ASEAN Geospatial Analytics Market Size and Share
ASEAN Geospatial Analytics Market Analysis by Mordor Intelligence
The ASEAN geospatial analytics market size is USD 0.76 billion in 2025 and is forecast to touch USD 1.35 billion by 2030, reflecting a robust 12.18% CAGR over the period. Demand expands as hyperscale cloud investments intersect with government smart-city agendas, sovereign data policies and ESG-linked financing, creating a virtuous cycle of infrastructure build-out and analytics adoption across member states. Microsoft’s USD 1.7 billion injection into Indonesia, Google’s USD 2 billion commitment to Malaysia and Microsoft’s USD 2.2 billion pledge to Malaysia illustrate the scale of capital flowing into AI-ready data estates. National digital frameworks such as the ASEAN Digital Economy Framework Agreement (expected 2025) aim to harmonize cross-border data rules, enabling regional analytics platforms previously stifled by patchwork regulations. While software retains dominance, rapid gains in managed services and LiDAR adoption signal that value is shifting toward outcome-oriented offerings and high-resolution sensing.
Key Report Takeaways
- By geography, Indonesia led with 30% ASEAN geospatial analytics market share in 2024, while Vietnam is poised to grow at a 13.9% CAGR through 2030.
- By component, software commanded 46% revenue share of the ASEAN geospatial analytics market in 2024; services are projected to expand at a 14.8% CAGR to 2030.
- By end-user vertical, government & public safety held 24% share of the ASEAN geospatial analytics market in 2024, whereas automotive & transportation is advancing at a 14.6% CAGR through 2030.
- By deployment mode, on-premise captured 52% share of the ASEAN geospatial analytics market size in 2024; cloud deployments are expected to register 13.5% CAGR to 2030.
- By technology, GIS represented 41% share of the ASEAN geospatial analytics market in 2024, and LiDAR technology is projected to climb at a 16.4% CAGR through 2030.
ASEAN Geospatial Analytics Market Trends and Insights
Drivers Impact Analysis
Driver | (~) % Impact on CAGR Forecast | Geographic Relevance | Impact Timeline |
---|---|---|---|
Smart-city investment surge across ASEAN capitals | +2.8% | Indonesia, Thailand, Singapore, Malaysia | Medium term (2-4 years) |
Rapid 5G roll-out unlocking high-volume, low-latency location data | +2.1% | Malaysia, Singapore, Thailand, Vietnam | Short term (≤ 2 years) |
National geospatial data-sharing mandates (e.g., Thailand GISTDA) | +1.9% | Thailand, Indonesia, Singapore | Long term (≥ 4 years) |
ESG-linked infrastructure funding favouring geospatial monitoring | +1.4% | Regional, emphasis on Indonesia & Malaysia | Medium term (2-4 years) |
Source: Mordor Intelligence
Smart-city Investment Surge Across ASEAN Capitals
Capital programmes targeting more than 100 Indonesian smart cities by 2045 are catalysing steady procurement of integrated spatial platforms that fuse IoT telemetry with analytics for traffic, utilities and citizen services. [1]Thailand’s collaboration with Japan under the ASEAN-Japan Smart Cities Network drives standardisation that favours scalable solution suites, while Singapore’s SGD 27 million (USD 21.07 million) workforce upskilling pool channels fresh talent into enterprise GIS operations. Multiplier effects are evident as utilities, real-estate developers and telecom operators align their roadmaps with municipal digital blueprints, enlarging the ASEAN geospatial analytics market beyond core government demand. Vendors with end-to-end capabilities capture share by bundling software, data and implementation services into outcome-oriented contracts.
Rapid 5G Roll-out Unlocking High-Volume, Low-Latency Location Data
Malaysia’s target of 80% 5G coverage by 2024 and a regional forecast of 620 million 5G subscriptions by 2028 herald a step-change in data velocity. [2]Ericsson, “5G in South East Asia and Oceania: A closer look”, Ericsson, ericsson.com AIS’s dedicated 5G network at Midea Thailand lifted factory efficiency 15-20%, illustrating how sub-10 millisecond latency reshapes geospatial use cases from autonomous forklifts to emergency dispatch. Telkomsel’s 5G smart warehouse in Indonesia cut errors by 25%, reinforcing the business case for edge analytics that ingest, process and act on spatial streams in near real time. As sensor density rises, machine-learning models exploit richer datasets to surface micro-patterns that were undetectable in the 4G era, boosting demand for GPU-accelerated spatial AI pipelines within the ASEAN geospatial analytics market.
National Geospatial Data-sharing Mandates Drive Standardisation
Thailand’s GISTDA portfolio spans fire monitoring to marine navigation, proving the efficiency gains from shared base layers and common metadata models. Indonesia’s One Map Policy compels ministries to converge on unified coordinate references, driving enterprise-grade platform roll-outs able to manage terabyte-scale repositories.[3]Malaysia’s MyGDI Explorer balances openness with role-based access, demonstrating governance architectures that accommodate security while encouraging reuse. The resultant interoperability pressures create competitive advantage for vendors offering plug-and-play connectors, positioning integrators as pivotal orchestrators within the ASEAN geospatial analytics market.
ESG-linked Infrastructure Funding Favours Geospatial Monitoring
The Asian Infrastructure Investment Bank’s AUD 500 million Climate Adaptation Bond and the Asian Development Bank’s USD 100 billion climate-finance target place quantifiable ESG reporting at the heart of project approval. Platforms that automate GHG baseline capture, biodiversity mapping and compliance dashboards help developers secure preferential financing, embedding geospatial analytics within due-diligence checklists. National sustainable-finance taxonomies in Indonesia and Thailand amplify this shift by codifying disclosure requirements that geospatial tools can address, reinforcing demand across water-management, renewable-energy and green-transport initiatives.
Restraints Impact Analysis
Restraint | (≈) % Impact on CAGR Forecast | Geographic Relevance | Impact Timeline |
---|---|---|---|
High-performance GPU/CPU costs for real-time analytics | -1.8% | Region-wide; acute in smaller economies | Short term (≤ 2 years) |
Fragmented spatial data standards among ASEAN member states | -1.2% | Cross-border applications | Medium term (2-4 years) |
Source: Mordor Intelligence
High-performance GPU/CPU Costs Constrain Real-time Processing Capabilities
The price premium on AI-class GPUs raises the entry bar for organisations aiming to shift from batch to live spatial analytics, particularly in currency-vulnerable markets such as Laos and Cambodia. Although hyperscale cloud regions in Malaysia and Indonesia offer on-demand alternatives, sovereign-data clauses and latency-sensitive apps—autonomous driving, emergency response—compel many agencies to retain local compute, keeping capital expenditure elevated. This cost friction segments the ASEAN geospatial analytics market into Tier 1 adopters with in-house clusters and Tier 2 users that outsource to service bureaux, inhibiting democratic diffusion of advanced analytics.
Fragmented Spatial Data Standards Limit Cross-border Integration
Divergent datum choices, metadata schemas and localisation laws frustrate pan-ASEAN logistics corridors that require continuous routing updates across customs zones. Transformation overheads inflate project timelines, while localisation mandates in Vietnam and Brunei necessitate mirror infrastructures that duplicate capex. Voluntary harmonisation initiatives under the ASEAN Framework on Personal Data Protection have yet to achieve consistent implementation, compelling platform vendors to maintain multi-tenant architectures customised per jurisdiction. The friction delays scaled roll-outs, clipping CAGR potential despite rising demand.
Segment Analysis
By Component: Software Dominance Faces Services Disruption
Software retained a 46% slice of the ASEAN geospatial analytics market in 2024, anchored by entrenched GIS stacks deployed across utilities and cadastral agencies. Yet managed services are outpacing at 14.8% CAGR as boards re-orient budgets toward measurable outcomes instead of perpetual licence fees. Indonesia’s PLN illustrated the pivot by outsourcing network-vulnerability analytics to an Esri services partner, accelerating deployment while conserving capex. [4]Esri Indonesia, “PLN innovates network vulnerability assessment with GIS”, Esri Indonesia, esriindonesia.co.id The ASEAN geospatial analytics market size for services is projected to rise steadily as AI skill shortages push enterprises to seek turnkey engagements that bundle algorithms, data engineering and change management. Hardware demand—edge servers, GPU arrays—remains resilient where sovereignty imperatives block cloud offloading, creating hybrid revenue streams.
Managed-service expansion recasts competitive dynamics. Global vendors launch consumption-based SaaS tiers, while regional integrators monetise localisation know-how, custom data models and regulatory navigation. Hexagon’s planned Asset Lifecycle Intelligence spin-off exemplifies the shift, aiming to package sensors, digital twins and advisory into a lifecycle value proposition. Over the medium term, pricing power is expected to migrate toward service providers orchestrating multi-cloud, multi-sensor ecosystems rather than standalone software licensors, embedding sustained annuity flows within the ASEAN geospatial analytics market.
Note: Segment shares of all individual segments available upon report purchase
By Type: Surface Analysis Leadership Challenged by Spatial AI Innovation
Surface analysis drove 38% of 2024 revenues as governments mapped terrain for land-use planning and infrastructure sits. However, spatial AI and predictive-modelling workflows are climbing at 15.2% CAGR, underscoring a leap from descriptive to anticipatory analytics. Random-forest classifiers running on cloud platforms delivered 95% accuracy in Indonesia’s commodity mapping—surpassing traditional photogrammetry outputs. Within the ASEAN geospatial analytics market, incremental compute costs are justified by higher decision accuracy, shortening project payback.
Emergent AI solutions harness fused LiDAR, SAR and optical streams to forecast flood risk, crop yield and congestion hours ahead of events. UAV-driven settlement-density studies in Jakarta demonstrate how machine-learning inference at the edge compresses field-to-insight cycles from days to minutes. For suppliers, capability gaps around data labelling, model governance and ethics open advisory revenue; for users, productivity gains compel re-allocation of OPEX toward algorithm subscriptions, intensifying the ASEAN geospatial analytics market’s transition to an insight-as-a-service paradigm.
By End-user Vertical: Government Dominance Yields to Automotive Innovation
Government and public-safety agencies accounted for 24% of 2024 spending, reflecting long-standing mandates for cadastral, census and emergency-management functions. Yet automotive and transportation workloads are accelerating at 14.6% CAGR as ride-hailing leaders, logistics integrators and OEMs embed location intelligence directly into core platforms. Grab’s ambition to monetise USD 1 billion in location-based services through proprietary mapping showcases vertical integration designed to differentiate user experience and optimise driver economics. The ASEAN geospatial analytics market sees rising R&D outlays for HD map generation, sensor fusion and simulation environments that feed advanced-driver-assistance systems.
Concurrently, healthcare deploys GIS to track disease spread and optimise facility placement under the Health GeoLab programme. Defence, utilities and agriculture segments maintain growth trajectories tied to ESG reporting, smart-grid roll-outs and precision farming. Diversification cushions the market against cyclical downturns in any single vertical, reinforcing a balanced demand portfolio for solution providers.
By Deployment Mode: On-premise Resilience Despite Cloud Acceleration
On-premise architectures held 52% ASEAN geospatial analytics market share in 2024 as ministries and defence outfits ring-fenced sensitive spatial repositories behind national firewalls. Nevertheless, new cloud regions in Malaysia and Indonesia are lifting regional cloud CAGR to 13.5%, luring commercial players seeking elasticity and managed AI tooling. Edge or hybrid topologies emerge fastest, enabling low-latency inference on-site while off-loading training workloads to hyperscale GPU clusters.
Batam’s designation as a national data-centre hub exemplifies a bridge approach—local sovereignty compliance plus connectivity to trans-ASEAN fibre rings, facilitating burst compute for flood-simulation or pandemic-spread modelling. Over time, service wrappers that abstract underlying heterogeneity will win share, as enterprises demand single-pane orchestration of distributed pipelines across cloud, colo and edge nodes.

Note: Segment shares of all individual segments available upon report purchase
By Technology: GIS Foundation Supports LiDAR Innovation Leadership
GIS formed the backbone, delivering 41% revenue share in 2024, but LiDAR outperforms at a 16.4% CAGR, catalysed by falling sensor prices and autonomous-vehicle pilots. Indonesian flood-mapping used airborne LiDAR data to derive digital-terrain models, accelerating hazard zoning. In Thailand, LiDAR quantified plant-area index gradients in tropical forests, advancing climate-monitoring protocols. Cross-domain deployments—roadside LiDAR for AV blind-spot elimination, plantation monitoring via drone-mounted scanners—highlight versatility. Suppliers combining LiDAR with AI post-processing layers command premiums, enlarging the ASEAN geospatial analytics market size captured per project.
Complementary technologies—GNSS augmentation, web-map APIs, remote-sensing spectral stacks—remain integral, delivering base layers and enrichment that extend LiDAR insights into comprehensive digital twins. Integration suites dominate procurement shortlists, favouring vendors able to harmonise multi-modal inputs within secure, low-latency pipelines.
Geography Analysis
Indonesia anchors the ASEAN geospatial analytics market with a 30% share in 2024, propelled by its One Map Policy, sprawling archipelagic geography and the USD 1.7 billion Microsoft cloud investment that underpins national AI ambitions Microsoft. Continuous initiatives in smart-city rollout, disaster-risk mitigation and natural-resource monitoring sustain multi-year contract flows. The country’s plan to elevate Batam into a sovereign data-centre hub further boosts domestic compute capacity and positions Indonesia as a regional processing waypoint..
Vietnam represents the fastest-rising contributor, advancing at a 13.9% CAGR as its National AI Strategy prioritises geospatial in agriculture and manufacturing. The government-backed planning information system, aimed at full GIS integration by 2035, provides long-run demand visibility that attracts foreign solution providers such as Esri through alliances with local engineering firm Portcoast. Precision-rice initiatives harness satellite and UAV data to fine-tune irrigation and fertiliser regimes, enhancing export competitiveness while unlocking carbon-credit opportunities.
Singapore, Thailand, Malaysia and the Philippines form a second cluster characterised by specialised capabilities. Singapore’s vision to become a global geospatial hub, supported by SGD 27 million (USD 21.07 million) in AI-skills funding, drives standards across the wider ASEAN geospatial analytics market Geospatial World. Thailand’s GISTDA satellite programme offers indigenous earth-observation streams that feed regional disaster-alert networks. Malaysia’s more than USD 23.3 billion data-centre pipeline lures hyperscale tenants, translating into regional cloud availability for compute-intensive geospatial workloads. [5]The Jakarta Post, “Can ASEAN build a sustainable data center future?”, The Jakarta Post, thejakartapost.com Emerging economies—Cambodia, Laos, Myanmar and Brunei—remain underserved but present greenfield potential as donor-funded capacity-building programmes establish foundational spatial infrastructures.
Competitive Landscape
The ASEAN geospatial analytics market exhibits moderate concentration, with tier-one global vendors competing alongside nimble local specialists. Hexagon’s plan to spin out its EUR 1.448 billion (USD 1.56 billion) Asset Lifecycle Intelligence division signals a strategic pivot toward integrated SaaS bundles that fuse sensors, analytics and advisory, aiming to lock in enterprise workflows from design through decommissioning. Esri deepens localisation via training and partner programmes, while Planet Labs leverages subscription-based earth-observation feeds to close multi-year contracts such as the USD 230 million JSAT deal, underscoring data-as-a-service momentum.
Regional disruptors exploit domain depth and regulatory fluency. Indonesia’s Integrasia Utama monetises agritech expertise through its One Spirit Ecosystem, offering IoT integrations tailored to plantation operations. Thai and Malaysian start-ups focus on edge-analytics appliances that satisfy data-residency clauses, carving niches where hyperscalers hesitate. Meanwhile, platform customers increasingly demand outcome-based SLAs, prompting vendors to couple licensing with KPI-tied services—for example, guaranteeing flood-warning lead times or logistics-route efficiency gains.
Strategic moves centre on capacity expansion, skill development and ecosystem partnerships. Microsoft and Google fund national AI academies to seed user communities that, in turn, consume more cloud cycles. Grab’s decision to internalise mapping functions illustrates vertical-integration playbooks designed to protect proprietary data and differentiate user experience. Collectively, these moves intensify competition on talent, GPU resources and governance compliance, but also expand total addressable spend within the ASEAN geospatial analytics market.
ASEAN Geospatial Analytics Industry Leaders
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GIS Co., Ltd.
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MappointAsia (Thailand) Public Company Limited
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Geospatial AI Sdn Bhd (Uzma Berhad)
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Hexagon AB
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PT. Bhumi Varta Technology
- *Disclaimer: Major Players sorted in no particular order

Recent Industry Developments
- May 2025: Google announced a USD 2 billion investment to build Malaysia’s first Google data centre and Google Cloud region, forecasting USD 3.2 billion in economic impact and 26,500 jobs by 2030, a capacity-expansion strategy securing proximity to sovereign workloads
- May 2025: Microsoft committed USD 2.2 billion to Malaysia’s cloud and AI transformation, including a national AI Centre of Excellence and training for 200,000 people, aligning product pull-through with skills pipeline creation
- April 2025: Esri partnered with Vietnam’s Portcoast to advance smart-urban and infrastructure analytics, reflecting a localisation strategy that leverages domestic EPC networks for market access
- March 2025: Hexagon began spinning off its Asset Lifecycle Intelligence division, sharpening strategic focus on high-growth SaaS verticals across geospatial and industrial IoT
ASEAN Geospatial Analytics Market Report Scope
Geospatial analytics is the process of acquiring, manipulating, and displaying imagery and data from the geographic information system (GIS), such as satellite photos and GPS data. The specific identifiers of a street address and a zip code are used in geospatial data analytics. They are used to create geographic models and data visualizations for more accurate trend modelling and forecasting.
The ASEAN geospatial analytics market is segmented by type (surface analysis, network analysis, geovisualization), end user vertical (agriculture, utility and communication, defence and intelligence, government, mining and natural resources, automotive and transportation, healthcare, real estate and construction), and country (Thailand, Indonesia, Malaysia, Singapore). The market sizes and forecasts are provided in terms of USD value for all the above segments.
By Component | Software |
Services | |
Hardware | |
By Type | Surface Analysis |
Network Analysis | |
Geo-visualization | |
Spatial AI & Predictive Modelling | |
By End-user Vertical | Government & Public Safety |
Defense & Intelligence | |
Utilities & Telecom | |
Agriculture | |
Mining & Natural Resources | |
Real Estate & Construction | |
Healthcare | |
Automotive & Transportation | |
Other Verticals | |
By Deployment Mode | On-premise |
Cloud | |
Edge / Hybrid | |
By Technology | GIS |
GPS | |
Remote Sensing | |
LiDAR | |
Web Map Services & APIs | |
By Country | Brunei |
Cambodia | |
Indonesia | |
Laos | |
Malaysia | |
Myanmar | |
Philippines | |
Singapore | |
Thailand | |
Vietnam |
Software |
Services |
Hardware |
Surface Analysis |
Network Analysis |
Geo-visualization |
Spatial AI & Predictive Modelling |
Government & Public Safety |
Defense & Intelligence |
Utilities & Telecom |
Agriculture |
Mining & Natural Resources |
Real Estate & Construction |
Healthcare |
Automotive & Transportation |
Other Verticals |
On-premise |
Cloud |
Edge / Hybrid |
GIS |
GPS |
Remote Sensing |
LiDAR |
Web Map Services & APIs |
Brunei |
Cambodia |
Indonesia |
Laos |
Malaysia |
Myanmar |
Philippines |
Singapore |
Thailand |
Vietnam |
Key Questions Answered in the Report
What is the current size of the ASEAN geospatial analytics market?
The market stands at USD 0.76 billion in 2025 and is projected to reach USD 1.35 billion by 2030 at a 12.18% CAGR.
Which country holds the largest ASEAN geospatial analytics market share today?
Indonesia leads with 30% market share in 2024, supported by its One Map Policy and major cloud investments.
Which segment is expanding fastest within the ASEAN geospatial analytics market?
LiDAR technology is growing at 16.4% CAGR, driven by autonomous-vehicle pilots and precision agriculture.
Why are services gaining ground over software licences?
Organisations prefer outcome-based engagements that bundle AI expertise and data engineering, propelling services to a 14.8% CAGR.
How does 5G deployment influence geospatial analytics demand?
5G delivers low-latency, high-volume data streams enabling real-time analytics for smart factories, ride-hailing and emergency response, adding an estimated +2.1% to market CAGR.
What are the main barriers to wider adoption in smaller ASEAN economies?
High GPU costs and fragmented data standards elevate project expenses and complexity, curbing deployment speed in resource-constrained markets.
Page last updated on: June 18, 2025