5 Free GSI Heat Map Creation Tools Compared

More and more practitioners are looking to create heat maps using maps and publicly available data from the Geospatial Information Authority of Japan. The reasons behind this trend include a desire to treat location information as a distribution rather than by intuition, to produce easy-to-read visualizations suitable for reports, and to quickly grasp trends at sites and in regions. In particular, for disaster prevention, urban planning, facility management, sales-area analysis, organization of traffic flows, and visualization of inspection records, there are many situations where heat maps that show trends with gradations are easier to understand than simple point plots.

On the other hand, many people struggle with concerns such as, "I want to create heat maps but can't use expensive dedicated environments," "I can view data from the Geospatial Information Authority of Japan, but I don't know how to process or overlay it," and "There are so many free tools that I can't choose one that fits my work." In fact, there are several ways to get started for free. However, not every method works the same, and if you don't choose the type of tool that matches your purpose, operations can become cumbersome and the information you want to show may not be expressed well.

This article is for practitioners who search for "ヒートマップ 国土地理院". It organizes five approaches to heatmap creation tools that can be used for free, and explains each while comparing their characteristics, suitable use cases, and caveats. Rather than relying on specific product names, the summary is based on criteria that make practical decisions genuinely easier, so you should be able to find an approach that fits your work.

Table of Contents

• Things to organize before making a heatmap with Geospatial Information Authority of Japan data

• Overview of 5 free tools for creating Geospatial Information Authority of Japan heatmaps

• A browser-based map overlay tool

• A simple visualization tool that easily integrates with spreadsheets

• Analysis-focused tool using free GIS software

• A no-code visualization tool with powerful open-data integration capabilities

• An extensible tool that uses an open-source development environment

• Decision criteria to avoid mistakes when selecting free tools

• Summary

Things to organize before creating a heat map using data from the Geospatial Information Authority of Japan

First and foremost, it’s important to understand that the purpose of a heatmap is not simply to “color a map.” The real value in practice comes from converting location data into a form that can be read as density, frequency, skew, concentration, and dispersion, and using that to inform the next decisions. Therefore, before choosing a tool, you need to clarify what you want to visualize.

For example, the required data granularity changes depending on whether you want to overlay inspection-record locations to identify areas with many anomalies, overlay disaster histories to observe risk trends, or understand concentrations of visits or traffic. In some cases a simple collection of positions is sufficient, while in others the data must include counts, time of day, attributes, and weighting to produce a meaningful heat map.

Next, you should consider what to use as the background map. Maps and related data from the Geospatial Information Authority of Japan (GSI) include many elements that aid on-site understanding—such as terrain, elevation, aerial photography, administrative boundaries, and fundamental map information—and are particularly well suited to operational use. Because you can overlay heat maps while capturing terrain relief and the contextual characteristics of the land that are difficult to grasp on general maps, they improve not only appearance but also the accuracy of decision-making.

However, using Geospatial Information Authority of Japan (GSI) data does not automatically produce a good heat map. If the original data’s coordinates are misaligned, positions will not match, and if the extent is set too wide the gradations will be blurred. Conversely, if it is set too narrowly, local biases may be overemphasized and the overall trend misread. When choosing free tools, it is important to prioritize how coordinates are handled, consistency with the basemap, and ease of updating data over flashy appearance.

Overview of 5 Free Tools for Creating Geospatial Information Authority of Japan (GSI) Heat Maps

Free methods for creating heat maps can broadly be categorized into five types. The first is opening a map in a browser and overlaying location data for a simple display. The second is using data organized in spreadsheet format to produce basic map visualizations. The third is using free GIS software to perform full-fledged analysis. The fourth is connecting external data via no-code tools to create easily shareable interfaces. The fifth is building in an open-source development environment for maximum flexibility.

These five should be chosen based on suitability rather than superiority. If you want to try something immediately, the browser-based type is advantageous; if you want to create clear figures for reports in a short time, the simple visualization type is more suitable. If you prioritize analytical accuracy, the GIS type is strongest, and if you plan for continuous operation or sharing among multiple people, the no-code type is convenient. If you foresee future feature additions or integration with business systems, the extensible type becomes a candidate.

In practice, you don't need to commit to a single option from the start. Rather, it's less likely to fail if you prototype using a simple method and then move to a different method for full-scale operation. From here, we will look in detail at the characteristics of each.

Browser-based map overlay tool

The simplest option is to display a map in the browser and overlay point data or simple layers to create a heatmap. The main advantage of this method is how easy it is to adopt. It doesn’t require setting up a dedicated environment, the interface is often intuitive, and it’s well suited to the initial stage when you just want to see what the distribution looks like.

An advantage is that it pairs well with data from the Geospatial Information Authority of Japan (GSI), making it easy to check how density distributions appear while switching background maps. For example, on flat terrain you can often judge solely from the shading distribution, but on slopes or near rivers it’s easier to understand if you overlay it on a background map that conveys terrain and elevation context. Because browser-based tools make this switching easy, they are well suited for initial on-site assessments.

However, as a trade-off for convenience, there are limits to detailed analysis. You may not be able to finely adjust parameters such as heatmap radius, blur, weighting, and aggregation conditions, and while you can create visuals, it can be difficult to carry out analysis grounded in solid evidence. Also, as the number of data records increases, the display may become sluggish, and even a slight difference in coordinate format can cause delays when loading.

This model is suited to trial deployments, obtaining a high-level overview for meetings, and creating a draft for on-site explanations. Conversely, when using it for audit responses or formal analytical work, you should not take the displayed results as conclusions but instead repeatedly verify them by other methods. While it’s easy to get started for free, do not forget that apparent visual clarity does not guarantee the correctness of judgments.

Lightweight visualization tool that easily integrates with spreadsheets

Another promising option is a simple approach that visualizes data organized in spreadsheet format. In many workplaces, raw location data are managed as lists with latitude and longitude, record tables with addresses, ledgers of inspection histories, or pre-aggregated count tables. With such data, it is more natural to first organize them as tables and then import them into a map.

The appeal of this format is that it makes it easy to link organizing input data with visualization. For example, if you include columns for each date, each person in charge, and each type of anomaly, it becomes easy to switch which attribute you render as a heat map. In practice, because there are many situations where you want to see "biases narrowed down to specific conditions" rather than simple location density, being able to visualize while maintaining a tabular list is a major advantage.

Moreover, spreadsheet formats have the advantage of being easy to share with stakeholders and of making revision histories easy to track. They also fit easily into a workflow in which on-site staff enter data, managers review it, and visualization staff ultimately map it, making them a method that is easy to operate within an organization. In particular, they are well suited to the early-stage request of "first, we want to see existing records on a map."

On the other hand, this format requires careful attention to coordinate accuracy. When deriving positions from addresses, errors are easily introduced, and facility-name-based data may be replaced by representative points for their locations. If, when overlaid with maps from the Geospatial Information Authority of Japan, points appear offset from the expected locations, you need to review how the original data are maintained. Also, if table organization is sloppy, the visualization results will naturally be unstable. Empty fields, inconsistent notation, duplicates, and the mixing of old coordinate systems all cause reduced accuracy regardless of whether the data are free.

This method is strong for internal reporting, daily operations, and simple analyses, but it is not suited to geographic computations or advanced spatial analysis. If you plan to use it in business, a realistic approach is to first solidify operations on a spreadsheet-based system and, as needed, develop it into a GIS-based model.

Analysis-focused tools using free GIS software

If you prioritize accuracy and reproducibility, using free GIS software is the most practical method for real-world work. A major feature of this approach is that it treats heatmaps not merely as color visualizations but as a form of spatial analysis. You can carry out a series of tasks relatively thoroughly—not only density distributions of point data but also extent extraction, attribute filters, aggregation units, overlaying with background data, and adjusting output maps.

This approach also has strengths when handling Geospatial Information Authority of Japan data. By not only looking at the base map but combining it with information such as terrain, elevation, administrative boundaries, roads, and land use, it becomes easier to interpret why biases occur in certain places. Rather than simply finding dense areas, because it lets you delve into the reasons behind the trends, reports and proposals tend to be more persuasive.

Furthermore, the ease of repeatedly recreating the same output under identical conditions should not be overlooked. In practice, the same analyses are often repeated regularly—monthly updates, quarterly updates, and year-on-year comparisons. GIS-based approaches are easy to reproduce once procedures are organized, and they make it relatively straightforward to produce consistent maps even when the person responsible changes. This is valuable even if it is free.

However, challenges include that it takes time to become comfortable with the interface, and beginners can be easily overwhelmed by the large number of features. The heat map also has many configuration options, and if you adjust them without understanding the meaning of radius and weighting, the result may look plausible but be difficult to interpret. In addition, because a basic understanding of the data's coordinate system and layer management is required, it is somewhat risky for complete novices to use it directly in real-world production work.

Even so, as a way to achieve this for free, it is extremely promising. If you will be handling heatmaps continuously in your work, ultimately understanding this approach will broaden the range of applications. It is especially suited to organizations that prioritize long-term operation and accuracy over short-term convenience.

No-code visualization tool with strong open data integration

If you consider not only the site but also sharing with management departments and other stakeholders, a visualization type that lets you build screens with no-code is also a strong option. This type is characterized by its ability to load data, switch display conditions, and easily compile everything into a screen for viewing. It is easy to use even without extensive specialized knowledge and is suited to situations where multiple people want to look at the same map while discussing.

When combined with Geospatial Information Authority of Japan data, one attractive feature is that it lets you provide geographic context on the background map while changing heatmap display conditions for comparison. For example, when you want to change the display by period, by category, or by location, allowing not only analysts but also viewers to interact with the display makes it easier to understand than distributing static materials. This is effective for internal briefings, government explanations, and stakeholder meetings.

Also, the high shareability of this format is an advantage. Not only can you deliver analysis results as images, but it is also easy to set up a system that allows people to view updated maps as needed, so data use is less likely to be a one-time occurrence. Because heat maps often change meaning over time, being able to establish a system for continuous review is a major practical strength.

On the other hand, no-code platforms may be strong at presentation but can fall short of GIS-based systems in terms of analytical depth. They can struggle with fine spatial processing and precise computations, so you may need to preprocess the source data separately. Also, even if you can start for free, you should be aware of operational conditions and feature limitations. Whether the free tier is sufficient depends on the number of viewers, update frequency, and the volume of data handled.

Therefore, this type is less likely to fail if you think of it as a "presentation mechanism" rather than the "main player of analysis." First create heatmaps by other methods, and in sharing situations it is realistic to combine that with a no-code approach.

Extensible tools that use open-source development environments

The most flexible approach is to build the heatmap display yourself using an open-source development environment. This approach is suitable when you want to finely adjust the display methods and processing to match operational requirements. It makes it easy to flexibly combine features such as switching base maps, controlling the display area, aggregating by condition, and representing temporal changes, and it also offers high scalability for future expansion.

In operations using data from the Geospatial Information Authority of Japan, simple visualization is often not enough, and there are cases where it is desirable to handle field data, ledger data, inspection results, photo location information, and so on in an integrated way. In such cases, the extended type is very well suited, making it easy to prepare the necessary screens and processes in-house, and it is also attractive for its ability to be adapted to an organization's own operational rules.

Also, even the same heat map can convey very different meanings depending on what you choose to emphasize. The value of the visualization changes depending on whether you shade by number of occurrences, weight by importance, restrict the time period, or show differences from a baseline. With an extensible implementation, such condition designs can be implemented flexibly, enabling representations that align with business operations.

However, the hurdles are, of course, relatively high. Knowledge of setup and maintenance is required, and you should be aware that it tends to lead to reliance on specific personnel. Although you can start for free, the time cost is by no means small. While it may be fine for individual prototyping, in organizational operations you need to consider transferability and maintenance arrangements.

This approach is not necessarily suitable for everyone. However, for organizations that already have map usage incorporated into their operations and want to continue improving over time, it is the most promising option. Rather than simply jumping at the word "free," it is important to evaluate it in light of your company's technical setup and the frequency of updates.

Decision Criteria to Avoid Failure When Selecting Free Tools

We've looked at five types so far, but when actually choosing one, it's important not to judge solely by whether it's free. What often causes failure in practice is becoming complacent because there is no upfront cost and overlooking the effort required for data preparation and update procedures. A heatmap is not something you create once and forget; as source data increases, the scope of coverage changes, or the audience you're showing it to changes, you'll need to revisit how it's constructed.

First, what I want to confirm is the division of roles: who creates the data, who updates it, and who views it. If one person handles everything, a somewhat complex operation isn't a problem, but if multiple people are involved, ease of input, ease of handover, and reproducibility become important. Especially in on-site operations, if only the person responsible for visualization understands the system, ongoing operation tends to stop.

Next, an important consideration is the level of accuracy you require. If you are only looking at trends, a simplified approach may be sufficient, but when differences in position directly influence operational decisions, the accuracy of the coordinates becomes critical. Even a small misalignment between the basemap and point locations can lead to misinterpretation in the field. In many cases, you should prioritize quality control of the source data and positional accuracy over visual appeal.

Moreover, the form of the deliverable also influences the choice. Whether you want a static image to paste into meeting materials, an interactive screen to share, or something to include in a regularly updated report will change which format is appropriate. When comparing free tools, it’s easier to decide based on "what you ultimately want to produce" rather than by looking at a list of features.

And it's also important what you overlay on the heat map. The value of Geospatial Information Authority of Japan data is not only that it's easy to read as a background map. By interpreting terrain, elevation, and land conditions, you can make judgments that go beyond a mere distribution of colors. That's why you should check whether you can change the background, view it together with other layers, or clip out only the area you need.

The essence of choosing free tools is not to reduce initial costs, but to find a way to integrate into your workflow with ease. Can it be updated with ease, explained with ease, and scaled to the next stage when necessary? If you choose from this perspective, you can reduce the likelihood of major failures.

Summary

Free tools for creating Geospatial Information Authority of Japan (GSI) heat maps are not limited to a single correct choice. If you want to try something immediately, a browser-based map-overlay type is suitable, while if you want to leverage existing record tables, a simple visualization type that easily integrates with spreadsheets is convenient. If you require analytical accuracy and reproducibility, an analysis-focused type using free GIS software is a strong candidate; if you want to improve shareability, a no-code visualization type is preferable; and if you are looking ahead to future business integration, an extensible type is a viable option.

The important thing is not to create a pretty heatmap, but to organize location information in a way that helps business decision-making. Geospatial Information Authority of Japan (GSI) data is excellent as background information for that purpose, and there are plenty of options that can be started for free. That is why it is realistic to begin by testing the smallest configuration that meets your goals and, through updates, develop it into a method that fits your operations.

Furthermore, while heat maps are powerful for understanding past records and distribution trends, a different approach is also needed when you want to verify positions on site with high accuracy. For example, when you want to improve the accuracy of coordinate verification and positioning on site while viewing Geospatial Information Authority of Japan data as a background, an iPhone-mounted high-precision GNSS positioning device such as LRTK is effective. In the office, you can grasp trends with heat maps, and on site, by handling your current location and target positions at the centimeter-level (half-inch accuracy) with LRTK, it becomes easier to operate in a way that connects visualization and actual measurement. If you want to take business improvement using Geospatial Information Authority of Japan data one step further, considering not only heat map creation but also on-site coordinate acquisition and verification methods will lead to improved operational efficiency.