This guide provides a simple and thorough method for converting MIF files to CSV format using the Converter Tool in MAPOG. Whether you’re just getting started with MAPOG or have some experience, this tutorial will guide you through the smooth conversion of MIF files to CSV.
What is MIF Data Format:
MIF files are also known as MapInfo Interchange Format files, and often end in a .mif suffix. This format — developed and used by MapInfo for the export of maps and data — contains the data necessary for plotting map features (such as points, lines, or polygons) on a map. MIF files are often accompanied by MID files. MID files contain data attributes, but are not a mandatory addition to the MIF file form
MAPOG offers a sophisticated Converter Tool has 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 MIF data into CSV 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 MIF to CSV:
Step 1: Upload Your Data:
Go to the top menu, click on “Process Data,” then select “Converter Tool” to start the conversion process.
2. To start the conversion, upload your MIF file by selecting the data you want to convert.
Step 2: Select the Output Format:
Choose CSV as your desired output format. Although the Converter Tool offers multiple format options, this guide focuses solely on converting your file to CSV.
2. You can also Choose the Output Coordinate Reference System (CRS) according to your spatial analysis requirement.
Step 3: Run the Conversion:
Head to the ‘Convert Files’ section and let the tool handle the process. Simply upload your MIF file, and the Converter Tool will efficiently convert it into CSV format, ensuring a fast and straightforward conversion experience.
Step 4: Verify and Download:
Review your converted CSV file to ensure it meets your expectations. Once you’ve confirmed that the conversion is accurate and all data is correctly maintained, go ahead and download the file. This step ensures the conversion was successful and the file fits your requirements.
MAPOG feature enables users to create interactive, map-based narratives by merging geospatial data with text, images, and multimedia. This versatile tool is ideal for various fields such as urban planning, tourism, education, and environmental conservation. With customizable and engaging options, MAPOG delivers valuable insights into specific locations or themes, making it easier to present complex spatial data in a clear and compelling way. Whether for professionals, educators, or students, this intuitive platform simplifies the exploration and presentation of geographic information, offering a visually captivating experience.
Looking to download Land use Data for mapping, environmental planning, or spatial analysis? GIS Data by MAPOG offers a reliable and intuitive platform to access land use datasets in over 15+ GIS formats including Shapefile, KML, GeoJSON, MID, and more. Land use data provides crucial insights into how land is utilized—covering agriculture, urban zones, forests, water bodies, and industrial areas—making it essential for planners, researchers, and developers seeking informed, data-driven decisions.
How to Download Land use Data
With thousands of layers available, GIS Data by MAPOG simplifies access to landuse information from diverse locations. Whether you’re working on zoning analysis, environmental impact studies, or infrastructure planning, the platform supports an extensive range of export formats like KML, SHP, CSV, DXF, SQL, GPX, TOPOJSON, MIF, and others—ensuring compatibility with almost all GIS applications.
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 Land use Data
Step 1: Search for Land use Data
Begin by typing “Land use Data” in the search bar within the MAPOG interface. You can explore detailed attributes that classify areas into various land categories. Layers may be available in polygon format, ideal for representing zonal data visually.
Speed up your search using MAPOG’s “Try AI” feature. Just enter terms like “Land use in area” and the system smartly identifies the most relevant layers. This AI-powered assistance makes data discovery smooth and less time-consuming.
Step 3: Apply State and District Filters
Want to narrow down your search? Use the Filter Data option to drill into specific states and districts. This allows for high-precision data extraction, especially useful when working on localized land management or development plans.
Step 4: Visualize with “Add on Map”
With the Add on Map option, users can directly overlay selected landuse layers onto the map analysis panel. This feature enhances spatial understanding and allows for better decision-making through real-time visualization and comparison.
Step 5: Download Land use Data
After reviewing the map and dataset, click “Download Data.” You can select a sample version or the complete dataset, then choose from various GIS-compatible formats like SHP, KML, GeoJSON, MID, and others. Once you accept the terms, your file is ready for download.
Final Thoughts
To sum up, download Land use Data using GIS Data by MAPOG offers a flexible and user-friendly experience tailored for professionals across planning, GIS research, and environmental analysis. With powerful tools like AI search, advanced filtering, and multi-format export, MAPOG empowers users to retrieve detailed land use information effortlessly and efficiently. Whether you’re analyzing rural development trends or urban expansion, MAPOG makes your GIS journey seamless.
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 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.
Explore the world of WMS (Web Map Service) with IGISMAP! Easily view WMS layers on a map.
A Web Map Service (WMS) is an interface that lets a user access geospatial data, maps, and comprehensive information about certain features that are displayed on the map. Rather than the actual geospatial data, a “map” is described here as a visual depiction of such data. A web map service can create maps as images, collections of graphics, or packaged sets of geographic feature data. It can respond to simple questions about a map’s detail, and it allows us to know what maps it is capable of producing and which ones can be queried more deeply. Here in article you can Add View WMS Layer Online on your Map.
Exploring WMS Layers with Visual Guidance: Video Tutorial Roundup
Checkout video below for step by step process.
To open and view the WMS layer the user has to use any GIS software, which will require prior knowledge of GIS. However, the Add WMS tool on the MAPOG Tool website allows the user to open and view different layers and helps the data to interpret and analyze according to their own requirement. You can also download GIS data from MAPOG Tool and analyze in the same tool. From IGISMap Tool you can add data and share your map with others.
Get directed to Add WMS tool using the following –link
Let’s look into the application of Add WMS tool in MAPOG Tool.
Adding WMS file
Firstly, open the Add WMS tool, and select the WMS URL layer file from your system.
Add WMS Tool
After selecting the WMS URL, click on the Submit option.
Add WMS URL
A WMS layer file can encompass either single or multiple layers, all accessible and visible on the IGISMap website. To initiate, choose the initial layer within the file and click on the “Publish” button.
Adding WMS Layer
The chosen WMS layer can be published and displayed on the base map. Users have the option to add additional layers from the same WMS file by clicking the “Add another layer” button. Additionally, users can incorporate another WMS file by selecting the “Add another WMS” button. These straightforward steps allow users to effortlessly view and analyze both single and multiple-layered WMS files on the IGISMap website.
WMS Layer uploaded
Here are the other tools you can leverage within IGISMAP
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.
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.
Raster data in GIS are pixelated data format or images that are georeferenced. Here each pixel represent a geographic area storing the values of any parameter associated with that area. Parameters represented by raster images are mostly continuous in geography such as precipitation, elevation, temperature, vegetation indices etc. Raster images also represents categorical features such as land use land cover.
The conversion of an object’s geometry, color, texture, lighting, and other attributes into a display image is called the rendering of an image. It is the technique of creating a photorealistic or non-photorealistic image from a 2D or 3D model using a computer program. A geospatial raster is only different from a digital photo in that it is accompanied by spatial information that connects the data to a particular location. A raster image can be visualized in different styles such as categorical, quantitative, paletted, multiband etc. These visualization can be stored and saved, so that to be used in other platforms for image interpretations for remote sensing analysis.
IGISMap Upload Raster File tool can add the rendered raster image in GeoTIFF format. 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.
After opening Upload Raster File tool, Browse your system folder and select the rendered raster file. Then click on the Upload option.
Uploading the Rendered Raster image
About the rendered raster data
As we said in the introduction, the conversion of an image’s geometry, color, texture, lighting, and other attributes into a display image is called the rendering of an image. When it comes to GIS raster images, the alteration in geometry and style of visualization depends on pixel values.
The image that we have uploaded here is a stacked image of Landsat bands – Green, Red, and Near Infrared. And this stacked image is rendered into the style of False Color Composite, which we have uploaded here.
Raster image visualized
After successfully uploading, the rendered raster image is published on the map, which can be further analyzed through image interpretations.
Viewing of the Rendered Raster image
Sharing Map
Share Map will also work with map conatining raster image uploaded. For this, first click Share Map button at the map.
Share Map
The Map Operation menu will open up to enter and enable the details for the shared map. Click Next button after completing the settings.
Map Operation
Now two options will appear – Share Map and Embed Map. Here we will simply share the map without any security. So click Share Map and click Public.
Share map Publicly
Then select Share Map button to open the popup containing a link. Copy this link and share with anyone whom you want to share your map with raster data.
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.
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
Search Address – Enter an appropriate address to replace the pin to that location
lat-lng – Enter latitude/longitude values to replace the pin to that coordinate
Current Location – To replace the pin to your current location
Add Point – Manually plot a point on the base map
Now click Submit button tosave the changes in the point GIS data
User can further edit the style of the points or share the map publicly or privately
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.
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‘
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.
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, Bubble Style and Icon Style are used to symboloze point GIS data, whereas Basic, Category and Quantity styling options are used to style polygon and polyline GIS data. Bubble Style is used to style the point GIS data quantitatively and Icon Style is used to style point GIS data with the icon or categorically by assigning separate icon for each categories.
In this article, we will talk about how to categorically represent point GIS data using Icon Style tool of IGISMap and will walk through the steps to style your data categorically like the following
Administrative Locations in London
Uploading the data
For the demonstration, we will upload the point GIS data of administrative buildings locations in London city and categorize it based on types. First lets upload this data using Upload Vector File tool of IGISMap.
In the Select Layer section we have to click on Browse and select the input file from the system, which is the GIS data of administrative building locations in Lonndon named as London_admins. After opening the file, click Upload.
Uploading the file
After uploading, input GIS data will be visible on the IGISMap screen, represented by default icon style as shown below.
Point GIS Data plotted on map
Open IGISMap Icon Style tool
After adding the input GIS data, we can style the points categorically using Icon Style tool. For accessing the tool, click Tools button at the upper left side of screen to open the map tools popup. Then select Icon Style tool listed under Style Your Data section.
Map Tools
We can also open the Icon Style tool by going to the More option of input point data and choose the Icon Style from the Edit Style option.
More options
Styling point GIS data categorically
After the tool appears, we have to select the layer from Select Layer section which is the London_admins data that is published in this map and then we have to click Next option.
Select Layer
Then the Edit Layer section is appeared. Here we have to choose Category Icon. Now in the Attribute field, select admin field to categorize the point data based on its individual attributes values. You can also assign a default icons size to applied for every icon style in the Set Market Size box.
Icon Style – Category Icon
In the Icon Overlap, you can change the option between True or False. Choose True if you want the icons to be overlapping when the map is zoomed out. Select False if you want to see every point icons any zoom extend of the map.
After selecting the required attribute field, all individual values will be listed with different icons assigned for each category, with default marker size. We can change the icons for each category by selecting the edit option and choosing the right icon from the list provided. We can also assign appropriate marker size for each category at Set Marker Size section.
Setting Icon and Marker Size
After editing we have to click on Save Style for styling the point data.
Save the Style after Edit Layer
Following all the process we get the desired output on the screen of IGISMap.
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