A government agency involved in urban planning and environmental conservation needed to process and analyze large volumes of geospatial data from satellite imagery and LiDAR scans. The goal was to create accurate land-use maps, monitor environmental changes, and plan infrastructure projects. The challenge lay in efficiently annotating complex geospatial data to identify features such as buildings, roads, forests, and water bodies across large geographic areas.
Objectways provided a comprehensive geospatial data annotation solution, utilizing AI to streamline the analysis and classification of satellite imagery, aerial photos, and 3D LiDAR data:
With Objectways’ geospatial data annotation and analysis capabilities, the client was able to significantly improve the accuracy and efficiency of their urban planning and environmental monitoring efforts. The AI-powered annotation system reduced manual labor by 60%, speeding up the production of land-use maps and environmental reports. The government agency could make more informed decisions on infrastructure development and environmental conservation based on accurate, up-to-date data.
Annotating satellite or aerial imagery of land use types (e.g., urban, agricultural, forest).
Train models that can automatically classify and monitor land use changes over time.
Labeling images with buildings, roads, bridges, and other infrastructure.
Train models that detect infrastructure, generate urban maps/diagrams, and more.
Annotating data related to natural features such as water bodies, vegetation, and more.
Track environmental changes, assess natural resources, and support conservation efforts.
Labeling images of natural disasters (e.g., floods, wildfires, earthquakes).
Detect disasters and aid in response planning and damage assessment.
Annotating images with crop types, health status, and growth stages.
Enhance precise agriculture by monitoring crop health and predicting yields.
Labeling areas with various habitats and species.
Support wildlife conservation and biodiversity studies by mapping and monitoring habitats.
Annotating images and sensor data with traffic patterns, road conditions, and transportation networks.
Improve traffic management, route planning, and infrastructure development.
Labeling elevation data to create topographic maps.
Support applications in geology, hydrology, and land management.
Annotating urban areas with land use types, infrastructure, and growth patterns.
Assist urban planning and policy-making in sustainable city development.
Labeling data related to temperature, precipitation, and other climate variables.
Track the impacts of climate change and forecast future scenarios.
Annotating maps with the locations of utilities (e.g., power lines, pipelines).
Manage and monitor critical infrastructure for maintenance and disaster planning.
Labeling coastal areas with data on erosion, sea level rise, and land use.
Manage coastal resources and mitigate the impacts of climate change on coastal areas.
Labeling transportation networks and traffic data to optimize routes for logistics and transportation.
Optimize transportation networks and reduce travel times.
Annotating images captured by drones & UAVs for various mapping applications.
Train and enhance high-resolution mapping and monitoring by aerial technology.
