Practical points for creating GSI heat maps usable in operations

Heat maps created using data from the Geospatial Information Authority of Japan (GSI) are most effective when used not as mere visual decoration but as practical tools that speed on-site decision-making, fulfill accountability, and align stakeholders’ understanding. Especially when overlaying point data with location information, mesh aggregations, work volumes or inspection results, disaster-related histories, and custom aggregations of population or traffic on a map, the reliability of the base map, ease of reading topography, coordinate consistency, and tracking of updates directly affect operational quality. GSI provides public datasets such as the GSI Maps viewing platform, GSI Tiles, Fundamental Geospatial Data, digital elevation models (DEMs), aerial photography, and landform classification, and the most realistic approach is to use these as background/auxiliary information while overlaying your operational data. On March 31, 2026, the elevation tiles on GSI Maps were updated to correspond to the Geodetic Results 2024, and updates to the coordinate reference systems have also been reflected on the Fundamental Geospatial Data side. In practice, proceeding with processing under old assumptions without being aware of such updates can later cause mismatches and insufficient explanations. GSI online viewing site+3

Table of contents

• What it means to use GSI heat maps in operations

• Purposes and evaluation metrics to clarify first

• How to choose the data to use

• Practical production steps

• Ways to avoid failures with accuracy and coordinates

• Points to check for updates and rights handling

• Common operational mistakes and remedies

• Use-case images by field

• Summary

What it means to use GSI heat maps in operations

Many people who search for "heat map GSI" are not just looking to color a map; they want to quickly grasp where issues concentrate, where to prioritize action, and which points need additional inspection. In that sense, the value of using GSI data lies in being able to base your work on nationally consistent, easily referable background information. GSI Tiles are distributed in the XYZ scheme, making them easy to handle in web maps. Furthermore, GSI Maps Vector allows map design adjustments, making it easy to choose presentations closer to blank maps or to limit shown information. In operational heat maps, the background is not the protagonist; the protagonists are your organization’s observation data, inspection results, inquiry locations, accident histories, patrol records, sales distributions, stay tendencies, and construction progress biases. Using GSI data as a reliable foundation to show those protagonists without misunderstanding results in an appropriately balanced composition.

Also, using GSI data makes it easier to explain the meaning of heat map colors in relation to terrain and land conditions. For example, even if abnormal values concentrate at a location, countermeasures differ greatly depending on whether that concentration is due to simple demand clustering, disaster vulnerability from valley or lowland topography, or characteristics of reclaimed land. If you use vector tile landform classification, elevation models, and aerial photography as auxiliary layers, you can go beyond viewing color intensity as a "result" and read into "why it is biased there." Practical value comes not from aesthetic appeal but from whether the map serves as decision material that includes that contextual understanding.

Purposes and evaluation metrics to clarify first

When making a heat map for operations, the first thing to decide is not "what should be displayed heavily" but "what will be decided by looking at that intensity." If this is ambiguous, the map may look plausible but be unusable on site. For example, in facility maintenance, whether you want to see density of failures, concentration of response delays, or unevenness of uninspected locations changes the aggregation unit and color coding. In civil engineering or infrastructure management, you need to separate indicators by purpose—bias in repair history, changes in pavement condition, abnormal concentration in patrol results, distribution of resident reports, etc. In sales or regional analysis, it is often easier to make decisions by looking separately at density per area, time-of-day bias, distribution differences by attribute, and correlation with terrain conditions rather than raw visit counts.

In practice, rather than fixing a single purpose too strictly, it is easier to design by dividing uses into four: "situational awareness," "prioritization," "explanatory materials," and "on-site inspection instructions." Situational awareness functions with coarse meshes if overall trends are sufficient, but on-site inspection instructions are meaningless unless you can identify the actual intersection, slope, or equipment vicinity to inspect. With the same data, create one map for broad trends and another for local decision-making; trying to make one map serve all purposes usually leads to mediocrity. To make an operationally usable map, decide in advance who will use it, in which meeting, and for which decision, then choose aggregation units and display extents accordingly.

Furthermore, it is more practical not to bias evaluation metrics toward counts alone. Places with many cases are not necessarily high priority. Using indicators normalized by denominators—failure rate per facility, incidence per population or household, report density per length of road, conversion rate per visit count, nonconformance rate per construction area—makes color intensity more likely to lead to decisions. GSI maps are an excellent foundation, but the final quality of a heat map is determined by which numbers you turn into colors. Carelessness here leads to wrong judgments even with accurate backgrounds.

How to choose the data to use

For GSI heat maps, it is helpful to think of data in three layers: background maps, analysis source data, and confirmation auxiliary information. Background maps help grasp roads and terrain; analysis source data are the point or mesh data you want to color; confirmation auxiliary information helps interpret those colors. On the GSI side, note first that GSI Tiles are provided in a format suitable for real-time loading and that conditions for use differ by tile. Items that qualify as basic survey results may require procedures, while others can be used with only source attribution. Moreover, cases where real-time loading in websites or applications is allowed with only source attribution and no application are clearly indicated. In other words, what you should first confirm for operations is not "whether GSI data can be used" but "which layers, by which method, and in which deliverables the data will be used."

As background maps, not only conventional map representations but aerial photography and more blank-map-like styles are effective. Heat maps overlay colors, so a noisy background buries the subject. The idea of adjusting map design with GSI Maps Vector or using aerial-photography-based GSI Tiles as auxiliary layers varies in effect depending on the subject. For example, for complaint distributions along roads or locations of maintenance targets, a simple background that makes linear features easy to read is suitable. On the other hand, for slopes, riverbanks, reclaimed land, or around farmland—where terrain and land use context are important—using aerial photography or landform classification together makes it easier to explain why a location is intense. The fact that GSI Maps Vector is presented as a new viewing site where you can design maps yourself matches the notion of "adjust the background to show the subject."

If you want to examine terrain influence as analysis source data, understanding digital elevation models (DEMs) and elevation tiles is useful. GSI offers multiple kinds of elevation tiles, with varying levels of precision from high to coarse. In operations, the granularity needed for wide-area trend grasp and local judgments differs, so you should not treat the same elevation data as universally suitable; determine resolution according to the target area. Also, elevation tiles are based on surface measurements and do not reflect the heights of structures such as buildings or viaducts. It is noted that elevation values may be missing or inaccurate in water bodies. Thus, relying solely on elevation tiles to evaluate three-dimensional urban structures or newly reclaimed sites in detail is risky. While effective for background understanding of terrain, they are not a substitute for on-site confirmation or other datasets when evaluating local structures.

As confirmation auxiliary information, landform classification, natural disaster memorials, and aerial photo history checks are effective. Particularly for disaster prevention, maintenance management, land use change confirmation, and facility placement review, you need materials to determine whether intense locations are truly hazardous or repeatedly occurring over time. Landform classification is offered as vector tiles summarizing natural and artificial landforms, enabling examination of terrain genesis across zoom levels. Natural disaster memorials are accompanied by a note that absence of listings does not imply safety, so they should not be used alone for safety judgments but treated as auxiliary information. Overlaying these on intense heat map areas adds persuasive power to prioritization.

Practical production steps

To create reproducible heat maps for operations, start by organizing source data with coordinates rather than jumping into drawing. Many field data—addresses, facility names, inspection records, photos, inquiry histories, patrol logs—are not directly mappable. Standardize location name variants, remove duplicates, fill missing timestamps, and normalize recorder accuracy so that at minimum the same place is counted as the same place. Next, decide whether to show points as-is, aggregate into meshes, or convert to lines or polygons. For narrow-range on-site decisions, point density works; for explanatory materials or sharing overall trends, aggregating into a fixed mesh reduces misreading. Prioritize readability of gradation over flashiness, and make legends clearly show whether a strong color truly indicates abnormality or merely high count.

When selecting a background map, don’t aim for the final version at the start; test with a simple background first. Determine which of road network, rivers, administrative boundaries, or terrain are necessary for decisions, and leave only the minimum needed to let the heat map subject come through. GSI Tiles are easy to handle in web maps and GSI Maps Vector allows expression adjustments tailored to the subject, so start with a background that does not obscure the color subject and add aerial photography or landform classification as needed. Adding too much background causes readers to focus on map detail rather than "where it’s intense." Operational maps are not better with more information; they are better when only decision-relevant information remains.

After that, always validate the heat map’s validity with separate layers. For example, if concentrations appear in lowlands, overlay elevation or landform classification to check terrain factors; if bias appears along roads, examine distances to road centerlines and proximity to intersections. For facility management, check site locations with aerial photos and be mindful of timing differences if reclaimed land or newly installed equipment may affect results. GSI’s aerial photo viewing service and various layers on GSI Maps are effective aids to verify "is it really happening at that location?" A heat map is an aggregation result and therefore retains aggregation granularity and input habits. That’s why you must corroborate with data from other perspectives rather than stopping at map creation. GSI Onla

Finally, design how to return deliverables to operations. Do not use the same map for meetings, on-site instructions, and reports. Meeting maps only need to show broad trends and priorities; reports require citations and update timestamps; on-site instruction maps require precise location specificity. When using GSI data, finalize the citation placement and use conditions at this stage. When displaying survey results on a display, it is recommended that the source be visible while displayed. For printouts or image exports, ensure citations remain on the output.

Ways to avoid failures with accuracy and coordinates

The most commonly overlooked issues in operations are coordinate and accuracy mismatches rather than color gradation. Even if you think you’re handling the same location, differences in the coordinate reference system of source data, how the map handles coordinates, definitions of elevation, and acquisition timing can make a heat map misleading. The Fundamental Geospatial Data provider announced that on April 1, 2025, specifications changed and the coordinate reference system moved from JGD2011 to JGD2024. Additionally, basic items and DEMs provided on or after July 31, 2025, reflect updated elevations. Therefore, overlaying point data created in an old coordinate system or internal data based on pre-update elevation without conversion can cause differences that are small visually but significant in field explanations. When mixing new and old data, explicitly state which result each datum is based on. GSI Onla

Regarding elevation, treating displayed numbers as absolute values is risky. GSI Maps elevation values use smoothed values derived from the four nearest elevation points in the elevation model for a given location, and may not exactly match original measurements or map-read values. Divergence can be large in areas with sharp local cut-and-fill topography. Thus, while useful for roughly reading slope risks or lowland tendencies in heat maps, it is dangerous to directly apply them to construction management, drainage design, or checking elevation differences around structures. Not confusing wide-area grasp with local judgment is essential to maintain operational quality.

Another important point is matching mesh size to the operational decision unit. Heat maps look more accurate when finer and easier to explain when coarser, but you need to find a practical middle. For road maintenance, match mesh to route or segment units; for facility inspection, to equipment-group units; for sales analysis, to trade area or visit-area units. Meshes that don’t align with decision units are hard to use. GSI data is excellent for background and terrain understanding, but it won’t automatically give the correct mesh design. High map accuracy and appropriate aggregation units are separate issues; whether you can separate these concerns is where the operational practitioner’s skill shows.

Points to check for updates and rights handling

For continued operation, design for not only correctness at creation but also a system to follow updates. GSI help and update information show continuous updates such as elevation tile updates, background map renewal plans, and expansion of DEM provision. For example, on March 31, 2026, elevation tiles were updated to Geodetic Results 2024 values and the provision range of DEM1A tiles was expanded. When doing periodic reporting or annual comparisons, even visually identical maps may not be directly comparable year-over-year due to background data updates. Therefore, internally managing not only the drawing date but also the reference time of background maps and update times of used layers is advisable.

Rights handling should not be overlooked. GSI content usage terms and the GSI Tiles list indicate which items can be used with source attribution only, which are subject to specific legal constraints, and which require attention to third-party rights. In particular, the GSI Tiles list notes that some tiles may require individual source statements in addition to labeling "Geospatial Information Authority of Japan" or "GSI Tiles." Aerial-photography-based tiles may require additional source statements depending on constituent data. Thus, you cannot treat all GSI data uniformly. Internal dashboards, external publication materials, printed handouts, and on-site apps have different required attribution placements, so establishing rules per usage category in advance stabilizes operation.

For downloads, acquiring Fundamental Geospatial Data requires user registration and login. The provision site also indicates authentication method changes from April 2025 onward and notes about login ID validity periods. In practice, administrative interruptions such as "it worked before but not today" are surprisingly common, so share update procedures not only with analysts but also with operation and IT staff. Heat map operations do not end with map processing; design the workflow to include data acquisition, storage, updates, and attribution management. GSI online viewing site+3

Common operational mistakes and remedies

One common mistake is oversimplifying heat maps as "the darker, the more dangerous" or "the darker, the more important." Intensity usually reflects counts, density, or weighting results. When target population, facility numbers, patrol frequency, recording omissions, input errors, and seasonal factors mix in, the meaning of color can change easily. The remedy is to avoid cramming too many subjects into one map. Creating separate maps for counts versus rates, all-time versus recent, day versus night, and normal versus disaster situations reduces misunderstandings significantly. GSI backgrounds provide a common foundation, making comparative maps easier to explain and good for aligning understanding in meetings.

The second mistake is treating data with different location accuracy equally. Points converted from manually entered addresses, points measured on site, and points linked to facility ledgers have different inherent reliabilities. If you layer them with equal weight, it becomes ambiguous whether a hotspot is truly at that point or in the surrounding area. The remedy is to assign accuracy categories. Keep data divided into on-site observation points, address-derived points, representative points, etc., and use only high-accuracy data for local decisions. A precise background map cannot compensate for ambiguous source coordinates.

The third mistake is overloading the background map. If you include roads, buildings, boundaries, facility symbols, annotations, photos, and elevation shading all at once, the heat map will be buried. The remedy is to keep only background elements necessary for decision-making. Prioritize road centerlines for route decisions, terrain for slope decisions, and facility layouts for equipment decisions. Mechanisms like GSI Maps Vector that let you adjust presentation by subject are helpful for this.

The fourth mistake is trying to use the finished map directly on site. Heat maps are strong for grasping overall trends but may not suit the final step of on-site inspection. Even if you know an area is intense, you still need other information to decide which equipment, slope, intersection, or lot to inspect first. The remedy is to use heat maps as an entry point, linking to target point lists, patrol routes, detailed maps, and on-site photo checks. Dividing roles between overview maps and detail maps brings out the heat map’s strengths.

Use-case images by field

In civil engineering and infrastructure management, mapping abnormal reports, repair histories, locations of cracks or subsidence, records of weeding or cleaning, and bias in uninspected locations as heat maps clarifies where limited personnel should be prioritized. In doing so, read counts together with elevation, landform classification, and proximity to rivers or slopes to develop discussions toward preventive maintenance. When relationships between land origin—such as lowlands, old river courses, slopes, and reclaimed land—and intensity become evident, you can move from ad hoc responses to planned measures.

For municipalities and disaster prevention, mapping past damage records, evacuation-related inquiries, road traffic obstructions, congestion trends around shelters, and patrol histories for persons requiring assistance helps bridge desk-based organization and operational implementation. Natural disaster memorials are an effective auxiliary source to recall regional disaster histories, but official warnings note that lack of listing does not mean safety. Therefore, overlay memorials and landform classification on intense heat map areas and combine them with your own damage histories and drill results to consider past, landform, and current operations three-dimensionally.

GSI maps are also useful for private facility operations and area analysis. Heat-map visitation records, maintenance requests, delivery stop points, on-site response backlogs, and patrol-route biases, supplemented with aerial photos and terrain, help explain geographic reasons not visible from planar numbers alone. For example, identical counts can imply different operational improvements if concentrated in valley bottoms, biased along trunk roads, or scattered across high-relief residential areas. GSI data makes it easy to build a common foundation nationwide, so it pairs well with work comparing multiple regions side by side.

Summary

The key to making GSI heat maps usable in operations is to cultivate density maps that support decision-making rather than aiming for flashy color schemes. To do this, decide in advance what you want to judge, design by separating background maps, analysis source data, and confirmation auxiliary information, and manage coordinate systems, update times, and attribution conditions. GSI provides practical materials—GSI Tiles, Fundamental Geospatial Data, DEMs, aerial photography, and landform classification—but how to combine them depends on the user’s design. If you do not make map creation the goal but instead use prioritization, explanation, on-site inspection, and improvement execution as criteria, heat maps become tools that last in the field.

Finally, after finding intense spots on the desk, it is important to verify their positions on site and quickly secure necessary points. Heat maps are strong for wide-area trend grasp, but the final confirmation depends on on-site position identification and records. In such situations, high-precision positioning devices usable with smartphones—like LRTK—facilitate on-site coordinate confirmation, control-point identification, and simple surveying efficiency. Connecting map-based analysis using GSI data with on-site centimeter-level accuracy (half-inch accuracy) verification by LRTK smooths the loop between desk-based judgment and field response.