5 Steps to Create a Heatmap of Elevation Data from the Geospatial Information Authority of Japan

When you want to create a heatmap using elevation data from the Geospatial Information Authority of Japan, the first things you’ll run into are which dataset to choose, how detailed your view should be, and how to connect the color-coded results to practical work. Although it may look like you are simply creating a colored map, in reality there are many elements to address: data granularity, range/extent settings, handling of coordinates, treatment of missing values, and color interval settings. If you proceed with these matters left ambiguous, you may produce a visually pleasing figure that is nevertheless unsuitable for decision-making.

On the other hand, if you organize the steps and think them through, elevation data from the Geospatial Information Authority of Japan becomes a powerful resource for intuitively grasping terrain differences and trends. There are many situations in field work where it is useful—disaster countermeasures, land development planning, drainage studies, maintenance management, understanding terrain before construction, and so on. This article, aimed at practitioners searching for "ヒートマップ 国土地理院", organizes the workflow for converting GSI elevation data into a heatmap from a practical perspective, including points where people tend to get confused. Rather than merely explaining how to draw a map, it delves into the thinking required to produce a map that is actually useful.

Table of Contents

• Fundamentals to understand before creating a heatmap of the Geospatial Information Authority of Japan's elevation data

• Step 1: Clarify the purpose and scope first

• Step 2: Select the appropriate elevation data from the Geospatial Information Authority of Japan

• Step 3: Format the data to make it easy to create a heatmap

• Step 4 Design color-coding rules and visualize them for clarity

• Step 5: Finalize into a form that facilitates interpretation and practical decision-making

• Common Pitfalls When Creating Heat Maps

• Summary

Basics to understand before visualizing the Geospatial Information Authority of Japan's elevation data as a heat map

The term "heat map" is used broadly, but here it refers to a diagram that represents the magnitude of numerical values across an area using differences in color, allowing distributions and imbalances to be understood intuitively. It can be applied not only to temperature or human movement but also to terrain data such as elevation. When elevation is shown in color, boundaries between low and high areas, valleys, ridges, gentle slopes, and steep slopes become easy to grasp at a glance. Even in situations where reading contour lines alone requires experience, adding color gradations and variations makes the material easier to explain to non-specialist stakeholders.

However, simply color-coding elevation data does not necessarily produce a good heat map. Elevation is a continuous variable, and the impression can change greatly depending on the display range and how the colors are stepped. For example, when displaying a wide area of flat terrain with only small elevation differences, most of the map can end up the same color and become a figure from which nothing can be read. Conversely, if local elevation differences are overemphasized, the relief can appear larger than it actually is and lead to mistaken judgments. In other words, when creating a heat map, not only the correctness of the source data but also the purpose, the scale, the extent shown, and the color gradations used to represent it are important.

Also, elevation data from the Geospatial Information Authority of Japan (GSI) is useful as a foundation for understanding terrain, but it does not always exactly match the latest on-site conditions. In areas where land development, excavation, embankment, road improvements, or disaster recovery have progressed, discrepancies can occur depending on when the terrain was last updated. Therefore, heat maps should not be treated as definitive, final documents, but rather as maps to be used as starting points for on-site assessment and additional verification. In practice, a realistic workflow is to first use GSI data to gain a broad understanding of the situation, and then follow up with on-site surveys, as-built verification, and position checks.

Furthermore, elevation data come in different resolutions, and data that appear more detailed are not always more accurate. The appropriate level of granularity varies depending on whether the target is a wide area or a local one, and on the theme you want to examine—whether it's trends in inundation, consideration of land development plans, or a rough comparison of cut-and-fill. Rather than diving into the details from the outset, start with an overview and refine as needed; thinking in that order reduces wasted effort when creating heat maps.

Step 1: First clarify the purpose and scope

The first step is to clarify what the heatmap is being created for. If this is vague, subsequent data selection and color-coding will all end up half-baked. A common mistake among practitioners is to first obtain elevation data from the Geospatial Information Authority of Japan and try applying colors, then decide the rest later. However, although this may be useful for checking appearance, it rarely yields a truly usable deliverable. By defining the purpose in advance, the required extent, resolution, color gradation, and output format naturally fall into place.

For example, the area you need to examine varies greatly depending on whether you want to see broad terrain trends, understand elevation differences on a planned development site, or anticipate drainage flows. If you cram too large an area into a single map, important local variations will be obscured. Conversely, if the area is too narrow, you won’t see the relationship with surrounding terrain, weakening the basis for decision-making. It’s important to decide in advance not only on the target site but also how much of the surrounding area to include. If you want to see the connections of valleys, ridges, and drainage basins, including a bit beyond the site boundary rather than cropping strictly to it will produce a more meaningful heat map.

Additionally, it’s important to decide the unit of comparison in advance. How you create the visualization changes depending on whether you want to view absolute elevation or relative height differences. A heat map of absolute elevation is suited to understanding elevation relationships across an entire region. On the other hand, if you want to inspect micro-topography of a development site or within a plot, a relative representation that colors values according to the zone’s minimum and maximum makes differences easier to read. If you don’t distinguish these, you may apply color settings that work for a wide area directly to a small area and end up producing a map that appears flat.

Furthermore, it is important to consider who the material will be shown to. Readability requirements change depending on whether it is for engineers, for the client, or for internal decision-making. For engineers, it may be better to prioritize numerical ranges and evenly spaced color settings. On the other hand, for stakeholder briefings you should limit the number of color steps, simplify the legend, and favor representations that convey meaning intuitively, which are easier to understand. The purpose of a heat map is not to make it look pretty, but to make it communicate. Sharing that premise up front prevents the direction of subsequent work from drifting.

Step 2 Select the appropriate elevation data from the Geospatial Information Authority of Japan

Once the purpose and scope are determined, the next step is to select from the Geospatial Information Authority of Japan's elevation data the dataset that suits your target. What is important here is to understand the nature of the data available and to choose appropriately according to the target area and required accuracy. The GSI's elevation data include formats that hold elevations on a grid, allowing elevation values at regular intervals to be treated as the height of the earth's surface. Such data pair well with areal visualizations and are easy to use as a basis for heatmaps.

However, the fineness of the grid and the extent of the target area must always be considered in balance. Using a fine grid over a wide area makes processing heavier and the visualization prone to information overload. Conversely, using a coarse grid in a small site will cause subtle elevation differences to be lost. In other words, the basic idea is fine data when you want to see detailed sites, and slightly coarser data when you want to see broad trends. In practice, it is efficient to first grasp the overall picture with data for surveying a wide area, and then switch to finer data only for the necessary locations.

When selecting data, you should also pay attention to the update timing and acquisition conditions. Although elevation data from the Geospatial Information Authority of Japan is highly reliable as a public baseline, if a site has been modified recently those changes may not be fully reflected. In particular, for newly developed land, areas under construction, or sites immediately following disaster recovery, it is safer not to assume that differences in heatmap colors directly indicate current ground elevation. Therefore, before using it you should clarify whether the target area is relatively stable terrain or has been altered recently. Heatmaps are useful not for completely replacing current conditions but for understanding terrain trends and identifying locations that require further verification.

Also, attention must be paid to the effects of the sea, rivers, water surfaces, structures, and the handling of missing values. Elevation data may include places where values are missing or areas that require careful interpretation even if they appear continuous. If these are color-coded as-is, they can appear as unnatural extreme colors or hole-like displays and lead to misinterpretation. Therefore, at the data selection stage, it is important to quickly check what kinds of features are included in the area and to proceed on the assumption that unnecessary parts will be excluded.

When working with elevation data from the Geospatial Information Authority of Japan, it is essential not to visualize the data immediately after acquisition but first to understand what the data can and cannot reveal. In particular, heat maps are highly visually persuasive, so viewers tend to accept color differences as facts. For that reason, creators need to understand the limitations of the source data and use it only when they are able to provide appropriate explanations.

Step 3: Format the data to make it easy to create a heatmap

After selecting the elevation data, carry out the preprocessing needed for heat map generation. This step is often overlooked, but it actually has a major influence on the final result. Preprocessing refers to the preparatory work before visualization, such as clipping the target area, removing unnecessary parts, checking for missing values, ensuring coordinate consistency, and organizing how the grid is handled. If this step is done roughly, the map itself can appear distorted even before coloring, or unwanted color unevenness can occur.

The first thing you should do is crop to the target area. If you use a large-area dataset as-is, not only does processing become heavier, but the color reference gets pulled across the whole area, which can bury the changes in the places you really want to see. Clearly define the target site and the necessary surrounding area, and extract only that range so the color classification works appropriately. Especially when looking at a site-level view, simply excluding unnecessary mountainous or low-lying areas can greatly improve the readability of the figure.

Next, it is important to check for missing values and outliers. If there are gaps or extreme values in the elevation data, the color distribution can become unnatural and even distort the legend’s range. For example, if a very small number of extreme values pull the scale, the overall color contrast can be compressed, effectively producing a heatmap that is almost a single color. For this reason, instead of simply adopting the raw maximum and minimum values, it is important to check for skewness in the distribution and, when necessary, narrow the display range to practical values. You need to consider not only statistical rigor but also the goal of producing figures that are readable in the field.

Furthermore, you should also properly organize how coordinates are handled. If you plan to overlay the heat map with other map data or later use it to verify locations, it is unusable in practical work if the positions are not aligned. Even if it looks plausible visually, it becomes a weak basis for decision-making if it is offset from actual on-site features. In particular, when you want to overlay multiple sources for explanation, it is essential to format them while being mindful of the reference coordinate system and positional reference. A heat map is not a standalone figure; it gains value when linked to other drawings and on-site information.

Also, where appropriate, the concept of smoothing may be incorporated. If gridded elevation values are colored as-is, for some subjects fine mottling can become pronounced and trends may become harder to read. In such cases, it is effective to slightly suppress local variability and use techniques that make the continuity of the surface easier to perceive. However, if overdone, important bumps and depressions can be lost, so it is important not to prioritize smoothness too much. In practice, when shaping the data you should base decisions on whether the representation prevents misinterpretation rather than on visual prettiness.

Step 4: Design color-coding rules and visualize them for clarity

The core of heatmap visualization is designing the color-mapping rule. Even with the same elevation data, simply changing how colors are applied can greatly alter readability and meaning. The most important thing is not whether the colors are flashy, but whether differences are conveyed correctly. For heatmaps used in the field, minimizing misunderstanding takes precedence over making a strong impression.

First, you should consider how many levels to use in the color scale. If there are too many levels it may look detailed at first glance, but the legend becomes complicated and it becomes hard to tell what is actually important. Conversely, if there are too few levels, differences are lost. In practice, it is effective to limit the number of levels to the minimum that still lets viewers discern changes, depending on the audience and purpose. A practical approach is to use slightly finer gradations for technical review and slightly coarser ones for explanatory purposes. The important thing is not to demonstrate expertise by using many colors, but to organize the scale so that only the differences necessary for decision-making are visible.

Next, decide where to place the color range. Assigning colors mechanically from the target area's minimum to maximum values is easy to understand, but in practice it is not always optimal. On flat terrain with only slight elevation differences, narrowing the range makes those differences more visible, while in regions with large relief you need to set a wider range or you will end up with large areas of extreme colors. In other words, you should adjust the display range to match the differences you want to read, rather than the absolute values themselves. This is not an arbitrary manipulation but a design decision to correctly interpret the terrain.

Additionally, attention must be paid to the flow of color. A color scheme that can be intuitively perceived as continuous from low areas to high areas is desirable. If there are large jumps in hue, the same continuous surface can be misinterpreted as having steps. What matters is not the flamboyance of the colors themselves but the continuity and the readability of boundaries. In particular, when you want to interpret drainage directions or ridge-and-valley relationships, representations that clearly show continuous change are effective.

Also, a legend is not merely supplementary information—it is the way to read a heat map. If the legend is ambiguous, you won't know how many meters the color differences represent or which ranges correspond to the same evaluation. The legend must be concise while clearly specifying the numerical ranges. Moreover, preparing the scale, the area covered, and any necessary annotations turns a simple figure into explanatory material.

A common mistake here is prioritizing appearance too much. Diagrams that use vivid colors attract the eye, but in practical use they become tiring to look at for long periods and present challenges for accurate reproduction when printed. What looks good on a screen is not the same as what is easy to use as meeting or explanatory material. A heat map is a tool for decision-making, not decoration. Designing color coding with that premise in mind helps avoid unnecessarily flashy expressions and brings the figure closer to one that conveys the terrain’s characteristics straightforwardly.

Step 5 Refine into a form that enables interpretation and practical decision-making

A heat map is not something you create and consider finished. Ultimately, what matters is what you read from the figure and which decisions you derive from it. If you produce it without keeping this in mind, it will remain a pretty visualization and fail to translate into practical results. In the final stage, you need to be able to clarify how to interpret the color distribution, which areas to focus on, and what additional checks should be performed.

For example, places where low colors are contiguous may not simply indicate low elevation but could be related to a tendency for water to accumulate and to considerations in drainage planning. Places where high colors continue in bands may indicate ridge-like topography or a tendency for elevation to rise. Areas of abrupt color change may indicate slope transitions or boundary-like terrain changes. In this way, a heatmap is used to read the meaning of the terrain rather than just the colors. When creating one, overlay the site boundary, major features, and the minimum necessary auxiliary information to make interpretation easier and improve practical usability.

Also, rather than leaving it as a single standalone figure, it is effective to give a comparative perspective. For example, using both a wide-area version and a local version makes it easier to grasp the flow of surrounding terrain and the elevation differences within the site at the same time. Alternatively, organizing slope and catchment concepts as complementary information in addition to an elevation heat map can reveal meanings beyond merely high and low. On site, what matters more than the elevation difference itself is what that difference causes. Therefore, the final deliverable should be prepared not as a colored image but as terrain documentation that serves as an entry point for decision-making.

Furthermore, you need to be mindful of how this links with on-site verification. The heat map produced from the Geospatial Information Authority of Japan's elevation data is extremely useful for preliminary studies and obtaining a broad overview, but at construction and maintenance sites an on-site verification step to confirm differences from the current conditions is indispensable. In particular, where excavation or embankment has progressed, where many temporary works are present, or where minute elevation differences are critical, it is safer not to draw conclusions based solely on desk-based data. By using the heat map to identify suspect locations and areas that should be prioritized for checking, and then concentrating on on-site verification there, you can reduce rework while improving efficiency.

In other words, finishing is not about tidying the appearance of the figure, but about bringing it into a state that leads to the next action. A good heat map enables the viewer not only to tell where things are high or low, but also to decide where to go to look, where to pay attention, and where to perform additional surveying.

Common Pitfalls When Creating Heatmaps

When creating heat maps from the Geospatial Information Authority of Japan (GSI) elevation data, there are several common points in practice that tend to lead to failure. The most common is assuming that simply applying colors to elevation data will produce a usable map. In reality, unless you organize the target area, color range, legend, handling of missing values, and the relationship with surrounding terrain, you will not get a meaningful map. A heat map is not a representation that automatically delivers the correct result; it only becomes effective when designed with intent.

Another common mistake is treating broad-scale and local-scale areas with the same approach. A color scheme that is appropriate for understanding broad-scale terrain can make differences indistinguishable when brought down to the site level. Conversely, applying a color scheme emphasized for site use to a broad area yields an exaggerated portrayal of relief. Even with the same elevation data, the design must be adapted to the target scale. If you cannot switch between these, you can end up with maps that exist but are not useful.

Moreover, being swayed by flashy visuals can also cause failure. If you try to make a figure stand out in presentation materials and oversaturate the colors, boundaries can become ambiguous and it may be difficult to reproduce in print. A heat map is not decoration to draw attention but an aid to terrain interpretation. Stronger colors are not necessarily better. What matters is that anyone looking at it can discern the same trends.

Also, it is dangerous to underestimate the effects of on-site alterations. Elevation data from the Geospatial Information Authority of Japan is useful, but it does not necessarily reflect the latest construction conditions. In areas with ongoing construction or newly developed land, the color distribution may differ from the current site. Therefore, heat maps should be used as tools for hypothesis formation and for identifying locations to verify, rather than as the basis for final decisions. In particular, when using them to judge drainage planning, construction planning, or maintenance management, it is important not to separate desk-based maps from on-site verification.

Finally, it is also important not to underestimate the explanatory power of the deliverable. Even if the person who created a heat map understands its meaning, the way to read it may not be conveyed to third parties. A figure whose legend, scope, purpose, and cautions are not organized will lead to inconsistent interpretations when viewed later. A good heat map is not a chart with pretty colors, but one that can be understood to a certain extent without explanation and that makes it easy to add supplementary explanations when necessary.

Summary

Creating a heat map from the Geospatial Information Authority of Japan's elevation data is not mere visualization. It only becomes a meaningful document when you set a purpose, define the area of interest, select appropriate elevation data, process it, design color-coding rules, and finally refine it so that it leads to practical decision-making. It is especially important not to make map-making itself the objective. Anyone can color-code high and low areas, but only by considering how to read those differences and how to connect them to on-site decisions does a heat map become useful in practice.

Heat maps are highly effective when you want to quickly grasp broad terrain trends, get a sense of drainage and elevation differences, or present information intuitively in explanatory materials. At the same time, they do not completely replace on-site inspections or the precise verification of positions and elevations after construction. That is why it is important to connect an overview using elevation data from the Geospatial Information Authority of Japan with high-precision on-site position checks and positioning.

In practical fieldwork, if you first grasp terrain trends using an elevation heatmap, mark areas that require attention or verification, and have a system on site to quickly check the necessary points, both analysis and explanations can be streamlined. As a means to make that workflow easier to implement in the field, smartphone-mounted high-precision GNSS positioning devices like LRTK are a good fit. They are easy to use as a bridge from broad-area understanding to on-site inspection when you want to verify a location with a notable elevation difference found at the desk, or when you want to quickly establish control points or on-site coordinates. The perspective of leveraging heatmaps based on elevation data from the Geospatial Information Authority of Japan not just for desk-based reporting but as part of a continuous workflow through on-site verification will become increasingly important in future practice.