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4 results for “UC2”
Overview of Automatic Preliminary Boundary Delineation Tool developed as part of UC2 (Prefilled Application) in NIVA4CAP
<p>UC2 Pre-filled application seeks to make it easier and more accurate for farmers to annually declare their lands by reducing the time needed to draw the new parcels boundaries or update the existing ones, thus, prevent the mistakes with input of the data on crops grown. The work focussed on (1) Creating an automatic preliminary boundary delineation tool, (2) Testing an early stage corp type/ land use classification tool and (3) Finding and testing a robotic process automation tool suitable for data harvesting from external registers. This document gives an overview of the parcel boundary delineation tool and is supplemented by a complementary report summarising results from tests of that tool in Lithuania and Spain and referenced below.</p>
Represent project UC2 Land Cover Dataset
<p>The dataset is composed of Sentinel-2 data, while the ground truths come from Copernicus Land Monitoring Service – Hot Spot Mapping (HSM), that provides high resolution land cover maps over several Natural Protected Areas mainly in Africa. The land cover legend is based on the FAO Land Cover Classification System (LCCS). These labels have been produced and validated mainly through photointerpretation of HR data.<br> The mapped area of interest (AOI) represents a key landscape for conservation area (KLC). The KLC has a total size of almost 14,000,000 140,000 km2 and is covering a vast area in southern Tanzania all the way to northern Mozambique.<br> In Tanzania the AOI is covering the entire Selous game reserve, an area of around 50,000 km2, representing 6% of Tanzania’s land surface. This world heritage site is not only the oldest, but also the largest single protected area in Africa. It is characterised by an extensive area of natural miombo woodlands representing also one of the most extensive forest areas under protection. the reserve contains some of the most important populations of elephants, buffalos, antelopes, lions, wild dogs and other predators in Africa.<br> Located in northern Mozambique, the Niassa reserve is with 42,400 km2 the largest conservation area of the country, containing also the greatest concentration of wildlife of the country. the two reserved are connected by the Selous – Niassa wildlife corridor, an area of approximately 9000 km2 located entirely on the Tanzanian side which represents an important biological link between the two reserves and consequently for the miombo woodland eco-system. the Selous - Niassa ecosystem is one of the largest trans-boundary natural dry forest eco-regions in Africa. It constitutes one of the largest elephant ranges in the world and contains half of the world remaining wild dog population. it enables migration of wildlife and gene flow and contributing to the conservation of biodiversity.</p> <p>The dataset is organised in tiles, thus there is one folder for each of the Sentinel-2 tiles used. For each of these folders, there are the labels (both in vector and raster format) and the acquisitions organised in different acquisitions times.<br> Specifically, the dataset has the following folder structure:</p> <ul> <li>LandCover_Train_v2: directory for the training dataset of UC2 <ul> <li>00XXX (e.g.: 37MCN): folders with Sentinel-2 tile name. <ul> <li>labels: folder with raster and vector labels. The name of the label files in both format is the name of the Sentinel-2 tile to which they refer to (e.g.: 37MCN.tif/37MCN.shp) <ul> <li>raster: labels in raster format (.tif)</li> <li>vector: labels in vector format (.shp)</li> </ul> </li> <li>AAAAMMDD (e.g.: 20170630): folders with datetime of the Sentinel-2 acquisition. It contains all the 13 bands of the acquisition plus the TCI (True Color Image) in jp2 format.</li> </ul> </li> </ul> </li> <li>LandCover_Test: directory for the test dataset of UC2 <ul> <li>00XXX (e.g.: 37MCN): folders with Sentinel-2 tile name. <ul> <li>labels: folder with raster and vector labels. The name of the label files in both format is the name of the Sentinel-2 tile to which they refer to (e.g.: 37MCN.tif/37MCN.shp) <ul> <li>raster: labels in raster format (.tif)</li> <li>vector: labels in vector format (.shp)</li> </ul> </li> <li>AAAAMMDD (e.g.: 20170630): folders with datetime of the Sentinel-2 acquisition. It contains all the 13 bands of the acquisition plus the TCI (True Color Image) in jp2 format.</li> </ul> </li> </ul> </li> <li>GT_legend.xlsx: excel file with the association between the classes and the assigned number value in the raster version of the labels</li> </ul>
UC2 KPI Dataset
Open the record for dataset details and reuse information.
H2020 DeepCube UC2: Climate Induced Migration in Africa Public Datacube
<p>This is the public datacube for UC2 climate induced migration in Africa (2015-2023)</p> <p>The input data includes varied data sources, environmental and climatic variables from Earth Observation data and relevant socioeconomic data sources accounting for the main drivers of drought displacement in Somalia. The Earth Observation data cube includes variables from ERA5 Land such as 2m Temperature, Potential Evaporation, Total Precipitation and the Volumetric soil water layers, the ESA CCI land cover map and the precipitation dataset captured from Climate Hazards Center InfraRed Precipitation with Station data (CHIRPS). The precipitation data from CHIRPS and the Potential Evaporation from ERA5 are used to compute the Standardized Precipitation and Evaporation Index (SPEI) that is a robust indicator for drought conditions accounting for both precipitation and temperature extremes.</p> <p>Regarding socioeconomic sources, the food security dimension is represented by market prices variables in different local markets like the price of livestock (for instance, Cattle, Camel, etc.) and harvest products (e.g., wheat, rice, maize, etc.). We also include the violent conflict data captured from the Armed Conflict Location & Event Data Project (ACLED) given the close link existing between droughts and conflict in Somalia. Finally, the dataset of Internal Displacement Somalia is obtained via the United Nations High Commissioner for Refugees (UNHCR) Protection & Return Monitoring Network (PRMN).</p> <p> </p>
ScienceDex guides
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
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