The datasets provided encompass all the statistics found on the Canadian Cluster Map Portal. Moreover, additional information such as cluster-concordance and cluster descriptions are provided to allow for accurate analysis of the data.

K=4 cluster map based on N=13 participants.

Collection description

K-means cluster maps of orbitofrontal cortex with K=2, 3, 4, 5, 6, and 7 clusters based on resting-state fMRI data.

Subject species

homo sapiens

Modality

fMRI-BOLD

Analysis level

group

Cognitive paradigm (task)

rest eyes open

Map type

R

World cluster map of the world based on a Coastal zone (LOICZ) database received in 1995 from the Netherlands Institute for Sea Research (NIOZ).

MCPS Cluster Service Areas

This data set describes Neighborhood Clusters that have been used for community planning and related purposes in the District of Columbia for many years. It does not represent boundaries of District of Columbia neighborhoods. Cluster boundaries were established in the early 2000s based on the professional judgment of the staff of the Office of Planning as reasonably descriptive units of the City for planning purposes. Once created, these boundaries have been maintained unchanged to facilitate comparisons over time, and have been used by many city agencies and outside analysts for this purpose. (The exception is that 7 “additional” areas were added to fill the gaps in the original dataset, which omitted areas without significant neighborhood character such as Rock Creek Park, the National Mall, and the Naval Observatory.) The District of Columbia does not have official neighborhood boundaries. The Office of Planning provides a separate data layer containing Neighborhood Labels that it uses to place neighborhood names on its maps. No formal set of standards describes which neighborhoods are included in that dataset.Whereas neighborhood boundaries can be subjective and fluid over time, these Neighborhood Clusters represent a stable set of boundaries that can be used to describe conditions within the District of Columbia over time.

Cluster Maps

The datasets provided encompass all the statistics found on the Canadian Cluster Map Portal. Moreover, additional information such as cluster-concordance and cluster descriptions are provided to allow for accurate analysis of the data.

PLEASE NOTE: this dataset has been retired. It has been superseded by data for Flood Risk Areas: https://environment.data.gov.uk/dataset/f3d63ec5-a21a-49fb-803a-0fa0fb7238b6

The Indicative Flood Risk Areas are primarily based on an aggregated 1km square grid Updated Flood Map for Surface Water (1 in 100 and 1000 annual probability rainfall), informally referred to as the “blue square map”.

• Cluster Maps – are aggregations of 3km by 3km squares that each contain at least 4 (in Wales) or 5 (in England) touching "blue squares" (i.e. 1km grid squares where one of the thresholds above is exceeded)

This dataset forms part of Indicative Flood Risk Areas (shapefiles)

A bundle download of all Indicative Flood Risk Areas spatial datasets is also available from this record. Please see individual records for full details and metadata on each product.

A database of the geologic map of the Katmai Volcanic Cluster as described in the original abstract: This digital publication contains all the geologic map information used to publish U.S. Geological Survey Geologic Investigations Map Series I-2778 (Hildreth and Fierstein, 2003). This is a geologic map of the Katmai volcanic cluster on the Alaska Peninsula (including Mount Katmai, Trident Volcano, Mount Mageik, Mount Martin, Mount Griggs, Snowy Mountain, Alagogshak volcano, and Novarupta volcano), and shows the distribution of ejecta from the great eruption of June, 1912 at Novarupta. Widely scattered erosional remnants of volcanic rocks, unrelated to but in the vicinity of the Katmai cluster, are also mapped. Distribution of glacial deposits, large landslides, debris avalanches, and surficial deposits are a snapshot of an ever-changing landscape.

MCPS Cluster Service Areas

This dataset is a series of digital map-posters accompanying the AdaptNRM Guide: Helping Biodiversity Adapt: supporting climate adaptation planning using a community-level modelling approach.

These represent supporting materials and information about the community-level biodiversity models applied to climate change. Map posters are organised by four biological groups (vascular plants, mammals, reptiles and amphibians), two climate change scenario (1990-2050 MIROC5 and CanESM2 for RCP8.5), and five measures of change in biodiversity.

The map-posters present the nationally consistent data at locally relevant resolutions in eight parts – representing broad groupings of NRM regions based on the cluster boundaries used for climate adaptation planning (http://www.environment.gov.au/climate-change/adaptation) and also Nationally.

Map-posters are provided in PNG image format at moderate resolution (300dpi) to suit A0 printing. The posters were designed to meet A0 print size and digital viewing resolution of map detail. An additional set in PDF image format has been created for ease of download for initial exploration and printing on A3 paper. Some text elements and map features may be fuzzy at this resolution.

Each map-poster contains four dataset images coloured using standard legends encompassing the potential range of the measure, even if that range is not represented in the dataset itself or across the map extent.

Most map series are provided in two parts: part 1 shows the two climate scenarios for vascular plants and mammals and part 2 shows reptiles and amphibians. Eight cluster maps for each series have a different colour theme and map extent. A national series is also provided. Annotation briefly outlines the topics presented in the Guide so that each poster stands alone for quick reference.

An additional 77 National maps presenting the probability distributions of each of 77 vegetation types – NVIS 4.1 major vegetation subgroups (NVIS subgroups) - are currently in preparation.

Example citations:

Williams KJ, Raisbeck-Brown N, Prober S, Harwood T (2015) Generalised projected distribution of vegetation types – NVIS 4.1 major vegetation subgroups (1990 and 2050), A0 map-poster 8.1 - East Coast NRM regions. CSIRO Land and Water Flagship, Canberra. Available online at www.AdaptNRM.org and https://data.csiro.au/dap/.

Williams KJ, Raisbeck-Brown N, Harwood T, Prober S (2015) Revegetation benefit (cleared natural areas) for vascular plants and mammals (1990-2050), A0 map-poster 9.1 - East Coast NRM regions. CSIRO Land and Water Flagship, Canberra. Available online at www.AdaptNRM.org and https://data.csiro.au/dap/.

This dataset has been delivered incrementally. Please check that you are accessing the latest version of the dataset. Lineage: The map posters show case the scientific data. The data layers have been developed at approximately 250m resolution (9 second) across the Australian continent to incorporate the interaction between climate and topography, and are best viewed using a geographic information system (GIS). Each data layers is 1Gb, and inaccessible to non-GIS users. The map posters provide easy access to the scientific data, enabling the outputs to be viewed at high resolution with geographical context information provided.

Maps were generated using layout and drawing tools in ArcGIS 10.2.2

A check list of map posters and datasets is provided with the collection.

Map Series: 7.(1-77) National probability distribution of vegetation type – NVIS 4.1 major vegetation subgroup pre-1750 #0x

8.1 Generalised projected distribution of vegetation types (NVIS subgroups) (1990 and 2050)

9.1 Revegetation benefit (cleared natural areas) for plants and mammals (1990-2050)

9.2 Revegetation benefit (cleared natural areas) for reptiles and amphibians (1990-2050)

10.1 Need for assisted dispersal for vascular plants and mammals (1990-2050)

10.2 Need for assisted dispersal for reptiles and amphibians (1990-2050)

11.1 Refugial potential for vascular plants and mammals (1990-2050)

11.1 Refugial potential for reptiles and amphibians (1990-2050)

12.1 Climate-driven future revegetation benefit for vascular plants and mammals (1990-2050)

12.2 Climate-driven future revegetation benefit for vascular reptiles and amphibians (1990-2050)

This folder contained R scripts and data sets used to generate clustering dendogram and heatmaps as shown Fig. 3.

Economic knowledge clusters. A distinction is made between "Metropolitan region", "Economic knowledge cluster" and "Indication economic cluster outside Brabant".

Building permit records in the City of Montgomery.

This geodatabase contains all the geologic map information for the Geologic Map of the San Juan caldera cluster, southwestern Colorado and is part of U.S. Geological Survey Geologic Investigations Map Series I-2799. The San Juan Mountains are the largest erosional remnant of a composite volcanic field that covered much of the southern Rocky Mountains in middle Tertiary time. The San Juan field consists mainly of intermediate-composition lavas and breccias, erupted about 35-30 Ma from scattered central volcanoes (Conejos Formation) and overlain by voluminous ash-flow sheets erupted from caldera sources. In the central San Juan Mountains, eruption of at least 8,800 km3 of dacitic-rhyolitic magma as nine major ash flow sheets (individually 150-5,000 km3) was accompanied by recurrent caldera subsidence between 28.3 Ma and about 26.5 Ma. Voluminous andesitic-dacitic lavas and breccias were erupted from central volcanoes prior to the ash-flow eruptions, and similar lava eruptions continued within and adjacent to the calderas during the period of more silicic explosive volcanism. Exposed calderas vary in size from 10 to 75 km in maximum dimension, the largest calderas being associated with the most voluminous eruptions.

Framing Psychology article map cluster colors (1960s)

Economic knowledge clusters. A distinction is made between ‘Metropolitan region’, ‘Economic knowledge cluster’ and ‘Indication economic cluster outside Brabant’.

Groups of geographically defined attendance areas. They include elementary and middle-level schools that feed into particular high schools and consortium schools.For further details: https://www2.montgomeryschoolsmd.org/departments/Clusteradmin/Clusters/indexFor more information, contact: GIS Manager Information Technology & Innovation (ITI) Montgomery County Planning Department, MNCPPC T: 301-650-5620

Map that mimics the geometry of 'fully developed slopes'.

Future Land Use Map for Alachua County, Fl