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Towards Principled Oceans Governance

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Book Series: Routledge Advances in Maritime Research ISBN: 9780203967935 9780415383783 9780415512398 9780415652865 9781134175888 9781134175871 9781134175833 Year: DOI: 10.4324/9780203967935 Language: English
Publisher: Taylor & Francis
Subject: Sports Science --- Geography --- Law
Added to DOAB on : 2019-11-08 11:21:05
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Abstract

Australia and Canada have been at the forefront of efforts to operationalize integrated oceans and coastal management. Throughout the 1990s both countries devoted considerable effort to developing strategies to give effect to international ocean management obligations. This key book focuses on principles of marine environmental conservation and management, maritime regulation and enforcement, and regional maritime planning and implementation. With contributions from respected scholars, this informative book collectively assesses the obligations, compliance, implementation and trends in international ocean law, particularly in giving effect to an Oceans Policy, regional maritime planning, international oceans governance, and maritime security. This book will be of interest to all academics involved with maritime studies and international law.

Biodiversity and Protected Areas

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ISBN: 9783038977322 9783038977339 Year: Pages: 196 DOI: 10.3390/books978-3-03897-733-9 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Science (General) --- Environmental Sciences
Added to DOAB on : 2019-04-25 16:37:17
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Biodiversity and Protected Areas assembles twelve topics from around the world, illustrating the complexities and promise of addressing the biodiversity crisis. Authors from Mongolia, Africa, India, Canada, Iraq, and the United States dwell on particular aspects and challenges relevant to those regions. Lessons and approaches from interesting localities, coupled with global analyses give the reader a synthetic view of emerging problems. The opportunities for understanding common issues across different geographies abound, such as comparing local conservation in sub-Saharan Africa with a distribution of very small protected areas in Massachusetts. Several topics will be of immediate interest to policymakers. The book is illustrated with numerous color maps and figures and the authors strove for clear, uncomplicated writing. The editors provide an overview of chapters, placing them in the context of other biodiversity and protected area literature. Students and conservationists attempting to broaden their views of biodiversity and protected areas should find this collection to be interesting.

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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