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Métiers, effort and catches of a Mediterranean small-scale coastal fishery: the case of the gulf of Lion Marine Natural Parc (Book chapter)

Book title: Eighth International Symposium “Monitoring of Mediterranean Coastal Areas. Problems and Measurement Techniques”

Authors: --- --- --- --- et al.
Book Series: Proceedings e report ISSN: 27045846 ISBN: 9788855181471 Year: Volume: 126 DOI: 10.36253/978-88-5518-147-1.57
Publisher: Firenze University Press
Subject: Forestry
Added to DOAB on : 2020-11-26 11:35:25
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Abstract

In the context of current fisheries crisis, this study aimed describing the characteristics of the artisanal fisheries in the Gulf of Lion Marine Natural Park located north-western Mediterranean. Catch Per Unit Effort and fishing effort were described on a spatio-temporal scale. Data were collected through questionnaires to fishers at landing sites for a one-year between 2019 and 2020. The most frequently used métiers were the hake gillnet and the sparids trammel net and gillnet, targeting two predominant species: hake (Merluccius merluccius) and gilthead seabream (Sparus aurata).

5 anni di monitoraggio, controllo e prevenzione della pesca illegale nel Parco Sommerso di Gaiola (Golfo di Napoli) (Book chapter)

Book title: Eighth International Symposium “Monitoring of Mediterranean Coastal Areas. Problems and Measurement Techniques”

Authors: --- --- --- --- et al.
Book Series: Proceedings e report ISSN: 27045846 ISBN: 9788855181471 Year: Volume: 126 DOI: 10.36253/978-88-5518-147-1.61
Publisher: Firenze University Press
Subject: Forestry
Added to DOAB on : 2020-11-26 11:35:25
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The Gaiola Underwater Park is a small Marine Protected Area located in Naples (Italy), funded in 2002 to preserve the biological and archaeological heritage. In fact, because of the metropolitan context in which it is integrated, the area is subject to constant anthropic pressure, which often results in illegal activities, especially in the fishing sector. In this work, the results of 5 years of monitoring and control of illegal fishing inside the MPA are presented. This research had an important impulse in 2015, thanks to the collected data and to the methodology developed within the Gaiola MedPAN Project. The experience acquired in these years resulted in the funding of the StAMM Project, a permanent station for the monitoring, control and prevention of environmental offences in the MPA.

Biodiversity and Protected Areas

Authors: ---
ISBN: 9783038977322 9783038977339 Year: Pages: 196 DOI: 10.3390/books978-3-03897-733-9 Language: English
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

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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