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65 results for “Land cover change”
NLCD 1992/2001 Retrofit Land Cover Change Product
Developments in mapping methodology, new sources of input data, and changes in the mapping legend for the 2001 National Land Cover Database (NLCD2001) will confound any direct comparison between NLCD2001 and National Land Cover Dataset 1992 (NLCD1992). Users are cautioned that direct comparison of these two independently created land cover products is not recommended. This NLCD 1992/2001 Retrofit Land Cover Change Product was developed to offer users more accurate direct change analysis between the two products. The NLCD 1992/2001 Retrofit Land Cover Change Product uses a specially developed methodology to provide land cover change information at the Anderson Level I classification scale (Anderson et al., 1976*), relying on decision tree classification of Landsat satellite imagery from circa 1992 and 2001. Unchanged pixels between the two dates are coded with the NLCD01 Anderson Level I class code, while changed pixels are labeled with a "from-to" land cover change value. Additional details about this product are available in the metadata included in the multi-zone downloadable zip file. This product is designed for regional application only and is not recommended for local scales.
Investigating the Combined Impact of Climate Change and Land Use/Land Cover on Flood Vulnerability Using a Machine Learning Algorithm
<p>Using the uploaded code in preparation of the Flood vulnerability maps.</p><p> </p>
Mapping land cover change over continental Africa using Landsat and Google Earth Engine cloud computing
<p>This dataset contains continental (Africa) land cover and impervious surface changes over a long period of time (15 years) using high resolution Landsat satellite observations and Google Earth Engine cloud computing platform. The approach applied here to overcome the computational challenges of handling big earth observation data by using cloud computing can help scientists and practitioners who lack high-performance computational resources. The dataset contains seven classes, prepared annually from 2000 to 2015, using high‐resolution Landsat 7 images (ETM+) and analyzed by Google Earth Engine cloud computing method. The model that generated the LULC classification was evaluated for predictive accuracy across classes as well as overall accuracy. The model achieved an overall accuracy of 88% with class-specific user’s and producer’s accuracies ranged from 84-94% and 79-96% respectively (Midekisa et al., 2017).</p> <p> </p>
Investigating the Combined Impact of Climate Change and Land Use/Land Cover on Flood Vulnerability Using a Machine Learning Algorithm.
<p>The used data in the paper</p>
Investigating the Combined Impact of Climate Change and Land Use/Land Cover on Flood Vulnerability Using a Machine Learning Algorithm.
<p>Flood points and Meteorological data</p>
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
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DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
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
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.