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Wetlands for the Treatment of Agricultural Drainage Water

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ISBN: 9783038972082 9783038972099 Year: Pages: 150 DOI: 10.3390/books978-3-03897-209-9 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Environmental Engineering --- General and Civil Engineering
Added to DOAB on : 2018-10-11 10:44:12
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Agricultural drainage, such as runoffs from farmlands and wineries, are contaminated waters. Their management is monitored by environmental protection authorities who set targets of volume or pollutant reductions. Due to large quantities and seasonal variations, the targets are often not met, and effective management remains a problem in many parts of the world.Natural wetlands are known as the ‘kidneys’ of the earth with unique water purification functions that have long been recognized. Imitating the functions of natural wetlands, constructed wetlands are engineered systems purposely built to treat contaminated waters. They may therefore be called the ‘artificial kidneys’ of the earth. Rural areas often only have low-value lands available for constructed wetlands. Where large quantities of drainage are produced, farmlands are often adjacent to degraded natural wetlands that have reduced ecosystem functions. Controlled discharge and treatment in the wetlands can potentially be part of an integrated solution to multiple environmental problems.This book includes some recent studies on the fate of pollutants removed from agricultural drainage in wetlands, modelling of wetland performance, innovative systems, and the use of non-hazardous agricultural waste in constructed wetlands for wastewater treatment. These studies enhance our understanding of wetland systems, and will help develop wetland technology towards solving the problems associated with agricultural drainage.

Guide de gestion des dunes et des plages associées

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ISBN: 9782759224821 9782759224838 Year: Pages: 224 DOI: 10.35690/978-2-7592-2482-1 Language: French
Publisher: éditions Quae
Subject: Environmental Technology
Added to DOAB on : 2019-09-13 11:21:04
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This practical guide benefits from the experience of several authors and experts in managing coastal dune environments and in preventing natural risks. It presents useful tools in resolving problems of daily dune management.

Sustainable Drainage Systems

ISBN: 9783038420927 9783038420910 Year: Pages: XII, 236 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Added to DOAB on : 2016-07-12 11:05:05
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Google Earth Engine Applications

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ISBN: 9783038978848 9783038978855 Year: Pages: 420 DOI: 10.3390/books978-3-03897-885-5 Language: eng
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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