Download Construction Sites Data in Shapefile, KML, MID +15 GIS Formats

Looking for accurate and structured location data of construction activity? Download Construction sites Data easily using GIS Data by MAPOG. This intuitive platform supports over 15+ GIS formats including Shapefile, KML, GeoJSON, and MID, enabling compatibility across popular GIS software. Whether you’re engaged in infrastructure planning, monitoring urban expansion, or conducting land-use analysis, MAPOG offers detailed and reliable construction site datasets that support efficient decision-making and mapping tasks.

Why Construction Sites Data Matters

Construction sites represent areas where new structures are being built or existing ones are undergoing significant changes. These locations are vital for urban planners, real estate analysts, environmental consultants, and development authorities. With the right data, professionals can assess developmental density, identify growth trends, and evaluate impact on surrounding zones.

Download Construction Sites Data of any countries

Note:
  • All data is provided in GCS datum EPSG:4326 WGS84 CRS (Coordinate Reference System).
  • Users need to log in to access and download their preferred data formats.

Step-by-Step Guide to Download Construction Sites Data

Step 1: Search for Construction Sites Data

Begin by selecting your desired region from the GIS Data by MAPOG platform. Use the built-in search tool to look for “Construction Sites.” Datasets may include point or polygon geometries depending on how the information was mapped.

Download Construction Sites Data
Step 2: Use the AI-Powered Search Tool

MAPOG’s “Try AI” search assistant speeds up the process. Enter terms like “construction activity in zone” or “urban development sites,” and the AI tool will fetch the most relevant datasets for you—perfect when time or specificity is key.

Step 3: Filter for Precision

To narrow down your results, apply the “Filter Data” option. This helps you sort construction data by city blocks, local authorities, or planning zones, giving you a refined dataset tailored to your needs.

Step 4: Visualize Data on Interactive Map

Click “Add on Map” to instantly view your selected construction data overlaid on a live map. This visualization aids in understanding spatial distribution, construction clusters, and nearby infrastructures, allowing for more informed analysis.

Step 5: Download Construction Sites Data

Once you’ve verified the dataset, proceed to download. Choose your preferred format—be it Shapefile, KML, MID, GeoJSON, or others—and opt for either a sample preview or the complete dataset. Accept the terms, and your download will be ready in seconds.

Final Thoughts

In a world where spatial awareness and development monitoring are critical, Download Construction sites Data using GIS Data by MAPOG to stay ahead. The platform simplifies the retrieval of comprehensive construction datasets for planners, GIS analysts, and researchers alike. With its robust features and multiple export formats, it empowers users to conduct thorough analysis, plan efficiently, and visualize construction patterns with ease.

With MAPOG’s versatile toolkit, you can effortlessly upload vector and upload Excel or CSV data, incorporate existing layers, perform polyline splitting, use the converter for various formats, calculate isochrones, and utilize the Export Tool.

For any questions or further assistance, feel free to reach out to us at support@mapog.com. We’re here to help you make the most of your GIS data.

Download Shapefile for the following:

  1. World Countries Shapefile
  2. Australia
  3. Argentina
  4. Austria
  5. Belgium
  6. Brazil
  7. Canada
  8. Denmark
  9. Fiji
  10. Finland
  11. Germany
  12. Greece
  13. India
  14. Indonesia
  15. Ireland
  16. Italy
  17. Japan
  18. Kenya
  19. Lebanon
  20. Madagascar
  21. Malaysia
  22. Mexico
  23. Mongolia
  24. Netherlands
  25. New Zealand
  26. Nigeria
  27. Papua New Guinea
  28. Philippines
  29. Poland
  30. Russia
  31. Singapore
  32. South Africa
  33. South Korea
  34. Spain
  35. Switzerland
  36. Tunisia
  37. United Kingdom Shapefile
  38. United States of America
  39. Vietnam
  40. Croatia
  41. Chile
  42. Norway
  43. Maldives
  44. Bhutan
  45. Colombia
  46. Libya
  47. Comoros
  48. Hungary
  49. Laos
  50. Estonia
  51. Iraq
  52. Portugal
  53. Azerbaijan
  54. Macedonia
  55. Romania
  56. Peru
  57. Marshall Islands
  58. Slovenia
  59. Nauru
  60. Guatemala
  61. El Salvador
  62. Afghanistan
  63. Cyprus
  64. Syria
  65. Slovakia
  66. Luxembourg
  67. Jordan
  68. Armenia
  69. Haiti And Dominican Republic
  70. Malta
  71. Djibouti
  72. East Timor
  73. Micronesia
  74. Morocco
  75. Liberia
  76. Kosovo
  77. Isle Of Man
  78. Paraguay
  79. Tokelau
  80. Palau
  81. Ile De Clipperton
  82. Mauritius
  83. Equatorial Guinea
  84. Tonga
  85. Myanmar
  86. Thailand
  87. New Caledonia
  88. Niger
  89. Nicaragua
  90. Pakistan
  91. Nepal
  92. Seychelles
  93. Democratic Republic of the Congo
  94. China
  95. Kenya
  96. Kyrgyzstan
  97. Bosnia Herzegovina
  98. Burkina Faso
  99. Canary Island
  100. Togo
  101. Israel And Palestine
  102. Algeria
  103. Suriname
  104. Angola
  105. Cape Verde
  106. Liechtenstein
  107. Taiwan
  108. Turkmenistan
  109. Tuvalu
  110. Ivory Coast
  111. Moldova
  112. Somalia
  113. Belize
  114. Swaziland
  115. Solomon Islands
  116. North Korea
  117. Sao Tome And Principe
  118. Guyana
  119. Serbia
  120. Senegal And Gambia
  121. Faroe Islands
  122. Guernsey Jersey
  123. Monaco
  124. Tajikistan
  125. Pitcairn

Disclaimer : The GIS data provided for download in this article was initially sourced from OpenStreetMap (OSM) and further modified to enhance its usability. Please note that the original data is licensed under the Open Database License (ODbL) by the OpenStreetMap contributors. While modifications have been made to improve the data, any use, redistribution, or modification of this data must comply with the ODbL license terms. For more information on the ODbL, please visit OpenStreetMap’s License Page.

Here are some blogs you might be interested in:


Online GIS data Conversion |Converting GeoJSON to KMZ

In this guide, we’ll walk you through how to efficiently convert your GeoJSON files to KMZ using the powerful Converter Tool in MAPOG. Whether you’re a beginner or an experienced user, Converting GeoJSON to KMZ with MAPOG, this tutorial will help you understand the process in easy steps.

Key Concept to Converting files

The Converter Tool is a feature in MAPOG that helps you change your data from one format to another. It’s like magic! You give it your data in one form, and it transforms it into another form that you need for your analysis. Additionally, with GIS Data, you can download data in any format, making it versatile and adaptable for various applications.

Online GeoJSON to KMZ GIS Converter

Step 1: Upload the Data

1. Click on the “Process Data” menu and choose the “Converter Tool” option.

2. Upload your GeoJSON file. This is your starting point where you provide the data that needs conversion.

Step 2: Select the Format for Conversion

1. Choose the output file format as KMZ. The tool offers various formats, but for this guide, we are focusing on converting to KMZ.

2.You can also set the CRS at this stage.

Step 3: Run the Conversion

Click ‘Convert Files’ and let the tool work its magic. The Converter Tool processes your data, transforming it from GeoJSON to KMZ format.

Step 4: Review and Download

Finally, review your converted KMZ data to ensure it looks right. Once satisfied, download the converted file. This step is crucial to verify that the conversion has been successful and the data integrity is maintained.

And there you have it! You’ve successfully used the Converter Tool in MAPOG to convert your GeoJSON files to KMZ. Now you can easily convert your data for all your analysis needs. This feature simplifies the process of handling different data formats, making your workflow more efficient and effective.

With MAPOG’s versatile toolkit, you can effortlessly upload vector and upload Excel or CSV data, incorporate existing layers, perform polyline splitting, use the converter for various formats, calculate isochrones, and utilize the Export Tool.

Here are some other blogs you might be interested in

Download Drop-in Centers Data in Shapefile, KML, MID +15 GIS Formats

Looking to Download Drop-in Centers Data for your next GIS project or planning initiative? With GIS Data by MAPOG, accessing reliable, up-to-date geographic datasets is simple and efficient. Whether you’re working in the fields of social welfare, community health outreach, or urban resource mapping, this platform supports over 15 GIS formats including Shapefile, KML, MID, and GeoJSON—ensuring smooth compatibility with major GIS tools and software.

How GIS Data by MAPOG Works?

MAPOG’s intuitive system simplifies the process of discovering, visualizing, and downloading location-based datasets. It supports users with advanced tools like AI-assisted search, layer visualization, and customizable format options. Whether you’re analyzing accessibility or planning expansion, you can easily download Drop-in Centers Data for more informed spatial analysis.

Download Drop-in Centers Data of any countries

Note:
  • All data is provided in GCS datum EPSG:4326 WGS84 CRS (Coordinate Reference System).
  • Users need to log in to access and download their preferred data formats.

Step-by-Step Guide to Download Drop-in Centers Data

Step 1: Search for Drop-in Centers Data

Begin by logging into the GIS Data by MAPOG portal. Use the search layer function and type in “Drop-in Centers Data.” Review the attributes available—data may appear as points or polygons, depending on how it has been collected and categorized.

Download Drop-in Centers Data
Step 2: Try the AI Search Tool

Use MAPOG’s built-in “Try AI” feature to quickly find relevant datasets. Enter phrases like “Drop-in centers near me” or “Community shelters,” and the tool will auto-suggest matching layers, saving you time and effort.

Step 3: Apply Filters for Targeted Results

Narrow your results using the Filter Data option. This allows users to search by state or district, enabling deeper exploration within a region. Whether you’re working locally or across multiple jurisdictions, this feature ensures data accuracy and relevance.

Step 4: Visualize with “Add on Map”

Click on “Add on Map” to view your selected data on MAPOG’s interactive GIS interface. This lets you analyze spatial distribution, evaluate service gaps, and understand proximity to other key facilities—all in real time.

Step 5: Download Drop-in Centers Data

Once you’re satisfied with your selection, click on “Download Data.” Choose from sample or full datasets and select from formats like Shapefile, KML, MID, CSV, GeoJSON, DXF, or SQL, among others.

Final Thoughts

With powerful tools, smart filters, and diverse format options, GIS Data by MAPOG makes it seamless to download Drop-in Centers Data for any kind of mapping, analysis, or planning task. Whether you’re a researcher, urban planner, social worker, or GIS professional, this platform equips you with the spatial intelligence needed to make meaningful, data-driven decisions.

With MAPOG’s versatile toolkit, you can effortlessly upload vector and upload Excel or CSV data, incorporate existing layers, perform polyline splitting, use the converter for various formats, calculate isochrones, and utilize the Export Tool.

For any questions or further assistance, feel free to reach out to us at support@mapog.com. We’re here to help you make the most of your GIS data.

Download Shapefile for the following:

  1. World Countries Shapefile
  2. Australia
  3. Argentina
  4. Austria
  5. Belgium
  6. Brazil
  7. Canada
  8. Denmark
  9. Fiji
  10. Finland
  11. Germany
  12. Greece
  13. India
  14. Indonesia
  15. Ireland
  16. Italy
  17. Japan
  18. Kenya
  19. Lebanon
  20. Madagascar
  21. Malaysia
  22. Mexico
  23. Mongolia
  24. Netherlands
  25. New Zealand
  26. Nigeria
  27. Papua New Guinea
  28. Philippines
  29. Poland
  30. Russia
  31. Singapore
  32. South Africa
  33. South Korea
  34. Spain
  35. Switzerland
  36. Tunisia
  37. United Kingdom Shapefile
  38. United States of America
  39. Vietnam
  40. Croatia
  41. Chile
  42. Norway
  43. Maldives
  44. Bhutan
  45. Colombia
  46. Libya
  47. Comoros
  48. Hungary
  49. Laos
  50. Estonia
  51. Iraq
  52. Portugal
  53. Azerbaijan
  54. Macedonia
  55. Romania
  56. Peru
  57. Marshall Islands
  58. Slovenia
  59. Nauru
  60. Guatemala
  61. El Salvador
  62. Afghanistan
  63. Cyprus
  64. Syria
  65. Slovakia
  66. Luxembourg
  67. Jordan
  68. Armenia
  69. Haiti And Dominican Republic
  70. Malta
  71. Djibouti
  72. East Timor
  73. Micronesia
  74. Morocco
  75. Liberia
  76. Kosovo
  77. Isle Of Man
  78. Paraguay
  79. Tokelau
  80. Palau
  81. Ile De Clipperton
  82. Mauritius
  83. Equatorial Guinea
  84. Tonga
  85. Myanmar
  86. Thailand
  87. New Caledonia
  88. Niger
  89. Nicaragua
  90. Pakistan
  91. Nepal
  92. Seychelles
  93. Democratic Republic of the Congo
  94. China
  95. Kenya
  96. Kyrgyzstan
  97. Bosnia Herzegovina
  98. Burkina Faso
  99. Canary Island
  100. Togo
  101. Israel And Palestine
  102. Algeria
  103. Suriname
  104. Angola
  105. Cape Verde
  106. Liechtenstein
  107. Taiwan
  108. Turkmenistan
  109. Tuvalu
  110. Ivory Coast
  111. Moldova
  112. Somalia
  113. Belize
  114. Swaziland
  115. Solomon Islands
  116. North Korea
  117. Sao Tome And Principe
  118. Guyana
  119. Serbia
  120. Senegal And Gambia
  121. Faroe Islands
  122. Guernsey Jersey
  123. Monaco
  124. Tajikistan
  125. Pitcairn

Disclaimer : The GIS data provided for download in this article was initially sourced from OpenStreetMap (OSM) and further modified to enhance its usability. Please note that the original data is licensed under the Open Database License (ODbL) by the OpenStreetMap contributors. While modifications have been made to improve the data, any use, redistribution, or modification of this data must comply with the ODbL license terms. For more information on the ODbL, please visit OpenStreetMap’s License Page.

Here are some blogs you might be interested in:

Download Historical Monuments Data in Shapefile, KML, MID +15 GIS Formats

Looking to explore or map culturally significant sites? Download Historical Monuments Data quickly and accurately using GIS Data by MAPOG. This intuitive platform offers data in over 15 GIS formats—including Shapefile, KML, GeoJSON, and MID—ensuring compatibility with major GIS tools. Whether you’re engaged in heritage conservation, academic research, urban planning, or tourism development, this tool provides well-structured, ready-to-use datasets that support detailed spatial analysis and visualization.

How to Download Historical Monuments Data

GIS Data by MAPOG offers a robust way to explore and download monument data from hundreds of geographic layers. The system supports a wide variety of file formats—such as KML, SHP, CSV, GeoJSON, SQL, DXF, MIF, TOPOJSON, and GPX—making it a preferred choice for GIS professionals, developers, and researchers alike.

Download Historical Monuments Data of any countries

Note:
  • All data is provided in GCS datum EPSG:4326 WGS84 CRS (Coordinate Reference System).
  • Users need to log in to access and download their preferred data formats.

Step-by-Step Guide to Download Historical Monuments Data

Step 1: Search for Historical Monuments Data

Begin by selecting the region of interest within the MAPOG interface. Use the “Search Layer” function and look for “Historical Monuments Data.” Depending on the dataset, the information may appear as points or polygons, representing locations or boundaries.

Download Historical Monuments Data
Step 2: Use the AI Search Tool

Let MAPOG’s “Try AI” assist you. Simply input keywords like “Monuments near me” or “Heritage sites,” and the AI tool will present the most relevant layers. This feature not only saves time but also enhances search accuracy.

Step 3: Apply Data Filters

Fine-tune your search using the Filter Data option. You can narrow the dataset by selecting specific states and districts. For nationwide datasets, this feature enables deep-level filtering—making it easier to locate and analyze monuments based on administrative boundaries.

Step 4: Visualize with ‘Add on Map’

Click the Add on Map option to overlay the selected layer onto the GIS map analysis interface. This allows for better visualization and spatial examination of monument locations, clustering, accessibility, and relation to nearby landmarks or infrastructure.

Step 5: Download Historical Monuments Data

Once you’ve finalized your dataset, click “Download Data.” Choose whether to download a sample or the full dataset. Select your desired format—Shapefile, KML, GeoJSON, MID, or others—accept the usage terms, and download your data for offline or project use.

Final Thoughts

With MAPOG’s powerful GIS platform, the ability to download Historical Monuments Data becomes efficient and user-friendly. The platform caters to diverse GIS applications, offering detailed insights and flexibility in how data is accessed and applied. Whether you’re a cultural researcher, urban planner, or GIS enthusiast, MAPOG ensures that heritage-focused spatial data is always within reach.

With MAPOG’s versatile toolkit, you can effortlessly upload vector and upload Excel or CSV data, incorporate existing layers, perform polyline splitting, use the converter for various formats, calculate isochrones, and utilize the Export Tool.

For any questions or further assistance, feel free to reach out to us at support@mapog.com. We’re here to help you make the most of your GIS data.

Download Shapefile for the following:

  1. World Countries Shapefile
  2. Australia
  3. Argentina
  4. Austria
  5. Belgium
  6. Brazil
  7. Canada
  8. Denmark
  9. Fiji
  10. Finland
  11. Germany
  12. Greece
  13. India
  14. Indonesia
  15. Ireland
  16. Italy
  17. Japan
  18. Kenya
  19. Lebanon
  20. Madagascar
  21. Malaysia
  22. Mexico
  23. Mongolia
  24. Netherlands
  25. New Zealand
  26. Nigeria
  27. Papua New Guinea
  28. Philippines
  29. Poland
  30. Russia
  31. Singapore
  32. South Africa
  33. South Korea
  34. Spain
  35. Switzerland
  36. Tunisia
  37. United Kingdom Shapefile
  38. United States of America
  39. Vietnam
  40. Croatia
  41. Chile
  42. Norway
  43. Maldives
  44. Bhutan
  45. Colombia
  46. Libya
  47. Comoros
  48. Hungary
  49. Laos
  50. Estonia
  51. Iraq
  52. Portugal
  53. Azerbaijan
  54. Macedonia
  55. Romania
  56. Peru
  57. Marshall Islands
  58. Slovenia
  59. Nauru
  60. Guatemala
  61. El Salvador
  62. Afghanistan
  63. Cyprus
  64. Syria
  65. Slovakia
  66. Luxembourg
  67. Jordan
  68. Armenia
  69. Haiti And Dominican Republic
  70. Malta
  71. Djibouti
  72. East Timor
  73. Micronesia
  74. Morocco
  75. Liberia
  76. Kosovo
  77. Isle Of Man
  78. Paraguay
  79. Tokelau
  80. Palau
  81. Ile De Clipperton
  82. Mauritius
  83. Equatorial Guinea
  84. Tonga
  85. Myanmar
  86. Thailand
  87. New Caledonia
  88. Niger
  89. Nicaragua
  90. Pakistan
  91. Nepal
  92. Seychelles
  93. Democratic Republic of the Congo
  94. China
  95. Kenya
  96. Kyrgyzstan
  97. Bosnia Herzegovina
  98. Burkina Faso
  99. Canary Island
  100. Togo
  101. Israel And Palestine
  102. Algeria
  103. Suriname
  104. Angola
  105. Cape Verde
  106. Liechtenstein
  107. Taiwan
  108. Turkmenistan
  109. Tuvalu
  110. Ivory Coast
  111. Moldova
  112. Somalia
  113. Belize
  114. Swaziland
  115. Solomon Islands
  116. North Korea
  117. Sao Tome And Principe
  118. Guyana
  119. Serbia
  120. Senegal And Gambia
  121. Faroe Islands
  122. Guernsey Jersey
  123. Monaco
  124. Tajikistan
  125. Pitcairn

Disclaimer : The GIS data provided for download in this article was initially sourced from OpenStreetMap (OSM) and further modified to enhance its usability. Please note that the original data is licensed under the Open Database License (ODbL) by the OpenStreetMap contributors. While modifications have been made to improve the data, any use, redistribution, or modification of this data must comply with the ODbL license terms. For more information on the ODbL, please visit OpenStreetMap’s License Page.

Here are some blogs you might be interested in:

Download Fast Food Restaurant Data in Shapefile, KML, MID +15 GIS Formats

Looking to map the spread of fast food chains or analyze urban food landscapes? Download Fast Food Restaurant Data easily and efficiently using GIS Data by MAPOG. This powerful and intuitive platform supports multiple GIS formats such as Shapefile, KML, GeoJSON, MID, and more—making it compatible with various GIS tools for both beginners and experts. Whether you’re studying urban sprawl, planning zoning policies, or exploring consumer patterns, MAPOG delivers accurate, location-based datasets to meet your analytical needs.

How to Download Fast Food Restaurant Data

GIS Data by MAPOG has simplified the entire process of acquiring restaurant datasets from across the globe. With over 900+ thematic layers and coverage in more than 200 regions, the platform allows you to download data in formats like SHP, KML, CSV, SQL, DXF, MIF, GPX, TOPOJSON, and more. This versatility makes it ideal for use in ArcGIS, QGIS, Google Earth, and other GIS software.

Download Fast Food Restaurant Data of any countries

Note:
  • All data is provided in GCS datum EPSG:4326 WGS84 CRS (Coordinate Reference System).
  • Users need to log in to access and download their preferred data formats.

Step-by-Step Guide to Download Fast Food Restaurant Data

Step 1: Search for Fast Food Restaurant Data

Begin by entering the platform and selecting your area of interest. Use the “Search Layer” option and type “Fast Food Restaurant Data” to locate relevant datasets. Preview the data type—most will be in point format with essential attributes like name, location, and category.

Download Fast Food Restaurant Data
Step 2: Use the AI Search Tool

Save time by using MAPOG’s “Try AI” feature. Just type something like “Fast food outlets near city center” and let the AI assist you in finding accurate and contextual datasets without manual filtering.

Step 3: Apply State and District Filters

Need more refined data? Use the Filter Data option to narrow results by specific states or districts. This is especially useful for those who want to focus on micro-level planning or regional market research.

Step 4: Visualize with “Add on Map”

With the Add on Map feature, you can view the selected fast food restaurant data directly on the GIS interface. This enables deeper spatial analysis—like identifying clusters, gaps in service areas, or proximity to residential zones.

Step 5: Download Fast Food Restaurant Data

Finally, click “Download Data” once your dataset looks good. You’ll have the option to choose a sample or full version, select your preferred format (such as Shapefile, KML, MID, GeoJSON, etc.), and proceed with the download after agreeing to the terms.

Final Thoughts

Using GIS Data by MAPOG, you can download Fast Food Restaurant Data quickly and in a format that suits your GIS workflow. From urban researchers and business analysts to geography enthusiasts, everyone can benefit from this rich, location-based resource. Thanks to MAPOG’s clean interface, advanced search tools, and diverse export options, gathering food infrastructure data for analysis has never been this seamless.

With MAPOG’s versatile toolkit, you can effortlessly upload vector and upload Excel or CSV data, incorporate existing layers, perform polyline splitting, use the converter for various formats, calculate isochrones, and utilize the Export Tool.

For any questions or further assistance, feel free to reach out to us at support@mapog.com. We’re here to help you make the most of your GIS data.

Download Shapefile for the following:

  1. World Countries Shapefile
  2. Australia
  3. Argentina
  4. Austria
  5. Belgium
  6. Brazil
  7. Canada
  8. Denmark
  9. Fiji
  10. Finland
  11. Germany
  12. Greece
  13. India
  14. Indonesia
  15. Ireland
  16. Italy
  17. Japan
  18. Kenya
  19. Lebanon
  20. Madagascar
  21. Malaysia
  22. Mexico
  23. Mongolia
  24. Netherlands
  25. New Zealand
  26. Nigeria
  27. Papua New Guinea
  28. Philippines
  29. Poland
  30. Russia
  31. Singapore
  32. South Africa
  33. South Korea
  34. Spain
  35. Switzerland
  36. Tunisia
  37. United Kingdom Shapefile
  38. United States of America
  39. Vietnam
  40. Croatia
  41. Chile
  42. Norway
  43. Maldives
  44. Bhutan
  45. Colombia
  46. Libya
  47. Comoros
  48. Hungary
  49. Laos
  50. Estonia
  51. Iraq
  52. Portugal
  53. Azerbaijan
  54. Macedonia
  55. Romania
  56. Peru
  57. Marshall Islands
  58. Slovenia
  59. Nauru
  60. Guatemala
  61. El Salvador
  62. Afghanistan
  63. Cyprus
  64. Syria
  65. Slovakia
  66. Luxembourg
  67. Jordan
  68. Armenia
  69. Haiti And Dominican Republic
  70. Malta
  71. Djibouti
  72. East Timor
  73. Micronesia
  74. Morocco
  75. Liberia
  76. Kosovo
  77. Isle Of Man
  78. Paraguay
  79. Tokelau
  80. Palau
  81. Ile De Clipperton
  82. Mauritius
  83. Equatorial Guinea
  84. Tonga
  85. Myanmar
  86. Thailand
  87. New Caledonia
  88. Niger
  89. Nicaragua
  90. Pakistan
  91. Nepal
  92. Seychelles
  93. Democratic Republic of the Congo
  94. China
  95. Kenya
  96. Kyrgyzstan
  97. Bosnia Herzegovina
  98. Burkina Faso
  99. Canary Island
  100. Togo
  101. Israel And Palestine
  102. Algeria
  103. Suriname
  104. Angola
  105. Cape Verde
  106. Liechtenstein
  107. Taiwan
  108. Turkmenistan
  109. Tuvalu
  110. Ivory Coast
  111. Moldova
  112. Somalia
  113. Belize
  114. Swaziland
  115. Solomon Islands
  116. North Korea
  117. Sao Tome And Principe
  118. Guyana
  119. Serbia
  120. Senegal And Gambia
  121. Faroe Islands
  122. Guernsey Jersey
  123. Monaco
  124. Tajikistan
  125. Pitcairn

Disclaimer : The GIS data provided for download in this article was initially sourced from OpenStreetMap (OSM) and further modified to enhance its usability. Please note that the original data is licensed under the Open Database License (ODbL) by the OpenStreetMap contributors. While modifications have been made to improve the data, any use, redistribution, or modification of this data must comply with the ODbL license terms. For more information on the ODbL, please visit OpenStreetMap’s License Page.

Here are some blogs you might be interested in:

Convert CSV to GeoJSON Online: A Step-by-Step Guide

File conversion is a crucial part of the GIS process, ensuring that geospatial data can be easily utilized across different applications. CSV is a simple text format for tabular data, while GeoJSON is a popular format for encoding geographic data structures, widely used in web mapping and spatial analysis.

What is CSV File?

A CSV file (Comma-Separated Values) is a simple text file that stores data in a table format. Each line represents a row, and the values in each row are separated by commas, making it easy to organize and share information like a spreadsheet.

                                      ONLINE GIS DATA CONVERSION

Key Concept for Conversion CSV to Geojson:

The MAPOG Converter Tool offers an intuitive and user-friendly platform for converting data between various formats. Below is a step-by-step guide on how to convert CSV files to GeoJSON format using MAPOG.

Step-by-Step Guide to Converting CSV to GeoJSON

Step 1: Upload Your CSV Data

Start by navigating to the “Process Data” section in MAPOG MapAnalysis. Select the “Converter Tool” option. Before uploading your CSV file, ensure that it is properly organized.

Upload the Data

Step 2: Select GeoJSON as the Output Format

Next, select GeoJSON from the list of available output formats. GeoJSON is widely used in web applications and supports various geometry types, making it an excellent choice for web-based mapping and spatial analysis.

Select GeoJSON as Output format

Step 3: Choose the Output CRS

Selecting the appropriate Output CRS is essential to guarantee that the GEOJSON file appropriately represents your spatial data.

Choose the Output Format

Step 4: Execute the Conversion

Once you’ve configured the input parameters and selected GeoJSON as the output format, click the “Convert” button. The MAPOG tool will process the CSV file and generate a GeoJSON file that accurately represents the geographic data.

Execute the Format

Step 5: Review and Download the GeoJSON File

After the conversion is complete, review the GeoJSON file to ensure all data has been correctly transformed. Once satisfied, download the GeoJSON file. It is now ready to be used in web mapping applications, GIS software, or any other platform that supports GeoJSON.

Review the Data

Conclusion:

The MAPOG Converter Tool is a valuable resource for GIS professionals and web developers, simplifying the process of converting data into various geospatial formats. By following these steps, you can efficiently convert CSV files to GeoJSON format, ensuring your data is ready for use in a wide range of geospatial applications. If you need to download any data file in CSV or in any other formats like KML, GPX. visit GIS DATA. Here we have 900+ data layers for 200+ countries.

Feature Tool:
Story by MAPOG:

MAPOG is an engaging tool that brings geographical data to life through interactive maps and narratives. Imagine combining detailed maps with photos, videos, and text to tell captivating stories about places, events, or trends. Whether you’re showcasing beautiful landscapes, tracking environmental changes, or exploring cultural sites, Story by MAPOG makes it easy to guide viewers through a visual journey. It’s perfect for educators, travel enthusiasts, or anyone who wants to make their data-driven stories interactive and visually compelling.

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Download Pipeline data in Shapefile, KML , Tiff +15 GIS format – Filter and download

GIS Data by MAPOG is a versatile platform designed to provide users with easy access to a wide range of GIS Data formats, such as Shapefile, KML, GeoJSON, and many more. The platform offers a user-friendly interface for downloading both administrative and geographic data sets and other datasets like pipeline data, allowing users to effortlessly locate and utilize data tailored to their specific needs.

Understanding the Process

Downloading pipeline data using GIS Data by MAPOG is a simple and efficient process, requiring users to select their preferred data format, such as Shapefile or KML, suitable for various GIS applications. The platform encompasses data from over 200+ countries, with access to more than 900+ layers. It streamlines the downloading procedure by offering a step-by-step guide, enabling users to quickly obtain the data required for analysis, planning, or mapping tasks.

An extensive range of data formats is available, including KML, SHP, CSV, GeoJSON, Tab, SQL, TIFF, GML, KMZ, GPKG, SQLITE, DXF, MIF, TOPOJSON, XLSX, GPX, ODS, MID, and GPS, ensuring compatibility and accessibility for numerous applications and analytical needs.

Note:
  • All data is provided in GCS datum EPSG:4326 WGS84 CRS (Coordinate Reference System).
  • Users need to log in to access and download their preferred data formats.

Step-by-Step Process to Download Pipeline Data

Step 1: Access GIS Data

Begin by logging into MAPOG with a valid email address. Once successfully logged in, navigate to the GIS data section to begin your search.

Step 2: Search for ‘Pipeline Data’

After accessing the GIS Data interface, select the country from which you wish to download data. Use the search layer option to look for the desired layer, such as “pipelines“. Review the data, its attributes, and its format (e.g., point or polygon). You can also utilize the “Try AI” tool located in the upper left corner to simplify your search—just specify the data you need and the area, and the tool will provide the corresponding data.

Download Pipeline Data
Step 3: Filter Data

Use the filter data option to refine your search by selecting specific states and districts. This feature allows for the location of more precise geographic information, enabling a deeper dive into data, such as narrowing down to specific states or districts. It enhances the accuracy and relevance of the data for targeted analysis or mapping.

Step 4: Add on Map

Leverage the “Add on Map” feature to overlay the selected pipeline data onto the MAPOG interface for further investigation. This function helps users visualize spatial relationships and patterns, enhancing decision-making in GIS projects. You can add the dataset to a new map or include it in an existing map.

Step 5: Download Data

Click on the “Download Data” button. Choose between downloading sample data or the full dataset, depending on your needs. Then, select the desired format from the available options—Shapefile, KML, GeoJSON, or any of the other 15+ supported GIS formats. After agreeing to the terms and conditions, click on the download button again to complete the process, and your data will be downloaded.

Conclusion

Downloading pipeline data in multiple GIS formats from GIS Data by MAPOG is an uncomplicated and efficient process, facilitated by a series of easy steps. This platform enables access to accurate and current geographic data in numerous formats, providing flexibility and support for a wide array of planning, mapping, and analytical applications.

With MAPOG’s versatile toolkit, you can effortlessly upload vector and upload Excel or CSV data, incorporate existing layers, perform polyline splitting, use the converter for various formats, calculate isochrones, and utilize the Export Tool.

For any questions or further assistance, feel free to reach out to us at support@mapog.com. We’re here to help you make the most of your GIS data.

Download Shapefile for the following:

  1. World Countries Shapefile
  2. Australia
  3. Argentina
  4. Austria
  5. Belgium
  6. Brazil
  7. Canada
  8. Denmark
  9. Fiji
  10. Finland
  11. Germany
  12. Greece
  13. India
  14. Indonesia
  15. Ireland
  16. Italy
  17. Japan
  18. Kenya
  19. Lebanon
  20. Madagascar
  21. Malaysia
  22. Mexico
  23. Mongolia
  24. Netherlands
  25. New Zealand
  26. Nigeria
  27. Papua New Guinea
  28. Philippines
  29. Poland
  30. Russia
  31. Singapore
  32. South Africa
  33. South Korea
  34. Spain
  35. Switzerland
  36. Tunisia
  37. United Kingdom Shapefile
  38. United States of America
  39. Vietnam
  40. Croatia
  41. Chile
  42. Norway
  43. Maldives
  44. Bhutan
  45. Colombia
  46. Libya
  47. Comoros
  48. Hungary
  49. Laos
  50. Estonia
  51. Iraq
  52. Portugal
  53. Azerbaijan
  54. Macedonia
  55. Romania
  56. Peru
  57. Marshall Islands
  58. Slovenia
  59. Nauru
  60. Guatemala
  61. El Salvador
  62. Afghanistan
  63. Cyprus
  64. Syria
  65. Slovakia
  66. Luxembourg
  67. Jordan
  68. Armenia
  69. Haiti And Dominican Republic
  70. Malta
  71. Djibouti
  72. East Timor
  73. Micronesia
  74. Morocco
  75. Liberia
  76. Kosovo
  77. Isle Of Man
  78. Paraguay
  79. Tokelau
  80. Palau
  81. Ile De Clipperton
  82. Mauritius
  83. Equatorial Guinea
  84. Tonga
  85. Myanmar
  86. Thailand
  87. New Caledonia
  88. Niger
  89. Nicaragua
  90. Pakistan
  91. Nepal
  92. Seychelles
  93. Democratic Republic of the Congo
  94. China
  95. Kenya
  96. Kyrgyzstan
  97. Bosnia Herzegovina
  98. Burkina Faso
  99. Canary Island
  100. Togo
  101. Israel And Palestine
  102. Algeria
  103. Suriname
  104. Angola
  105. Cape Verde
  106. Liechtenstein
  107. Taiwan
  108. Turkmenistan
  109. Tuvalu
  110. Ivory Coast
  111. Moldova
  112. Somalia
  113. Belize
  114. Swaziland
  115. Solomon Islands
  116. North Korea
  117. Sao Tome And Principe
  118. Guyana
  119. Serbia
  120. Senegal And Gambia
  121. Faroe Islands
  122. Guernsey Jersey
  123. Monaco
  124. Tajikistan
  125. Pitcairn

Disclaimer : The GIS data provided for download in this article was initially sourced from OpenStreetMap (OSM) and further modified to enhance its usability. Please note that the original data is licensed under the Open Database License (ODbL) by the OpenStreetMap contributors. While modifications have been made to improve the data, any use, redistribution, or modification of this data must comply with the ODbL license terms. For more information on the ODbL, please visit OpenStreetMap’s License Page.

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Merge polygons features online using IGISMap

In GIS data, a geographic area is represented in a polygon shape. Geospatial features such as administrative boundaries are digitized in the polygon vector model. In some cases, we need to merge the polygon features based on attribute values or location. After merging, input polygons will merge into a single polygon feature assigned with a single row to store attribute values. When the adjacent polygons with common border lines are merged, they combine to form a single polygon. Through merge functionality, we can create any primary-level administrative boundaries like national boundaries from the secondary level divisions like state or district level boundaries. So here in this article, we are providing steps to merge polygons features online in a single layer.

Merging is a common geoprocessing used in GIS projects for two important cases. One is to merge multiple GIS features into single GIS feature within a GIS data itself. Another application is to merge multiple GIS data into single GIS data. In both cases, geometry entity of the input GIS feature or GIS data should be same ie., either point, polyline or polygon.

IGISMap provides Merge Polygons tool to merge multiple polygon features of a polygon GIS data into single polygon feature. IGISMap is a GIS-based web platform, that provides multiple GIS applications that are most important in the field of geospatial analytics. The peculiarity of IGISMAP in the GIS Industry is its user interface which helps the user to perform effortless geospatial operations. Merge Polygons tool is very easy to use and you can merge the required polgons in just two steps.

In this article we will create the national boundary of USA by merging the polygons of state boundaries. Without further due, lets dive into Merge Polygons tool.

Click https://map.igismap.com/merge-polygon to open Merge Polygons tool.

Add your data

After opening Merge Polygons tool, first step is to add or upload polygon GIS data. Here we will choose Upload Data option to upload the data from your personal computer. Then, click on the Browse button to open the browsing box, where you will choose the file from your pc. In this article, we will be uploading a polygon GIS data of USA state level boundaries.

Upload Data

After opening the file, click the Upload button to start the upload process.

Uploading GIS data

Check the article Add / Upload polygon GIS data and merge required polygon features to understand how to use IGISMap GIS data in Merge Polygons tool.

Select polygons using Lasso Tool

When uploading is complete, polygon GIS data of USA state level boundaries will be published in the map. This data will be selected as the input data for carying out the merge operation.

Select Lasso Tool

You can access this same data from IGISMap GIS Data collection through Add GIS Data option provided in the Data Selection section.

Click https://map.igismap.com/add-gis to access Add GIS Data tool directly

Click below to download polygon GIS data of USA state level boundaries

Download USA State Level Boundaries Shapefile

Next step is to select the required polygon features from the input polygon data. IGISMap provides two options to select the polygons. They are – Lasso Tool and Select Manually. Lasso Tool option is suitable to selecte large number of polygon features, hence we will select Lasso Tool tab.

Lasso Tool will open the list of modes to draw a polygon over the required polygon features. These are Draw Polygon With Free Hand, Draw Circle, Draw Rectangle, and Draw Polygon. Select Draw Polygon and draw a polygon intersecting all the polygons of the states.

Draw Polygon using the Lasso Tool

Polygon features of the input polygon GIS data that intersected by the lasso polygon will be selected for merging. Then click Submit to start merging.

Polygons selected using Lasso tool

Output polygon

After submitting, merged polygon GIS data of USA national ouline boundary is published in the map, as shown below

Merged Layer

In the above article we uploaded polygon GIS data and merge polygons features online. But if you have point data you can also convert it into polygon by point to polygon conversion feature of IGISMap Tool. This is good if you have point data. If you don’t have data you can Create Point Data using our tool.

Check the article Share your Map to understand the Share Map feature of IGISMap.

Check other articles:
Check the following IGISMap tools:

Convert addresses from spreadsheet to points on Map in two steps

Consider a customer service manager working for a supermarket company wants to connect with some of their best customers for giving winning prizes and to promote their business. The manager has a list of contacts along with their address which is located all over America. In order to deliver the winning prizes to their doorstep, he has to find the best route which takes a minimum number of days to receive it. Hence he has to give the delivery partner the best route which is easier and less time-consuming.

In such cases, Geocoding helps to make the process easier. Geocoding is the process of converting one or more valid address with location details into GIS points.Geocoder tool of IGISMap can be used for converting address details to point GIS data in a few steps. You only need to upload the spreadsheet file with address columns and assign the address columns to start plotting. Option to review the plotting and edit the points are also available in this tool.

IGISMap is a GIS-based web platform, that provides multiple GIS applications that are most important in the field of geospatial analytics. The peculiarity of IGISMap in the GIS Industry is its UI/UX, which helps the user to perform effortless geospatial operations. IGISMap allows users to edit the data table of vector data by editing the name of the columns, deleting the columns, and adding new columns. The Geocoder tool on the IGISMap increases efficiency by enabling different companies to better coordinate their sales in both domestic and foreign marketing activities.

Open Geocoder tool using the following link https://map.igismap.com/geocoder

Upload spreadsheet file

For uploading the input file, click on the Browse option, select the excel/CSV file from your system that you want to visualize on IGISMap, and click on the Upload option.

Upload Excel/CSV file

Match the Columns

After successfully uploading the file, the next step is to assign the address columns in your file to be used for geocoding. There are 2 options to match the columns – Full Address and Other. Full Address option is used for files with address information provided in a single column. In our case, we have address distributed in several columns, thus we will choose Other option. Click Other option and select the right address columns from you file at the right address types such as address, city, zip, state. Then select the country and click Submit button to geocode the address.

Match The Columns

Review the geocoded locations

A GIS layer gets published after submitting, with point locations based on the address information from the input spreadsheet file. Result section also opens with datatable and Relevance_score column.

Geocoder Result

Relevance_score is a value ranging between 0 to 10 provided for every row depicting the accuracy of the plotted locations after the geocoding each address, where 10 being the highest accuracy. User can check the relevance score for each row and edit the point location if needed. Rows of the point features will be highlighted in red color if the relevance score is below 8. This is to notify the user to confirm the location plotted.

Relevance Score

How to edit location by checking relevance score

The user can delete any feature by using the Delete Feature button present on the Relevance_score table. Click Edit Attribute button of any required feature to start editing the attribute values of that feature and then click Save icon.

The user can edit the location of any point feature by using the Edit Location button. After clicking the Edit Location button in the row of any point feature, a pop-up menu with the options to edit the location.

Edit Location
  1. Search Address – Enter an appropriate address to replace the pin to that location
  2. lat-lng – Enter latitude/longitude values to replace the pin to that coordinate
  3. Current Location – To replace the pin to your current location
  4. Add Point – Manually plot a point on the base map

Now click Submit button to save the changes in the point GIS data

User can further edit the style of the points or share the map publicly or privately

How to style your polygon GIS data categorically

GIS helps users to understand patterns, relationships and geographic context. It benefit includes improved communication and efficiency, as well as improved management and decision-making. GIS combines datasets with maps, integrated regional datasets with any type of descriptive information or data. It provides mapping and assessment prerequisites for technology and almost every industry.

Visualization and intepretaion of data is what makes GIS a beautiful and interesting fields in data analytics. Science of visualization is the core essence in the art of cartography and mapping. Any type of geospatial features presented in the map with proper color combination, accurate size and location helps in better image interpretation. Quantity and category based representation of spatial features are the common visualization styles used in GIS.

IGISMap Styling Tools

IGISMap is a web platform providing multiple GIS applications that are most important in the field of geospatial analytics. The peculiarity of IGISMap in the GIS Industry is its UI/UX that helps the user to perform effortless geospatial operations. IGISMap provides the following styling tools:

  • Basic Style
  • Category Style
  • Quantity Style
  • Bubble Style
  • Icon Style

Among the styling options listed above – Basic, Category and Quantity styling options are used to style polygon and points, whereas Bubble Style and Icon Style are used to symboloze point GIS data. Basic Style will give any single color for the while GIS layer. Quantity Style is used to visualize the GIS data quantitatively. And Category Style will style your GIS map with separate colors assigned to each category of features

In this article we will talk about Category Style tool of IGISMap and how it can be used to categorically visualize your polygon GIS data like the following.

USA County Boundaries Data Categorized Based On States

Add your GIS data

For the demonstration, let’s add county boundary polygon data of USA from IGISMap GIS data collection. For this let’s use Add GIS Data tool of IGISMap.

Click to open https://story.mapog.com/app/tools/vector Upload Vector File tool.

After opening the Add GIS Data tool, in the Select Country section we will select United States of America. Then Search Layer section opens with the list of GIS data of USA, where we need to select ‘administrative county boundaries‘.

Add GIS Data

Before adding this data, lets check the data table of this data and verify the attribute field which we need to categorize this data. Switch the view from Map to Datatable and review the attribute fields. Here we are going to categorize the polygon features of county boundaries based on the state which it belongs to.

As you can see below, we have the attribute field for counties and the attribute field with states it belongs to.

Datatable in Add GIS Data

Since we have confirmed the data, lets continue downloading. First click the download icon beside the data name and then click the Add Layer button in the next section that opens.

Add Layer

Now the layer is published in the map with the name ‘united_states_administrative_county_boundaries

Data published from Add GIS Data

Click here – Download USA County Boundaries GIS Data

Open IGISMap Category Style tool

After adding the input GIS data from Add GIS Data, we can style the counties categorically using Category Style tool. For accessing the tool, click Tools button at the upper left side of screen to open the map tools popup. Then select Category Style tool listed under Style Your Data section.

Map Tools

We can also open the Category Style tool by going to the More option of input point data and choose the Category Style from the Edit Style option.

More options -Edit Style – Category Style

Styling GIS data categorically

Then the tool is appeared on the screen of IGISMap.

Category Style

Then the tool appears and we have to select the layer from Select Layer section which is the ‘united_states_administrative_county_boundaries‘ data that is published in this map and then we have to click Next option.

Select Layer

After clicking Next, in the Edit Layer section, we can change the style as we want. In this section we can can change Opacity and change the Border Width as required. Now in the Attribute field, select state field to categorize the counties based on its individual attributes values.

Edit Layer

After selecting the required attribute field, all individual values will be listed with different colors assigned for each category.

Select Attribute Field

We can change the color for each category by the color and choosing the right color. Then we have to click OK.

Assign color to each category

After changing all color of the attributes we have to click on Save Style for styling the map categorically.

Save the Style

Now as you can see the map is converted into categorical style and the output map is shown.

Polygon GIS data categorized

For better view and make your data more interactive in the map, go to More and enable Make Interactive option.

Make Interactable

Now as you see below, the USA county level boundaries GIS data is better visualized in state based categories and the map got more interactive.

Interactable Map

You can share your map with others in public or private mode. Article Share your Map will help you understand more about Share Map feature of IGISMap.

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