The geospatial dataset maps organic carbon (OC) storage (kg OC m-2) and OC stocks (tonnes OC) of surficial soils across 438 Great British saltmarshes. The OC density for the surficial soils (top 10 cm) is mapped across 451.65 km2 of saltmarshes, identified from current saltmarsh maps of Great Britain’s three constituent countries; Scotland, England and Wales The spatial maps are built upon surficial (top 10 cm) soil bulk density and carbon data produced by the NERC C-Side project and Marine Scotland data combined with existing saltmarsh vegetation maps. The work was carried out under the NERC programme - Carbon Storage in Intertidal Environment (C-SIDE), NERC grant reference NE/R010846/1. Full details about this dataset can be found at https://doi.org/10.5285/cb8840f2-c630-4a86-9bba-d0e070d56f04

The dataset contains daily grass-reference evapotranspiration (ETo) maps stored as ASCII files. ETo at a 2 km spatial resolution are calculated statewide using the American Society of Civil Engineers version of the Penman-Monteith equation (ASCE-PM). Required input parameters for the ASCE-PM ETo equation are solar radiation, air temperature, relative humidity, and wind speed at two meters height. These parameters are estimated for each 2 km pixel using various methods.

Daily solar radiation is generated from the visible band of the National Oceanic and Atmospheric Administration's (NOAA) Geostationary Operational Environmental Satellite (GOES) using the Heliosat-II model. This model is designed to convert images acquired by the Meteosat satellite into maps of global (direct plus diffused) irradiation received at ground level.

These spatial-index maps act as an important finding aid for map collections in libraries. They serve as a spatial 'table of contents' for the maps contained in a series of maps and are important for users to determine which sheet covers a particular location–-information that cannot be adequately described in a traditional catalog record.

Maps and map applications of all kinds—interactive map viewers, downloadable maps, map collections and more—from all around King County government.

6.0.1

Collection description

These spatial maps represent resting state networks identified in 47 subjects 2-4 days post cardiac arrest, using an ICA approach.
We provide both the spatial maps, as well as masks after thresholding on F>3.2

Preprocessed data were submitted to probabilistic independent component analysis (ICA) on a group level, using FSL’s MELODIC (Beckmann and Smith, 2004). This decomposed the BOLD data into 20 group-average spatially independent components. We identified 10 resting state networks, and 10 noise components.

Subject species

homo sapiens

Modality

fMRI-BOLD

Analysis level

group

Cognitive paradigm (task)

rest eyes closed

Map type

R

Model outputs were updated on Dec 20, 2017. This project used a machine learning data-driven model to predict the distribution of soil carbon under mangrove forests globally. Specifically this dataset contains: 1) a compilation of georeferenced and harmonized soil profile data under mangroves compiled from literature, reports and unpublished contributions 2) global mosaics of soil carbon stocks to 1m and 2m depths produced at 100 m resolution 3) tiled predictions of soil carbon stocks produced at 30 m resolution 4) shape file containing the tiling system 5) shape file containing country boundaries used for calculating national level statistics For detailed methodologies, please contact JS directly until the paper is published. 30m data can be quickly visualized at: https://storage.googleapis.com/gfiske1/global_mangrove/index_w_slider.html (2017-12-20)

MAPDAT is a program for plotting spatial data held in the ORACLE relational database onto any map within the Australian region at any scale. MAPDAT also includes a system for defining geological structures, thus any geological structure can be stored in the database and plotted. The program enables the plotting of sample locations along with infomration specific to each location. The information can be displayed beside each point or in a list to the side of the map. The symbols can be sized proportionally to the value of a column in a table or a SQL expression. Town locations, survey paths, gridlines, survey areas, coastlines and other geographical lines can be plotted. The program does not compete with geographical information systems but fills a niche at a much lower level of complexity. As a result of its simplicity a minimum in setting up of data is required and using the program is very straight forward with the user always aware of the database operations being performed.

Abstract This research investigates subjective user preference for using Floor Plans and Schematic Maps in an indoor environment, and how users locate and orient themselves when using these representations. We sought to verify the efficiency of these two kinds of digital maps and evaluate which elements found in physical environments and which elements found in the representations influence the user spatial orientation process. Users answered questions and performed orientation tasks which indicated their level of familiarity with the area being studied, their understanding of the symbology used, and their identification of Points of Interest (POI) in the environment. The initial results indicated a preference for the Schematic Map, because users thought that the symbology used on the map adopted was easy to understand.

These spatial-index maps act as an important finding aid for map collections in libraries. They serve as a spatial 'table of contents' for the maps contained in a series of maps and are important for users to determine which sheet covers a particular location–-information that cannot be adequately described in a traditional catalog record.

The list of study sites, meteorological stations and locations of interest that are shown on the Bonanza Creek Long Term Ecological Research site (BNZ LTER) internet map server (IMS, available at http://www.lter.uaf.edu/ims_intro.cfm) is generated from the LTER study sites database. The information is converted into a shapefile and posted to the IMS. Some study sites shown on the main LTER website will not appear on the IMS because they do not have location coordinates. In all cases the most up-to-date information will be found on the (study sites website ).

The spatial information represented on the IMS is available to the public according to the restrictions outlined in the LTER data policy. The dataset represented here consists of the map layers shown on the IMS. The information consists of shapefiles in Environmental Systems Research Institute (ESRI) format. Users of this dataset should be aware that the contents are dynamic. Portions of the information shown on the IMS are derived from the Bonanza Creek LTER databank and are constantly being updated.

ABSTRACT: The U.S. Geological Survey (USGS) Upper Midwest Environmental Sciences Center (UMESC) has produced the Vegetation Spatial Database Coverage (vegetation map) for the Acadia National Park Vegetation Mapping Project, USGS-NPS Vegetation Mapping Program (VMP). The vegetation map is of Acadia National Park (NP) and extended environs, providing 99,693 hectares (246,347 acres) of map data. Of this coverage, 52,872 hectares (130,650 acres) is non-vegetated ocean, bay, and estuary (53% of coverage). Acadia NP comprises 19,276 hectares (47,633 acres) of the total data coverage area (19%, 40% not counting ocean and estuary data). Over 7,120 polygons make up the coverage, each with map class description and, for vegetation classes, physiognomic feature information. The spatial database provides crosswalk information to all National Vegetation Classification System (NVCS) floristic and physiognomic levels, and to other established classification systems (NatureServe's U.S. Terrestrial Ecological System Classification, Maine Natural Community Classification, and the USGS Land Use and Land Cover Classification). This mapping project has identified 53 NVCS associations (vegetation communities) at Acadia National Park through analyses of vegetation sample data. These associations are represented in the map coverage with 33 map classes. With all vegetation types, land use classes, and park specific categories combined, 57 map classes define the ground features within the project area (58 classes including the class for no map data). Each polygon within the spatial database map is identified with one of these map classes. In addition, physiognomic modifiers are added to map classes representing vegetation to describe the vegetation structure within a polygon (density, pattern, and height). The spatial database was produced from the interpretation of spring 1997 1:15,840-scale color infrared aerial photographs. The standard minimum mapping unit (MMU) applied is 0.5 hectares (1.25 acres). The interpreted data were transferred and automated using base maps produced from USGS digital orthophoto quadrangles. The finished spatial database is a single seamless coverage, projected in Universal Transverse Mercator, Zone 19, with datum in North American Datum of 1983. The estimated overall thematic accuracy for vegetation map classes is 80%.

Golden eagle (Aquila chrysaetos) nest site model spatial data and maps as described in Dunk JR, Woodbridge B, Lickfett TM, Bedrosian G, Noon BR, LaPlante DW, et al. (2019) Modeling spatial variation in density of golden eagle nest sites in the western United States. PLoS ONE 14(9): e0223143. https://doi.org/10.1371/journal.pone.0223143

Map Direct focus for viewing Spatial Air Quality System (SAQS) data. Please refer to https://floridadep.gov/air/air-monitoring/content/floridas-air-quality for more information. Originally created on 03/12/2007, and moved to Map Direct Lite on 11/29/2016. Please contact GIS.Librarian@floridadep.gov for more information.

Have you ever wanted to create your own maps, or integrate and visualize spatial datasets to examine changes in trends between locations and over time? Follow along with these training tutorials on QGIS, an open source geographic information system (GIS) and learn key concepts, procedures and skills for performing common GIS tasks – such as creating maps, as well as joining, overlaying and visualizing spatial datasets. These tutorials are geared towards new GIS users. We’ll start with foundational concepts, and build towards more advanced topics throughout – demonstrating how with a few relatively easy steps you can get quite a lot out of GIS. You can then extend these skills to datasets of thematic relevance to you in addressing tasks faced in your day-to-day work.

This presentation looks at DMTI software. DMTI develops and markets web enabled spatial data and software products used in corporate and institutional information and marketing systems.

OpenStreetMap (OSM) is a free, editable map & spatial database of the whole world. This dataset is an extract of OpenStreetMap data for 21 Pacific Island Countries, in a GIS-friendly format. The OSM data has been split into separate layers based on themes (buildings, roads, points of interest, etc), and it comes bundled with a QGIS project and styles, to help you get started with using the data in your maps. This OSM product will be updated weekly and contains data for Cook Islands, Federated States of Micronesia, Fiji, Kiribati, Republic of the Marshall Islands, Nauru, Niue, Palau, Papua New Guinea, Samoa, Solomon Islands, Tonga, Tuvalu, Vanuatu, Guam, Northern Mariana Islands, French Polynesia, Wallis and Futuna, Tokelau, American Samoa as well as data on the Pacific region. The goal is to increase awareness among Pacific GIS users of the richness of OpenStreetMap data in Pacific countries, as well as the gaps, so that they can take advantage of this free resource, become interested in contributing to OSM, and perhaps join the global OSM community.

Wildlands in New England is the first U.S. study to map and characterize within one region all conserved lands that, by design, allow natural processes to unfold with no active management or intervention. These “forever wild lands” include federal Wilderness areas along with diverse public and private natural areas and reserves. Knowing the precise locations of Wildlands, their characteristics, and their protection status is important as both a baseline for advancing conservation initiatives and an urgent call to action for supporting nature and society. Wildlands play a unique role in the integrated approach to conservation and land planning advanced by the Wildlands, Woodlands, Farmlands & Communities (WWF&C) initiative, which calls for: at least 70 percent of the region to be protected forest; Wildlands to occupy at least 10 percent of the land; and all existing farmland to be permanently conserved. This research was conducted by WWF&C partners Harvard Forest (Harvard University), Highstead Foundation, and Northeast Wilderness Trust, in collaboration with over one hundred conservation organizations and municipal, state, and federal agencies. This dataset contains the Geographical Information System (GIS) polygon layer of Wildlands created by this project and used in all analyses for the 2023 report. Another GIS layer will be updated as new Wildlands are brought to our attention or created and will be available at https://wildlandsandwoodlands.org/ for researchers.

This file set includes:Two raster datasets of marine ecosystems in Spencer Gulf produced for a cumulative impact assessment. There is one raster for the benthic ecosystems and one for the pelagic ecosystem. For each of the rasters there is an associated projection file with the same name.Two tiff files of the ecosystem maps (illustrating what they look like when plotted)A metadata text file with details of the spatial data layers and their projection - as well as sources of further information.

This report publishes a geologic digital spatial database (ORGEO) for the geologic map of Oregon by Walker and MacLeod (1991) which was originally printed on a single sheet of paper at a scale of 1:500,000 and accompanied by a second sheet for map unit descriptions and ancillary data. The spatial digital database (GIS) provided in this report supersedes an earlier digital edition by Raines and others (1996).

Data shared from 2002 study

A Consumption-Based Approach.

This dataset includes geospatial data from the Planning Institute of Jamaica.