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30 results for “imperviousness”
Data from: Herbivory on the pedunculate oak along an urbanization gradient in Europe: effects of impervious surface, local tree cover and insect feeding guild
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Spectrally unmixed percent of impervious surface, soil, and vegetation cover in central Arizona-Phoenix, year 2000
Urban land covers (e.g., cement parking lots, asphalt roads, shingle rooftops, grass, tress, exposed soil) can only be recorded as either present or absent in each pixel when using traditional per-pixel classifiers. Sub-pixel analysis approaches that can provide the relative fraction of surface covers within a pixel may be a potential solution to effectively identifying urban impervious areas. Spectral mixture analysis approach is probably the most commonly used approach that models image spectra as spatial average of spectral signatures from two or more surface features. However, spectral mixture analysis does not account for the absence of one of the surface features or spectral variation within pure materials since it utilizes an invariable set of surface features. Multiple endmember spectral mixture analysis (MESMA) approach addresses these issues by allowing endmembers to vary on a per pixel basis. The MESMA technique was employed in this study to model Landsat ETM+ reflectance in the Phoenix metropolitan area. Field spectra of vegetation, soil, and impervious surface areas collected with the use of a fine resolution Quickbird image and pixel purity index tool in ENVI software were modeled as reference endmembers in addition to photometric shade that was incorporated in every model. This study employs thirty endmembers and six hundred and sixty spectral models to identify soil, impervious, vegetation, and shade in the Phoenix metropolitan area. The mean RMS error for the selected land use land cover classes range from 0.003 to 0.018. The Pearson correlation between the fraction outputs from MESMA and reference data from Quickbird 60 cm resolution data for soil, impervious, and vegetation were 0.7052, 0.7249, and 0.8184 respectively.
Imperviousness_area2
<p>Imperviousness layer was derived from remote sensing data (Pleiades images)</p>
Imperviousness_area1
<p>Imperviousness layer was derived from remote sensing data (Pleiades images)</p>
Urban impervious surface expansion intensifies heavy rainfall in Beijing's rainy season
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Improving the local climate zone classification with building height, imperviousness, and machine learning
<p>Dataset and python script for the Local Climate Zone classification analysis used in the study. </p>
The Arabidopsis DNA methylome is relatively impervious to abiotic stress
GEO Series GSE94075. Arabidopsis thaliana. 29 samples. Type: Methylation profiling by high throughput sequencing.
Global Man-made Impervious Surface (GMIS) Dataset From Landsat
The Global Man-made Impervious Surface (GMIS) Dataset From Landsat consists of global estimates of fractional impervious cover derived from the Global Land Survey (GLS) Landsat dataset for the target year 2010. The GMIS dataset consists of two components: 1) global percent of impervious cover; and 2) per-pixel associated uncertainty for the global impervious cover. These layers are co-registered to the same spatial extent at a common 30m spatial resolution. The spatial extent covers the entire globe except Antarctica and some small islands. This dataset is one of the first global, 30m datasets of man-made impervious cover to be derived from the GLS data for 2010 and is a companion dataset to the Global Human Built-up And Settlement Extent (HBASE) dataset. The dataset is expected to have a rather broad spectrum of users, from those wishing to examine/study the fine details of urban land cover over the globe at full 30m resolution to global modelers trying to understand the climate/environmental impacts of man-made surfaces at continental to global scales. For example, the data are applicable to local modeling studies of urban impacts on the energy, water, and carbon cycles, as well as analyses at the individual country level.
California HOLC grades with NDVI, impervious surface, and iNaturalist data (2017-2022)
<p>HOLC grade maps linked to iNaturalist data across six taxonomic clades from (2017-2022)</p>
The impact of impervious surface expansion in Indonesia from 1992 to 2020 on terrestrial vertebrates
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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.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
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.