Where should a growing city build its next school?
The answer involves more than finding available land. Planners need to understand where school-age populations are growing, whether existing schools have sufficient capacity, how safely children can reach them, and whether potential sites face flood risks or planning constraints. These considerations draw on information held across different datasets, systems and agencies.
For government agencies, planners and infrastructure leaders, the challenge is turning available data into evidence that can inform decisions in time. A map showing where schools are located is a starting point. Planning requires understanding which communities remain underserved, how demand may change and where investment could make the greatest difference.
This is becoming more important across Asia Pacific. The United Nations Economic and Social Commission for Asia and the Pacific (ESCAP) estimates that the region is already home to more than 2.2 billion urban residents, with its urban population projected to increase by 50% by 2050.
More people, infrastructure and services mean more interconnected planning decisions. They also raise the cost of getting those decisions wrong.
Poor visibility can become a delivery problem
When relevant information is fragmented, constraints may emerge only after a preferred site has been selected or a proposal has progressed. This can mean revisiting site options, redesigning infrastructure or repeating consultations. For public agencies, the consequences extend beyond project delivery: investments may fail to reach the communities with the greatest need.
More data does not always mean better decisions
Spatial analysis often requires specialist tools and several preparation and processing steps. When each new question or change in criteria requires another technical request, comparing options can take longer.
Making routine analysis more accessible can help planners and decision-makers explore initial questions, while GIS specialists focus on data quality, complex analysis and validation.
The issue is not necessarily a shortage of data. It is whether that data can be brought together and used in the context of the decision being made.
Spatial intelligence can broaden access to analysis
More accessible spatial technology can help address this gap.
SpatialQ, developed by Gamuda Technologies, is an AI-powered geospatial analysis platform that enables users to ask questions in everyday language and analyse available spatial data without writing code. Its purpose is to make spatial analysis accessible to more people, helping planners and decision-makers explore questions and use the results in their work.
Returning to the school example, the planning question could be: “Which residential areas have limited access to existing schools, and which potential sites fall outside mapped flood-risk areas?”
With suitable datasets and supported analysis functions, SpatialQ can help users explore these factors together. Planners can then assess the findings alongside school capacity, future demand, land availability and applicable planning requirements.
Users should assess the results against the data sources, assumptions and criteria used. Any shortlist or recommendation should inform further professional assessment, with planners and relevant agencies retaining responsibility for the final decision.
Broader access to spatial analysis allows more people to participate meaningfully in planning discussions. Planners, engineers and GIS specialists remain essential to interpreting results, weighing competing priorities and assessing the implications for communities. AI can assist the analysis; professional judgement determines how the findings should inform action.
Reliable results also depend on accurate, current and sufficiently complete data. Gaps in school capacity records, outdated population figures or incomplete flood mapping can affect the conclusions. Making analysis easier must therefore go hand in hand with maintaining data quality and communicating uncertainty.
Better visibility supports better planning decisions
The value of spatial intelligence lies in helping people make better decisions about places.
For planners and public agencies, that means identifying underserved communities, assessing constraints earlier and directing investment where it can deliver greater benefit. SpatialQ’s role is to make spatial analysis more accessible, while keeping professional judgement and community outcomes at the centre of decision-making.
See how SpatialQ can help make complex geospatial analysis more accessible.
