Dataset Overview
Drone Modelling Data SetYes.Changsha Langhui Information Technology Co., Ltd. DataAssetsAPI platform operates. The data on the tilted photos of drones covering 2,000 square kilometres of cumulative national flight range, totalling 16 million + million fragments (approximately 100 TB), are suitable for the three-dimensional reconstruction of the larger landscape, urban planning modelling and digitization of infrastructure.
| Dataset Name | Drone Modelling Data Set |
| Total of 2,000 square kilometres nationwide | |
| Number of flights | 16 + 10,000 (approximately 100 TB) |
| Data Type | Images (UAV aerial) |
| Data Source | There's a drone. |
| Data Status | Fully Cleaned |
Core Data Fields
Each piece of data contains complete structured fields that cover everything from raw data to annotated information.
| Field Category | Field Count | Typical Fields |
|---|---|---|
| Flight Image | 8 | High-resolution aerial imagery, POS data (GPS/IMU), flight altitude, flight line parameters |
| Shoot parameters | 6 | Camera type/focal length, sized image, direction/side overlap, GSD |
| Geographic information | 8 | Longitude, altitude, coordinates (CGCS2000/WGS84), projection parameters |
| ScenesClassification | 6 | Type of scene (urban/rural/ mountainous/water/industrial zone), type of feature coverage |
Data Sample Showcase
The following is a structured JSON sample showing typical data formats.
Other Organiser
"DRONE-2024-000234",
"area": {"location": } } } } } } } } } } } } } } } } } } } } } } } } } } } } } } } } } } } } } }
"Flight": {"altitude m": 150, ""gsd cm": 2.5, "overlap": {"forward pct": 80, "side pct": 65},
"Images": "count": 12480, "format": "JPEG+DNG", "total size gb": 620, "camera": "PhaseOne iXM-RS150F"
♪ I'm sorry ♪AI Application Scenarios
Large-scale 3D reconstruction of the landscape
Training in flight data for 2000km2 and validation of large-scale tilt photo reconstruction algorithms.
Urban planning digital twin
The urban area airflips build city-level digital twines.
Infrastructure BIM modelling
Infrastructure regional air space is used for BIM modelling and GIS integration.
Change detection AI
Multi-time phase space training on automatic surface change detection models.
Feature classification and identification
Multi-species space training on auto-classification and identification of features in AI.
Large model space understanding
The space scenario understanding capability of the large multi-modular model is being trained in the space data.
Frequently asked questions
Build your digital twin world?
Langham Technology has the nation's leading real-world 3D data acquisition capabilities, collecting a total of 2000 + square kilometers of flight data and 1200 + fine models. All data has been cleaned and quality inspected and can be used directly for AI model training.
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