This tutorial provides a clear and detailed walkthrough for converting a SQLITE file into DXF format using the Converter Tool in MAPOG. Whether you’re a beginner or have some experience with MAPOG, this guide will help you smoothly convert your SQLITE files to DXF.
What is SQLITE Data Format:
A file with .sqlite extension is a lightweight SQL database file created with the SQLITE software. It is a database in a file itself and implements a self-contained, full-featured, highly-reliable SQL database engine. SQLITE database files can be used to share rich contents between systems by simple exchanging these files over the network. Almost all mobiles and computers use SQLITE for storing and sharing of data, and is the choice of file format for cross-platform applications. Due to its compact use and easy usability, it comes bundled inside other applications. SQLITE bindings exist for programming languages such as C, C#, C++, Java, PHP, and many others.
Converter Tool in MAPOG enables users to seamlessly convert data between different formats based on their specific needs. This tool simplifies the data transformation process for a variety of GIS applications, ensuring both flexibility and efficiency when working with multiple file types. For instance, MAPOG’s Converter Tool can convert SQLITE data into DXF format, reducing file size while preserving essential geographic information. This conversion improves the data’s compatibility with online mapping and interactive platforms, ultimately enhancing workflows and significantly increasing GIS data usability.
Steps to Convert SQLITE to DXF:
Step 1: Upload the Data:
Navigate to the header menu, click on “Process Data,” and then choose the “Converter Tool” option to begin.
2.To start the conversion, upload your SQLITE file by selecting the data you want to convert.
Step 2: Choose the Output Format
1.Set DXF as the desired output format for your data export. While the Converter Tool provides various format options, this guide is specifically dedicated to converting your file into the DXF format.
2. You can also Choose the Output Coordinate Reference System (CRS) according to your spatial analysis requirement.
Step 3: Execute the Conversion:
Head over to the ‘Convert Files’ section, and allow the tool to handle the conversion process for you. Just upload your SQLITE file, and the Converter Tool will seamlessly transform it into DXF format, making the conversion quick and easy.
Step 4: Review and Download:
Review your converted DXF file to confirm its accuracy. After ensuring that the conversion is correct and meets your requirements, proceed to download the file. This step is crucial to validate that the conversion was successful and that your data has been accurately preserved.
Need accurate coastal and marine boundary information? Now you can Download Maritime Boundary Data with ease using GIS Data by MAPOG. This intuitive platform supports over 15 GIS formats, including Shapefile, KML, GeoJSON, and MID, making it suitable for a wide range of geospatial tools. Whether you’re involved in marine conservation, coastal planning, or international boundary studies, MAPOG provides structured, ready-to-use datasets for seamless visualization and spatial analysis.
How to Download Maritime Boundary Data with MAPOG
The process is efficient and user-focused, offering access to maritime datasets across global water bodies. With over 900+ GIS layers and 200+ data themes, MAPOG ensures accessibility in formats like SHP, KML, MIF, DXF, CSV, GeoJSON, SQL, TOPOJSON, and GPX. This flexibility empowers professionals, researchers, and students alike.
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 Maritime Boundary Data
Step 1: Search Maritime Boundary Layer
Begin by navigating through the MAPOG interface and using the search function to find “Maritime Boundary Data.” Each layer includes detailed metadata and geometry type—whether it’s a line representing maritime zones or a polygon for exclusive zones.
Speed up your search using MAPOG’s “Try AI” feature. Just type queries like “Exclusive zones” or “Maritime boundaries near coastlines,” and the system instantly fetches relevant datasets. This feature is particularly helpful for new users or those exploring specific marine areas.
Step 3: Filter by Region
Use the Filter Data option to narrow your dataset by region, state, or district-level boundaries when applicable. This makes it easier to retrieve precise data, especially for local marine management, coastal development, or spatial policy-making.
Step 4: Add Layers to Map for Visualization
Click on the “Add on Map” option to view your selected maritime boundary layers in the analysis interface. This helps in examining overlaps, nearby zones, and distances—crucial for maritime planning and dispute resolution.
Step 5: Download Maritime Boundary Data
Once the layer is finalized, select the “Download” button. Choose from a sample or full dataset, select the preferred format (such as Shapefile, KML, MID, GeoJSON, etc.), agree to the terms, and complete the download process. The data can then be imported into platforms like QGIS, ArcGIS, or AutoCAD for further use.
Final Thoughts
With a few clicks, you can now Download Maritime Boundary Data in the format that best suits your GIS workflow. MAPOG’s rich repository, AI-powered search, and map-based tools make it a powerful resource for accessing high-quality geographic data. Whether you’re analyzing coastal zones or mapping maritime jurisdiction, this platform offers everything you need to make informed, data-driven decisions.
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.
Looking to map residential patterns or study human settlements with precision? Download Settlements Polygon Data easily using GIS Data by MAPOG—a robust platform that offers access to well-structured spatial datasets in over 15 GIS-supported formats such as Shapefile, KML, MID, GeoJSON, and more. Whether you’re planning urban infrastructure, conducting demographic analysis, or working on environmental studies, MAPOG’s detailed settlement polygons allow you to explore populated areas with accuracy and clarity.
How It Works – A Smart, Streamlined Process
GIS Data by MAPOG is designed with user experience in mind, offering a quick and intelligent way to access settlement boundaries from a massive database covering 900+ layers. You can Download Settlements Polygon Data in multiple formats including KML, SHP, CSV, SQL, DXF, MIF, and GPX. Whether you’re a professional, student, or policy planner, the platform ensures that you get high-quality data ready for integration into any GIS software.
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 Settlements Polygon Data
Step 1: Search for Settlement Layers
Begin by selecting your area of interest within the MAPOG interface. Use the search bar to locate “Settlements Polygon” layers. You’ll be able to check attributes such as population details, area, and density coverage.
The built-in “Try AI” feature can instantly fetch the most relevant datasets. Just type phrases like “Residential areas polygon” or “Settlements in a region,” and let the AI deliver accurate results without the hassle of manual browsing.
Step 3: Filter the Data for Precision
Narrow down your results using the Filter Data option. Whether you’re looking for settlement data in a specific district or state, this feature ensures you’re only working with the most relevant polygons.
Step 4: Add Data to Map for Live Visualization
Click on the “Add on Map” button to overlay your selected dataset onto the analysis interface. This allows you to visualize the shape and spread of settlements in real time, compare multiple layers, or assess accessibility and proximity to other features.
Step 5: Download in Your Preferred Format
Once satisfied with the dataset, proceed to download. Choose a sample or full version, select your required format—whether it’s Shapefile, KML, MID, or any of the supported 15+ options—agree to the terms, and initiate your download.
Final Thoughts
MAPOG makes it remarkably simple to Download Settlements Polygon Data for a wide range of GIS applications. The combination of smart search tools, flexible download formats, and interactive mapping ensures that your workflow remains efficient and insightful. Whether you’re building a city model, conducting a field study, or managing a development project, MAPOG gives you access to settlement polygons that are accurate, reliable, and ready to use.
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.
Need accurate and structured data for administrative infrastructure? Download Townhall Data easily using GIS Data by MAPOG — a robust platform designed to support urban planning, governance, and civic infrastructure analysis. Townhalls, as administrative buildings for local governments, play a crucial role in managing civic services, hosting council meetings, and engaging with citizens. With MAPOG, accessing geospatial datasets of townhall locations becomes smooth, reliable, and highly customizable, thanks to its support for over 15 GIS formats including Shapefile, KML, GeoJSON, and MID.
Why Use MAPOG to Download Townhall Data?
GIS Data by MAPOG is built to simplify geospatial data collection. It caters to planners, researchers, civic authorities, and GIS professionals by offering downloadable datasets that align with various GIS software. Whether you’re working on a local governance project, spatial urban study, or service accessibility model, you can download Townhall Data from MAPOG in your preferred format with ease.
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 Townhall Data
Step 1: Search for Townhall Data
To get started, navigate to GIS Data by MAPOG and use the search feature to locate “Townhall Data.” Each layer comes with rich metadata — you can quickly identify if the data is in point, polygon, or multipoint format based on the available attributes.
Not sure where to look? MAPOG offers an AI-assisted search feature called “Try AI.” Just type queries like “Townhall locations” or “Townhall data for selected area” and let the AI engine retrieve the most relevant datasets. This reduces search time and increases accuracy in dataset discovery.
Step 3: Filter by Region
The Filter Data option helps users refine their search further. You can narrow datasets down by selecting specific states, districts, or city levels. For instance, if the main dataset covers an entire country or region, this tool allows you to extract more localized information relevant to your analysis.
Step 4: Visualize Using “Add on Map”
The “Add on Map” button lets you overlay selected townhall datasets directly on the GIS interface. This helps you visualize their geographic distribution and spatial relationships instantly. It’s a crucial step for those who want to examine patterns, density, or service coverage zones before downloading the files.
Step 5: Download Townhall Data
Once the appropriate dataset is selected and verified on the map, proceed to download. You can choose between a sample version or full dataset. Then, pick the file format you need — such as Shapefile, KML, GeoJSON, MID, or others — agree to the usage terms, and download with a single click. The files are instantly ready for integration into your GIS workflow.
Final Thoughts
Whether you’re an urban planner, public policy researcher, GIS analyst, or a civic tech innovator, having access to structured, multi-format administrative location data is vital. Thanks to GIS Data by MAPOG, the process to download Townhall Data is both accessible and intuitive. Its smart search tools, data filters, and visualization options make it a go-to resource for high-quality, location-based datasets.
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.
In this guide, it will provide step by step of how the GeoJSON files can be easily and quickly converted to CSV format with the help of Converter Tool in MAPOG. So, both if you are a first-time user and a regular one, Converting GeoJSON to CSV with MAPOG, the entire process will be explained in simple steps for you.
Key Concept to Converting files
Converter Tool is a tool in the MAPOG Map Analysis used for the purpose of converting the information you have from one type to another. It’s like magic! You input data into it in one form, and you get it output in another form that you could use in your analysis. Moreover, GIS Data has a download in any format that means it is shift able in any kind of uses.
Online GeoJSON to CSV GIS Converter
Step 1: Upload the Data
1. Select the data through the “Process Data” and go to the “Converter Tool”.
2. Upload your GeoJSON file. This is your entry point where you feed in the information that needs conversion.
Step 2: Select the Format for Conversion
Select the output format as CSV or Comma-Separated Values if you want to expatriate only the data. The tool provides several options in arriving at the result but for this guide, we are using the option to convert the file to CSV.
2. You can also set the Output CRS at this stage.
Step 3: Run the Conversion
Go to ‘Convert Files’ and watch the tool at work. Working with the Converter Tool you input your data and then the tool converts it from the GeoJSON format to the CSV format.
Step 4: Review and Download
Take a moment to review your converted CSV data to make sure everything looks correct. Once you’re happy with it, go ahead and download the file. This step is really important to ensure that the conversion worked properly and that all your data is intact.
Step 5: Add Label Feature
1. We can add the Lebel on this map using the Label Feature in the map analysis interface. First, We need to go to the action button of the newly converted layer. Then select the Label feature from the drop down section.
2. Next, we need to provide the newly converted file in layer selection and the desired attribute in the feature name section. Label feature has the option to select the font size and color. When you are happy with it, Click the save button.
3. Now here you can see the newly converted data with all boundaries name mentioned into it.
That’s it! You’ve mastered the Converter Tool in MAPOG Map Analysis to turn your GeoJSON files into CSVs. Now, transforming your data is easier than ever, ready for any analysis you need. This handy feature streamlines dealing with various data formats, making your work smoother and more productive.
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In this article, my primary goal is to show you, from my perspective as a healthcare official, how I effectively use buffer analysis techniques with hospital point data specific to California. Throughout this article, I’ll walk you through the steps within MAPOG‘s GIS Buffer Analysis of hospital locations, a resource I personally consider indispensable in my role.
The core of this spatial analysis is about uncovering crucial insights into the geographic relationships and proximity of hospital locations within the state. By following the instructions provided here, you’ll gain a clear understanding of how I create buffers around these hospital points. These buffers, which are part of my responsibilities, reveal important spatial patterns and distribution insights regarding healthcare facilities in California. It’s a powerful tool that assists me in making informed decisions to enhance healthcare access and quality in our state.
Buffer Analysis
Buffer analysis is a spatial analysis technique used in geographic information systems (GIS) to create a zone or area of influence around a particular geographic feature, such as a point, line, or polygon. This zone, known as a buffer, is typically defined by a specified distance or radius and is used to analyze spatial relationships, proximity, and accessibility between features. Buffer analysis is valuable for various applications, including urban planning, environmental impact assessment, and determining service areas around facilities like hospitals, schools, or stores.
Below are the steps for Buffer Analysis of hospital locations
Step 1 – Select Buffer Tool
To initiate a buffer analysis using MAPOG, I begin by opening the application. Subsequently, I proceed to select the Buffer Tool, which is my preferred choice for adding data for in-depth spatial analysis.
Buffer Analysis Tool
Step 2 – Select Country
Once the Buffer Tool is selected, my next step involves choosing the specific geographical region for analysis. In this particular case, I opt to analyze the state of California, a region of paramount importance for healthcare planning and resource allocation.
Select Country
Step 3 – Select the Data Set
After choosing California for analysis, the next vital step is to smoothly add the hospital points dataset to the project. This dataset is fundamental to our thorough buffer analysis, enabling us to understand how healthcare facilities are distributed and accessible throughout the state.
Hospital Points
Step 4 – Create the Buffer Zone
With the hospital points dataset in hand, my next task is to define the buffer zone around these critical locations. To create a buffer with a radius of 5000 meters, I simply input “5000m” into the designated box, precisely specifying the desired buffer distance for the analysis. This step is pivotal in examining the spatial relationships and accessibility of healthcare facilities within the state of California.
Buffer Zone 5000m
After the initial buffer creation, I proceed to provide a more comprehensive illustration of hospital accessibility. This involves adding a second buffer with a radius of 10,000 meters, showcasing the typical range within which hospitals should ideally be accessible, typically ranging from 5 to 10 kilometers. This step is instrumental in highlighting the areas where healthcare services should be readily available to ensure optimal coverage and accessibility for the residents of California.
Buffer Zone 10000m
Step 5 – Add Other Feature Layers
To achieve a more thorough analysis and better grasp hospital distribution in California, I strategically choose to include county and city/town data in the project. This additional dataset significantly improves our comprehension by offering valuable context and insights into how healthcare facilities are spread across various administrative regions in the state. By examining the spatial connection between hospitals and these administrative boundaries, I can develop a more nuanced understanding of healthcare accessibility and resource allocation.
To easily enhance my project with county and city/town data, I use the “Add/Upload” option found in the upper-left corner of MAPOG’s interface. This valuable feature allows me to smoothly integrate extra geographic datasets, adding depth and context to my spatial analysis. This helps me conduct a comprehensive and insightful examination of hospital distribution in California.
Add Data
Result And Analysis
As I combine county borders, city/town data, and hospital buffer zones (5000m in blue and 10000m in red), my aim is to decipher the intricate patterns and factors affecting hospital distribution in California.
The different buffer colors, blue and red, act as important visual aids. They assist me in assessing how easily healthcare facilities can be reached within different administrative areas of the state.
Buffer Zones and Cities
As I analyze the image, a distinct pattern becomes evident: hospitals are notably concentrated within city regions, highlighted in green. This pattern resonates with my understanding of higher healthcare service demand in urban areas, owing to their greater population density and improved transportation access.
This observation underscores the critical importance of strategic healthcare planning and resource allocation. It highlights the imperative to address healthcare disparities, ensuring equitable access to medical services not only in thriving urban centers but also in the more remote or underserved regions across California.
Result and Analysis
When I examine the image, I clearly observe that hospitals do not have an even distribution across California’s counties. The reason for this uneven distribution is the varying population densities in different regions. It’s a reminder that when it comes to placing healthcare facilities, we must consider population and urbanization factors carefully. This understanding guides our healthcare planning and resource allocation efforts to ensure everyone in California gets the care they need, regardless of where they live.
As a healthcare officer, I find the results of this buffer analysis to be incredibly valuable for our strategic healthcare planning and resource allocation efforts. Here’s how we can put this information to good use:
Findings and Factors to Consider
Identify High-Traffic Hospitals: The buffer analysis helps us pinpoint hospitals within the 5000m (blue) and 10000m (red) zones, revealing those with higher patient visitation rates. This insight helps us understand where healthcare services are in high demand.
Capacity Assessment: We can assess the capacity and readiness of these hospitals to meet patient demand. This assessment may prompt decisions about expansions or improvements to ensure these high-traffic facilities can provide quality care efficiently.
Identify Underserved Areas: The analysis highlights regions with limited hospital access, particularly outside the buffer zones. These areas represent potential locations for establishing new healthcare facilities, addressing gaps in service coverage.
Emergency Response Planning: We can strategically position hospitals based on geographical distribution insights, ensuring efficient emergency response capabilities across the region.
Resource Allocation: The data helps us allocate resources effectively, whether it involves redistributing medical personnel, investing in new infrastructure, or deploying mobile healthcare units to reach underserved regions and improve healthcare access.
Community Health Promotion: We use insights from the analysis to inform our community health promotion and awareness programs, especially benefiting underserved communities with limited healthcare access.
Transparency and Public Engagement: Sharing analysis results with the public and local stakeholders fosters transparency and encourages valuable input into healthcare planning decisions.
I’ve found that utilizing MAPOG’s buffer analysis tool has been pivotal in uncovering these spatial patterns and revealing essential insights for our research.
In this case, we’ve harnessed its capabilities to gain a deeper understanding of healthcare accessibility and distribution, emphasizing the role of urban areas in healthcare infrastructure. This article serves as a testament to the value of MAPOG’s GIS Buffer Analysis of hospital locations in spatial research and planning, offering a practical and clear path to unlocking geographic insights.
Download Bhutan Map Shapefile GIS Data, Bhutan Districts , Bhutan Villages Shapefile data. Available in Shapefile, KML, GeoJSON, CSV
Have you been hunting GIS data too long and couldn’t find the right data or a proper data collection hub for fulfilling your requirements? Worry no more, IGISMAP GIS solutions offer a comprehensive collection of GIS data for over 150 countries, providing access to more than 150 datasets per country. Each dataset is carefully curated and accurately represents the administrative divisions of the respective countries. IGISMAP provides two essential tools for accessing this data: the Download GIS Data and Add GIS Data functionalities. Users can download the data in multiple formats, including ESRI Shapefile, KML, GeoJSON, or CSV, depending on their preferences and requirements. The platform ensures that users have a seamless experience in accessing valuable GIS data for their projects. Check the article – Add GIS data from IGISMap GIS data collection to understand more about Add GIS Data.
In this article, we will talk about IGISMAP GIS data of Bhutan and how it can be accessed from Download GIS Data tool. GIS data of almost all natural and man made geographic features are available for Bhutan. This article will give you an overview of all the administrative divisions GIS data available for Bhutan.
Note:
All data available are in GCS datum EPSG:4326 WGS84 CRS (Coordinate Reference System).
In Bangladesh, a village is the smallest territorial and social unit for administrative and representative purposes. It is an elective unit of a Union Council from which a single council member is elected. Usually one village is designated as a ward and each union is made up of nine villages.
Disclaimer : If you find any shapefile data of country provided is incorrect do contact us or comment below, so that we will correct the same in our system as well we will try to correct the same in OpenStreetMap.
Consider that you are working in the urban planning sector. Higher authorities in the sector have decided to develop the surroundings of the bank area. Your senior has assigned you a project to create a buffer so that later the architect can design the area separately.
When you are working with spatial operations and analysis, GIS is the best method to find a solution to any task. A geographic information system (GIS) is a system that creates, manages, analyzes, and maps all types of data.
IGISMap provides you with all the facilities for spatial operations and analysis without any difficulty. It is easy to use, and it saves your time.
How to upload file in IGISMap
An upload vector file is a GIS tool in IGISMap. This tool helps you to upload a file of your requirement.
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.
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.
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.
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.
For a GIS project, accessing the required data is the first step that determines the further workflow of the project. Online sources either provides the data or provide tools to work with data. There are very few web tools that provides important data and services to work with the data in a single platform. Yes, that is right – MAPOG is one of that kind, where you can find most demanding GIS data in vector formats with a number of tools to carry out analysis and other operations over the GIS data. In the article below we will how to add/upload data and merge polygons. In addition, to merge the feature you can addGIS Data i.e shapefile, kml, kmz, geojson etc.
GIS Data in IGISMap contains administrative boundaries such as country, states, districts, roads, railway lines, and other geographical features such as roads, farmlands, waterbody, etc. IGISMap gis data tool provides you data for 30+ countries, and 51 US states. Also, a few spatial data on a global level are also provided. These data can be directly accessed using Add GIS Data tool from the dashboard or from the map tools. Add GIS Data is also made available in certain IGISMap tools to help users access GIS data directly within the tool itself.
In Merge Polygonstool, Add GIS Data option is provided to access polygon GIS data of various administrative level boundaries of each country. Users can add any polygon data from IGISMap collection and merge the required polygon features. In this article we are going to see how this is done.
There are multiple options in Merge Polygons tool to add the input data. In this article, we will select Add GIS Data option to add the required data from IGISMap data collection. For demonstration, we will use the GIS data of local government area boundaries of South Australia. Thus we will select Australia from the Select Country list.
Add GIS Data – Select Country
After selecting the country, list of GIS data associated with Australia will open.
Add GIS Data – Select Layer
Scroll down or search for local government area in the search bar to filter the list to the required data. Select administrative local government area boundaries data from the list and click Add Layer icon.
Local Government Area Boundaries of Australia
Add Layer will preview the selected layer in the map and the options to crop the layer will be available in the tool. Since we only want the LGA boundaries of South Australia. Thus click the Crop Layer button and start drawing a polygon completely enclosing the LGA polygon features of South Australia and click Add Layer button.
Crop Layer
Add Layer button will publish the cropped LGA boundaries of South Australia on the map and the Select Polygon section of the Merge Polygons tool will open.
There are two options to select the required polygon features – Lasso Tool and Select Manually. We will use Select Manually option. After selecting Select Manually, click Select Multiple Polygon button. Now select the polygon features of Roxby Downs, Coober Pady, and Unincorporated SA boundaries, which we want to merge the polygons together. After selecting the polygons, click on the Submit button to start the process of merging the selected polygon features.
Select Polygon – Select Manually
In a few seconds, a new layer of the input GIS data of LGA boundaries gets published. In this layer, the selected polygon features are merged into a single polygon as shown below.
Polygons Merged and Published
Check the article Share your Map to know how to share your map with others using Share Map feature.
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