Defence & National Security

3D Terrain for Air Force Simulators and Mission Rehearsal Training

Air forces train pilots in simulators because live flying hours are expensive, airspace is limited and some situations are too risky to practise in a real aircraft. A simulator is only as convincing as the world it shows. The terrain, imagery, obstacles and airfields in its database decide whether a trainee learns to read the real landscape or a generic one. GIS turns national elevation models, satellite imagery and surveyed obstacle data into accurate, standards-based 3D synthetic environments that simulators and planning tools can share, update and reuse across many training courses.

What the evidence shows

$48,000 vs $2,100[1]

Cost per hour: F-22 flying hour vs simulator centre hour

RAND estimated an F-22 flying hour at about $48,000, while a distributed simulator training centre cost about $2,100 per hour at full capacity. Realistic terrain helps more training move into the cheaper medium.

8 m LE90[8]

Design vertical accuracy of India's free national DEM

NRSC's CartoDEM, made from Cartosat-1 stereo data, is offered at 30 m posting with a design vertical accuracy of 8 m at 90 percent confidence, a ready national base for wide-area terrain.

Per-dataset[6]

Update granularity in a CDB data store

OGC CDB guidance states that a single dataset, such as terrain imagery, can be modified without reprocessing the complete tile, which permits rapid deployment for mission planning and rehearsal.

Nearly 2x[10]

Growth in Indian Air Force pilot intake

Published reporting on IAF training notes that pilot intake has nearly doubled while standards are maintained by optimising training resources, which raises demand for simulator content.

Simulation is now central to air force training

Simulation has moved from a supplement to a planned part of military training. In September 2021 India's Ministry of Defence issued a Framework for Simulators in Armed Forces under the motto 'Fight as you train, train as you fight', aiming to reduce live equipment use, plan simulators into capability and procurement decisions, and build them with Indian companies. MoD year-end reviews since then record simulator procurement for cadets, a C-295 simulator brought into service and combined simulator training for pilots of all three Services and the Coast Guard.

The economic case is clear in published research. A RAND Project AIR FORCE study for the US Air Force put the cost of flying an F-22 at about $48,000 per flying hour, while a distributed simulator training centre cost roughly $2,100 per hour to run at full capacity. RAND also noted that safety considerations, airspace and range restrictions and real-world commitments limit how much training can be done in live aircraft. A 2023 RAND study reported unmet simulator needs for some fleets and recommended wider use of synthetic training environments.

Every one of these simulators depends on geospatial content. A synthetic environment needs terrain relief, imagery, 3D models of natural and built features, airfields and navigation aids, all held in a consistent coordinate system. The OGC CDB standard was written for this purpose: it organises such data into tiles, layers and levels of detail so that several simulators can draw on one shared, versioned representation of the earth.

The challenges

Where productivity is lost today

01

Generic terrain weakens training transfer

When a simulator shows typical rather than real terrain, trainees practise navigation, approaches and visual recognition against landscapes that do not match the ground they will fly over. Instructors then spend live sorties correcting habits that a more faithful database could have built on the ground, which wastes expensive flying hours.

02

Slow, costly database generation

Building a terrain database for a new training area often means collecting imagery, elevation and feature data from many sources, cleaning it and compiling it into each vendor's proprietary format. Each change to an airfield or feature can trigger another round of rework, so databases lag behind the real world and training content goes stale.

03

Different simulators, different worlds

Flight, radar and computer-generated-forces simulators often run separate databases built from different sources. When a runway, ridge or obstacle sits in slightly different places in each, linked training exercises lose credibility and debriefs become harder. OGC guidance identifies these correlation errors as a known problem that a common data store reduces.

04

Incomplete obstacle and airfield detail

Masts, power lines, wind turbines and new buildings change around airfields and along training routes. If simulator databases do not reflect them, trainees miss practice in recognising hazards that matter in low-level and approach phases. Keeping obstacle and airfield models current needs a disciplined data pipeline, not one-off modelling.

05

Growing training throughput

Indian Air Force training is absorbing a larger pilot intake while keeping standards, according to published industry reporting. More trainees per course means more simulator hours and more training areas to model. Without reusable geospatial content, each new course or platform demands fresh database effort and delays training capacity.

How GLOBEIR helps

Business needs and how we solve them

Each solution starts from a need Air Force 3D Terrain & Mission Rehearsal Simulation faces today, then shows how GLOBEIR delivers it and what changes as a result.

01 · The business need

India's 2021 Framework for Simulators in Armed Forces asks the Services to cut live equipment use and move more training into simulators. That only works if simulator time teaches skills that carry over to real flying. Generic or typical terrain gives trainees landscapes that do not match the ground they will fly over, so the training value per simulator hour stays low.[2]

3D Terrain Models

Geospecific 3D terrain databases for simulators

GLOBEIR builds 3D terrain models from national and global elevation data, draped with orthorectified imagery and populated with roads, rivers, built-up areas and vegetation. Terrain is prepared at several levels of detail, from wide-area background down to high-detail zones around airfields and training areas, and delivered in formats that simulator image generators and planning tools can ingest for training and education use.

  1. 1Agree training areas, airfields and level of detail with the training authority
  2. 2Fuse national elevation data with orthoimagery and real topographic features
  3. 3Deliver tiled 3D terrain in the formats the client's simulators ingest

The result

Trainees practise against terrain that matches the real ground, so more learning carries over to live sorties.

02 · The business need

Training now links flight, radar and computer-generated-forces simulators, and every device must see the same world. When each runs its own compiled database, positions drift apart and every update is repeated per vendor. OGC CDB guidance says a common data store reduces correlation errors and shortens development, update and configuration management timelines, which the old per-device approach cannot match.[6]

Training Simulation

CDB-aligned synthetic environment data stores

GLOBEIR can organise terrain elevation, imagery, vector features and 3D models into a structure aligned with the OGC CDB standard, with geodetic tiles, separate layers and levels of detail. Because datasets are independent, imagery or features for one area can be refreshed without reprocessing whole tiles, and several simulator types can read the same versioned repository for training and rehearsal exercises.

  1. 1Map source datasets to CDB tiles, layers and levels of detail
  2. 2Build and version the shared data store with full metadata
  3. 3Refresh changed datasets only and publish new versions to connected simulators

The result

Database updates reach every connected simulator faster and with fewer correlation errors between devices.

03 · The business need

RAND notes that high-fidelity simulators are perishable resources that need continued funding to stay current. The same is true of their visual and terrain content: imagery ages, built-up areas grow and elevation artefacts undermine realism. Training managers need documented, current source data for each area, not textures and heights whose origin and accuracy nobody can state.[1]

Remote Sensing

High-resolution imagery and elevation processing

GLOBEIR processes satellite and aerial imagery into seamless, colour-balanced orthomosaics and refines elevation models by removing artefacts, filling voids and flattening water bodies. Where needed, stereo imagery or LiDAR is used to produce finer surface models for small, high-detail zones. All products carry metadata on source, date and accuracy so training authorities know how far each area can be trusted.

  1. 1Process satellite and aerial imagery into seamless, colour-balanced orthomosaics
  2. 2Clean elevation models by removing artefacts, filling voids and flattening water
  3. 3Record source, date and accuracy metadata for every delivered layer

The result

Simulator visuals and terrain heights rest on documented, current source data rather than ageing generic textures.

04 · The business need

Masts, power lines, wind turbines and new buildings keep appearing near airfields and training routes. ICAO Annex 15 terrain and obstacle data provisions, explained in the EUROCONTROL manual, list flight simulators among the uses of structured obstacle data. One-off airfield modelling falls behind these changes, so trainees practise approaches against an obstacle picture that is out of date.[9]

Cartography

3D airfield and obstacle models

GLOBEIR models runways, taxiways, aprons, lighting layouts and surrounding structures as 3D features, and captures vertical obstacles such as masts, towers, power lines and wind turbines as attributed points, lines and polygons. Modelling follows the approach of ICAO terrain and obstacle data guidance, so the same structured dataset serves simulator visuals, briefing charts and training materials.

  1. 1Model runways, taxiways, aprons and nearby structures as attributed 3D features
  2. 2Capture vertical obstacles as points, lines and polygons following ICAO guidance
  3. 3Reuse the same dataset for simulator visuals, briefing charts and training notes

The result

Approach, circuit and recovery training reflects the real obstacle environment around each modelled airfield.

05 · The business need

RAND reports that safety considerations, airspace and range restrictions and real-world commitments limit how much training can happen in live aircraft. That raises the value of ground-based preparation. Flat paper charts and slide briefings do not show how relief shapes a route or an approach, so trainees reach the simulator without a clear terrain and airspace picture.[1]

GIS Mapping

Airspace and training route visualisation

GLOBEIR builds GIS layers that show published airspace structures, training areas and generic route corridors over 3D terrain, with terrain clearance profiles and visibility analysis along each route. Instructors can use these 3D views in classrooms and briefing rooms to teach terrain awareness, route planning principles and the effect of relief on flight paths, without exposing sensitive operational data.

  1. 1Overlay published airspace, training areas and generic corridors on 3D terrain
  2. 2Generate terrain clearance profiles and visibility analysis along each route
  3. 3Package 3D views for classrooms and briefing rooms without operational data

The result

Trainees understand the terrain and airspace picture before entering the simulator, so simulator time goes further.

06 · The business need

Published reporting says Indian Air Force pilot intake has nearly doubled while standards are held by optimising training resources. More courses and platforms mean more areas to model and more updates to schedule. Spreadsheets and file lists cannot show where terrain content is current, where it is ageing and where the next course will need new coverage.[10]

Data Analysis

Database quality and coverage dashboards

GLOBEIR tracks the state of a terrain programme spatially: which tiles exist at which level of detail, the age of imagery in each area, elevation accuracy checks against control points and the status of airfield and obstacle updates. Training managers see where content is current, where it is ageing and where new courses will need fresh coverage.

  1. 1Index every tile, level of detail and imagery date on a map
  2. 2Track accuracy checks and airfield or obstacle update status per area
  3. 3Publish a dashboard that flags ageing or missing coverage against training plans

The result

Database effort is targeted at the areas and airfields that training plans actually need next.

In depth

Problem, solution, benefits and data security, topic by topic

Each topic below explains the evidence, the business problem it creates, how GLOBEIR solves it, the benefits to your organisation, and how your data stays private and secure.

  1. 1. What a 3D Terrain Model Is
  2. 2. Air Force and Aviation Uses
  3. 3. Training and Simulation
  4. 4. Civil and Disaster-Response Uses of the Same Technology
  5. 5. Proven Benefits

1. What a 3D Terrain Model Is

A 3D terrain model is a digital copy of the Earth's surface, built from elevation data and usually draped with imagery so it can be viewed, measured and simulated on.

  • DEM (Digital Elevation Model): the bare-earth surface, excluding trees, buildings and other surface objects. DSM (Digital Surface Model): includes buildings and vegetation. DTM is often used interchangeably with DEM [12].
  • SRTM: flown on Space Shuttle Endeavour in February 2000, jointly by NASA and the US National Geospatial-Intelligence Agency, producing the first near-global high-resolution digital elevation model [13], at about 30 m spacing [14].
  • Cartosat-1 / CartoDEM (India): launched 5 May 2005 with fore (+26°) and aft (−5°) cameras for 2.5 m along-track stereo. Its data built a national DEM for India, and the 30 m CartoDEM released free on Bhuvan was downloaded about 74,000 times. ISRO lists topographic mapping, coastal vulnerability assessment and disaster management among its uses [15].
  • Drone photogrammetry: the US Army describes a backpack kit in which a soldier marks an area of up to 1 km² on a tablet and a drone collects imagery automatically, cutting a process that previously took weeks to about three hours from flight to 3D view [16].
  • 3D Tiles: an OGC Community Standard for streaming massive 3D content such as photogrammetry, 3D buildings, BIM/CAD and point clouds [17]. It is the basis for the "Well Formed Format" of the US Army's One World Terrain [18].
  • Augmented-reality sand tables: the US Army Research Laboratory's ARES projects a topographic map onto real sand and adjusts it as the sand is reshaped, built from low-cost commercial parts to cut the time needed to create a terrain model and scenario [19][20].

Business problem

Many training establishments still prepare terrain study on hand-built sand models and paper maps. A sand table takes time to build, cannot be measured precisely, cannot be shared between classrooms and is lost once the exercise ends. Instructors also face a confusing mix of elevation sources and formats (DEM, DSM, SRTM, CartoDEM, drone surveys) and rarely have the specialist time to turn them into one consistent, usable model [12][14][15].

Our solution

  • The Digital Sand Model builds 3D terrain for the areas an institution specifies, from public elevation data such as CartoDEM and SRTM or from drone photogrammetry where the institution has authorised the survey, draped with imagery.
  • Terrain is streamed in the open 3D Tiles format [17], so large areas, buildings and point clouds load in a standard browser without special hardware.
  • Each terrain package records its source, resolution and date, so instructors know what the model can and cannot show.
  • The same terrain can be used alongside 2D map work in the Army GIS Map.

Benefits

  • Terrain for a new area in hours rather than weeks. In one published industry example, a drone-to-3D workflow for about 1 km² fell from weeks to about three hours [16].
  • A measurable model: heights, slopes and distances are read directly instead of estimated by eye.
  • Reusable and shareable across classrooms, courses and years, unlike a physical sand table.
  • An open streaming standard avoids lock-in to a single vendor [17].
  • Free national datasets such as the 30 m CartoDEM keep data costs low for broad-area study [15].

Privacy & data security

  • Data involved: elevation models, imagery and drone surveys of training areas. High-resolution terrain of sensitive locations needs protection even when it is unclassified.
  • Stored and processed in India: data finer than the DST threshold (1 m horizontal, 3 m vertical) is stored and processed only in India and is never transmitted to servers of a non-Indian entity [21][22]. Public 30 m CartoDEM and SRTM data are far coarser than this threshold [14][15].
  • Negative list and restricted premises: attributes on the DST negative list are excluded or handled as the client directs, and drone or field surveys are carried out only where the client has authorised access, since the guidelines give no right of access to restricted premises [21].
  • Delivered offline: terrain packages can be built and delivered for on-premise or air-gapped installation, with no dependency on external servers.

2. Air Force and Aviation Uses

  • Flight simulators and mission rehearsal. On 11 November 2024 the Indian Air Force inaugurated a C-295 Full Motion Simulator at Air Force Station Agra for tactical airlift, para-dropping, medical evacuation and disaster-relief missions. A significant part of pilot training can be done in the simulator, saving valuable flying hours [23].
  • Terrain awareness. Terrain-following and terrain-awareness systems (such as TAWS) rely on stored terrain and obstacle databases alongside GPS, so the accuracy of the terrain model is central to flight safety [24].
  • Synthetic vision. NASA's Synthetic Vision system shows a computer-generated 3D view of terrain and obstacles on the cockpit display, built from onboard terrain, obstacle and airport databases. In NASA testing it lowered the chance of hazardous events by 85% compared with traditional instruments [25].
  • Landing-zone and airfield planning. Geospatial products cover helicopter landing zones, drop zones, airfield analysis and vertical-obstruction analysis [26].

Business problem

Flying hours are expensive and limited, yet aircrew must prepare for tactical airlift, para-dropping, medical evacuation and disaster-relief missions over unfamiliar ground [23]. Terrain and obstacle data are central to flight safety [24], and studying landing zones, drop zones and airfield surroundings from maps and photographs alone is slow and gives aircrew little feel for the ground before they fly.

Our solution

  • 3D terrain and imagery of the areas a course needs, for ground-school briefing and route familiarisation on the Digital Sand Model.
  • Study layers for landing and drop zones: slope, elevation profiles, vegetation and surface objects from a DSM, and approach views along a planned route.
  • Terrain exported in standard formats, so it can be integrated with existing simulators where the institution requires it.
  • GLOBEIR terrain supports briefing and study; it does not replace certified avionics or simulator databases.

Benefits

  • Better-prepared aircrew who have seen the ground in 3D before flying.
  • Supports the shift of training to simulators: the IAF notes that a significant part of pilot training can be done in the C-295 simulator, saving valuable flying hours (industry example) [23].
  • Terrain awareness improves safety: in NASA testing, synthetic 3D terrain views lowered the chance of hazardous events by 85% compared with traditional instruments (industry example) [25].
  • The same terrain package serves briefing, simulator integration and disaster-relief exercises.

Privacy & data security

  • Data involved: high-resolution terrain and surface-object data around airfields and training areas.
  • Stored in India: any data finer than the DST threshold stays on servers in India, or entirely on the client's own systems, and never reaches non-Indian servers [21][22].
  • Air-gapped option: terrain can be delivered and run fully offline, with no external server dependency.
  • Authorised areas only: surveys are done only where the client has authorised access, and negative-list attributes are handled as the client directs [21].

3. Training and Simulation

The Live-Virtual-Constructive (LVC) framework. US defence modelling-and-simulation terminology defines three types: Live (real people operating real systems), Virtual (real people operating simulated systems) and Constructive (simulated people operating simulated systems) [27]. A shared, accurate 3D terrain is what allows the three to be combined in one exercise.

US Army Synthetic Training Environment (STE) and One World Terrain (OWT). STE combines live, virtual, constructive and gaming environments for training and mission rehearsal, with One World Terrain as its common 3D terrain [16][28], described as a virtual representation of the physical Earth accessible through the Army network [18]. In March 2024, tank, helicopter and Stryker crews tested STE; one participant noted the value of training virtually instead of spending the fuel, ammunition and logistics of going out in the field [29]. The Army says the STE Live Training System lets soldiers do more repetitions than live fire allows while reducing training costs and improving safety, with fielding at Combat Training Centres starting in FY2026 [30].

NATO. The NATO Modelling & Simulation Centre of Excellence in Rome supports NATO, member nations and partners in all aspects of M&S, with the aim of improving both operational effectiveness and resource management [31][32].

India.

  • Army Training Command (ARTRAC), formed in 1991 and based at Shimla, includes among its roles integrating technology such as simulation-based war-gaming into training [33].
  • Wargaming Development Centre (WARDEC): at a February 2026 seminar on Enhancing Military Decision-Making through Wargaming and Simulation in New Delhi, the Indian Army released three indigenous tools, including an Auto Evaluation Map Marking Tool and Automated Intelligence Preparation of the Battlefield [34].
  • Combat Training Node, Infantry School, Mhow: described as India's first Combat Training Node, with 60+ simulators, live-virtual-constructive training and after-action review (reported December 2025) [35].
  • Indian Air Force: C-295 Full Motion Simulator at Agra (see above) [23].

Business problem

Live exercises consume fuel, ammunition and equipment life and allow only a limited number of repetitions [29][30]. Combining live, virtual and constructive training needs a shared, accurate terrain [27], and institutions want indigenous systems that run on their own networks. Without a record of how an exercise unfolded, after-action review depends on memory and hand-drawn sketches, so lessons are lost between courses.

Our solution

  • A common terrain package that every classroom and exercise uses, built on open standards [17] so it can be shared with existing simulation tools where needed.
  • Phase-wise scenario playback and route and movement replay for after-action discussion.
  • Scenario builder, symbology library and course-ready exercise templates, with instructor training.
  • Developed in India and deployable on-premise or offline on the institution's own hardware.

Benefits

  • More repetitions at lower cost: training establishments abroad report lower training costs, safer training and more repetitions than live fire allows (industry example) [29][30].
  • A TERI study estimates that simulator-based training could save the Indian Armed Forces over ₹1,000 crore a year; this is a modelled projection, not a measured result [36].
  • Better learning from each exercise through replay-based after-action review.
  • Consistent exercises across courses, with less live resource use in the preparatory stages.

Privacy & data security

  • Data involved: scenario files, exercise replays and trainee assessment records.
  • Kept inside the institution: all of this stays on the institution's own servers or an air-gapped system, with no dependency on external servers.
  • Client policies and audits: handling follows the institution's information-security policies, and GLOBEIR supports its security audits.
  • NDA: confidentiality obligations are set out in a non-disclosure agreement.

4. Civil and Disaster-Response Uses of the Same Technology

The same terrain and 3D-modelling methods support relief work. US Army Corps of Engineers researchers used 2D/3D machine-learning models of aerial imagery to locate debris and estimate its volume after the 2023 Maui wildfires and Hurricane Helene, helping responders allocate resources and plan clean-up [37]. ISRO lists coastal tsunami and cyclone vulnerability assessment, watershed planning and disaster management among CartoDEM's uses [15], and the IAF C-295 simulator explicitly includes disaster-relief and medical-evacuation scenarios [23].

Business problem

Armed forces are often called on for flood, landslide and cyclone relief, and planning staff must prepare quickly: which areas will flood, which routes stay open, where helicopters can land. If training terrain and civil-response maps sit in separate systems, the work is duplicated, and preparation time is lost when it matters most [15][37].

Our solution

  • Flood-inundation, landslide-susceptibility and access-route layers on the same 3D terrain used for training.
  • Humanitarian assistance and disaster-relief scenarios that use the same scenario builder and replay tools.
  • Coordination maps prepared for civil agencies when the client chooses to share them, through WebGIS.

Benefits

  • One platform for training and humanitarian assistance, so staff already know the tools when a disaster strikes.
  • Faster relief planning: 2D/3D models of aerial imagery have been used to locate debris and estimate its volume after major disasters, helping responders allocate resources (industry example) [37].
  • Disaster-relief scenarios can be rehearsed in advance, as in the C-295 simulator's training scope [23].
  • Public CartoDEM data already supports coastal vulnerability and disaster-management studies, keeping data costs low [15].

Privacy & data security

  • Data involved: terrain, imagery and access routes for disaster-prone areas, often combined with the client's own sensitive layers.
  • Client controls sharing: nothing is shared with civil agencies unless the client approves it, and shared maps can be generalised to coarser detail.
  • DST rules: finer-than-threshold data stays in India, and negative-list attributes are kept out of shared products [21][22].
  • Offline when needed: the full system can run on-premise or air-gapped.

5. Proven Benefits

Benefit Evidence
Faster terrain production Drone-to-3D terrain for about 1 km² reduced from weeks to about 3 hours [16]
Lower cost Avoided fuel, ammunition and logistics cited by STE testers [29]; reduced training costs [30]
Repeatability More repetitions than live fire allows [30]
Safety Safer training [30]; 85% fewer hazardous events with synthetic vision in NASA testing [25]
Saved flying hours Significant share of pilot training moved to the simulator [23]
Faster planning Geospatial products reduce analysis time for planners [26]
India-specific estimate A TERI study (reported May 2026) estimates simulator-based training could save the Indian Armed Forces over ₹1,000 crore a year. This is a modelled projection, not a measured result [36]

How a project runs

From first data to daily decisions

  1. 1

    Define training needs

    Work with the training authority to list the platforms, courses, training areas and airfields to be modelled, the level of detail needed in each zone and the target simulator formats. Security and data-handling rules are agreed at this stage.

  2. 2

    Assemble source data

    Collect elevation models, satellite and aerial imagery, topographic vectors, airfield layouts and obstacle records from authorised public and client-supplied sources. Each input is logged with its date, resolution and accuracy so gaps are visible early.

  3. 3

    Process and model

    Correct and fuse elevation data, build orthomosaics, extract and attribute features, and model airfields and obstacles in 3D. Products are generated at several levels of detail and checked against ground control and reference data.

  4. 4

    Structure and export

    Organise the content into tiles, layers and levels of detail aligned with OGC CDB, or export it into the formats required by the client's image generators and planning tools, with full metadata.

  5. 5

    Validate with instructors

    Review terrain, airfields and features in the simulator and in 3D viewers with instructors, fix visual or positional issues, and confirm that the content fully supports the intended training objectives of each course.

  6. 6

    Maintain and refresh

    Schedule imagery and obstacle updates, refresh only the affected datasets, and publish new versions to connected simulators. A coverage dashboard tracks data age and accuracy across the whole training programme over time.

Data we work with

  • NRSC CartoDEM (Bhuvan)

    India's national elevation model from Cartosat-1 stereo data, available at 30 m posting with co-registered orthoimagery, for wide-area terrain relief.

  • Copernicus DEM GLO-30

    A freely available global 30 m digital surface model derived mainly from TanDEM-X radar data, useful for consistent terrain beyond national coverage.

  • High-resolution satellite and aerial imagery

    Sub-metre to metre-level imagery that supplies geospecific textures and the basis for feature extraction around airfields and training areas.

  • Survey of India topographic data

    Authoritative topographic vectors such as roads, rivers, settlements and contours that populate the synthetic environment with real features.

  • ICAO-style terrain and obstacle datasets

    Structured terrain and obstacle data following ICAO Annex 15 coverage areas, giving positions and heights of vertical obstacles near aerodromes.

  • LiDAR and drone surveys

    Detailed surface models and 3D structure data for small high-detail zones such as airfield surroundings, where national DEMs are too coarse.

  • Published aeronautical information

    Publicly available aeronautical charts and airspace descriptions that inform airfield layouts and generic airspace layers for training visualisation.

KPIs you can track

  • Share of planned training areas covered by geospecific terrain
  • Average age of imagery across the terrain database
  • Vertical accuracy of terrain checked against ground control points
  • Time from source data receipt to simulator-ready database release
  • Number of airfields modelled in 3D and kept current
  • Correlation discrepancies found between linked simulators per exercise
  • Share of database updates delivered as partial dataset refreshes
  • Instructor-reported terrain or visual issues per training course

Privacy & data security

How we keep your data private and secure

Terrain data for training areas is sensitive even when it is built entirely from public sources. Once high-resolution elevation, imagery, annotations and exercise replays are brought together, they reflect how an institution trains and plans, so they must stay under the institution's control at every stage, from survey to classroom.

Regulations we design for

  • DST Guidelines for Geospatial Data (2021): data finer than the threshold (1 m horizontal, 3 m vertical) can only be created and owned by Indian entities and must be stored and processed in India; a negative list of sensitive attributes may be regulated; and the guidelines give no right of access to restricted premises [21].
  • DST clarification (November 2022): finer-than-threshold data must never be transmitted to or reach the servers of any non-Indian entity [22].
  • National Geospatial Policy 2022: confirms that data acquisition, production and access continue to be governed by the Guidelines [38].
  • The client's own security instructions: each engagement follows the security policies and directions the institution sets out in its contract.

How GLOBEIR protects your data

Safeguard How it works
Air-gapped / offline deployment The full platform and terrain packages run on a system with no internet connection
On-premise installation Installed on the institution's own hardware and network, under its own administration
No external server dependency Terrain, tools and scenarios work without calling any outside server, map service or licence server
Storage and processing in India Finer-than-threshold data is stored and processed only in India and never sent to non-Indian servers [21][22]
Negative-list handling Sensitive attributes on the DST negative list are excluded or handled as the client directs [21]
Authorised areas only Drone and field surveys are carried out only where the client has authorised access; no access to restricted premises is assumed [21]
Non-disclosure agreement GLOBEIR signs an NDA for each engagement
Client security policies GLOBEIR follows the institution's information-security policies for access, storage and handling
Audit support GLOBEIR supports the client's security audits and vendor assessments

Your data, your control

  • The institution owns its terrain packages, scenarios, annotations and exercise records.
  • Data is used only for the agreed training or planning purpose; it is not sold or shared, and not used to train models for other clients.
  • Deployment is the client's choice: on its own servers or data centre, on-premise in the classroom, or fully air-gapped.
  • At the end of an engagement, or on request, data is exported to the client and deleted from any GLOBEIR systems.
  • An NDA is available for every engagement.
  • Privacy contact: privacy@globeir.com.

Frequently asked questions

Why does terrain accuracy matter in a flight simulator?

Trainees learn to navigate, recognise landmarks and judge approaches from what they see. If the simulator shows generic or misplaced terrain, those skills do not carry over well to real flying. Geospecific elevation, imagery and airfield models let simulator time build habits that match the real environment, so live sorties can focus on what only live flying can teach.

What is the OGC CDB standard?

CDB is an Open Geospatial Consortium standard that defines a model and structure for a single, versionable virtual representation of the earth for simulation. It organises terrain, imagery, vector features and 3D models into tiles, layers and levels of detail, so several simulators can read the same data store and share a common view of the environment.

Can public datasets be used to build simulator terrain?

Yes, for many purposes. National and global elevation models such as CartoDEM and Copernicus DEM give a consistent base for wide areas, and topographic data adds real features. High-detail zones around airfields usually need finer imagery, LiDAR or survey data. GLOBEIR documents the source and accuracy of every layer so users know its limits.

Does GLOBEIR handle sensitive or operational data?

GLOBEIR's work in this area focuses on training, education and planning value. Content is built from authorised public or client-supplied data under the client's security rules, and GLOBEIR does not publish operational, tactical or unit-specific information. Data handling arrangements are agreed with the client at the start of each engagement.

How often should a simulator terrain database be updated?

It depends on how fast the real environment changes. Airfields, obstacles and built-up areas near training routes change most often and benefit from scheduled refreshes, while wide-area relief is stable. Structuring data so individual datasets can be updated without rebuilding whole tiles keeps refresh cycles short and affordable.

Sources

  1. [1]Investment Strategies for Improving Fifth-Generation Fighter Training (TR-871) · RAND Corporation, Project AIR FORCE, 2011
  2. [2]Simulators for Armed Forces (on the MoD Framework for Simulators in Armed Forces) · SP's MAI, 2021
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