1. Purpose and Application
- Lidar:
- Application Scope: Primarily used for large-scale mapping and remote sensing applications such as topographic mapping, environmental monitoring, forestry, and autonomous vehicle navigation.
- Data Integration: Often integrated with GPS and Inertial Measurement Units (IMUs) to provide georeferenced 3D data, which is crucial for creating accurate maps and models.
- Laser Scanners:
- Application Scope: More commonly used for detailed, close-range scanning applications such as building and construction surveying, industrial inspection, heritage preservation, and 3D modeling of objects.
- Precision: Known for high precision and accuracy in capturing fine details, which is essential for applications requiring exact measurements and detailed models.
2. Technology and Operation
- Lidar:
- Pulse-Based: Uses pulsed laser beams to measure distances by calculating the time it takes for the laser pulse to return after hitting an object. This allows for the measurement of longer distances and is effective in a variety of environmental conditions.
- Multiple Returns: Can capture multiple returns from a single laser pulse, which helps in distinguishing between different layers of vegetation, ground, and other surfaces.
- Wide Coverage: Capable of covering large areas quickly, making it ideal for aerial and terrestrial surveys.
- Laser Scanners:
- Continuous Wave: Often uses continuous wave laser beams (though some can use pulsed laser) and measures distances based on phase shift or time-of-flight principles.
- Single Return: Typically captures a single return per laser beam, which is suitable for detailed, high-resolution scans of surfaces.
- Focused Coverage: Usually employed for scanning specific objects or smaller areas with high detail.
3. Data Output and Processing
- Lidar:
- Point Cloud Data: Generates large point clouds that represent the scanned environment or objects in 3D space. These point clouds are often sparse compared to those from laser scanners but cover larger areas.
- Data Integration: Requires sophisticated processing to integrate with other geospatial data and often involves complex algorithms to interpret multiple returns and filter out noise.
- Laser Scanners:
- Dense Point Clouds: Produces very dense point clouds with high resolution, capturing intricate details of scanned objects or surfaces.
- Simpler Integration: Data is generally easier to process for applications requiring detailed and precise 3D models without the need for extensive integration with other geospatial data.
4. Typical Use Cases
- Lidar:
- Mapping large areas such as forests, mountains, and urban environments.
- Autonomous vehicle navigation and obstacle detection.
- Environmental monitoring and disaster management.
- Laser Scanners:
- Building and construction surveys.
- Industrial inspection and quality control.
- Heritage and archaeological preservation.
- Creating detailed 3D models of objects and structures.
In summary, while both lidar and laser scanners use laser technology for distance measurement and 3D modeling, lidar is optimized for large-scale, georeferenced mapping and environmental sensing, whereas laser scanners are designed for detailed, close-range scanning with high precision.