Seven cautions when turning GSI map information into heatmaps

Many practitioners who search for "heatmap GSI" (Geospatial Information Authority of Japan) are likely trying to visualize terrain trends, hazard locations, or the spatial distribution of sites using publicly available map information. Indeed, GSI maps provide a variety of datasets—topographic maps, aerial photos, elevations, terrain classification, disaster information, etc.—and offer representations that make conditions easy to grasp at a glance, such as colored elevation maps, shaded relief maps, and slope maps.

However, something that looks like a heatmap is not the same as something you can use for operational decisions. If you assume that any colored map is comparable, mismatches will emerge in the meaning, accuracy, update timing, coordinate system, or usage conditions of the source data. This is especially important in industries like construction, civil engineering, disaster prevention, and asset management, where teams often want to translate map colors directly into on-site judgments. Understanding these mismatches from the start is essential. This article organizes and explains seven commonly overlooked cautions when turning GSI map information into heatmaps, in a practical form. Read it not just as instructions for plotting, but as a mindset for creating visualizations you can be accountable for afterward.

Contents

• Preconditions to clarify before heatmapping

• Caution 1 Decide in advance what you want to represent with color

• Caution 2 Do not confuse elevation data with the height of structures

• Caution 3 Do not mistake zoom or visual detail for accuracy

• Caution 4 Align coordinate systems and projections

• Caution 5 Do not overlook mismatches in photo dates and update timing

• Caution 6 Do not evaluate using automatic color classification as-is

• Caution 7 Do not put off source attribution and usage conditions

• Tips for connecting heatmaps to operational decisions

• Summary

Preconditions to clarify before heatmapping

First, clarify that the phrase "turning GSI map information into a heatmap" can actually mix two different tasks. One is directly color-coding existing geographic information such as elevation, slope, or land classification. The other is color-coding your own operational data—inspection results, as-built deviations, temperature, traffic volume, number of complaints, etc.—using GSI maps as a background. Although these look similar, the source data meanings, comparison methods, and cautions differ.

Moreover, maps themselves are not a perfect mirror of the real world. GSI states that map display items are selected according to purpose and scale, and that, for readability, map features may be moved from their true positions. In other words, if you treat lines and symbols on a background map as raw survey values and use them as the basis for analysis, your fundamental assumption is already wrong. Just recognizing this changes how you make heatmaps. Will you use the background map for positional understanding and explanation, or as the raw data for analysis? Do you want to look at elevation, density of events, comparisons, or anomalies? If you start coloring while leaving this ambiguous, neither adjusting the legend nor changing thresholds later will resolve the fundamental mismatch.

Caution 1 Decide in advance what you want to represent with color

The most common mistake in heatmapping is choosing a convenient-looking map layer before deciding what you want the colors to represent. GSI provides colored elevation maps, shaded relief maps, slope maps, geomorphological maps, vegetation indices, aerial photography, and more—items that look similar but contain different information. They are all useful, but they represent different phenomena. The appropriate layer depends on whether you want to view elevation differences, read valleys and ridges, or see differences in land use or vegetation.

For example, if you want to map the distribution of fill and cut areas but treat simple aerial photo tonal differences as a heatmap, the color differences will reflect surface materials and photographic conditions. Conversely, if you want to assess slope hazard but rely only on a colored elevation map, elevation alone may show high and low areas but not adequately convey where slopes are steep or gentle. If you begin coloring without defining what you are converting to color, readers will receive inconsistent meanings.

In practice, be able to state in one sentence whether you want to color "height," "slope," "terrain classification," "surface condition at the time of photography," or "attributes observed by your organization." Once that is fixed, the required data type, processing method, and legend breaks become obvious. A heatmap is not a representation for aesthetic purposes; it is the process of replacing the variable you need to judge with color. Simply following this order will greatly reduce plotting confusion.

Caution 2 Do not confuse elevation data with the height of structures

GSI elevation tiles are very convenient, but they are not万能. Officially, the elevation points underlying the elevation model are based on ground-surface measurements and do not reflect the heights of buildings, elevated bridges, or other structures. It is also stated that elevation values may be missing or inaccurate in water areas.

Therefore, directly using elevation tiles as a heatmap will not let you read rooftop heights, bridge girder elevations, top-of-structure management elevations, or equipment installation heights. Even if visual high-and-low differences appear, they primarily represent ground-surface undulation and do not indicate the upper surfaces of artificial structures. Overlooking this difference in construction sites can lead to situations where the data were usable for slope management but not for as-built structure verification.

Also, the elevation values displayed on GSI maps are derived by smoothing multiple nearby elevation points closest to the latitude/longitude and thus do not exactly match original source data or raw measurements. It is noted that in places with locally steep terrain or rapid changes such as cut-and-fill, these discrepancies can be significant.

For these reasons, heatmaps based on GSI elevations are suitable for viewing broad terrain trends but should not be used as-is for shape confirmation of structures or checking management values at the centimeter level. They are strong for understanding ground flow, identifying lowlands, confirming drainage directions, and grasping surrounding terrain, but you should draw a clear line that they do not represent detailed current artificial features.

Caution 3 Do not mistake zoom or visual detail for accuracy

When you zoom a map, it is easy to feel that accuracy has improved. However, GSI tiles are displayed by dividing them into tiles of 256 pixels square per zoom level, and zooming in itself does not create new survey values. For the GSI base map, zoom levels 5 through 14 are indicated to be reduced-and-edited versions of zoom level 15.

Moreover, the horizontal accuracy of features shown on the GSI base map for zoom levels 15 through 18 is generally within 17.5 m (57.4 ft), and features may be displaced for the sake of map readability. Nearby roads or railways may be drawn shifted from their true positions to make the map easier to read. The caution here is that even if heatmap boundaries or color transitions appear to match site boundaries or management lines exactly, you must not treat them as precise boundaries. Especially if you use map road edges, river edges, or lines on topographic maps as boundaries for earthwork calculations or construction decisions, you are substituting visualization lines for analysis baselines.

Regarding colored elevation maps, GSI states that while they are based on a seamless nationwide 10 m mesh (10 m (32.8 ft)) to create a coherent map and use a 5 m mesh (5 m (16.4 ft)) at high zooms to make fine topography easier to see, differences in surveying methods and measurement timing across district boundaries can cause subtle elevation differences to appear as steps. Unnatural differences can also appear between water areas and their surroundings.

In short, visual smoothness and detail do not necessarily mean the data meet the precision required for analysis. If you plan to use heatmaps for operations, make it a habit to check the source data resolution, how they were created, and whether any display editing has been applied—not just how detailed they look.

Caution 4 Align coordinate systems and projections

GSI tiles for domestic maps adopt the JGD2011 world geodetic system and are tiled using Mercator projection formulas. This is convenient for display, but if you overlay data in other coordinate systems without understanding this mechanism, the map may look fine while positions are actually shifted.

Operational data are not limited to latitude/longitude. Drawings managed in the plane rectangular coordinate system, as-built data in custom coordinates, point clouds or ledger coordinates from asset registers—standards vary by operation. If you align everything visually using GSI tiles as the reference, the background may appear to match while analytic values gradually shift, affecting mesh aggregations and overlays.

Especially because heatmaps invite reading overall tendencies from color distributions, a mismatch of several meters to a dozen or so meters can be hard for the human eye to notice. Point data can be checked one by one, but density distributions and interpolated surfaces can look plausible even when shifted. Therefore, it is safer to separate the coordinate system used in analysis from the coordinate system used for final public display.

If the goal is only broad trend recognition, visualizations aligned to GSI tile display coordinates may suffice. However, when numerical judgments are involved—area, length, earthwork volume, separation distances—perform calculations in the operational standard coordinate system first, and then overlay the results on GSI maps for explanatory purposes. This order reduces rework.

Caution 5 Do not overlook mismatches in photo dates and update timing

When people read a heatmap, they tend to assume it depicts "the current situation." But GSI photos and various layers do not necessarily represent the same point in time. The nationwide seamless aerial photo layer is created by combining multiple types of aerial photographs and images so the entire country can be browsed, and the data source and acquisition dates for each tile can be checked in a separate layer. The tile list also specifies that tiles are created from multiple photo sources.

In other words, the background photo you use may not be a single image taken on one day. Some parts of the area may be covered by newer photos, while other parts use older photos. If you overlay inspection results or observations from different dates to create a heatmap, the color distribution may be up-to-date while background features reflect an earlier state. In rapidly changing places—newly developed sites, temporary roads, material yards, riverworks—this mismatch can lead to wrong decisions.

Update timing is not uniform either. The status page for the Basic Map Information project shows maintenance and update statuses, and the full history of downloadable data updates indicates that core items and numerical elevation models are updated by mesh or area units. Nationwide updates are not performed all at once; timing and coverage differ. Therefore, when creating a heatmap, manage reference dates in addition to the legend. Do not mix the photo acquisition date, the elevation model maintenance date, your organization’s data acquisition date, and the aggregation period on the same figure. Even if the colors are consistent, if the comparison times differ, the comparison is invalid.

Caution 6 Do not evaluate using automatic color classification as-is

GSI maps offer a "create your own colored elevation map" function that can automatically classify colors based on the minimum and maximum elevation of the displayed area, or automatically shade ranges lower than the elevation at the screen center. This is useful for finding fine elevation changes in lowlands.

However, convenience does not guarantee comparability. Automatic color classification can change the meaning of colors for the same location when the displayed range changes. A point that was yellow yesterday might turn green today simply because the displayed range was widened. It is fine for exploratory terrain viewing, but dangerous to use as-is in reports or explanatory materials.

For operational heatmaps, colors should be fixed according to decision criteria, not local readability. For example, when identifying lowlands, cut elevation bands at fixed intervals; for slope management, fix slope class breaks; for inspection results, fix evaluation score ranges. Without this, the thing you are comparing becomes the display rules, not the terrain or condition.

Furthermore, the legend is not a mere accessory added at the end of plotting; it is essentially the body of the heatmap. Thresholds, color order, transparency, whether interpolation was used, whether the value is mean or maximum, and the definition of the display extent—all of these must be recorded so readers can interpret consistently. For site handovers and reproducibility, manage the color settings themselves as files or procedures.

Caution 7 Do not put off source attribution and usage conditions

GSI content is available under the public data usage terms unless otherwise noted, and when using content you must indicate the source. Moreover, when you edit or process content before using it, you must state that you edited or processed it separately from the source attribution and must not present it as if GSI created it. Heatmapping is often precisely a case of "processing." Creating custom color schemes from elevation tiles, expressing slope with your own legend, overlaying your own data to produce density distributions, or annotating photos—these activities require more than merely noting that the background is from GSI; you must clearly communicate what you used and how you processed it so readers are not misled.

In addition, not all layers can be used under the same conditions. The tile list categorizes layers into those that are basic survey results, those usable with only a source attribution, and those requiring special attention. There are cases—such as seamless aerial photos—where additional source clarification is required, and cases—such as colored elevation maps—where additional notation is requested for marine areas. Be aware that some parts may include content for which third parties hold rights.

For web display that reads tiles in real time, there are cases where usage is allowed with source attribution, but confirmation procedures may change depending on the usage and the form of the deliverable. Therefore, decide up front which layers you will use, in what form, and where you will publish them, and proceed with operations that meet those conditions. Otherwise, you may need to replace layers or correct attributions just before completion, which is a major loss in practice.

Tips for connecting heatmaps to operational decisions

Considering the seven points above, GSI map-based heatmaps are excellent tools for overviewing a site, forming hypotheses, and setting priorities rather than for immediately reaching conclusions. They are powerful for grasping lowland distributions, reading slope changes, noticing update timing differences, and discovering mismatches between photos and ledgers. Such initial understanding is where they shine.

On the other hand, do not rely solely on public maps when final decisions are required. For tasks that need the current location in present coordinates—construction management, simple surveying, inspections, equipment position confirmation, as-built comparisons—overlaying high-precision point clouds, surveyed points, or field observations you acquired yourself is what turns a heatmap into a practical tool. Using GSI maps as a background is effective, but the core of the decision should be current data obtained on site.

In that sense, combining broad understanding from public maps with high-precision on-site position acquisition works well. Using iPhone-mounted GNSS high-precision positioning devices such as LRTK allows you to quickly collect points and location data on site and compare them with GSI map information, helping you decide what can be understood from public data and what must be supplemented by field measurement. For teams that want to move beyond mere visualization to measure, compare, and explain, this combination is highly practical.

Summary

When turning GSI map information into heatmaps, the most important thing is to decide what value you will represent with color before worrying about coloring techniques. Then remember: elevation data do not represent structure heights; zoomed display does not imply increased accuracy; coordinate systems and projections must be aligned; photo and map update dates can differ; automatic color classification is not a valid comparison standard; and source attribution and usage conditions should be incorporated into the design from the start. Keeping these seven points in mind moves you beyond appearance-focused heatmaps toward visualizations you can be accountable for.

And to make heatmaps truly useful in the field, do not stop at understanding public maps. Use GSI map information to broadly grasp conditions, and supplement where necessary with on-site measurements. If you want to make simple surveys and position checks more reliable, leverage LRTK to capture high-precision current location data, combine them with GSI map information, and raise the resolution of your decisions.