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AI in Surveying

The AI Wave in Land Development, Surveying and GIS

By Aaron Fleury

Over the past year, a major focus of mine has been researching and tinkering with various advances in Artificial Intelligence (AI) to utilise in both my business and to help inform decision-making in my role at ISNSW. As of today, we are seeing significant and rapid leaps in the advancement of AI technology. The democratisation of AI has allowed for broad user engagement without needing specialised technical knowledge or significant financial investment, resulting in daily leaps in the progress and use of the technology.

In the dynamic field of land development and surveying, staying ahead of technological advancements is not solely about embracing the new; it’s about working towards a smarter, more efficient, and sustainable future for the communities we help to build. The fusion of AI with Geographic Information Systems (GIS), Land Use Planning and Surveying is an exciting step towards a future with many possibilities and potential.

As urban landscapes continue to expand, the complexities of land development and urban planning demand a blend of precise data, intelligent analysis, and proactive decision-making. AI emerges as a powerful ally, offering tools and methodologies that significantly enhance data collection, analysis, and predictive forecasting.

Whether it’s AI-enhanced drone mapping or intelligent decision-making tools that streamline urban planning processes, the impact of AI is self-evident and transformative. The advent of Geospatial Artificial Intelligence (GeoAI) promises a new horizon of spatial problem-solving and data generation, modernising operations to run at a larger scale with automated data generation and accessible spatial tools and algorithms.

This article explores this technological synergy, exploring the ways AI is reshaping the domains of surveying, land development and planning. As professionals striving to stay on the forefront of industry advancements, understanding and harnessing the potential of AI is not just about keeping pace with the digital wave; it’s about riding it to forge innovative solutions, enhance operational efficiencies, and drive informed, sustainable decision-making in the ever-evolving property development space.

Intelligent Decision-making in Land Use Planning

In the heart of urban development, a rapidly evolving set of AI-powered generative design tools is starting to gain attention. Software like Delve by Sidewalk Labs, Autodesk’s Forma (formerly Spacemaker), and others hold the potential to automate the design and planning of entire neighbourhoods and suburbs, simplifying complexities for architects, surveyors, engineers and planners with valuable tools to hasten the route to construction.

These tools can crunch through large numerical and contextual datasets, generating optimised designs for developments, suburbs, or even entire city areas based on project priorities and constraints. The power of AI and machine learning enables these tools to process more data and weigh a large set of project considerations much faster than human design teams.

A significant leap was observed when the city of Sofia, Bulgaria, employed Delve to explore a sustainable development approach using geospatial data to analyse an entire ‘city unit’, considering the city’s and its citizens’ specific needs. Similarly, Autodesk Forma, a pioneering AI-driven tool, is facilitating a streamlined approach to urban planning and architectural design by simplifying design concepts, enabling real-time environmental analysis, and promoting iterative workflow among architects and urban planners.

However, these tools need to be well understood and are no replacement for the critical thinking of an expert professional. While AI excels in analysing performance criteria like energy efficiency and transportation systems, the ‘softer’ areas concerning social sustainability, community, justice, and ethics still have a long way to go.

Experts like Dr Dragana Nikolic, a lecturer in digital architecture at the University of Reading, echo the sentiment that while AI’s superfast analysis of different options is promising, its ability to handle variables for making value judgments in ‘softer’ areas is still under scrutiny.

The advent of cloud computation and advancements in AI/machine learning has grown the generative design process, offering new opportunities to work with more complex data sets and tackle projects on a larger scale. Tools like Autodesk Forma focus on the planning phase of building development, where numerous decisions about what, where, and how to build are made. By removing errors early on, they significantly reduce the project’s duration, aiding in the creation of higher-density developments with higher-quality living units.

Yet, the essence of human intuition remains irreplaceable, especially when understanding local nuances like aesthetic preferences, political environments, zoning/planning requirements, and the complex relationships inherent in urban planning. The ‘human in the loop’ approach is deemed crucial to balance AI’s numerical prowess with the qualitative criteria that shape our urban landscapes.

In a world where technology often outpaces our understanding of its consequences, the marriage between AI and urban planning invites a deeper exploration to ensure that the cities of tomorrow are smart and resonate with the needs and aspirations of the people inhabiting them.

Geospatial Intelligence Amplified with AI GIS

The fusion of Artificial Intelligence (AI) with Geographic Information Systems (GIS) and geospatial data is spearheading a new era in spatial problem-solving and data generation, referred to as Geospatial Artificial Intelligence (GeoAI). This synergy is not only accelerating real-world understanding of business opportunities, environmental impacts, and operational risks but is also modernising operations to run at a larger scale through automated data generation and accessible spatial tools and algorithms.

This is a rapidly evolving space, and with each passing day, we’re gradually seeing some of these conceptual benefits become reality:

Automated Data Extraction and Classification: GeoAI facilitates the automation of extracting, classifying, and detecting information from various types of data, such as imagery, video, point clouds and text. This automation is instrumental in streamlining manual data generation workflows, thus enhancing data quality, consistency, and reducing costs.

Predictive Analysis and Forecasting: Leveraging machine learning algorithms, GeoAI enables the building of more precise models to detect clusters, calculate changes, find patterns, and forecast outcomes backed by spatial algorithms. This predictive capability is crucial in making data-driven decisions with real-world awareness, improving business outcomes through insight from spatial patterns and accurate predictions.

Real-world Modelling for Prediction: Aerial imagery, for instance, can be used to extract imagery of buildings and roads to identify populations and infrastructure at risk for events such as landslides. AI can enhance the pace at which this data is handled to offer realtime updates and predictions of potentially disastrous events.

GeoAI in Different Sectors: Various sectors benefit from GeoAI. For instance, in state and local government, GeoAI accelerates urban development impact modelling, resource availability understanding to populations, and road or infrastructure deterioration forecasting. In the realm of natural resources, GeoAI aids in the automated detection of invasive species and monitoring assets in the oil and gas industry. Additionally, in the defence and intelligence sectors, GeoAI quickens information extraction, pattern identification, and big data change determination.

Enhanced Geospatial Data Analytics: GeoAI enriches geospatial data analytics by enabling GIS software like ArcGIS to handle complex analytics tasks. For instance, GeoAI software in ArcGIS allows the use and training of AI models with geospatial and tabular data, which is a stride toward advanced geospatial data analytics.

Accelerated Situation Awareness: GeoAI helps monitor and analyse events, assets, and entities from various sensors and sources such as videos to enable quicker response times and proactive decisions, which is particularly crucial in public safety concerning traffic accidents, emergency response, and disaster management.

GeoAI is a transformative force in the domain of GIS and geospatial intelligence, offering a robust framework for tackling complex spatial challenges, improving operational efficiencies, and enhancing decision-making processes across various industries.

Digital Twins and AI

Digital Twins are virtual replicas or digital representations of physical objects, systems, or processes. They bridge the physical and digital worlds by collecting real-time data from their physical counterparts through sensors and other data collection mechanisms. This data can include information on the state, behavior, and motion of the physical object or system.

The NSW Department of Spatial Services is pioneering the utilisation of Digital Twins technology through its NSW Spatial Digital Twin (SDT) initiative. This program aims to foster a collaborative environment across various sectors by sharing and visualising location information within a 4D model (comprising 3D spatial data plus time) of the real world in near real-time, thereby aiding in better decision-making processes. Initially, the program was implemented as a digital representation of Western Sydney, mapping out significant details such as 22 million trees along with their height and canopy attributes, 546,206 buildings, close to 20,000km of 3D roads, and 7,000 3D strata plans. This digital twin facilitates the visualisation of historical data alongside real-time visuals even before the commencement of construction projects.

Digital Twins represent a significant stride in the marriage between the digital and physical realms, especially within the domains of land development, surveying and planning.

Here are some of the ways the Digital Twin can aid with the advancements in AI, GIS, and related fields:

Real-time Monitoring and Analysis

Digital Twins, being virtual replicas of physical assets or systems, facilitate real-time monitoring and analysis. Integrating with GIS and AI can provide dynamic insights into urban environments, infrastructure conditions, and spatial relationships, enabling more informed decision-making in land use and urban planning.

Predictive Maintenance and Forecasting

By harnessing AI and machine learning algorithms, Digital Twins can predict when infrastructure might fail or require maintenance before issues arise. This predictive ability is crucial for proactive management in land development and urban planning, reducing costs and ensuring the longevity and efficiency of infrastructure.

Enhanced Planning and Simulation

Digital Twins allow for the simulation of various scenarios in a risk-free virtual environment. In the context of urban planning and land development, this means testing different planning scenarios, understanding potential impacts, and making adjustments before any real-world implementation, saving both time and resources.

Integrative Data Management

The amalgamation of AI, GIS, and Digital Twins facilitates a more integrative approach to managing vast arrays of spatial and non-spatial data. This integration is instrumental in creating more accurate and comprehensive models for land development, construction and planning projects.

Improved Stakeholder Engagement

Digital Twins can enhance stakeholder engagement by providing intuitive, interactive, and visual representations of planned developments or existing assets. This visualisation can foster better understanding and communication among stakeholders, facilitating more collaborative and informed decision-making processes.

Sustainability and Resource Efficiency

Digital Twins, coupled with AI and GIS, can help devise strategies for more sustainable and resource-efficient land use and urban planning by enabling a deeper understanding and control over urban and environmental systems.

Educational and Training Tool

The realistic, interactive nature of Digital Twins makes them excellent tools for education and training in the fields of surveying, land development and planning. They provide a hands-on, visual way to understand complex systems and scenarios.

The convergence of Digital Twins with AI and GIS technologies heralds a new era of advanced, data-driven, and interactive approaches in surveying, land development, and urban planning. It’s the epitome of how digital transformation can significantly contribute to smarter, sustainable, and more efficient land use practices, ensuring that professionals in these fields keep pace with technological advancements and leverage them to drive innovation and improve outcomes.

AI-Enhanced Drone Mapping


With the convergence of Geographic Information Systems (GIS), drone technology, and Artificial Intelligence (AI), the landscape of land surveying and mapping is being reimagined. AI-powered drones are not just propelling the efficiency and accuracy of data collection but are also fostering safety and cost-effectiveness in operations.

Advanced Data Collection and Analysis: AI augments drone capabilities, enabling sophisticated collection, analysis, and prediction of geographic and location-based data. This amalgamation of technologies enables many opportunities in various sectors, including agriculture, energy, construction, and emergency response.

Autonomous Drone Surveying: The rapid evolution of technology has seen autonomous drone surveying and mapping, which are now transformative forces in the realms of construction, mining, and geospatial mapping. Businesses grappling with the need for precision, speed, and efficiency in critical data capture are finding great potential in drones powered by AI.

Conversion of Aerial Data to CAD Drawings: Large surveying projects, traditionally beset with prolonged timelines due to the tedious process of data gathering and conversion to 2D and 3D models, are witnessing a significant acceleration. Assisted by AI technology, drone services can swiftly convert aerial datasets into CAD site plans, reducing the time and resources required for such conversions.

Uncovering Patterns and Trends: The integration of AI and Machine Learning (ML) with drones is ushering in novel possibilities in land surveying and mapping. By scrutinising the data amassed by drones through AI and ML algorithms, surveyors can discern patterns and trends that were previously elusive, thereby enriching the analytical depth and actionable insights derived from survey data.

The horizon of what’s achievable in land development, surveying, and GIS is being significantly expanded as AI entwines with drone technology. The ensuing synergy not only augments the operational efficacy but also unravels new avenues for innovation and enhanced decision-making in land use planning.



The integration of Artificial Intelligence (AI) with Geographic Information Systems (GIS), Drone Technology, and Digital Twins is reshaping the landscape of land development, surveying, and planning. The NSW Spatial Digital Twin initiative and AI-enhanced drone mapping are prime examples of how digital transformation is driving real-time decision-making, predictive analysis, and operational efficiency in our field.

Tools like Delve by Sidewalk Labs and Autodesk’s Forma aren’t just automating processes; they are opening doors to optimised urban planning and design, bridging the gap between data-driven insights and human intuition. They help translate complex data into actionable insights, speeding up project timelines and enhancing the quality of outcomes.

Learning and adapting to these technological advancements is more than just staying current; it’s about paving the way for smarter, more sustainable urban development. It’s about harnessing the potential of AI to drive innovation, improve operational efficiencies, and make informed decisions that resonate with community needs.

As professionals in this field, embracing these digital advancements is crucial to enhance our practice and contribute towards building smart, sustainable, and inclusive urban landscapes. It is not without its challenges, and the importance of recognising AI as a tool and not a replacement to human critical thinking is crucial as we begin to implement new processes and procedures. This digital journey, though challenging, is filled with opportunities to innovate and improve, propelling our profession into a new era of enhanced decision-making and strategic insight.

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