77 datasets found
  1. M

    LUCAS NZ Land Use Map 1990 2008 2012 2016 v011 DEPRECATED

    • data.mfe.govt.nz
    csv, dwg, geodatabase +6
    Updated Jul 22, 2012
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    Ministry for the Environment (2012). LUCAS NZ Land Use Map 1990 2008 2012 2016 v011 DEPRECATED [Dataset]. https://data.mfe.govt.nz/layer/52375-lucas-nz-land-use-map-1990-2008-2012-2016-v011-deprecated/
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    geopackage / sqlite, pdf, mapinfo tab, shapefile, kml, mapinfo mif, dwg, csv, geodatabaseAvailable download formats
    Dataset updated
    Jul 22, 2012
    Dataset authored and provided by
    Ministry for the Environment
    License

    https://data.mfe.govt.nz/license/attribution-4-0-international/https://data.mfe.govt.nz/license/attribution-4-0-international/

    Area covered
    Description

    This data is deprecated. Please visit https://data.mfe.govt.nz/layer/117733 for the latest version.

    The LUCAS NZ Land Use Map 2016 v011 is composed of New Zealand-wide land use classifications (12) nominally at 1 January 1990, 1 January 2008, 31 December 2012 and 31 December 2016 (known as "1990", "2008", "2012" and "2016"). These date boundaries were dictated by the First and Second Commitment Periods of the Kyoto Protocol. The layer can therefore be used to create either a 1990, 2008, 2012 or 2016 land use map depending on what field is symbolised.

  2. M

    LUCAS NZ Land Use Map 2020 v005

    • data.mfe.govt.nz
    csv, dwg, geodatabase +6
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    Ministry for the Environment, LUCAS NZ Land Use Map 2020 v005 [Dataset]. https://data.mfe.govt.nz/layer/117733-lucas-nz-land-use-map-2020-v005/
    Explore at:
    mapinfo tab, pdf, kml, csv, dwg, mapinfo mif, geodatabase, shapefile, geopackage / sqliteAvailable download formats
    Dataset authored and provided by
    Ministry for the Environment
    License

    https://data.mfe.govt.nz/license/attribution-4-0-international/https://data.mfe.govt.nz/license/attribution-4-0-international/

    Area covered
    Description

    The LUCAS NZ Land Use Map 2020 v005 is composed of New Zealand-wide land use classes (12) nominally at 31 December 1989, 31 December 2007, 31 December 2012, 31 December 2016, and 31 December 2020. These date boundaries are dictated by the Paris Agreement and former Kyoto Protocol. The data can therefore be used to create a map at any of the nominal mapping dates depending on what field is symbolised.

    Land use areas and areas of land-use change, identified in the LUCAS NZ Land Use Map, are used to calculate greenhouse gas emissions and removals for the Land Use, Land Use Change and Forestry (LULUCF) sector of New Zealand’s annual Greenhouse Gas Inventory and the Biennial Transparency Report. These reports are submitted to meet New Zealand’s reporting and accounting obligations under the United Nations Framework Convention on Climate Change (UNFCCC) and the Paris Agreement.

  3. M

    LUCAS NZ Forest LiDAR Footprints

    • data.mfe.govt.nz
    csv, dwg, geodatabase +6
    Updated Sep 11, 2017
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    Ministry for the Environment (2017). LUCAS NZ Forest LiDAR Footprints [Dataset]. https://data.mfe.govt.nz/layer/88106-lucas-nz-forest-lidar-footprints/
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    shapefile, dwg, geodatabase, mapinfo mif, csv, pdf, kml, mapinfo tab, geopackage / sqliteAvailable download formats
    Dataset updated
    Sep 11, 2017
    Dataset authored and provided by
    Ministry for the Environment
    License

    https://data.mfe.govt.nz/license/attribution-3-0-new-zealand/https://data.mfe.govt.nz/license/attribution-3-0-new-zealand/

    Area covered
    Description

    Note: Metadata relates to LiDAR point clouds. This layer has been provided to enable users to explore coverage and capture dates of the LiDAR. To enquire about ordering the LiDAR and/or related orthophotography, please e-mail lucas[at]mfe.govt.nz.

    Ministry for the Environment, Land Use Carbon Analysis System collection of swaths of LiDAR over planted forests of interest (raw and classified returns) from 2006 to 2015.

  4. Continental Europe land cover mapping at 30m resolution based CORINE and...

    • zenodo.org
    bin, png, tiff
    Updated Jul 19, 2024
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    Leandro Parente; Leandro Parente; Martijn Witjes; Tomislav Hengl; Tomislav Hengl; Martin Landa; Lukas Brodsky; Martijn Witjes; Martin Landa; Lukas Brodsky (2024). Continental Europe land cover mapping at 30m resolution based CORINE and LUCAS on samples [Dataset]. http://doi.org/10.5281/zenodo.4725429
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    bin, tiff, pngAvailable download formats
    Dataset updated
    Jul 19, 2024
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Leandro Parente; Leandro Parente; Martijn Witjes; Tomislav Hengl; Tomislav Hengl; Martin Landa; Lukas Brodsky; Martijn Witjes; Martin Landa; Lukas Brodsky
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Continental Europe
    Description

    Annual land cover mapping for continental Europe based on Ensemble Machine Learning (EML), samples obtained from LUCAS (Land Use and Coverage Area frame Survey) and CLC (CORINE Land Cover) Maps, and several harmonized raster layers (e.g. GLAD Landsat ARD imagery and Continental EU DTM). The EML predicted the dominant land cover, probabilities and uncertainties for 33 classes compatible with CLC over 20 years (2000–2019), and was implemented in R and Python (eumap library).

    The raster layers were mainly composed by the GLAD Landsat ARD imagery, which were downloaded for the years 1999 to 2020 considering the Continental Europe extent (land mask area and tiling system), screened to reduce cloud cover (GLAD quality assessment band), aggregated by season according with three different quantiles (i.e. 25th, 50th and 75th), and gap-filled using the Temporal Moving Window Median approach available in the eumap library. The images for each season were selected using the same calendar dates for all period:

    • Winter: December 2 of previous year until March 20 of current year
    • Spring: March 21 until June 24 of current year
    • Summer: June 25 until September 12 of current year
    • Fall: September 13 until December 1 of current year

    In addition to Landsat spectral data, the EML considered night lights (VIIRS/SUOMI NPP), Global surface water frequency, Continental EU DTM, Landsat spectral indices (SAVI, NDVI, NBR, NBR2, REI and NDWI) and the max/min. monthly geometric temperature, estimated on a pixel basis and for each month.

    The training data were obtained from the geographic location of LUCAS (in-situ source) and the centroid of all polygons of CORINE (supplementary source), harmonized according to the 33 CLC and organized by year, where each unique combination of longitude, latitude and year was treated as a independent sample with the following classes (the class descriptions are here):

    • 111: Urban fabric
    • 122: Road and rail networks and associated land
    • 123: Port areas
    • 124: Airports
    • 131: Mineral extraction sites
    • 132: Dump sites
    • 133: Construction sites
    • 141: Green urban areas
    • 211: Non-irrigated arable land
    • 212: Permanently irrigated arable land
    • 213: Rice fields
    • 221: Vineyards
    • 222: Fruit trees and berry plantations
    • 223: Olive groves
    • 231: Pastures
    • 311: Broad-leaved forest
    • 312: Coniferous forest
    • 321: Natural grasslands
    • 322: Moors and heathland
    • 323: Sclerophyllous vegetation
    • 324: Transitional woodland-shrub
    • 331: Beaches, dunes, sands
    • 332: Bare rocks
    • 333: Sparsely vegetated areas
    • 334: Burnt areas
    • 335: Glaciers and perpetual snow
    • 411: Inland wetlands
    • 421: Maritime wetlands
    • 511: Water courses
    • 512: Water bodies
    • 521: Coastal lagoons
    • 522: Estuaries
    • 523: Sea and ocean

    The LUCAS points with a unique land cover class received a confidence rating of 100%, while CORINE points received 85%, values which were considered by EML as sample weight in the training phase. The points were used in a spacetime overlay approach, which considered the location and the year to retrieve the pixel values of all rasters. Some specific land cover samples (i.e. 111, 122, 131, 141, 211, 221, 222, 223, 231, 311, 312, 321, 411, 512) were screened according to convergence with pre-existing mapping products (OSM roads, OSM railways and Copernicus-OSM buildings; Copernicus high resolution layers), where, for example, “111: Urban fabric” samples located in low density building areas (> 50% according to Copernicus-OSM building layer) were removed from the final training data ( ~5.3 million samples and 178 covariates/features).

    Using this training data, three ML models were trained to predict probabilities (i.e. Random Forest, XGBoost, Artificial Neural Network), which served as input to train a linear meta-model (i.e. Logistic regression classifier), responsable for predicting the final land cover probabilities of all classes. The hyperparameter optimization was conducted using a 5-fold spatial cross validation, based on a 30x30km tilling system. The uncertainties were calculated for all classes according to the standard deviation of the three predicted probabilities for each pixel, and the highest probability was selected as the dominant land cover class, resulting in 20 annual maps for continental Europe.

    The training samples, covariates/features and fitted models are available through lcv_landcover.hcl_lucas.corine.eml_p_landmapper_full.lz4, a LandMapper class instance that can be loaded by eumap library (check the code demonstration). The production code used to generate the current version of the annual land cover maps is available in the spatial layer repository and considered a lighter LandMapper class instance (lcv_landcover.hcl_lucas.corine.eml_p_landmapper_light.lz4,), which not includes the training samples.

    Only the dominant land cover classes are provided here. To access the probabilities and uncertainties use:

    A publication describing, in detail, all processing steps, accuracy assessment and general analysis of land-cover changes in continental Europe is under preparation. To suggest any improvement/fix use https://gitlab.com/geoharmonizer_inea/spatial-layers/-/issues

  5. g

    Digital Geologic-GIS Map of the Lucas Quadrangle, Kentucky (NPS, GRD, GRI,...

    • gimi9.com
    Updated Jul 1, 2024
    + more versions
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    (2024). Digital Geologic-GIS Map of the Lucas Quadrangle, Kentucky (NPS, GRD, GRI, MACA, LUCA digital map) adapted from a U.S. Geological Survey Geologic Quadrangle Map by Haynes (1963) | gimi9.com [Dataset]. https://gimi9.com/dataset/data-gov_digital-geologic-gis-map-of-the-lucas-quadrangle-kentucky-nps-grd-gri-maca-luca-digital-ma/
    Explore at:
    Dataset updated
    Jul 1, 2024
    Description

    The Digital Geologic Map of the Lucas quadrangle, Kentucky is composed of GIS data layers, two ancillary GIS tables, a Windows Help File with ancillary map text, figures and tables, GIS data layer and table FGDC metadata and ArcMap 9.1 layer (.LYR) files. The data were completed as a component of the Geologic Resources Evaluation (GRE) program, a National Park Service (NPS) Inventory and Monitoring (I&M) funded program that is administered by the NPS Geologic Resources Division (GRD). All GIS and ancillary tables were produced as per the NPS GRE Geology-GIS Geodatabase Data Model v. 1.4. (available at: http://science.nature.nps.gov/im/inventory/geology/GeologyGISDataModel.cfm). The GIS data is available as a 9.1 personal geodatabase (luca_geology.mdb), as coverage and table export (.E00) files, and as a shapefile (.SHP) and DBASEIV (.DBF) table files. The GIS data projection is NAD83, UTM Zone 16N. That data is within the area of interest of Mammoth Cave National Park.

  6. M

    LUCAS NZ Forest Clearing 2008 2022 v022

    • data.mfe.govt.nz
    csv, dwg, geodatabase +6
    Updated Apr 17, 2019
    + more versions
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    Ministry for the Environment (2019). LUCAS NZ Forest Clearing 2008 2022 v022 [Dataset]. https://data.mfe.govt.nz/layer/99909-lucas-nz-forest-clearing-2008-2022-v022/
    Explore at:
    mapinfo tab, geopackage / sqlite, geodatabase, mapinfo mif, dwg, shapefile, csv, pdf, kmlAvailable download formats
    Dataset updated
    Apr 17, 2019
    Dataset authored and provided by
    Ministry for the Environment
    License

    https://data.mfe.govt.nz/license/attribution-4-0-international/https://data.mfe.govt.nz/license/attribution-4-0-international/

    Area covered
    Description

    Areas of LUCAS LUM forests that have been cleared between 2008 and 2022 inclusive. Forest clearing is detected using mosaics of satellite imagery captured over a range of dates; therefore the year of clearing provided is nominal.

  7. M

    LUCAS Chatham Islands Land Use Map 2020 v001

    • data.mfe.govt.nz
    csv, dwg, geodatabase +6
    Updated May 3, 2024
    + more versions
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    Ministry for the Environment (2024). LUCAS Chatham Islands Land Use Map 2020 v001 [Dataset]. https://data.mfe.govt.nz/layer/118263-lucas-chatham-islands-land-use-map-2020-v001/
    Explore at:
    geodatabase, mapinfo mif, shapefile, csv, pdf, geopackage / sqlite, kml, mapinfo tab, dwgAvailable download formats
    Dataset updated
    May 3, 2024
    Dataset authored and provided by
    Ministry for the Environment
    License

    https://data.mfe.govt.nz/license/attribution-4-0-international/https://data.mfe.govt.nz/license/attribution-4-0-international/

    Area covered
    Description

    The LUCAS Chatham Islands Land Use Map 2020 v001 is composed of New Zealand-wide land use classes (12) nominally at 31 December 1989, 31 December 2007, 31 December 2012, 31 December 2016, and 31 December 2020. These date boundaries are dictated by the Paris Agreement and former Kyoto Protocol. The data can therefore be used to create a map at any of the nominal mapping dates depending on what field is symbolised.

  8. K

    Lucas County, Ohio Right of Way

    • koordinates.com
    csv, dwg, geodatabase +6
    Updated Apr 11, 2019
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    Lucas County, Ohio (2019). Lucas County, Ohio Right of Way [Dataset]. https://koordinates.com/layer/99849-lucas-county-ohio-right-of-way/
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    mapinfo tab, pdf, csv, kml, dwg, mapinfo mif, geodatabase, shapefile, geopackage / sqliteAvailable download formats
    Dataset updated
    Apr 11, 2019
    Dataset authored and provided by
    Lucas County, Ohio
    Area covered
    Description

    Right of Way data from Lucas County, Ohio

  9. K

    Lucas County, Ohio Soils (NRCS)

    • koordinates.com
    csv, dwg, geodatabase +6
    Updated Apr 11, 2019
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    Lucas County, Ohio (2019). Lucas County, Ohio Soils (NRCS) [Dataset]. https://koordinates.com/layer/99850-lucas-county-ohio-soils-nrcs/
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    mapinfo tab, geodatabase, dwg, csv, kml, pdf, mapinfo mif, geopackage / sqlite, shapefileAvailable download formats
    Dataset updated
    Apr 11, 2019
    Dataset authored and provided by
    Lucas County, Ohio
    Area covered
    Description

    Geospatial data about Lucas County, Ohio Soils (NRCS). Export to CAD, GIS, PDF, CSV and access via API.

  10. Multi-year harmonized land cover samples based on LUCAS and CORINE datasets

    • zenodo.org
    application/gzip, bin +1
    Updated Jul 19, 2024
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    Martin Landa; Lukas Brodsky; Leandro Parente; Leandro Parente; Martijn Witjes; Tomislav Hengl; Tomislav Hengl; Martin Landa; Lukas Brodsky; Martijn Witjes (2024). Multi-year harmonized land cover samples based on LUCAS and CORINE datasets [Dataset]. http://doi.org/10.5281/zenodo.4740691
    Explore at:
    bin, png, application/gzipAvailable download formats
    Dataset updated
    Jul 19, 2024
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Martin Landa; Lukas Brodsky; Leandro Parente; Leandro Parente; Martijn Witjes; Tomislav Hengl; Tomislav Hengl; Martin Landa; Lukas Brodsky; Martijn Witjes
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Harmonized training samples based on LUCAS (Land Use and Coverage Area frame Survey) and CLC (CORINE Land Cover) Maps, according to the following classes:

    • 111 - Urban fabric: the aggregated continuous and discontinuous urban fabric class is classified when urban structures are dominating the surface area. The impermeable features like buildings and artificially surfaced areas range from 30 to 100% land coverage.
    • 122 - Road and rail networks and associated land: motorways and railways, including associated installations.
    • 123 - Port areas: infrastructure of port areas, including quays, dockyards and marinas.
    • 124 - Airports: airports installations as runways, buildings and associated land.
    • 131 - Mineral extraction sites: areas of open-pit extraction of construction materials (sandpits, quarries) or other minerals (open-cast mines).
    • 132 - Dump sites: public, industrial or mine dump sites.
    • 133 - Construction sites: spaces under construction development, soil or bedrock excavations, earthworks.
    • 141 - Green urban areas: areas with vegetation within urban fabric.
    • 211 - Non-irrigated arable land: cultivated land parcels under rain-fed agricultural use for annually harvested non-permanent crops, normally under a crop rotation system.
    • 212 - Permanently irrigated arable land: cultivated land parcels under agricultural use for arable crops that are permanently or periodically irrigated, using a permanent infrastructure (irrigation channels, drainage network and additional irrigation facilities).
    • 213 - Rice fields: cultivated land parcels prepared for rice production, consisting of periodically flooded flat surfaces with irrigation channels.
    • 221 - Vineyards: areas planted with vines.
    • 222 - Fruit trees and berry plantations: cultivated parcels planted with fruit trees and shrubs, including nuts, intended for fruit production.
    • 223 - Olive groves: cultivated areas planted with olive trees, including mixed occurrence of vines on the same parcel.
    • 231 - Pastures: meadows where dispersed trees and shrubs may occupy up to 50% of surface. These meadows are characterized by rich floristic composition.
    • 311 - Broad-leaved forest: vegetation formation composed principally of trees, including shrub and bush understorey, where broad-leaved species predominate.
    • 312 - Coniferous forest: vegetation formation composed principally of trees, including shrub and bush understorey, where coniferous species predominate.
    • 321 - Natural grasslands: grasslands under no or moderate human influence. Low productivity grasslands. Often situated in areas of rough, uneven ground, frequently include rocky areas, or patches of other (semi-)natural vegetation.
    • 322 - Moors and heathland: vegetation with low and closed cover, dominated by bushes, shrubs (heather, briars, broom, gorse, laburnum, etc.
    • 323 - Sclerophyllous vegetation: bushy sclerophyllous vegetation in a climax stage of development, including maquis, matorral and garrigue.
    • 324 - Transitional woodland-shrub: transitional bushy and herbaceous vegetation with occasional scattered trees. Can represent either woodland degradation or forest regeneration / re-colonization
    • 331 - Beaches, dunes, sands: unvegetated expanses of sand or pebble/gravel, in coastal or continental locations, like beaches, dunes, gravel pads.
    • 332 - Bare rocks: scree, cliffs, rock outcrops, including areas of active erosion.
    • 333 - Sparsely vegetated areas: Areas with sparse vegetation, covering 10-50% of the surface.
    • 334 - Burnt areas: Areas affected by recent fires.
    • 335 - Glaciers and perpetual snow: Land covered by ice or permanent snowfields
    • 411 - Inland wetlands: low-lying land usually flooded in winter, and more or less saturated by water all year round; and wetlands with accumulation of considerable amount of decomposed moss and vegetation matter.
    • 421 - Maritime wetlands: vegetated low-lying areas in the coastal zone, above the high-tide line, susceptible to flooding by seawater; salt-pans for extraction of salt from salt water; and coastal zones under tidal influence between open sea and land.
    • 511 - Water courses: natural or artificial water courses serving as water drainage channels
    • 512 - Water bodies: natural or artificial water surfaces covered by standing water most of the year
    • 521 - Coastal lagoons: stretches of salt or brackish water in coastal areas which are separated from the sea by a tongue of land or other similar topography
    • 522 - Estuaries: the mouth of a river under tidal influence within which the tide ebbs and flows.
    • 523 - Sea and ocean: zone seaward of the lowest tide limit.

    The samples were obtained from the geographic location of LUCAS (in-situ source) and the centroid of all polygons from CLC maps, harmonized according to the above classes and organized by year, where each unique combination of longitude, latitude and year was considered as a independent sample. Some specific CORINE samples (i.e. 111, 122, 131, 141, 211, 221, 222, 223, 231, 311, 312, 321, 411, 512) were filtered according to convergence with existing mapping products (OSM roads, railways and buildings; Copernicus High-Res. Layers - HRL), where, for example, “111 - Urban fabric” samples located in low density building areas (> 50% according to Copernicus-OSM building layer) were removed. The LUCAS points with a unique land-cover class received a confidence rating of 100%, while CORINE received 85%. Using these filtered samples a spacetime overlay was performed (check the code demonstration in eumap library) considering several raster layers for Continental Europe: four season quantiles for GLAD Landsat ARD (spectral bands and indices - Potapov, 2020), DTM-based elevation and slope (Hengl, 2020), VIIRS/SUOMI NPP night lights (Hillger, 2013), Global surface water frequency (Pekel, 2016), and geometric minimum and maximum temperature derived according to Kilibarda, 2014.

    The provided samples has 5,362,229 rows and 263 columns, including the geographic location, the metadata of land cover harmonization, the mapped classes according to OSM and HRL, and the result of the spacetime overlay (178 covariates).

    Use the following Python/R code to open the files lcv_landcover.hcl_lucas.corine_harm.samples.overlaid.*

    import joblib
    samples = joblib.load('lcv_landcover.hcl_lucas.corine_harm.samples.overlaid')
    readRDS('lcv_landcover.hcl_lucas.corine_harm.samples.overlaid.rds')

    These samples were used to train a spatiotemporal model, which predicts the land cover for continental Europe over 20 years (2000 - 2019). To access the predictions results (dominant class, probabilities and uncertainties) use the following services:

    A publication describing, in detail, all processing steps, accuracy assessment and general analysis of land-cover changes in continental Europe is under preparation. To suggest any improvement/fix use https://gitlab.com/geoharmonizer_inea/spatial-layers/-/issues

  11. K

    Lucas County, Ohio Historical Lot Lines

    • koordinates.com
    csv, dwg, geodatabase +6
    Updated Apr 11, 2019
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    Lucas County, Ohio (2019). Lucas County, Ohio Historical Lot Lines [Dataset]. https://koordinates.com/layer/99844-lucas-county-ohio-historical-lot-lines/
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    pdf, geopackage / sqlite, csv, dwg, geodatabase, mapinfo mif, shapefile, kml, mapinfo tabAvailable download formats
    Dataset updated
    Apr 11, 2019
    Dataset authored and provided by
    Lucas County, Ohio
    Area covered
    Description

    Historical Lot Lines data for Lucas County, Ohio.

  12. M

    LUCAS Chatham Islands Land Use Map 1990 2008 2012 2016 v002 DEPRECATED

    • data.mfe.govt.nz
    csv, dwg, geodatabase +6
    Updated Apr 15, 2019
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    Ministry for the Environment (2019). LUCAS Chatham Islands Land Use Map 1990 2008 2012 2016 v002 DEPRECATED [Dataset]. https://data.mfe.govt.nz/layer/99857-lucas-chatham-islands-land-use-map-1990-2008-2012-2016-v002-deprecated/
    Explore at:
    mapinfo mif, geodatabase, dwg, geopackage / sqlite, kml, mapinfo tab, pdf, csv, shapefileAvailable download formats
    Dataset updated
    Apr 15, 2019
    Dataset authored and provided by
    Ministry for the Environment
    License

    https://data.mfe.govt.nz/license/attribution-4-0-international/https://data.mfe.govt.nz/license/attribution-4-0-international/

    Area covered
    Description

    This data is deprecated. Please visit https://data.mfe.govt.nz/layer/118263 for the latest version.

    The Chatham Islands Land Use Map is composed of 12 land use classifications nominally at 1 January 1990, 1 January 2008, 31 December 2012 and 31 December 2016 (known as "1990", "2008", "2012" and "2016") and was created using broadly the same methodology as was used for mainland LUCAS NZ LUM 2016. These date boundaries were dictated by the First and Second Commitment Periods of the Kyoto Protocol. The layer can therefore be used to create either a 1990, 2008, 2012 or 2016 land use map depending on what field is symbolised.

  13. a

    Jurisdictions

    • hub.arcgis.com
    Updated Feb 11, 2025
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    JasonClay (2025). Jurisdictions [Dataset]. https://hub.arcgis.com/datasets/e6661515aaf341569502af43ae08cb20
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    Dataset updated
    Feb 11, 2025
    Dataset authored and provided by
    JasonClay
    Area covered
    Description

    Tax DuplicateItems in the Tax Duplicate are from the CADASTRE dataset and are exclusively maintained by the Lucas County Engineer’s Tax Map Department, and hosted by the Lucas County Auditor's Office GIS Department.The Cadastre dataset contains three polygon layers, one polyline layer, and sixteen annotation layers.Lucas County Engineers Tax Map Department maintains the tax maps and parcel mapping portion of the county's GIS. They review all legal descriptions before transfers are made and assign street numbers for addresses in the County outside of city limits.Cadastre Parcels are identified by Assessor number, which is a unique land identifier. Road Centerlines are provided by Lucas County EMA/911Inquiries about cadastral data should be directed to Shawn Shaffer, Engineer's Tax Map Department at 419-213-4658.Inquiries regarding the map and feature services should be directed to Jason Clay, Auditor's GIS Department at 419-213-2110.Inquiries regarding Road Centerlines should be directed to Greg Bonfiglio, Lucas County 911 Regional Council of Governments, 419-720-0275

  14. W

    Soil Survey Geographic (SSURGO) database for Lucas County, Ohio

    • cloud.csiss.gmu.edu
    Updated Mar 6, 2021
    + more versions
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    United States (2021). Soil Survey Geographic (SSURGO) database for Lucas County, Ohio [Dataset]. https://cloud.csiss.gmu.edu/uddi/dataset/soil-survey-geographic-ssurgo-database-for-lucas-county-ohio
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    Dataset updated
    Mar 6, 2021
    Dataset provided by
    United States
    Area covered
    Lucas County, Ohio
    Description

    This data set is a digital soil survey and generally is the most detailed level of soil geographic data developed by the National Cooperative Soil Survey. The information was prepared by digitizing maps, by compiling information onto a planimetric correct base and digitizing, or by revising digitized maps using remotely sensed and other information. This data set consists of georeferenced digital map data and computerized attribute data. The map data are in a soil survey area extent format and include a detailed, field verified inventory of soils and miscellaneous areas that normally occur in a repeatable pattern on the landscape and that can be cartographically shown at the scale mapped. A special soil features layer (point and line features) is optional. This layer displays the location of features too small to delineate at the mapping scale, but they are large enough and contrasting enough to significantly influence use and management. The soil map units are linked to attributes in the National Soil Information System relational database, which gives the proportionate extent of the component soils and their properties.

  15. K

    Lucas County, Ohio Census Tracts

    • koordinates.com
    csv, dwg, geodatabase +6
    Updated Apr 11, 2019
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    Lucas County, Ohio (2019). Lucas County, Ohio Census Tracts [Dataset]. https://koordinates.com/layer/99834-lucas-county-ohio-census-tracts/
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    pdf, csv, mapinfo tab, kml, shapefile, geodatabase, mapinfo mif, dwg, geopackage / sqliteAvailable download formats
    Dataset updated
    Apr 11, 2019
    Dataset authored and provided by
    Lucas County, Ohio
    Area covered
    Description

    Geospatial data about Lucas County, Ohio Census Tracts. Export to CAD, GIS, PDF, CSV and access via API.

  16. K

    Lucas County, Ohio Waterlines

    • koordinates.com
    csv, dwg, geodatabase +6
    Updated Apr 11, 2019
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    Lucas County, Ohio (2019). Lucas County, Ohio Waterlines [Dataset]. https://koordinates.com/layer/99852-lucas-county-ohio-waterlines/
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    geodatabase, shapefile, mapinfo tab, geopackage / sqlite, dwg, csv, kml, mapinfo mif, pdfAvailable download formats
    Dataset updated
    Apr 11, 2019
    Dataset authored and provided by
    Lucas County, Ohio
    Area covered
    Description

    Geospatial data about Lucas County, Ohio Waterlines. Export to CAD, GIS, PDF, CSV and access via API.

  17. K

    Lucas County, Ohio High School Areas

    • koordinates.com
    csv, dwg, geodatabase +6
    Updated Apr 11, 2019
    + more versions
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    Lucas County, Ohio (2019). Lucas County, Ohio High School Areas [Dataset]. https://koordinates.com/layer/99843-lucas-county-ohio-high-school-areas/
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    geopackage / sqlite, shapefile, pdf, geodatabase, mapinfo tab, kml, csv, dwg, mapinfo mifAvailable download formats
    Dataset updated
    Apr 11, 2019
    Dataset authored and provided by
    Lucas County, Ohio
    Area covered
    Description

    Geospatial data about Lucas County, Ohio High School Areas. Export to CAD, GIS, PDF, CSV and access via API.

  18. z

    EJP Soil double sampling study (Task 6.3): physicochemical soil data of 166...

    • zenodo.org
    • data.europa.eu
    csv
    Updated Apr 2, 2025
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    Bruno De Vos; Bruno De Vos (2025). EJP Soil double sampling study (Task 6.3): physicochemical soil data of 166 Belgian LUCAS 2022 sampling points [Dataset]. http://doi.org/10.5281/zenodo.15114209
    Explore at:
    csvAvailable download formats
    Dataset updated
    Apr 2, 2025
    Dataset provided by
    Research Institute for Nature and Forest (INBO)
    Authors
    Bruno De Vos; Bruno De Vos
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    May 23, 2023
    Area covered
    Belgium
    Description

    EJP Soil Double Sampling Study: physicochemical data Flanders (Belgium)

    During the elaboration of EJP Soil deliverable 6.3 of Work Package 6, entitled ‘Proposal of methodological development for the LUCAS programme in accordance with national monitoring programmes’ (Bispo et al., 2021), a large majority of partners (23) suggested to launch a double sampling study by collecting national soil samples on LUCAS points to compare LUCAS and National design strategies and sampling and analytical protocols.

    For Flanders region, we conducted a double-double sampling study on 166 LUCAS points that were selected as representative for cropland, grassland and woodland soils.

    Each of these LUCAS points were sampled according to the LUCAS sampling scheme and the national (Cmon) scheme by our national surveyors (double sampling type 1) , and sampled by LUCAS surveyors (COBA group) for analysis by the LUCAS central lab so that also the laboratory results could be compared for the LUCAS 2022 campaign (double sampling type 2).

    The LUCAS 2022 campaign selected also for Belgium 11 LUCAS Biopoints: 5 in Flanders, 1 in Brussels region and 5 in Wallonia. At the EJP National HUB we agreed to sample all 11 Belgian biopoints both for physico-chemical soil properties (this study) as for soil biodiversity assessment through eDNA metabarcoding (Lambrechts et al., 2025).

    The dataset comprises 3 CSV files: (1) list of sampling points with LUCAS pointID, coordinates and metadata, (2) the physico-chemical soil data of each point according to the LUCAS and Cmon sampling scheme, (3) the soil bulk density data according to the Cmon sampling scheme.

    Samples were collected between 15 June 2022 and 23 May 2023.

    Variables and units

    VariableDescriptionUnitMethod
    ThicknessLayer thicknesscm
    DepthDepth of layer (negative for forest floor)cm
    SandSand fraction by Laser Diffraction (LD)vol%ISO11277 & ISO13320
    SiltSilt fraction by LDvol%ISO11277 & ISO13320
    ClayClay fraction by LDvol%ISO11277 & ISO13320
    TCTotal carbong/kgISO 10694
    TICTotal inorganic carbong/kgISO 10694
    TOCTotal organic carbon (TC-TIC)g/kgISO 10694
    TNTotal nitrogeng/kgISO 13878
    pH_KCl_v_vpH KCl 1:5 v/v-ISO 10390
    EC_m_vElectric conductivity m/vµS/cmISO 11265
    EC_v_vElectric conductivity v/vµS/cmISO 11265
    pH_H20_m_vpH H2O 1:5 m/v-ISO 10390
    pH_H20_v_vpH H2O 1:5 v/v-ISO 10390
    pH_KCl_v_vpH KCl 1:5 v/v-ISO 10390
    pH_CaCl2_m_vpH CaCl2 1:5 m/v-ISO 10390
    pH_CaCl2_v_vpH CaCl2 1:5 v/v-ISO 10390
    BD_meanBulk density mean of 4 repg/cm³ISO 11272
    BD_sdBulk density stdev of 4 repg/cm³
    BD_CVBulk density CV of 4 repg/cm³
    SWC_volp_meanVolumetric moisture content mean of 4 repvol%
    SWC_volp_sdVolumetric moisture content sd of 4 repvol%

    The data are evaluated in the report: De Vos, B. & Lambrechts, S. 2025. Comparing LUCAS and Cmon sampling schemes and survey data on 166 LUCAS 2022 points in Flanders, Belgium. EJP Soil Deliverable 6.3. Horizon 2020 EJP Soil grant agreement 862695. (to be published on Zenodo after Embargo period of 6 months).

  19. K

    Lucas County, Ohio Water Course - Major ditch

    • koordinates.com
    csv, dwg, geodatabase +6
    Updated Apr 11, 2019
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    Lucas County, Ohio (2019). Lucas County, Ohio Water Course - Major ditch [Dataset]. https://koordinates.com/layer/99821-lucas-county-ohio-water-course-major-ditch/
    Explore at:
    dwg, mapinfo tab, geopackage / sqlite, pdf, mapinfo mif, kml, csv, geodatabase, shapefileAvailable download formats
    Dataset updated
    Apr 11, 2019
    Dataset authored and provided by
    Lucas County, Ohio
    Area covered
    Description

    Geospatial data about Lucas County, Ohio Water Course - Major ditch. Export to CAD, GIS, PDF, CSV and access via API.

  20. OEMC Hackathon 2023: EU Land Cover Classification Dataset

    • zenodo.org
    • data.niaid.nih.gov
    • +1more
    application/gzip, csv +1
    Updated Jul 11, 2024
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    Leandro Parente; Leandro Parente; Martijn Witjes; Martijn Witjes; Hengl Tomislav; Hengl Tomislav (2024). OEMC Hackathon 2023: EU Land Cover Classification Dataset [Dataset]. http://doi.org/10.5281/zenodo.8306554
    Explore at:
    application/gzip, png, csvAvailable download formats
    Dataset updated
    Jul 11, 2024
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Leandro Parente; Leandro Parente; Martijn Witjes; Martijn Witjes; Hengl Tomislav; Hengl Tomislav
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Dataset organized by the Open-Earth-Monitor (OEMC) project within the context of Hackathon 2023.

    The dataset (both train and test) was produced by stratified sampling of the ground-truth data provided by LUCAS Survey, funded by the European Commission. The target land cover considered level-3 classes from the harmonized legend, resulting in 72 classes distributed over 5 years (2006, 2009, 2012, 2015, 2018):

    All samples were overlaid with 416 raster spatial layers, including satellite (spectral bands and indices) and temperature images (land surface temperature), climate images (precipitation, air temperature), accessibility and distance maps (highways, water bodies, burned areas), digital terrain model (slope and elevation) and other existing maps (population count and snow covering). The result values were organized in columns, one for each spatial layers, which combined represent the feature space available for ML modeling.

    Column names:

    The columns are formed by six metadata fields separated by _:

    • Example: red_landsat.glad.ard_p50_30m_jun25_sep12
    • Metadata fields:
      • F1 - Variable name: red
      • F2 - Variable procedure including product name: landsat.glad.ard
      • F3 - Position in the probability distribution: p50
      • F4 - Spatial resolution: 30m
      • F5 - Start date: jun25
      • F6 - End date: sep12

    Column description:

    All the columns can be aggregated in six thematic groups according to F1 and F2:

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Ministry for the Environment (2012). LUCAS NZ Land Use Map 1990 2008 2012 2016 v011 DEPRECATED [Dataset]. https://data.mfe.govt.nz/layer/52375-lucas-nz-land-use-map-1990-2008-2012-2016-v011-deprecated/

LUCAS NZ Land Use Map 1990 2008 2012 2016 v011 DEPRECATED

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geopackage / sqlite, pdf, mapinfo tab, shapefile, kml, mapinfo mif, dwg, csv, geodatabaseAvailable download formats
Dataset updated
Jul 22, 2012
Dataset authored and provided by
Ministry for the Environment
License

https://data.mfe.govt.nz/license/attribution-4-0-international/https://data.mfe.govt.nz/license/attribution-4-0-international/

Area covered
Description

This data is deprecated. Please visit https://data.mfe.govt.nz/layer/117733 for the latest version.

The LUCAS NZ Land Use Map 2016 v011 is composed of New Zealand-wide land use classifications (12) nominally at 1 January 1990, 1 January 2008, 31 December 2012 and 31 December 2016 (known as "1990", "2008", "2012" and "2016"). These date boundaries were dictated by the First and Second Commitment Periods of the Kyoto Protocol. The layer can therefore be used to create either a 1990, 2008, 2012 or 2016 land use map depending on what field is symbolised.

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