Location: Chiang Mai, Thailand
Client Type: Public Sector Organisation
Northern Thailand experiences recurring forest fires during the dry season, driven by prolonged drought, dense vegetation buildup, agricultural burning practices, and complex mountainous terrain. These fires threaten biodiversity, air quality, public health, and local livelihoods, while also placing significant pressure on emergency response teams. Limited visibility in high-risk zones and fragmented historical fire data made it difficult for authorities to anticipate ignition hotspots and allocate resources efficiently.
We developed an integrated wildfire risk model using satellite-derived vegetation indices, slope and elevation analysis, climate variables, and historical fire occurrence records. By mapping fuel loads and identifying terrain conditions that accelerate fire spread, we produced dynamic risk layers highlighting priority intervention areas. The model supported targeted prevention strategies, optimised patrol deployment, and informed long-term forest management planning aimed at reducing fire frequency and limiting ecological and economic damage.
Location: Mekong Delta, Vietnam
Client Type: Government
Rapid coastal erosion, upstream dam construction, aquaculture expansion, and rising sea levels have significantly reduced mangrove coverage across parts of the Mekong Delta. The loss of these natural buffers has increased vulnerability to storm surges, saltwater intrusion, and shoreline retreat, threatening coastal communities, fisheries, and agricultural land. Restoration efforts were underway, but lacked a comprehensive spatial framework to determine where replanting would be most effective and sustainable over the long term.
We conducted detailed spatial mapping of existing mangrove extent using satellite imagery and historical land cover data, combined with analysis of tidal dynamics, sediment movement, and erosion rates. By identifying zones with stable sediment accumulation and favourable hydrological conditions, we defined priority restoration areas with the highest likelihood of long-term survival. The project also established a GIS-based monitoring system to track regrowth, shoreline change, and ecosystem health, enabling data-driven coastal management and improved resilience planning.
Location: Texas, United States
Client Type: Private Agricultural Company
A severe winter freeze brought prolonged sub-zero temperatures and snowfall across southern Texas, damaging thousands of hectares of citrus orchards and vegetable farmland. Frost penetration destroyed fruit trees, irrigation systems froze, and large sections of agricultural infrastructure became unusable. The event caused major production losses, disrupted regional supply chains, and created uncertainty around which orchards could realistically recover versus those requiring complete replanting.
We conducted high-resolution satellite analysis and thermal mapping to identify the extent and severity of frost damage across the affected agricultural zones. Using elevation models, temperature datasets, and drone imagery, we identified vulnerable cold-air pooling areas and prioritised recovery zones based on long-term viability. The project also included frost-risk modelling and infrastructure planning recommendations to help reduce future cold weather exposure and improve agricultural resilience.
Location: Rajasthan, India
Client Type: Private Sector Company
Large-scale solar development in Rajasthan presents significant opportunity due to high solar irradiance, but site selection is constrained by land ownership complexity, grid connectivity limitations, environmental regulations, and water scarcity. Poorly selected locations can face costly delays related to transmission access, land acquisition disputes, or environmental clearance challenges. The client required a rigorous, data-driven approach to reduce investment risk while ensuring long-term operational viability and maximum energy yield.
We carried out a multi-criteria spatial analysis combining long-term solar radiation datasets, land use and land cover mapping, terrain slope modelling, proximity to substations and transmission lines, and environmental exclusion zones. By overlaying infrastructure accessibility, grid capacity data, and regulatory constraints, we identified priority development corridors with strong generation potential and minimal permitting risk. The final GIS-based suitability model supported strategic land acquisition decisions, optimised capital deployment, and reduced future operational and maintenance costs.
Location: Punjab, India
Client Type: Government
Punjab faces increasing pressure on its water resources due to intensive agriculture, groundwater over-extraction, erratic monsoon rainfall, and the dominance of water-intensive crops such as rice. Falling water tables and declining aquifer recharge rates have created long-term sustainability concerns, while uneven irrigation infrastructure has resulted in inefficient water distribution across districts. Policymakers required a spatial understanding of water stress patterns to balance agricultural productivity with resource conservation.
We developed a GIS-based water management framework integrating groundwater depth measurements, rainfall variability data, canal irrigation networks, and crop-specific water demand modelling. By mapping recharge zones and identifying areas of excessive extraction, we supported targeted irrigation optimisation and crop diversification planning. The analysis informed more efficient resource allocation, improved irrigation scheduling, and strategic interventions designed to stabilise groundwater levels while maintaining agricultural output.
Location: Sumatra, Indonesia
Client Type: Public Sector Organisation
Rapid deforestation, palm oil expansion, illegal logging, and infrastructure development have fragmented critical habitats across Sumatra, threatening endangered species such as orangutans, Sumatran tigers, and elephants. Habitat fragmentation has reduced wildlife movement corridors, increased human-wildlife conflict, and placed additional pressure on already vulnerable ecosystems. Conservation authorities required a spatially precise assessment of priority habitats and emerging threat zones to guide intervention and policy decisions.
We integrated high-resolution satellite imagery, historical land cover datasets, and wildlife tracking data to map habitat extent, fragmentation patterns, and migration corridors. Spatial analysis identified areas of high biodiversity value alongside zones experiencing rapid encroachment or infrastructure expansion. The resulting conservation prioritisation framework supported targeted protection measures, corridor restoration planning, and evidence-based policy development aimed at safeguarding biodiversity while balancing regional land use pressures.
Location: Minas Gerais, Brazil
Client Type: Commodity Export Company
Rare frost events affected major coffee-growing regions following an intense cold air outbreak that pushed temperatures below freezing. Coffee trees suffered structural damage and crop losses across large plantation areas, reducing harvest forecasts and impacting international coffee markets. Many farms faced multi-year recovery periods due to the permanent nature of frost injury on mature coffee plants.
We used satellite imagery, elevation analysis, and climate modelling to map frost exposure across coffee-producing regions. The project identified plantation zones most vulnerable to future cold weather events and highlighted safer long-term cultivation areas based on topography and climate stability. Spatial yield forecasting tools were also developed to support recovery planning, insurance assessment, and future agricultural investment decisions.
Location: Malaysia
Client Type: Private Sector Company
Malaysia’s tropical climate, steep terrain, and intense seasonal rainfall create significant landslide risk, particularly in rapidly developing hillside regions. Infrastructure expansion, road construction, and land clearing can destabilise slopes by altering drainage patterns and removing vegetation cover. The client required a thorough risk evaluation to ensure that planned development would not expose assets, personnel, or surrounding communities to long-term geotechnical instability.
We carried out a spatial analysis combining digital elevation models, rainfall intensity records, soil composition mapping, and land cover classification to assess slope susceptibility across the project area. By modelling drainage flow paths and identifying zones of high shear stress and soil saturation, we produced a landslide risk map highlighting critical hazard corridors. The findings informed site design adjustments, drainage engineering recommendations, and construction sequencing strategies aimed at reducing slope failure risk and improving long-term infrastructure resilience.
Location: Doha, Qatar
Client Type: Government
Rapid urban expansion in Doha has placed increasing pressure on transport networks, utilities, and public services. Population growth, large-scale construction projects, and concentrated commercial districts created traffic congestion, uneven service provision, and inefficiencies in infrastructure deployment. The government required an integrated spatial framework to ensure that future development aligned with long-term sustainability goals while maintaining efficient mobility and service delivery across the city.
We developed a GIS-driven urban planning platform integrating real-time traffic flows, population density models, land use data, and smart sensor inputs from key infrastructure systems. Spatial analysis identified congestion hotspots, under-served residential areas, and optimal corridors for future transport and utility expansion. The project supported evidence-based infrastructure placement, improved traffic management strategies, and long-term planning initiatives designed to enhance connectivity, reduce urban stress, and support sustainable city growth.
Location: Dubai, United Arab Emirates
Client Type: Government
Rapid urban development, high-rise construction, and extensive use of heat-absorbing materials have intensified the urban heat island effect across Dubai. Dense building clusters, limited vegetation cover, and large expanses of asphalt and concrete contribute to elevated surface temperatures, particularly during peak summer months. These conditions increase energy demand for cooling, strain public infrastructure, and create health risks for vulnerable populations. Authorities required a spatially detailed understanding of heat concentration patterns to inform long-term urban design strategies.
We conducted land surface temperature analysis using satellite thermal imagery combined with building material classification, urban density metrics, and shading assessments. Spatial modelling identified priority heat concentration zones and areas lacking adequate green infrastructure. Based on these findings, we developed targeted mitigation recommendations including strategic green space expansion, reflective roofing materials, urban shading design, and revised zoning guidelines. The project established a data-driven framework to reduce heat intensity, improve urban comfort, and enhance climate resilience across the city.
Location: Uttar Pradesh, India
Client Type: Government
Repeated winter cold waves and dense fog conditions affected potato and mustard growing regions across northern India. Frost damage, poor sunlight penetration, and excess moisture contributed to lower crop yields and increased fungal disease outbreaks. Farmers experienced delayed growth cycles, reduced productivity, and growing uncertainty around seasonal harvest reliability.
We integrated satellite crop monitoring, frost-risk mapping, and soil moisture analysis to assess agricultural vulnerability across affected districts. GIS modelling identified regions facing the highest exposure to cold-related crop stress and disease development. The work supported regional food security planning, resource allocation, and the development of early warning systems for future cold weather events.
Location: Jakarta, Indonesia
Client Type: Government
Jakarta faces chronic flooding driven by a combination of low-lying topography, land subsidence, intense monsoon rainfall, and rising sea levels. Rapid urbanisation has reduced natural drainage capacity, while extensive groundwater extraction has accelerated ground sinking in several districts. Frequent flood events disrupt transport networks, damage property, and threaten vulnerable coastal communities. Authorities required a comprehensive spatial assessment to understand the interaction between tidal surges, river overflow, and surface runoff under current and future climate scenarios.
We developed an integrated flood risk model combining high-resolution elevation data, tidal records, rainfall intensity patterns, and long-term climate projections. Spatial analysis identified flood-prone corridors, subsidence hotspots, and critical infrastructure exposed to combined coastal and pluvial flooding. The results informed drainage system upgrades, coastal defence planning, and zoning adjustments aimed at reducing future exposure. The project provided a data-driven framework to strengthen urban resilience and support long-term adaptation strategies for the city.
Location: Oman
Client Type: Private Sector Company
Expanding energy infrastructure across Oman presents complex challenges due to mountainous terrain, desert conditions, protected environmental areas, and proximity to settlements and existing infrastructure. Poorly planned pipeline routes can increase construction costs, create long-term maintenance risks, and expose operators to environmental or social conflict. The client required a comprehensive spatial evaluation to balance engineering feasibility, environmental compliance, safety considerations, and long-term operational performance.
We conducted a multi-layer GIS analysis integrating digital elevation models, geotechnical data, land ownership records, environmental exclusion zones, and population distribution mapping. By modelling slope gradients, access corridors, and operational constraints, we identified optimal routing options that reduced earthworks, avoided sensitive habitats, and minimised disruption to communities. The resulting route optimisation framework supported cost-efficient construction planning, streamlined regulatory approval processes, and enhanced long-term operational resilience.
Location: Japan
Client Type: Government
Coastal regions of Japan face persistent tsunami risk due to seismic activity along major tectonic boundaries. Dense urban populations, ageing infrastructure, and complex coastal topography increase the potential for large-scale casualties if evacuation routes are inadequate or poorly coordinated. In several municipalities, existing evacuation plans were based on outdated population data and did not fully account for vertical evacuation capacity, traffic congestion, or the time required for vulnerable groups to reach safe ground.
We conducted a comprehensive spatial risk assessment using high-resolution elevation models, coastal inundation scenarios, and detailed population distribution data. By modelling projected wave heights and travel times against available evacuation routes and vertical shelter locations, we identified critical bottlenecks and underserved neighbourhoods. The analysis informed updated evacuation zoning, optimised route planning, and the strategic placement of additional safe shelters, strengthening community resilience and improving response readiness for future tsunami events.
Location: Kathmandu, Nepal
Client Type: Government
Kathmandu sits in a highly active seismic zone where dense urban development, ageing buildings, and informal construction increase vulnerability to major earthquakes. Rapid population growth has led to tightly packed neighbourhoods with limited open space for evacuation, while critical infrastructure such as hospitals, schools, and transport corridors remain exposed to structural risk. Previous seismic events have demonstrated the potential for widespread casualties and infrastructure collapse if preparedness measures are insufficient.
We conducted a comprehensive seismic risk assessment integrating fault line data, ground shaking probability models, building age and construction type inventories, and detailed population distribution mapping. Spatial analysis identified high-risk districts where structural vulnerability and population density intersected. The findings informed updates to building code enforcement priorities, emergency response planning, and the designation of evacuation and relief staging zones, supporting long-term resilience and improved disaster preparedness across the city.
Location: South China Sea
Client Type: Government
The South China Sea is a major maritime corridor with extensive offshore drilling, shipping activity, and sensitive coastal ecosystems. An accidental oil spill in this region could rapidly spread across international waters, affecting fisheries, coral reefs, mangroves, and densely populated coastlines. Complex ocean currents, seasonal monsoon winds, and variable sea conditions make it difficult to predict spill movement and coordinate rapid containment efforts. Authorities required a detailed spatial understanding of potential spill trajectories and shoreline vulnerability to strengthen emergency preparedness.
We developed a dynamic GIS-based spill simulation model integrating ocean current data, wind patterns, bathymetry, and shoreline sensitivity mapping. By modelling multiple spill scenarios under varying seasonal conditions, we identified high-risk coastal zones and priority containment corridors. The analysis supported pre-positioning of response equipment, improved inter-agency coordination, and the development of structured emergency response protocols designed to minimise environmental damage and economic disruption in the event of a spill.
Location: Henan Province, China
Client Type: Public Sector Organisation
Severe snowstorms and freezing rain damaged greenhouse farming infrastructure across central China during the winter growing season. Heavy snow accumulation caused greenhouse collapses, disrupted vegetable production, and interrupted food supply chains to nearby urban areas. Agricultural operators faced significant financial losses alongside logistical challenges caused by road closures and transport disruption.
We conducted spatial analysis of greenhouse density, structural exposure, transport accessibility, and snow accumulation risk across the affected region. The project identified priority infrastructure reinforcement zones and supported emergency response planning by mapping vulnerable agricultural corridors. Long-term recommendations included climate resilience strategies for protected agriculture systems and improved regional supply chain planning.
Location: Japan
Client Type: Private Sector Company
Japan’s complex tectonic setting exposes critical infrastructure to significant seismic risk, including strong ground shaking, surface rupture, and secondary hazards such as liquefaction and tsunami generation. For nuclear power facilities, even low-probability seismic events must be rigorously evaluated due to the potentially severe consequences of structural failure. The client required a comprehensive spatial assessment of regional fault systems, historical earthquake patterns, and site-specific geotechnical conditions to support regulatory compliance and long-term operational safety.
We conducted an integrated seismic hazard analysis combining mapped fault lines, probabilistic seismic hazard models, historical earthquake records, and detailed subsurface geological data. Using ground motion simulations and site response modelling, we assessed potential shaking intensity and soil amplification effects across the facility footprint. The findings informed structural design parameters, foundation engineering requirements, and emergency safety planning, ensuring alignment with stringent regulatory standards and enhancing resilience against future seismic events.
Location: Kathmandu, Nepal
Client Type: Public Sector Organisation
Kathmandu’s rapid urban growth, ageing building stock, and informal construction practices have increased exposure to seismic risk across densely populated neighbourhoods. Many structures were built without consistent enforcement of earthquake-resistant design standards, and critical infrastructure such as hospitals, schools, bridges, and utility networks remain unevenly distributed across the city. High population density combined with limited evacuation space and narrow road networks further amplifies the potential human and economic impact of a major seismic event.
We integrated detailed infrastructure inventories, building typology classifications, probabilistic seismic hazard models, and high-resolution population density mapping into a unified GIS platform. Spatial analysis identified zones where structural vulnerability, population concentration, and limited access routes overlapped, creating priority intervention areas. The findings supported targeted retrofitting strategies, improved land use planning, emergency access optimisation, and long-term resilience planning designed to reduce risk and strengthen urban preparedness.
Location: India
Client Type: Private Sector Company
Rapid industrial growth, expanding urban populations, and increasing energy demand created pressure to extend an existing pipeline network across multiple Indian states. The expansion required careful consideration of terrain diversity, land acquisition challenges, regulatory approvals, environmental sensitivities, and integration with existing infrastructure capacity. Without a structured spatial strategy, the project risked cost overruns, bottlenecks, and inefficient coverage that could limit long-term operational performance.
We developed a GIS-based expansion model integrating projected market demand, topographic constraints, infrastructure interconnection points, land use patterns, and regulatory exclusion zones. Spatial optimisation techniques were applied to identify priority corridors that maximised coverage while minimising construction complexity and environmental impact. The resulting network design improved service reach, enhanced capacity utilisation, and provided a scalable framework to support efficient long-term growth and operational resilience.
Location: United Arab Emirates
Client Type: Private Sector Company
Large-scale industrial and energy assets across the United Arab Emirates operate in harsh environmental conditions characterised by extreme heat, sand exposure, corrosion risk, and heavy operational loads. Fragmented inspection records and isolated maintenance databases limited the client’s ability to identify emerging weaknesses across geographically dispersed facilities. Without a unified spatial view of asset condition, reactive maintenance cycles increased downtime risk and long-term operational costs.
We developed an integrated GIS-based asset management platform combining inspection reports, maintenance histories, sensor data, and spatial infrastructure mapping. By linking asset condition indicators to precise geographic locations, we enabled risk-based prioritisation and predictive maintenance scheduling. The system provided real-time visibility into infrastructure health, supported compliance reporting, and improved operational performance through proactive intervention strategies designed to reduce failure risk and optimise lifecycle management.
Location: Southeast Asia
Client Type: Private Sector Company
Rapid urbanisation, expanding digital demand, and challenging terrain across Southeast Asia created uneven network coverage and capacity constraints for the client’s telecommunications infrastructure. Mountainous regions, dense urban high-rises, coastal settlements, and remote rural communities all presented different signal propagation challenges. Existing tower placement and backhaul routes did not fully align with shifting population patterns and rising data consumption, limiting service quality and long-term growth potential.
We conducted a comprehensive GIS-based network optimisation analysis integrating population density projections, terrain modelling, signal propagation simulations, and existing infrastructure mapping. Spatial modelling identified coverage gaps, interference zones, and priority expansion corridors based on demand and accessibility. The resulting optimisation strategy guided tower placement, fibre routing, and phased infrastructure investment, improving service coverage, reducing capital expenditure inefficiencies, and supporting scalable, long-term network growth across diverse operating environments.
Location: Limpopo, South Africa
Client Type: Private Sector Company
Cold weather and frost events affected export-focused citrus farms during winter production cycles, damaging fruit quality and reducing export volumes. Freezing conditions also disrupted irrigation systems and transport infrastructure, increasing operational costs and threatening international supply commitments.
We developed an integrated GIS platform combining orchard temperature monitoring, terrain analysis, and infrastructure risk mapping. The project identified high-risk production zones and supported the placement of frost mitigation systems and improved irrigation planning. Spatial logistics analysis also helped reduce transport disruption risks during future cold weather events.
Location: United Arab Emirates
Client Type: Private Sector Company
Rapid urban expansion, shifting consumer preferences, and intense competition across major cities in the United Arab Emirates created uncertainty around optimal retail expansion. High rental costs, evolving residential patterns, and the growth of mixed-use developments meant that poorly chosen locations could significantly reduce profitability. The client required a data-driven assessment to identify areas with strong purchasing power, convenient accessibility, and limited competitive saturation.
We developed a GIS-based market intelligence model integrating demographic segmentation, income distribution, traffic flow analysis, accessibility mapping, and competitor location data. Spatial analysis identified high-potential trade areas based on consumer density, spending behaviour, and ease of access. The resulting site selection framework supported strategic expansion decisions, reduced investment risk, and improved projected return on investment by aligning store placement with long-term market growth patterns.
Location: Singapore
Client Type: Private Sector Company
Singapore’s limited land availability, strict planning controls, and high development costs require precise site selection to ensure commercial viability. Zoning regulations, transport connectivity, environmental buffers, and surrounding land use significantly influence the feasibility of residential and mixed-use projects. Without a structured spatial evaluation, development proposals risk delays in approval, underperformance in sales, or long-term value constraints due to overlooked infrastructure or regulatory factors.
We conducted a comprehensive GIS-based feasibility assessment integrating land use zoning, transport accessibility, utility infrastructure capacity, environmental constraint mapping, and current market demand indicators. Spatial analysis identified parcels with strong connectivity, regulatory alignment, and favourable surrounding development patterns. The results informed investment decision-making by highlighting high-potential sites, reducing planning uncertainty, and supporting financially sound development strategies aligned with long-term urban growth objectives.
Location: Ghana, West Africa
Client Type: Private Sector Company
Cocoa production in Ghana faces increasing pressure from climate variability, soil degradation, ageing tree stock, and expanding land use competition. Irregular rainfall patterns, rising temperature fluctuations, and declining soil fertility have contributed to uneven yields across plantation regions. In some areas, cultivation had expanded into marginal lands where long-term productivity was unsustainable, increasing vulnerability to disease, drought stress, and environmental degradation. The client required a spatially detailed assessment to identify high-potential cultivation zones while minimising ecological impact.
We conducted a comprehensive GIS-based suitability analysis integrating soil classification data, long-term rainfall and temperature records, elevation modelling, and terrain slope analysis. Satellite imagery was combined with historical yield performance data to identify correlations between environmental variables and plantation productivity. The resulting suitability model highlighted optimal expansion corridors, recommended targeted replanting strategies, and supported precision input management. This approach improved yield forecasting, enhanced land-use efficiency, and strengthened long-term plantation resilience while reducing environmental risk.
Location: Malatya, Turkey
Client Type: Regional Government Authority
A sudden spring freeze struck major apricot-producing regions after early seasonal warming accelerated blossom development. Freezing temperatures destroyed large sections of fruit blossoms, severely reducing annual production volumes and impacting export revenues for local agricultural communities.
We carried out spatial damage assessments using drone imagery, satellite analysis, and topographic modelling to identify frost concentration zones across orchard regions. The project supported agricultural recovery planning and helped optimise the placement of future frost mitigation infrastructure. Long-term recommendations included climate adaptation strategies and improved agricultural monitoring systems.
Location: Colombia, South America
Client Type: Public Sector Organisation
Colombia’s coffee sector is highly sensitive to elevation-dependent climate conditions, where small shifts in temperature and rainfall patterns can significantly affect flowering cycles, pest prevalence, and bean quality. Increasing temperature variability, irregular rainfall, and the spread of crop diseases such as coffee leaf rust have placed pressure on traditional growing zones. Many smallholder farmers operate within narrow climatic thresholds, making long-term yield stability increasingly uncertain as climate patterns evolve.
We developed a comprehensive GIS-based mapping framework integrating elevation models, temperature variability datasets, rainfall distribution analysis, and long-term climate projections. Spatial modelling identified high-risk zones where warming trends and rainfall shifts could reduce productivity or increase disease exposure. The analysis supported adaptive planning strategies, including altitudinal migration mapping, crop diversification guidance, and targeted extension support programs, helping protect farmer livelihoods while maintaining national coffee production resilience.
Location: Brazil, South America
Client Type: Government
Large-scale deforestation across parts of Brazil has been driven by agricultural expansion, cattle ranching, illegal logging, mining activity, and infrastructure development. Rapid land clearing has fragmented forest ecosystems, increased carbon emissions, and threatened biodiversity in sensitive regions. Enforcement agencies faced challenges in detecting illegal activity quickly, monitoring vast and remote forest areas, and distinguishing between authorised land conversion and unlawful clearing.
We implemented a GIS-based monitoring system integrating high-resolution satellite imagery, historical land cover datasets, and automated change detection algorithms to track forest loss over time. Spatial analysis identified emerging deforestation hotspots, proximity to road networks, and patterns linked to specific land use activities. The platform enabled near real-time alerts for suspected illegal clearing, strengthened enforcement response capabilities, and supported evidence-based policy development aimed at balancing economic activity with long-term forest conservation objectives.
Location: Saudi Arabia
Client Type: Private Sector Company
Large oilfield developments in Saudi Arabia involve extensive networks of wells, pipelines, processing facilities, and supporting infrastructure spread across challenging desert environments. Complex subsurface geology, seismic activity, corrosion risks, and extreme climatic conditions can create operational inefficiencies and asset vulnerabilities if infrastructure is not optimally configured. The client required a comprehensive spatial assessment to align subsurface reservoir data with surface infrastructure planning while minimising exposure to operational and environmental risks.
We developed an integrated GIS platform combining seismic survey data, well locations, production volumes, pipeline routing, and facility layouts into a unified spatial framework. By analysing infrastructure proximity, flow optimisation pathways, and geohazard exposure zones, we identified more efficient asset configurations and prioritised risk mitigation measures. The analysis supported improved production planning, reduced operational bottlenecks, enhanced asset integrity monitoring, and strengthened long-term resource management across the field.
Location: Seoul, South Korea
Client Type: Government
Seoul experiences increasingly intense rainfall events during the monsoon season, combined with highly urbanised surfaces that limit natural infiltration. Dense development, underground transport systems, and ageing drainage infrastructure have increased vulnerability to flash flooding in low-lying districts. Extreme rainfall episodes in recent years have caused property damage, transport disruption, and public safety risks, highlighting the need for a detailed spatial understanding of flood pathways and drainage performance across the city.
We conducted a comprehensive GIS-based flood risk assessment integrating rainfall intensity records, stormwater drainage capacity data, land surface permeability mapping, and high-resolution elevation models. Hydrological modelling identified flood-prone corridors, drainage bottlenecks, and areas where surface runoff exceeded system capacity. The findings informed targeted drainage upgrades, green infrastructure placement, and revised urban design strategies aimed at improving stormwater management and enhancing long-term resilience to extreme weather events.
Location: Kericho, Kenya
Client Type: International Agricultural Organisation
Cold nighttime temperatures and frost events affected tea-growing regions located in elevated highland zones. Frost damage reduced leaf quality and disrupted production cycles across several plantation areas. Agricultural operators also faced difficulties predicting which regions were becoming increasingly vulnerable to changing climatic conditions.
We developed a GIS-based frost monitoring system using elevation analysis, satellite imagery, and climate datasets to track temperature variability across plantation regions. The project identified emerging frost-prone zones and supported yield forecasting, plantation management, and long-term climate adaptation planning. Spatial analysis also helped prioritise vulnerable farming communities for targeted agricultural support initiatives.
Location: Eastern China
Client Type: Government
Rapid urbanisation and economic integration across eastern China created strong demand for expanded high-speed rail connectivity between major metropolitan regions and emerging secondary cities. However, densely populated corridors, agricultural land preservation requirements, protected environmental zones, and complex terrain presented significant planning challenges. Poorly aligned routes could lead to high land acquisition costs, environmental disruption, and long-term operational inefficiencies.
We conducted a multi-criteria GIS analysis integrating terrain modelling, population distribution mapping, land use constraints, ecological sensitivity zones, and existing transport infrastructure networks. Spatial optimisation techniques were applied to evaluate alternative corridors based on connectivity efficiency, construction feasibility, and environmental impact. The resulting analysis supported evidence-based route selection, reduced social displacement risk, and enhanced long-term network performance while aligning with national development and sustainability objectives.
Location: Western Australia, Australia
Client Type: Private Sector Company
Western Australia contains vast mineral-rich regions, but exploration across remote and geologically complex terrain carries significant financial risk. Large concession areas, limited surface exposure, and sparse infrastructure make it difficult to prioritise drilling targets without a detailed understanding of subsurface geology. Early-stage exploration uncertainty can lead to high capital expenditure with limited return if drilling programs are not strategically guided by reliable spatial evidence.
We developed an integrated GIS-based exploration framework combining geological survey maps, satellite-derived alteration signatures, airborne geophysical datasets, and structural fault analysis. By overlaying magnetic, radiometric, and gravity anomaly data with known mineralisation trends, we identified high-probability target zones for further investigation. The resulting spatial model refined drilling priorities, reduced exploration risk, and supported more efficient allocation of capital during early-stage resource development.
Location: Shenzhen, China
Client Type: Private Sector Company
Shenzhen’s rapid industrial growth and dense urban development have created complex logistics demands across manufacturing clusters, port facilities, and cross-border trade corridors. Congestion along arterial roads, uneven distribution centre placement, and fragmented supply chain visibility increased delivery times and operational costs. The client required a spatially integrated assessment to optimise hub locations, streamline distribution flows, and improve connectivity between production sites and export gateways.
We developed a GIS-based logistics optimisation model integrating transport network data, industrial land use patterns, warehouse capacity mapping, and real-time traffic flow analysis. Spatial modelling identified congestion hotspots, underutilised corridors, and priority locations for new distribution hubs. The resulting strategy improved route efficiency, reduced transit times, enhanced warehouse placement decisions, and supported scalable supply chain operations aligned with long-term industrial growth.
Location: Phuket, Thailand
Client Type: Public Sector Organisation
Phuket’s rapid tourism growth has increased pressure on fragile coastal ecosystems, including coral reefs, mangroves, and sandy shorelines. Expanding beachfront development, marine traffic, and seasonal visitor surges have contributed to coastal erosion, habitat degradation, and water quality concerns. Without careful spatial planning, further infrastructure expansion risked accelerating environmental damage while undermining the long-term sustainability of the tourism economy.
We implemented a GIS-based environmental assessment integrating coastal land cover mapping, tourism infrastructure inventories, shoreline change analysis, and erosion trend modelling. Spatial analysis identified high-impact development zones and ecologically sensitive areas requiring protection or restoration. The findings informed sustainable zoning guidelines, infrastructure placement controls, and conservation prioritisation measures designed to balance economic development with long-term coastal ecosystem resilience.
Location: Beijing, China
Client Type: Government
Beijing has experienced persistent air quality challenges driven by vehicle emissions, industrial activity, construction dust, and seasonal heating demand. Complex meteorological conditions, including temperature inversions and regional wind patterns, can trap pollutants over the urban basin, creating prolonged episodes of hazardous smog. Uneven distribution of pollution across districts made it difficult for authorities to prioritise intervention zones and evaluate the effectiveness of regulatory measures.
We developed a GIS-based pollution modelling framework integrating satellite-derived aerosol data, fixed and mobile ground sensor readings, and detailed meteorological datasets. Spatial interpolation and atmospheric dispersion modelling were used to map pollutant concentration patterns and identify high-exposure corridors. The analysis supported targeted emission control strategies, informed traffic and industrial policy adjustments, and provided a data-driven foundation for long-term air quality improvement planning across the metropolitan region.
Location: Busan, South Korea
Client Type: Private Sector Company
Busan’s transition toward renewable energy required careful coordination between variable solar and wind generation sources and an existing grid designed around conventional power plants. Fluctuating generation output, coastal wind variability, and uneven rooftop solar distribution created challenges for grid stability and load balancing. Without detailed spatial assessment, integrating new renewable assets risked congestion in certain substations, voltage instability, and inefficient capital deployment.
We developed a GIS-based integration model combining energy demand distribution, substation capacity mapping, transmission line infrastructure, and renewable resource availability data. Spatial analysis identified optimal zones for solar and wind development based on proximity to grid capacity and demand centres. The framework supported phased infrastructure upgrades, improved load balancing strategies, and enhanced network stability while accelerating the transition toward a more resilient and cleaner energy system.
Location: Inner Mongolia, China
Client Type: Private Sector Company
Inner Mongolia contains some of the world’s most significant rare earth deposits, yet exploration across vast semi-arid terrain presents geological and operational complexity. Mineralisation patterns are often associated with specific structural formations and geochemical signatures that can be difficult to delineate using isolated datasets. Large concession areas, environmental constraints, and high exploration costs increased the need for precise targeting to avoid inefficient drilling campaigns and unnecessary land disturbance.
We developed a GIS-driven exploration framework integrating regional geological surveys, satellite-derived alteration mapping, geochemical sampling results, and structural fault analysis. By overlaying spectral anomaly detection with known mineralisation trends and subsurface geophysical indicators, we identified high-probability target zones for prioritised field investigation. The resulting spatial prioritisation model reduced exploration uncertainty, improved drill site selection accuracy, and enhanced the overall efficiency of rare earth resource discovery and development planning.
Location: Tokyo, Japan
Client Type: Private Sector Company
Tokyo’s dense urban fabric, extensive public transport network, and highly competitive retail environment create complex dynamics for store placement. High pedestrian volumes around major stations do not always translate into purchasing behaviour, while subtle differences in neighbourhood demographics and commuter flows can significantly influence store performance. Without a detailed spatial understanding of consumer movement patterns and competitive clustering, expansion decisions risked underperforming locations and reduced return on investment.
We developed a GIS-based retail intelligence model integrating footfall analytics, demographic segmentation data, transport accessibility mapping, and competitor location analysis. Spatial modelling defined precise consumer catchment areas based on walking time, transit connectivity, and spending profiles. The resulting insights enabled targeted site selection aligned with purchasing behaviour trends, improved demand forecasting, and supported long-term store performance optimisation across Tokyo’s diverse retail districts.
Location: East Africa (Kenya–Uganda–Rwanda)
Client Type: Private Sector Company
Trade flows between Kenya, Uganda, and Rwanda rely heavily on overland transport corridors that connect ports, inland depots, and industrial centres. Congestion at border posts, inconsistent road quality, informal checkpoints, and uneven infrastructure capacity have contributed to unpredictable transit times and higher logistics costs. These inefficiencies disrupted supply chains, increased fuel consumption, and reduced competitiveness for businesses operating across the region.
We developed a GIS-based corridor optimisation model integrating transport network mapping, freight volume data, border crossing performance metrics, and infrastructure capacity assessments. Spatial analysis identified bottlenecks, high-delay segments, and alternative routing options that improved corridor resilience. The resulting optimisation strategy reduced average transit times, enhanced route reliability, and supported more efficient cross-border supply chain operations aligned with long-term regional trade growth.
Location: Kalimantan, Indonesia
Client Type: Private Sector Company
Expansion of palm oil plantations in Kalimantan presents both economic opportunity and significant environmental risk. Land conversion can affect tropical rainforest ecosystems, peatlands, biodiversity corridors, and local communities if not carefully managed. Regulatory scrutiny, sustainability certification requirements, and international market pressure have increased the need for responsible expansion strategies. The client required a spatially detailed evaluation to identify commercially viable land while avoiding high-conservation-value forests and environmentally sensitive zones.
We developed a GIS-based land suitability framework integrating soil classification, rainfall distribution, elevation and slope analysis, and land cover mapping. Environmental constraint layers including peat depth, protected areas, biodiversity corridors, and hydrological sensitivity zones were overlaid to define exclusion areas. The resulting analysis identified priority expansion zones that balanced productivity potential with sustainability criteria, supporting compliant development planning, reduced environmental risk, and improved long-term plantation resilience.
Location: Northern Laos
Client Type: Private Sector Company
Northern Laos contains steep terrain and high seasonal rainfall, creating strong hydropower potential but also complex environmental and operational considerations. River flow variability, sediment transport, remote access constraints, and ecological sensitivity within catchment areas can significantly influence project viability. Without a comprehensive spatial assessment, proposed dam locations risked underperforming generation capacity, increased construction complexity, or unintended downstream environmental impacts.
We developed a GIS-based feasibility model integrating digital elevation models, long-term river discharge data, rainfall distribution patterns, watershed delineation, and transport accessibility mapping. Hydrological modelling identified catchment areas with stable flow regimes and suitable head height for efficient generation. Environmental constraint layers were incorporated to avoid sensitive ecosystems and minimise downstream disruption. The analysis improved site selection precision, reduced investment uncertainty, and supported environmentally responsible hydropower development planning.