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TwitterThis excel contains results from the 2017 State of Narragansett Bay and Its Watershed Technical Report (nbep.org), Chapter 22: "Open Space." Protected open space in 2015 in the Narragansett Bay, Little Narragansett Bay, and Southwest Coastal Ponds watersheds was analyzed via an overlay of 2015 conservation land data from Massachusetts and Rhode Island (RIDEM 2006, 2007, EOEEA 2015) and Rhode Island 2011 and Massachusetts 2005 state land use data (RIGIS 2014, MassGIS 2009). Four overarching land use categories were defined by NBEP: (1) natural lands, (2) agricultural lands, (3) recreational lands, and (4) other lands (the latter two categories were combined to “recreational and other lands" for the summary statistics presented in the Technical Report and data tables for Open Space). State land-use classifications were used to define the type of protected open space. Natural protected open space included forest, forested and non-forested wetlands, pasture not suitable for tillage, and some additional undeveloped land uses. Agricultural protected open space included cropland, orchards, and nurseries. Recreational and other protected open space included golf courses, recreational spaces, residential land uses, cemeteries, vacant land, and other developed land uses.
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TwitterThis excel contains results from the 2017 State of Narragansett Bay and Its Watershed Technical Report (nbep.org), Chapter 4: "Population." The methods for analyzing population were developed by the US Environmental Protection Agency ORD Atlantic Coastal Environmental Sciences Division in collaboration with the Narragansett Bay Estuary Program and other partners. Population rasters were generated using the USGS dasymetric mapping tool (see http://geography.wr.usgs.gov/science/dasymetric/index.htm) which uses land use data to distribute population data more accurately than simply within a census mapping unit. The 1990, 2000, and 2010 10m cell population density rasters were produced using Rhode Island state land use data, Massachusetts state land use, Connecticut NLCD land use data, and U.S. Census data. To generate a population estimate (number of persons) for any given area within the boundaries of this raster, NBEP used the the Zonal Statistics as Table tool to sum the 10m cell density values within a given zone dataset (e.g., watershed polygon layer). Results presented include population estimates (1990, 2000, 2010) as well as calculation of acres of developed lands per 100 persons and percent change in estimated population (1990-2000; 2000-2010; 1990-2010).
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TwitterAttribution-ShareAlike 4.0 (CC BY-SA 4.0)https://creativecommons.org/licenses/by-sa/4.0/
License information was derived automatically
Describes soil type as one of 5 soils classes: Forest soil, Agricultural soil, Other and > 500 m (shallow), Rice soil, Organic soil. This is a temporary solution as soil-type from the European soils database (ESDB) had problems describing soil types over northern Europe. Soil type was instead inferred from land use class from the land use data provided on this site based on the assumption that landuse generally follows soil suitability. Data is presented as the percentage of each soil-type within each subbasin (i.e. subbasin level) OR the percentage of each soil-type distributed over the subbasin's total catchment (including basins upstream of the local subbasin) area of E-HYPE2.5 (i.e. catchment level, mean area 215 km2). Original data source: Based on the landuse data provided on this site. Rice fields according toCLC2000 and GLC2000 Asia, and average subbasin elevation according to HYDOSHEDS/HYDRO1K Tools for repurposing: WHIST. Data formate: Table (Excel file) with unique subID which could be linked to the shapefile EHYPE_polygons_v2pt5.shp.
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TwitterThis dataset was derived by the Bioregional Assessment Programme. The parent dataset is identified in the Lineage field in this metadata statement. The processes undertaken to produce this derived dataset are described in the History field in this metadata statement.
This dataset contains extracts and clips of national landuse databases from the Galilee subregion.
This dataset is for use in deriving land use statistics within the Galilee subregion reporting extents.
This dataset has been derived from clips and extracts of the Catchment-scale Land Use Management (CLUM) dataset (GUID: 88995758-2993-405e-bd0b-a2001a6539e6). It contains the following shapefiles:
GAL_Subregions_LandUse_PAE_Clip.shp - "Catchment-scale Land Use Management (CLUM)" clipped to the Galilee PAE: Galilee Subregion whole potential assessment extent v02 (GUID: 7d48db4e-d4fc-431e-89c5-a36b97073656)
GAL_LandUse_SubregionBoundary_Clip.shp - "Catchment-scale Land Use Management (CLUM)" clipped to the Galilee subregion extent: Bioregional Assessment areas v03 (GUID: 96dbf469-5463-4f4d-8fad-4214c97e5aac)
GAL_LandUse_NatureReserves_Clip.shp - extract of "Catchment-scale Land Use Management (CLUM)" where 'SecondV7' = "1.1 Nature conservation"
GAL_Landuse_GrazingNativeVegetation_Clip.shp - "Catchment-scale Land Use Management (CLUM)" with the 'Tert_V7' code = "2.1.0 Grazing natural vegetation", clipped to the Galilee subregion boundary
In addition, the following excel tables (.xlsx) were created to aid in the statistical analysis of spatial land use information for the Galilee Basin:
GAL_ContextualReport_Table2_LandUseArea_PAE.xlsx - Attribute table from shapefile - GAL_Subregions_LandUse_PAE_Clip.shp
GAL_ContextualReport_Table2_LandUseArea_SubregionBoundary.xlsx - Attribute table from shapefile - GAL_LandUse_SubregionBoundary_Clip.shp
Summary_PAE_SymDiff.xls - Table showing the difference in land use statistics from the version 1, Galilee Groundwater PAE\* (Lake Eyre Basin Groundwater Potential Assessment Extents v01, GUID: 3d59fd39-8d26-49d4-b6de-2e1fba315ddb) to the version 2, Galiee whole PAE (Galilee Subregion whole potential assessment extent v02, GUID: 7d48db4e-d4fc-431e-89c5-a36b97073656). This file was used as a reference only and was not included in any BA products
\* Spatial files for the version 1 Galilee Groundwater PAE Land Use Assessment were not retained.
Bioregional Assessment Programme (2014) Bioregional_Assessment_Programme_Catchment-scale Land Use Management (CLUM) - Extracts and Galilee subregion clips for landuse assessment. Bioregional Assessment Derived Dataset. Viewed 21 December 2017, http://data.bioregionalassessments.gov.au/dataset/1c19671a-e37f-471f-9246-fbeea4fc5f1a.
Derived From SA Petroleum Exploration Licence/Permit Applications
Derived From South Australia Mineral Leases Production, 6 March 2013
Derived From SA Petroleum Production License Applications
Derived From Galilee Subregion whole potential assessment extent v02
Derived From Bioregional_Assessment_Programme_Catchment-scale Land Use Management (CLUM)
Derived From Natural Resource Management (NRM) Regions 2010
Derived From SA Mineral and/or Opal Exploration Licenses
Derived From QLD Current Exploration Permits for Coal 6/3/2013
Derived From QLD Current Authorities to Prospect for Petroleum (ATP), 6/3/2013
Derived From Lake Eyre Basin Groundwater Potential Assessment Extents (PAE) v01
Derived From QLD Mining Lease 6/3/2013
Derived From GEODATA TOPO 250K Series 3, File Geodatabase format (.gdb)
Derived From GEODATA TOPO 250K Series 3
Derived From Australian Geological Provinces, v02
Derived From NSW Catchment Management Authority Boundaries 20130917
Derived From SA Mineral and/or Opal Exploration Licence Applications
Derived From South Australia Mineral Production Claims, 6 March 2013
Derived From SA Mining and Production Tenement Applications
Derived From QLD Petroleum Leases 6/3/2013
Derived From Bioregional Assessment areas v03
Derived From QLD Mining Claim 6/3/2013
Derived From SA Petroleum Exploration Licences/Permits
Derived From South Australia Petroleum Production Licenses
Derived From Galilee Surface Water Preliminary Assessment Extent (PAE) v02
Derived From Lake Eyre Basin Surface water Potential Assessment Extents v01
Derived From Geological Provinces - Full Extent
Derived From QLD Mineral Development License 6/3/2013
Derived From Bioregional Assessment areas v01
Derived From Bioregional Assessment areas v02
Derived From QLD Current Exploration Permits for Minerals (EPM) in Queensland 6/3/2013
Derived From Galilee Groundwater Preliminary Assessment Extent (PAE) v02
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TwitterCC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
The dataset contains input information used to prepare exposure maps for 37 European countries and territories from 1870 to 2020. It includes baseline land cover/use map and population map, and Excel tables with national or regional-level data on the environment, population and economy. Inofrmation on currencies and inflation can be used to convert nominal value of natural hazard-related losses to present-value euro.
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TwitterAttribution-ShareAlike 4.0 (CC BY-SA 4.0)https://creativecommons.org/licenses/by-sa/4.0/
License information was derived automatically
Land use is given as the percentage of one of 9 land use classes within a subbasin (i.e. subbasin level). The classes are Water, Glacier/Snow, Urban area, Forest, Agricultural land, Other and > 500 m, Wetland, Tundra/Permafrost, Extensive grassland/pasture. This is also given as percentage of each land use class upstream of (and including) a subbasin (i.e. catchment level, mean area 215 km2). Original data source: CORINE Land Cover (CLC2000), GLC2000 Northern Eurasia v4.0, GLC2000 Asia v1.0, GLC2000 Europe v2.0, Euroland SoilSealing 2009. Tools for repurposing: WHIST. Data format: Table (Excel file) with unique subID which could be linked to the shapefile EHYPE_polygons_v2pt5.shp.
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TwitterFrom July to August 2019, 147 soil samples of different land use types were collected every 20km,in sections from Xining City to Golmud of Qinghai Province, from Golmud of Qinghai Province to Lhasa of Tibet Autonomous Region, and from Golmud to Xining, far away from human disturbance. Totally, 147 soil samples were collected, including 83 grassland, 48 sandy land, 14 agricultural land and 3 forest land. The data set includes serial number, geographical location of sampling points, land use type, longitude and latitude coordinates, altitude, soil total nitrogen, total phosphorus, total potassium content and soil pH. The data format is Excel table. This data set is obtained by the combination of field sampling and indoor experiments. Soil samples in 0-15 cm layer was collected with a soil drill (8 cm in diameter) in each square by random sampling method, and the soil separated from the root system was screened by using a coarse screen. The total nitrogen, total phosphorus and total potassium was measured from the whole sample, and the 0.15 mm soil sample was used, in which the total nitrogen was measured by semi-automatic Kjeldahl nitrogen determinator, the total phosphorus was measured by spectrophotometer, and the total potassium was measured by flame photometer. The measurement of soil PH value was as: weighed 10g of air dried soil sample screened by 1mm into a 50ml beaker, added carbon dioxide free distilled water to maintain the water-soil ratio of 2.5:1, and measured it in PHSJ-4F laboratory. This data can provide data support and scientific basis for alpine ecosystem restoration.
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TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This is a parcel-level dataset of cropland in Xizang, China, and includes the field shape indicators of each parcel. The vector data are stored in ESRI Shapefile format, which can be visualized and edited using software such as ArcGIS Pro, ArcMap, and QGIS. Field shape indicators are further recorded in Excel tables, with unique FIDs for data-parcel associations.
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TwitterNOTE: Not all properties are mapped - several are confidential locations (e.g. group homes for the disabled) and some have poor address information.NOTE: EOHLC's table includes multiple records for a given site ID (one record for each subsidizing agency involved with the site). NMCOG's GIS version of the data as of 4/5/2024 does not have duplicate points (237 records versus 287 records in EOHLC's table).Excel file with all subsidized housing provided by the MA Department of Housing & Community Development (EOHLC) 4/5/2024. Data was formatted for GIS in Excel, subsidizing agency attributes for duplicate records were consolidated into one record (duplicates were removed), and x/y coordinates were added to the file from NMCOG's 2021 GIS data. Attributes added from 2019 inventory: NMCOG_Note, Label, Geo_Status, and AddressGeo11/4/21 Property ID removed (since 2019): 1654, 1656, 339711/4/21 Property ID added since 2019: 10561 and 10570 (2230 Main St Tewksbury), 10595 (Alder Point), and 10386 (Sugar Maple Lane)4/5/24: Property ID added since 2021: 10645 (Roberta McGuire Senior Residences, 2 Balsam Circle)Data provided 4/5/2024 by: MA Department of Housing & Community Development, 100 Cambridge Street, Suite 300, Boston, MA 02114
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TwitterThis theme presents the location of samples of contaminants of emerging interest (CIE) carried out by the Directorate-General for Monitoring the State of the Environment (DGSEE) as part of its work since 2000. Each station is accompanied by a link in the attribute table allowing the reader to access an Excel file presenting the concentrations of CIE detected, the list of CIE analyzed at least once at the station, the list of reports produced from the samples taken at the station, as well as information on surface water quality criteria for the protection of aquatic life. The dataset on contaminants of emerging interest also includes a layer of polygons presenting the drainage areas of some of the stations and a data table including the compilation of land use by category for the last year available at the time the data was generated. The drainage areas and the land use table are linked to the sampling stations based on the BQMA station number.This third party metadata element was translated using an automated translation tool (Amazon Translate).
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TwitterThis theme presents the location of samples of contaminants of emerging interest (CIE) carried out by the Directorate-General for Monitoring the State of the Environment (DGSEE) as part of its work since 2000. Each station is accompanied by a link in the attribute table allowing the reader to access an Excel file presenting the concentrations of CIE detected, the list of CIE analyzed at least once at the station, the list of reports produced from the samples taken at the station, as well as information on surface water quality criteria for the protection of aquatic life. The dataset on contaminants of emerging interest also includes a layer of polygons presenting the drainage areas of some of the stations and a data table including the compilation of land use by category for the last year available at the time the data was generated. The drainage areas and the land use table are linked to the sampling stations based on the BQMA station number.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**
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TwitterThis dataset is an excel spreadsheet of photo centres from aerial photography flown at Casey station in the 2002/2003 summer by John Hyslop. Some details about the photography are provided below. The photography was taken during voyage 7 of the Australian Antarctic Program 2002/2003 summer season. Voyage 7 was undertaken by the Polar Bird, and was a voyage to resupply Casey Station.
Voyage 7 / Polar Bird Casey round trip / re-supply Surveyor - John Hyslop Purpose - aerial photography Clark Peninsula / Casey Station region in the Windmill Islands Aerial photography flown - 4 and 5 March 2003 Camera - Zeiss UMK Film number - ANTC1216 Height - 400 and 800 metres
Flight line and photo centre coordinates are available from the AADC online aerial photography catalogue at the URL given below.
Hard copies of photos are available from the AADC aerial photo collection, Kingston.
The excel spreadsheet contains the following fields:
Longitude Latitude Film Run Camera Focal Length Oblique Camera Oblique Focal Length Height (metres) Quality Date Start End Frame Film Type Location Comments Positional Quality RMS
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