Gist 972852

100%

✓ Published0🌍 Public

Last edited May 15, 2011

Created on May 15, 2011

This visualization shows range maps for two species—Puma concolor and Ursus americanus—derived from MOL range data, alongside ecoregion occurrences for Puma concolor sourced from WWF. It uses a custom `MetaDataProfile` structure to attach metadata like names, bounding boxes, and EML profiles to each dataset. The ranges are rendered as `MultiPolygon` objects, while occurrences are grouped in an `OccurrenceSet`, with cross-references linking species to their metadata collections. The code defines these spatial and metadata relationships programmatically, though it does not include explicit rendering calls.

AI-generated description

Similar vizzes

Loading thumbnail…

Gist 991608

This visualization maps the global range of the puma (Puma concolor) using data from the IUCN Global Mammal Assessment, displaying the species’ habitat extent as a coarse-resolution vector polygon across the Americas. The example uses d3.geoPath to project and draw the shapefile-derived boundaries onto a canvas, while d3.forceSimulation likely positions map elements or labels. The rendering relies on Canvas getImageData to process pixel-level details, and the underlying spatial data is stored as an ESRI shapefile with a WGS84 coordinate system, resampled to a 200-kilometer grid for simplified display.

Aandrewxhill

83% match

Loading thumbnail…

Gist 954622

This visualization maps a network of species occurrence records and their associated ecoregion polygons. It shows how occurrence sets cluster together through shared taxonomic and geographic references, using an interactive force-directed layout. The code relies on d3.forceSimulation to position nodes representing occurrence sets and polygons, while d3.geoPath renders the underlying geographic boundaries from the stored polygon data. Data is pulled from Google App Engine’s datastore models, including OccurrenceSet and OccurrencePolygon, with the visualization highlighting relationships between species names, sources, and ecoregion types.

Aandrewxhill

71% match

Loading thumbnail…

Gist 975514

This visualization maps amphibian and mammal species distributions across protected areas using force-directed network graphs. It links species to sites via WDPA biodiversity inventory data, with nodes colored and sized by taxonomic family or threat status. The code employs d3.forceSimulation for layout and d3.geoPath for rendering spatial relationships, while Canvas getImageData enables pixel-level interaction. Red List status and population trends are encoded through node styling, with volant versus terrestrial mammals distinguished by shape or color.

Aandrewxhill

70% match

Loading thumbnail…

Gist 896930

This example shows how biological species names and their associated geographic data types can be linked through shared layer identifiers. A force-directed layout, likely using d3.forceSimulation, maps the relationships between search terms, source types (GBIF points and MOL ranges), and matched species names. The visualization connects name matches like “Puma concolor” to overlapping layer IDs, while distinguishing whether each layer originates from GBIF or MOL. It demonstrates a data model for reconciling multiple taxonomic and spatial datasets, though the actual rendering logic is not included in the provided code.

Aandrewxhill

69% match

Loading thumbnail…

Gist 991610

This visualization maps the Admiralty Islands lowland rain forests ecoregion, plotting species occurrence data from the World Wildlife Fund as a spatial assemblage list. It renders geographic boundaries and species locations using D3.js, likely employing `d3.geoPath` for map projection and `d3.forceSimulation` to distribute overlapping species points. The visualization encodes each taxon as a distinct mark, with non-introduced species indicated by a false flag in the dataset. The temporal coverage spans 1990 to 2020, though the static display focuses on the spatial distribution of the 25 listed species across the ecoregion.

Aandrewxhill

68% match

Loading thumbnail…

Gist 4047799

This visualization displays a collection of geographic polygons overlaid on what appears to be a map, using a MultiPolygon GeoJSON structure. The coordinates trace irregular land parcels or boundaries across a region spanning approximately 15.6-17.1 longitude and 56.0-57.4 latitude. The author, andrewxhill, rendered the polygons with a custom JavaScript implementation that encodes the spatial data as geographic shapes. The visualization highlights the boundaries and shapes of these land areas, with the coordinates forming two distinct polygon groups. The rendering emphasizes the geometric contours and spatial relationships of the mapped regions.

Aandrewxhill

66% match

Loading thumbnail…

Gist 956273

A graph visualization maps ecological occurrence sets and multipolygon indexes through their shared terms, using a force-directed layout to reveal clusters of related species and regions. The code builds the network from App Engine datastore models, connecting occurrences to their parent sets via reference properties. It renders nodes and edges using d3.forceSimulation, with spatial positioning driven by simulated physics rather than geographic projection, while styling reflects term rank and type metadata from the stored entities.

Aandrewxhill

66% match

Loading thumbnail…

Gist 991607

This visualization maps the Admiralty Islands lowland rain forests ecoregion using a World Wildlife Fund shapefile, displaying its geographic boundary as a multipolygon vector. It uses d3.geoPath to render the projected shape onto a Canvas, with geographic coordinates derived from the WWF dataset’s spatial extent and CRS metadata. The example also reads pixel data via Canvas getImageData to inspect the rendered area, though it does not animate or filter the shape further.

Aandrewxhill

64% match