsat --- Vision Transformer --- Bidirectional long-short term memory --- Google Earth Engine --- Explainable Artificial Intelligence