Urban Landbank Using Aerial Survey and Artificial Intelligence: Advancing Oman’s Digital Land Management
As Oman continues to expand its cities and diversify its economy, the Urban Landbank AI Mapping Project in Oman supports faster, more informed land-use decisions. K&A delivered the Urban Landbank Using Aerial Survey & Artificial Intelligence project in Dhofar, Oman, to address a national challenge: outdated or incomplete land records that hinder planning and sustainable growth, and increase costs.
By replacing fragmented data with a digital landbank supported by advanced aerial surveying, GIS automation, and Artificial Intelligence (AI), the Ministry of Housing & Urban Planning provides decision-makers with real-time insights. As a result, they can prioritize investments. They can also protect natural resources, accelerate approvals, and guide development in alignment with Oman’s long-term transformation goals. Moreover, as a national initiative, the Urban Landbank AI Mapping Project enhances the Ministry’s capacity to manage land resources effectively. Therefore, it leverages real-time intelligence to improve decision-making.
How the Urban Landbank AI Mapping Project in Oman Supports Smarter Land Management
The project aims to create a digital database of the area’s above-ground buildings, roads, fences, and utilities to assist the Ministry of Housing in making proper land plans and generating accurate site plans and deeds.
Due to social constraints and the rugged topography of the area, our team combined Airborne LiDAR, Aerial Photography, GIS automation, and Esri-based deep learning to classify land parcels across 760 km². This enabled previously unseen visibility into topographic constraints, existing structures, encroachments, and land potential.
Digital Mapping Accelerating Development
Despite the vast and varied terrain, K&A completed the aerial survey in just nine days using a lean 10-person team—showcasing how automation can dramatically boost speed and accuracy. This efficiency minimized human error and administrative delays, enabling more responsive governance, optimized land use, and stronger environmental compliance.
Initially planned for 30 days, the flights were completed in less than a third of the time. High-resolution imagery, LIDAR data, and effective re-planning allowed seamless image processing and AI analysis, shortening the total project timeline to 16 months instead of the expected 24. Traditionally, a survey of this scale would have taken up to nine years and thousands of labor hours. Moreover, automation achieved cost savings of over 20% and paved the way for a new engagement covering an area seven times larger.
Innovative Features of the Urban Landbank AI Mapping Project in Oman
The Urban Landbank project leverages aerial surveying and artificial intelligence to build a highly accurate (10 cm precision) geospatial database with automated land classification, real-time analytics, and integrated site plan generation. By combining AI with high-resolution aerial data, it transforms land management—enabling predictive development analysis, early issue detection, and faster deed issuance and permitting.
A hallmark of this innovation is its advanced method for enhancing point cloud density. By converting aerial imagery pixels into colorized points and accurately estimating their height, the system delivers sharper, more detailed mapping for precise identification of buildings and infrastructure. This seamless integration of aerial imagery and point cloud data creates a complete view of the terrain and built environment, improving accuracy and efficiency.
By automating detection, the project minimizes manual work, reduces costs, and streamlines data analysis. Its integration with existing information systems centralizes and standardizes data, empowering better decision-making, stronger urban planning, and more transparent governance.
Scaling Digital Intelligence Across the Sultanate
The project showcases digital innovation through its pioneering approach to automating the detection of infrastructure, roads, fences, and buildings across a vast 750 km² area. By integrating advanced technologies and methodologies, it transforms how infrastructure is detected and analyzed. Using cutting-edge Artificial Intelligence models with a 5 cm ground sampling distance (GSD), the system automatically identified over 10,000 buildings and 13,000 fences—all without any fieldwork. The scale and impact of the Urban Landbank AI Mapping Project in Oman highlight its role as a benchmark for future digital land management programs across the Sultanate.
Recognized as Digital Project of the Year 2024 at the Construction Technology Awards, the project stands as a beacon of innovation, redefining what is possible in infrastructure detection and analysis. Through its groundbreaking technologies and methodologies, the project has set new benchmarks for accuracy, efficiency, and effectiveness, while demonstrating how smarter land administration can empower communities, accelerate development, and safeguard national resources for future generations.
