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423 results for “spatial use”
Supplementary material 4 from: Nedkov S, Zhiyanski M, Dimitrov S, Borisova B, Popov A, Ihtimanski I, Yaneva R, Nikolov P, Bratanova-Doncheva S (2017) Mapping and assessment of urban ecosystem condition and services using integrated index of spatial structure. One Ecosystem 2: e14499. https://doi.org/10.3897/oneeco.2.e14499
Contains descriptions of urban ecosystem subtypes and their relation to EUNIS habitat classess
Supplementary material 3 from: Nedkov S, Zhiyanski M, Dimitrov S, Borisova B, Popov A, Ihtimanski I, Yaneva R, Nikolov P, Bratanova-Doncheva S (2017) Mapping and assessment of urban ecosystem condition and services using integrated index of spatial structure. One Ecosystem 2: e14499. https://doi.org/10.3897/oneeco.2.e14499
Map of urban ecosystem condition representing an example of map sheets that cover the whole country
Fig. 1 in Relationships between morphology, diet and spatial distribution: testing the effects of intra and interspecific morphological variations on the patterns of resource use in two Neotropical Cichlids
Fig. 1. Dispersion of the scores of the first two PCA axes, calculated with the variance matrix of 22 ecomorphological indices. a) Scores classified by the type of environment; b) Scores classified by food resources, where: Emp = empty, Cru = crustacean, Aqu = aquatic insect, Fis = fish, Mol = mollusk, Hig = higher plant, Det = detritus. Dashed line: Crenicichla britskii; dotted line: Satanoperca pappaterra. ARA = Aspect ratio of the anal fin; ARC = Aspect ratio of the caudal fin; ARPt = Aspect ratio of the pectoral fin; ARPv = Aspect ratio of the pelvic fin; PI = Protrusion index; RAA = Relative area of the anal fin; RAD = Relative area of the dorsal fin; RAE = Relative area of the eye; RAPt = Relative area of the pectoral fin; RAPv = Relative area of the pelvic fin; RHM = Relative height of the mouth; RHPd = Relative width of the caudal peduncle; RWPd = Relative width of the caudal peduncle.
Figure 1. – Eastern English Channel spatial grid using a in Spatiotemporal patterns in marine fish and cephalopods communities across scales: using an autoregressive spatiotemporal clustering model. A study of fish and cephalopods of the Eastern English Channel
Figure 1. – Eastern English Channel spatial grid using a triangular mesh at a 522 km2 (A), 782 km2 (B) and 1043 km2 (C) average scale with the geographic coordinates in WGS84 of all the English Channel groundfish hauls survey from 1995 to 2014 (blue). The red points are the vertices used to define the mesh.
Figure 1 from: Underwood E, Taylor K, Tucker G (2018) The use of biodiversity data in spatial planning and impact assessment in Europe. Research Ideas and Outcomes 4: e28045. https://doi.org/10.3897/rio.4.e28045
Figure 1 Data use within the EIA process Own compilation based on information in (King et al. 2012).
Supplementary material 6 from: Winder L, Alexander C, Griffiths G, Holland J, Wooley C, Perry J (2019) Twenty years and counting with SADIE: Spatial Analysis by Distance Indices software and review of its adoption and use. Rethinking Ecology 4: 1-16. https://doi.org/10.3897/rethinkingecology.4.30890
: Data type: software
Supplementary material 4 from: Winder L, Alexander C, Griffiths G, Holland J, Wooley C, Perry J (2019) Twenty years and counting with SADIE: Spatial Analysis by Distance Indices software and review of its adoption and use. Rethinking Ecology 4: 1-16. https://doi.org/10.3897/rethinkingecology.4.30890
: Data type: software
Supplementary material 2 from: Winder L, Alexander C, Griffiths G, Holland J, Wooley C, Perry J (2019) Twenty years and counting with SADIE: Spatial Analysis by Distance Indices software and review of its adoption and use. Rethinking Ecology 4: 1-16. https://doi.org/10.3897/rethinkingecology.4.30890
: Data type: software
Supplementary material 1 from: Winder L, Alexander C, Griffiths G, Holland J, Wooley C, Perry J (2019) Twenty years and counting with SADIE: Spatial Analysis by Distance Indices software and review of its adoption and use. Rethinking Ecology 4: 1-16. https://doi.org/10.3897/rethinkingecology.4.30890
: Data type: software
Supplementary material 7 from: Winder L, Alexander C, Griffiths G, Holland J, Wooley C, Perry J (2019) Twenty years and counting with SADIE: Spatial Analysis by Distance Indices software and review of its adoption and use. Rethinking Ecology 4: 1-16. https://doi.org/10.3897/rethinkingecology.4.30890
: Data type: software
Supplementary material 5 from: Winder L, Alexander C, Griffiths G, Holland J, Wooley C, Perry J (2019) Twenty years and counting with SADIE: Spatial Analysis by Distance Indices software and review of its adoption and use. Rethinking Ecology 4: 1-16. https://doi.org/10.3897/rethinkingecology.4.30890
: Data type: software
Supplementary material 3 from: Winder L, Alexander C, Griffiths G, Holland J, Wooley C, Perry J (2019) Twenty years and counting with SADIE: Spatial Analysis by Distance Indices software and review of its adoption and use. Rethinking Ecology 4: 1-16. https://doi.org/10.3897/rethinkingecology.4.30890
: Data type: software
Figure 8b from: Briz-Redón Á (2019) SpNetPrep: An R package using Shiny to facilitate spatial statistics on road networks. Research Ideas and Outcomes 5: e33521. https://doi.org/10.3897/rio.5.e33521
Figure 8b "Point Pattern Edition" features. - Information that is displayed (marks of the point pattern, if available, as defined by the user) when an event is clicked
Figure 5a from: Briz-Redón Á (2019) SpNetPrep: An R package using Shiny to facilitate spatial statistics on road networks. Research Ideas and Outcomes 5: e33521. https://doi.org/10.3897/rio.5.e33521
Figure 5a Example of use of the SimplifyLinearNetwork function. - A road network introduced as input in which there is an excess of road segments and vertex
Figure 1 from: Briz-Redón Á (2019) SpNetPrep: An R package using Shiny to facilitate spatial statistics on road networks. Research Ideas and Outcomes 5: e33521. https://doi.org/10.3897/rio.5.e33521
Figure 1 Workflow that describes all the steps that could be carried out in order to perform a spatial analysis on a point pattern that lies on a linear network. Some of these steps which lead to the final statistical analysis may be skipped but, at least, all of them should be considered. The blocks pointing the steps of the process include some of the R packages that would allow to successfully achieve each of them.
Figure 3b from: Briz-Redón Á (2019) SpNetPrep: An R package using Shiny to facilitate spatial statistics on road networks. Research Ideas and Outcomes 5: e33521. https://doi.org/10.3897/rio.5.e33521
Figure 3b "Network Edition" example of use (I). - Network resulting from clicking on "Rebuild linear network" in the situation of a
Figure 2a from: Briz-Redón Á (2019) SpNetPrep: An R package using Shiny to facilitate spatial statistics on road networks. Research Ideas and Outcomes 5: e33521. https://doi.org/10.3897/rio.5.e33521
Figure 2a "Network Edition" features. - Overview of the "Network Edition" section of the SpNetPrep application
Figure 6b from: Briz-Redón Á (2019) SpNetPrep: An R package using Shiny to facilitate spatial statistics on road networks. Research Ideas and Outcomes 5: e33521. https://doi.org/10.3897/rio.5.e33521
Figure 6b "Network Direction" features. - Manual addition of traffic flow to the network by using the options "Add flow" and "Add long flow"
Figure 3a from: Briz-Redón Á (2019) SpNetPrep: An R package using Shiny to facilitate spatial statistics on road networks. Research Ideas and Outcomes 5: e33521. https://doi.org/10.3897/rio.5.e33521
Figure 3a "Network Edition" example of use (I). - Use of the "Join vertex" (in green), "Remove edge" (in red) and "Add point" options (in green) in the SpNetPrep application
Figure 8a from: Briz-Redón Á (2019) SpNetPrep: An R package using Shiny to facilitate spatial statistics on road networks. Research Ideas and Outcomes 5: e33521. https://doi.org/10.3897/rio.5.e33521
Figure 8a "Point Pattern Edition" features. - An example of a point pattern that lies on a road network as it can be visualized in SpNetPrep
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.