82 datasets found
  1. g

    Colombia Shapefile

    • geopostcodes.com
    shp
    Updated May 28, 2025
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    GeoPostcodes (2025). Colombia Shapefile [Dataset]. https://www.geopostcodes.com/country/colombia-shapefile
    Explore at:
    shpAvailable download formats
    Dataset updated
    May 28, 2025
    Dataset authored and provided by
    GeoPostcodes
    Area covered
    Colombia
    Description

    Download high-quality, up-to-date Colombia shapefile boundaries (SHP, projection system SRID 4326). Our Colombia Shapefile Database offers comprehensive boundary data for spatial analysis, including administrative areas and geographic boundaries. This dataset contains accurate and up-to-date information on all administrative divisions, zip codes, cities, and geographic boundaries, making it an invaluable resource for various applications such as geographic analysis, map and visualization, reporting and business intelligence (BI), master data management, logistics and supply chain management, and sales and marketing. Our location data packages are available in various formats, including Shapefile, GeoJSON, KML, ASC, DAT, CSV, and GML, optimized for seamless integration with popular systems like Esri ArcGIS, Snowflake, QGIS, and more. Companies choose our location databases for their enterprise-grade service, reduction in integration time and cost by 30%, and weekly updates to ensure the highest quality.

  2. w

    Rivers in Colombia - Dataset - waterdata

    • wbwaterdata.org
    Updated Mar 16, 2020
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    (2020). Rivers in Colombia - Dataset - waterdata [Dataset]. https://wbwaterdata.org/dataset/rivers-colombia
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    Dataset updated
    Mar 16, 2020
    License

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

    Area covered
    Colombia
    Description

    This shapefile contains the rivers in Colombia.

  3. d

    Data from: The Andes of Colombia and Ecuador as a barrier to fern and...

    • search.dataone.org
    • datadryad.org
    Updated Jan 10, 2025
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    Sarah Morris; Robbin Moran (2025). The Andes of Colombia and Ecuador as a barrier to fern and lycophyte species from Mesoamerica [Dataset]. http://doi.org/10.5061/dryad.79cnp5j3v
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    Dataset updated
    Jan 10, 2025
    Dataset provided by
    Dryad Digital Repository
    Authors
    Sarah Morris; Robbin Moran
    Area covered
    Mesoamerica, Ecuador, Andes, Colombia
    Description

    We compiled a list of the fern and lycophyte species that occur in Mesoamerica and extend into Colombia and Ecuador where they are restricted to the western side of the Andes; that is, they only occur west of the crest of the easternmost cordillera and are absent from that cordillera’s eastern slope and in adjacent Amazonia. We found 130 species with this Mesoamerican and west-of-the-eastern-cordillera distribution. Those 130 species constitute 7% of the total 1805 fern and lycophyte species that have been recorded west of the crest of the easternmost cordillera in Colombia and Ecuador. All 130 species had elevation ranges with midpoints lying in low (0–900 m) or middle (900–3000 m) elevations, and none were above 3000 m. This suggests the cordilleras have acted as elevational barriers. We also investigated the blockage of these 130 species by each of the Andean cordilleras. We found that 74 (57%) of the 130 species were limited eastward by the western cordillera, 15 (11%) by the centra..., , , # The Andes of Colombia and Ecuador as a barrier to fern and lycophyte species from Mesoamerica

    https://doi.org/10.5061/dryad.79cnp5j3v

    In this repository are the zipped shapefiles, custom R-script and species lists related to Morris & Moran 2024.Â

    available files:

    •    Zipped shapefiles for Regions A, B, and C of Colombia and Ecuador

    •      R script used to calculate the total number of fern and lycophyte species in Regions A, B, and C

    •      Cleaned list of species present in Regions A, B, and C of Colombia and Ecuador as a .csv

    Description

    total_species_calculation_Morris_Moran_2024.R

    • The R script is linked to the shapefiles.
    • The R script takes a downloaded occurrence dataset from GBIF , cleans the records, and subsets the occurrences using the shapefiles.
    • The working directory in R should contain the shapefiles for the script to work properly. Â

    Polygons A, B, C, and ABC

    • Each...
  4. Cartografía Básica Digital Integrada. República de Colombia.. Escala...

    • metadatos.icde.gov.co
    Updated Sep 10, 2020
    + more versions
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    Instituto Geográfico Agustín Codazzi IGAC - Subdirección de Geografía y Cartografía– Grupo Interno de Trabajo Generación de Datos y Productos Cartográficos (2020). Cartografía Básica Digital Integrada. República de Colombia.. Escala 1:500.000. [Dataset]. https://metadatos.icde.gov.co/geonetwork/srv/api/records/49a90b44-565a-4cfc-bea7-9fd27a419682
    Explore at:
    Dataset updated
    Sep 10, 2020
    Dataset provided by
    Instituto Geográfico Agustín Codazzihttp://www.igac.gov.co/
    Area covered
    Description

    Cartografía vectorial a escala 1:500.000 con cobertura total de la República de Colombia. Contiene información sobre entidades territoriales, transporte terrestre y fluvial, hidrografía, relieve, orografía, construcciones. Referido al sistema de coordenadas MAGNA-SIRGAS, se genera a partir de la interpretación de objetos en una imagen ortorectificada provenientes de plataformas satelitales o aerotransportadas, disponible en los siguientes formatos: Geodatabase , Shapefile, PostGis , GeoPackage y servicios (WMS y WFS).

  5. o

    Shapes por municipios

    • bogota-laburbano.opendatasoft.com
    • redesdevalor-bogota-laburbano.opendatasoft.com
    • +1more
    csv, excel, geojson +1
    Updated Nov 26, 2016
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    (2016). Shapes por municipios [Dataset]. https://bogota-laburbano.opendatasoft.com/explore/dataset/shapes/
    Explore at:
    json, excel, geojson, csvAvailable download formats
    Dataset updated
    Nov 26, 2016
    Description

    Base de datos con los polígonos georeferenciados por municipio.

  6. Capa Digital Curvas de Nivel. República de Colombia. Escala 1:500.000.

    • metadatos.icde.gov.co
    Updated Dec 8, 2020
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    Instituto Geográfico Agustín Codazzi IGAC - Subdirección de Geografía y Cartografía– Grupo Interno de Trabajo Generación de Datos y Productos Cartográficos (2020). Capa Digital Curvas de Nivel. República de Colombia. Escala 1:500.000. [Dataset]. https://metadatos.icde.gov.co/geonetwork/srv/api/records/667a81ca-afab-43bd-9bc1-902c3bcaa958
    Explore at:
    Dataset updated
    Dec 8, 2020
    Dataset provided by
    Instituto Geográfico Agustín Codazzihttp://www.igac.gov.co/
    Area covered
    Description

    La capa digital curvas de nivel a escala 1:500.000, capturada a partir del Modelo Digital de Elevación SRTM 30 metros, con un Intervalo de 100 metros entre curvas, una curva de nivel es una línea imaginaria que une puntos de igual altitud con respecto al de referencia definido por el instituto Geográfico Agustín Codazzi - IGAC, la capa digital curvas de nivel tiene asociado el sistema de referencia MAGNA-SIRGAS, disponible en los formatos: Geodatabase , Shapefile, GeoPackage y servicios (WMS y WFS).

  7. s

    Second-level Administrative Divisions, Colombia, 2015

    • searchworks.stanford.edu
    zip
    Updated May 9, 2024
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    (2024). Second-level Administrative Divisions, Colombia, 2015 [Dataset]. https://searchworks.stanford.edu/view/mj028ht5751
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    zipAvailable download formats
    Dataset updated
    May 9, 2024
    Area covered
    Colombia
    Description

    This polygon shapefile contains the second-level administrative divisions of Colombia (adm2). Level 2 divisions include municipalities. This layer is part of the Global Administrative Areas 2015 (v2.8) dataset.

  8. Colombia mining titles

    • hub.arcgis.com
    Updated Feb 24, 2015
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    Global Forest Watch (2015). Colombia mining titles [Dataset]. https://hub.arcgis.com/datasets/gfw::colombia-mining-titles
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    Dataset updated
    Feb 24, 2015
    Dataset authored and provided by
    Global Forest Watchhttp://www.globalforestwatch.org/
    Area covered
    Description

    This data set provides the boundaries of mining titles (títulos mineros concedidos) for Colombia. The shapefiles are compiled by Tierra Minada, a Colombian civil society group, utilizing information from the Colombian Mining Registry, which is maintained by the National Mining Agency. For more information about the data sets, visit the Tierra Minada website or Colombia’s Mining Cadaster Portal.

  9. e

    Data from: The Tropical Andes Biodiversity Hotspot: A Comprehensive Dataset...

    • knb.ecoinformatics.org
    • dataone.org
    • +2more
    Updated May 30, 2024
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    Pablo Jarrín-V.; Mario H Yánez-Muñoz (2024). The Tropical Andes Biodiversity Hotspot: A Comprehensive Dataset for the Mira-Mataje Binational Basins [Dataset]. http://doi.org/10.5063/F14F1P6H
    Explore at:
    Dataset updated
    May 30, 2024
    Dataset provided by
    Knowledge Network for Biocomplexity
    Authors
    Pablo Jarrín-V.; Mario H Yánez-Muñoz
    Time period covered
    Jun 11, 2022 - Jun 11, 2023
    Area covered
    Description

    We present a flora and fauna dataset for the Mira-Mataje binational basins. This is an area shared between southwestern Colombia and northwestern Ecuador, where both the Chocó and Tropical Andes biodiversity hotspots converge. Information from 120 sources was systematized in the Darwin Core Archive (DwC-A) standard and geospatial vector data format for geographic information systems (GIS) (shapefiles). Sources included natural history museums, published literature, and citizen science repositories across 18 countries. The resulting database has 33,460 records from 5,281 species, of which 1,083 are endemic and 680 threatened. The diversity represented in the dataset is equivalent to 10\% of the total plant species and 26\% of the total terrestrial vertebrate species in the hotspots. It corresponds to 0.07\% of their total area. The dataset can be used to estimate and compare biodiversity patterns with environmental parameters and provide value to ecosystems, ecoregions, and protected areas. The dataset is a baseline for future assessments of biodiversity in the face of environmental degradation, climate change, and accelerated extinction processes. The data has been formally presented in the manuscript entitled "The Tropical Andes Biodiversity Hotspot: A Comprehensive Dataset for the Mira-Mataje Binational Basins" in the journal "Scientific Data". To maintain DOI integrity, this version will not change after publication of the manuscript and therefore we cannot provide further references on volume, issue, and DOI of manuscript publication. - Data format 1: The .rds file extension saves a single object to be read in R and provides better compression, serialization, and integration within the R environment, than simple .csv files. The description of file names is in the original manuscript. -- m_m_flora_2021_voucher_ecuador.rds -- m_m_flora_2021_observation_ecuador.rds -- m_m_flora_2021_total_ecuador.rds -- m_m_fauna_2021_ecuador.rds - Data format 2: The .csv file has been encoded in UTF-8, and is an ASCII file with text separated by commas. The description of file names is in the original manuscript. -- m_m_flora_fauna_2021_all.zip. This file includes all biodiversity datasets. -- m_m_flora_2021_voucher_ecuador.csv -- m_m_flora_2021_observation_ecuador.csv -- m_m_flora_2021_total_ecuador.csv -- m_m_fauna_2021_ecuador.csv - Data format 3: We consolidated a shapefile for the basin containing layers for vegetation ecosystems and the total number of occurrences, species, and endemic and threatened species for each ecosystem. -- biodiversity_measures_mira_mataje.zip. This file includes the .shp file and accessory geomatic files. - A set of 3D shaded-relief map representations of the data in the shapefile can be found at https://doi.org/10.6084/m9.figshare.23499180.v4 Three taxonomic data tables were used in our technical validation of the presented dataset. These three files are: 1) the_catalog_of_life.tsv (Source: Bánki, O. et al. Catalogue of life checklist (version 2024-03-26). https://doi.org/10.48580/dfz8d (2024)) 2) world_checklist_of_vascular_plants_names.csv (we are also including ancillary tables "world_checklist_of_vascular_plants_distribution.csv", and "README_world_checklist_of_vascular_plants_.xlsx") (Source: Govaerts, R., Lughadha, E. N., Black, N., Turner, R. & Paton, A. The World Checklist of Vascular Plants is a continuously updated resource for exploring global plant diversity. Sci. Data 8, 215, 10.1038/s41597-021-00997-6 (2021).) 3) world_flora_online.csv (Source: The World Flora Online Consortium et al. World flora online plant list December 2023, 10.5281/zenodo.10425161 (2023).)

  10. P

    Geolocalización de los depósitos de residuos en Colombia

    • papyrus-datos.co
    application/dbf +4
    Updated Nov 28, 2022
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    Anne Julissa Oduber Peñaloza; Anne Julissa Oduber Peñaloza (2022). Geolocalización de los depósitos de residuos en Colombia [Dataset]. http://doi.org/10.57924/XS1XQB
    Explore at:
    bin(5), application/shp(9340), application/dbf(56560), application/prj(145), application/shx(2740)Available download formats
    Dataset updated
    Nov 28, 2022
    Dataset provided by
    Papyrus
    Authors
    Anne Julissa Oduber Peñaloza; Anne Julissa Oduber Peñaloza
    License

    https://papyrus-datos.co/api/datasets/:persistentId/versions/1.0/customlicense?persistentId=doi:10.57924/XS1XQBhttps://papyrus-datos.co/api/datasets/:persistentId/versions/1.0/customlicense?persistentId=doi:10.57924/XS1XQB

    Area covered
    Colombia
    Description

    Conjunto de datos en formato shapefile de la ubicación de los sitios de disposición final de basura en Colombia Data set in shapefile format of the location of final garbage disposal sites in Colombia

  11. Páramos Delimitados Junio 2020

    • datos.icde.gov.co
    • siac-datosabiertos-mads.hub.arcgis.com
    Updated May 3, 2021
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    Ministerio de Ambiente y Desarrollo Sostenible (2021). Páramos Delimitados Junio 2020 [Dataset]. https://datos.icde.gov.co/datasets/9631ed8c44274baa824e6277276de48f
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    Dataset updated
    May 3, 2021
    Dataset authored and provided by
    Ministerio de Ambiente y Desarrollo Sosteniblehttp://www.minambiente.gov.co/
    Description

    Capa que contiene los limites de los páramos delimitados a Junio de 2020 (escalas 1:25000 y 1:100.000)

  12. Capa Digital Cuerpos de Agua. República de Colombia. Escala 1:100.000.

    • metadatos.icde.gov.co
    Updated Dec 24, 2020
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    Instituto Geográfico Agustín Codazzi IGAC - Subdirección de Geografía y Cartografía– Grupo Interno de Trabajo Generación de Datos y Productos Cartográficos (2020). Capa Digital Cuerpos de Agua. República de Colombia. Escala 1:100.000. [Dataset]. https://metadatos.icde.gov.co/geonetwork/srv/api/records/2ae17c2c-b793-4463-815c-76f36c2564de
    Explore at:
    Dataset updated
    Dec 24, 2020
    Dataset provided by
    Instituto Geográfico Agustín Codazzihttp://www.igac.gov.co/
    Area covered
    Description

    La capa digital Cuerpos de Agua a escala 1:100.000 comprende los objetos geográficos naturales y artificiales que representan la extensión del agua en estado líquido, la capa digital asocia el sistema de referencia MAGNA-SIRGAS, disponible en los formatos: Geodatabase, Shapefile, GeoPackage y servicios (WMS y WFS).

  13. d

    Mineral Resources Data System

    • search.dataone.org
    • data.wu.ac.at
    Updated Oct 29, 2016
    + more versions
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    U.S. Geological Survey (2016). Mineral Resources Data System [Dataset]. https://search.dataone.org/view/3e55bd49-a016-4172-ad78-7292618a08c2
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    Dataset updated
    Oct 29, 2016
    Dataset provided by
    USGS Science Data Catalog
    Authors
    U.S. Geological Survey
    Area covered
    Variables measured
    ORE, REF, ADMIN, MODEL, STATE, COUNTY, DEP_ID, GANGUE, MAS_ID, REGION, and 29 more
    Description

    Mineral resource occurrence data covering the world, most thoroughly within the U.S. This database contains the records previously provided in the Mineral Resource Data System (MRDS) of USGS and the Mineral Availability System/Mineral Industry Locator System (MAS/MILS) originated in the U.S. Bureau of Mines, which is now part of USGS. The MRDS is a large and complex relational database developed over several decades by hundreds of researchers and reporters. While database records describe mineral resources worldwide, the compilation of information was intended to cover the United States completely, and its coverage of resources in other countries is incomplete. The content of MRDS records was drawn from reports previously published or made available to USGS researchers. Some of those original source materials are no longer available. The information contained in MRDS was intended to reflect the reports used as sources and is current only as of the date of those source reports. Consequently MRDS does not reflect up-to-date changes to the operating status of mines, ownership, land status, production figures and estimates of reserves and resources, or the nature, size, and extent of workings. Information on the geological characteristics of the mineral resource are likely to remain correct, but aspects involving human activity are likely to be out of date.

  14. Veredas de Colombia

    • hub.arcgis.com
    • licenciasdecontruccion-gov-esri-co.hub.arcgis.com
    Updated Jul 25, 2016
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    Esri Colombia (2016). Veredas de Colombia [Dataset]. https://hub.arcgis.com/maps/esri-colombia::veredas-de-colombia
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    Dataset updated
    Jul 25, 2016
    Dataset provided by
    Esrihttp://esri.com/
    Authors
    Esri Colombia
    Area covered
    Description

    https://ags.esri.co/server/rest/services/DA_DatosAbiertos/VeredasColombia/MapServer/0Esta capa contienen los limites administrativos a nivel veredal de Colombia, con sus respectivos atributos de identificación. La información ha sido verificada y corregida topológica y atributivamente, puede existir discordancia entre límites municipales y veredales debido a la diferencia de escalas, algunas veredas comparten límites entre dos o más municipios. La información generada en ningún momento será tomada como información oficial del país, tómese como información de referencia.Fuente Geográfica y Atributiva: OCHA Colombia, DANE, Esri Colombia,Unidad para las Víctimas, Defensoría del Pueblo, Departamento para la prosperidad Social, Consejería DDHH Presidencia de la República, Unidad Administrativa para la Consolidación Territorial-UACT , Dirección para la Acción Integral contra Minas, Unidad de Planificación Rural Agropecuaria -UPRA.Año de publicación: 2016.Encuéntrelas también en : http://rni.unidadvictimas.gov.co/node/521Descripcción atributos: https://ags.esri.co/server/rest/services/DA_DatosAbiertos/VeredasColombia/MapServer/0

  15. CMS: Landsat-derived Annual Land Cover Maps for the Colombian Amazon,...

    • daac.ornl.gov
    • s.cnmilf.com
    • +4more
    geotiff
    Updated Sep 17, 2020
    + more versions
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    ARÉVALO, P. (2020). CMS: Landsat-derived Annual Land Cover Maps for the Colombian Amazon, 2001-2016 [Dataset]. http://doi.org/10.3334/ORNLDAAC/1783
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    geotiff(482.3 MB), geotiffAvailable download formats
    Dataset updated
    Sep 17, 2020
    Dataset provided by
    Oak Ridge National Laboratory Distributed Active Archive Center
    Authors
    ARÉVALO, P.
    Time period covered
    Jan 1, 2001 - Dec 31, 2016
    Area covered
    Description

    This dataset provides annual maps of land cover classes for the Colombian Amazon from 2001 through 2016 that were created by classifying time segments detected by the Continuous Change Detection and Classification (CCDC) algorithm. The CCDC algorithm detected changes in Landsat pixel surface reflectance across the time series, and the time segments were classified into land cover types using a Random Forest classifier and manually collected training data. Annual maps of land cover were created for each Landsat scene and then post-processed and mosaicked. Land cover types include unclassified, forest, natural grasslands, urban, pastures, secondary forest, water, or highly reflective surfaces. The training data are not included with this dataset.

  16. a

    SitiosReprodAves Oceanica shp

    • acceso-datos-ambientales-invemar.hub.arcgis.com
    Updated Feb 3, 2022
    + more versions
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    Instituto de Investigaciones Marinas y Costeras (2022). SitiosReprodAves Oceanica shp [Dataset]. https://acceso-datos-ambientales-invemar.hub.arcgis.com/items/cc45a541164148489ee6bc9a31fc865e
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    Dataset updated
    Feb 3, 2022
    Dataset authored and provided by
    Instituto de Investigaciones Marinas y Costeras
    Area covered
    Description

    Es una capa vector (shapefile)que contiene información suministrada por Castillo-Torres, P. A. 2012. Recopilación. Análisis de vacíos de conservación para el SIRAP Pacífico.Informe Final. INVEMARque a su vez contiene informacion suministrada por WWF, CALIDRIS, INVEMAR en INVEMAR – CI. 2008. Sistema de información geográfica “Estrategia de manejo regional para la conservación in situ de la biodiversidad marino costera del Pacífico colombiano. Informe técnico. INVEMAR- CI, Santa Marta - Colombia, 42p + anexos. Coordenadas.Adicionalmente contiene información suministrada por:*López-Victoria, M. & Rozo, D. 2006. Geomorfología de la isla de Malpelo y la distribución espacial de aves marinas en reproducción. Bol. Invest. Mar. Cost. 35:111-131. Santa Marta. Colombia.Escala 1:100.000

  17. D

    Coberturas 2022

    • datos.gov.co
    application/rdfxml +5
    Updated Dec 4, 2024
    + more versions
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    (2024). Coberturas 2022 [Dataset]. https://www.datos.gov.co/dataset/Coberturas-2022/thzy-4i5w
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    tsv, json, csv, xml, application/rssxml, application/rdfxmlAvailable download formats
    Dataset updated
    Dec 4, 2024
    Description
    Capa (Map Image Layer) a escala 1:25.000 de las coberturas de la tierra para los años 2019,2020, y 2021.

    Map Image Layer de la GDB Replica cartografia, que contiene los shapefile de:
    • sigparques.cartografia.COBEANT2019SPNN25K = Coberturas 2019
    • sigparques.cartografia.COBEANT2020SPNN25K = Coberturas 2020
    • sigparques.cartografia.COBEANT2021SPNN25K = Coberturas 2021

    Capa con la multitemporalidad de la capa de coberturas de la tierra a escala 1:25.000. Información disponible para los años 2019, 2020 y 2021.
    Links de descarga:

    Esta información es producida por Parques Nacionales Naturales de Colombia, por el equipo de Sensores Remotos del Grupo de Gestión del Conocimiento y la Innovación.

    Estos shapefile hacen parte del Feature Dataset <sigparques.cartografia.Coberturas_Tierra>

    Es un Map Image Layer publicado desde ArcGIS Server Manager

    |categoría: Ambiente y Desarrollo Sostenible |cobertura: Nacional|
  18. a

    MANGLARES COLOMBIA

    • hub.arcgis.com
    • acceso-datos-ambientales-invemar.hub.arcgis.com
    Updated Jul 27, 2023
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    Instituto de Investigaciones Marinas y Costeras (2023). MANGLARES COLOMBIA [Dataset]. https://hub.arcgis.com/datasets/5d48a57b4f4347519d28c09f9b7eb286
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    Dataset updated
    Jul 27, 2023
    Dataset authored and provided by
    Instituto de Investigaciones Marinas y Costeras
    Area covered
    Description

    Capa vectorial de manglares de Colombia realizada a partir de técnicas de procesamiento digital de imágenes. La metodología parte de la clasificación supervisada en la plataforma Google Earth Engine, utilizando imágenes ópticas y de radar. Se utilizaron muestras de entrenamiento y validación producto de información en campo e imágenes de alta resolución. Para el Pacífico se procesaron imágenes de los años 2019 y 2020 dada las condiciones de nubosidad; para el Pacífico, se procesaron imágenes del año 2020. En ambos casos la unidad mínima cartografiada fue de 1600 m2. Se realizó post-clasificación por criterio de experto, que incluyó interpretación y edición manual. Finalmente se calificó el nivel de incertidumbre, teniendo en cuenta si cada polígono definido tenía o no un vector de soporte generado en años anteriores, así: Alta: Sin información previa que argumente la presencia de manglar. Media: Con información previa que soporta la presencia de manglar, generada antes del 2015. Baja: Con información previa que soporta la presencia de manglar, generada entre el 2015 y 2020. Esta capa se presenta a una escala de 1:25,000 para los litorales Caribe y Pacífico, mientras que para la zona insular de San Andrés, Providencia y Santa Catalina, producto del proyecto “SeaFlower Plus 2021” y el proyecto "Fortalecimiento de la restauración de manglares en Colombia: Técnicas, saberes y experiencias" 2021, se presenta información a una escala de 1:5,000 con unidad mínima variable. Los límites departamentales se establecieron a partir de la cartografía vectorial a escala 1:100.000 del IGAC año 2022, con cobertura total de la República de Colombia.

  19. Global mangrove soil carbon: dataset and spatial maps

    • search.dataone.org
    • data.isric.org
    • +1more
    Updated Feb 5, 2025
    + more versions
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    ISRIC – World Soil Information (2025). Global mangrove soil carbon: dataset and spatial maps [Dataset]. https://search.dataone.org/view/sha256%3Afb2aa9552ef98976d90add13366f8218a979106b4b3a96a9f13e541b5b875265
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    Dataset updated
    Feb 5, 2025
    Dataset provided by
    International Soil Reference and Information Centre
    Time period covered
    Jan 1, 1969 - Sep 1, 2015
    Area covered
    Description

    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 see the scientific paper (https://doi.org/10.1088/1748-9326/aabe1c).

  20. Cartografía Básica Digital Integrada. República de Colombia.. Escala...

    • metadatos.icde.gov.co
    Updated Sep 10, 2020
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    Instituto Geográfico Agustín Codazzi IGAC - Subdirección de Geografía y Cartografía– Grupo Interno de Trabajo Generación de Datos y Productos Cartográficos (2020). Cartografía Básica Digital Integrada. República de Colombia.. Escala 1:100.000. [Dataset]. https://metadatos.icde.gov.co/geonetwork/srv/api/records/c1b4bfe5-f7c7-44a4-8849-c5f7c4257937
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    Dataset updated
    Sep 10, 2020
    Dataset provided by
    Instituto Geográfico Agustín Codazzihttp://www.igac.gov.co/
    Area covered
    Description

    Cartografía vectorial a escala 1:100.000 con cobertura total de la República de Colombia. Contiene información sobre entidades territoriales, transporte terrestre y fluvial, hidrografía, relieve, orografía, construcciones. Referido al sistema de coordenadas MAGNA-SIRGAS, se genera a partir de la interpretación de objetos en una imagen ortorectificada provenientes de plataformas satelitales o aerotransportadas, disponible en los siguientes formatos: Geodatabase , Shapefile, PostGis , GeoPackage y servicios (WMS y WFS).

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GeoPostcodes (2025). Colombia Shapefile [Dataset]. https://www.geopostcodes.com/country/colombia-shapefile

Colombia Shapefile

Colombia Shapefile - Data Download

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13 scholarly articles cite this dataset (View in Google Scholar)
shpAvailable download formats
Dataset updated
May 28, 2025
Dataset authored and provided by
GeoPostcodes
Area covered
Colombia
Description

Download high-quality, up-to-date Colombia shapefile boundaries (SHP, projection system SRID 4326). Our Colombia Shapefile Database offers comprehensive boundary data for spatial analysis, including administrative areas and geographic boundaries. This dataset contains accurate and up-to-date information on all administrative divisions, zip codes, cities, and geographic boundaries, making it an invaluable resource for various applications such as geographic analysis, map and visualization, reporting and business intelligence (BI), master data management, logistics and supply chain management, and sales and marketing. Our location data packages are available in various formats, including Shapefile, GeoJSON, KML, ASC, DAT, CSV, and GML, optimized for seamless integration with popular systems like Esri ArcGIS, Snowflake, QGIS, and more. Companies choose our location databases for their enterprise-grade service, reduction in integration time and cost by 30%, and weekly updates to ensure the highest quality.

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