This course will be focused on the description of 2D and 3D sensors commonly employed in geomatic applications: First, 2D sensors (photographic cameras) will be described and several digital image analysis concepts will be explored, from basic digital image processes to artificial intelligence based approaches. 3D sensors (mainly LiDAR systems) will be introduced and explored from a metrological perspective, finding error sources in 3D measurements. Then, a theorical and practical approach for fusing 2D and 3D data will finish the course.
1. 2D sensors
- Camera basics and optics. Light propagation
- Sensor and Image Models
- Image analysis basics: Histograms, binary images, local operators, convolution, edge detection.
- Introduction to Artificial Intelligence for 2D applications
- Image Classification and segmentation.
2. 3D sensors
- Introduction to 3D sensors. Typologies.
- LiDAR acquisition systems
- Error sources in LiDAR systems
- LiDAR vs Photogrammetry
3. Sensor fusion
- Mobile Mapping Systems
- 2D / 3D sensor fusion: Basics
4. Sensor fusion: Practical application
- 2D / 3D sensor fusion: Adding color to a 3D point cloud
The course is designed to be developed in 12 weeks after the presentation that is scheduled in September 2021.
Orientative schedule by topic:
1. 2D Sensors: Week 1 to Week 4
2. 3D Sensors: Week 4 to Week 8
3. Sensor fusion: Week 9 to Week 10
4. Sensor fusion: Practica application: Week 11 to Week 12.
Teachers of the subject:
Ana Sánchez Rodríguez
Mario Soilán Rodríguez
- Jesús Balado Frías, Ana Sánchez Rodríguez, Mario Soilán Rodríguez: Pedro Arias
- Jesús Balado Frías, Ana Sánchez Rodríguez, Mario Soilán Rodríguez: Suzanna Laguela
The course describes the leading technologies used in the acquisition of cartographic information and the mapping of land and structures. A brief introduction to GIS systems is given as well as how to layout the data obtained. Throughout the course, we will study and demonstrate the operation of high-precision sensors such as 2D imaging in different spectra with cameras and 3D mapping by active sensorization (LiDAR). Real applications of these sensors will also be explored: during the practical part of the course, the acquisition with sensors and the use of different software for the processing of the obtained data will be demonstrated.
1. Satellite image
- Characteristics
- Satellites and data sources
- Spectral indices
2. Satellite image: Advanced processing and applications
- Practical implementation
3. 3D point clouds: Introduction
- Introduction to LiDAR and its applications
- Structural organization of 3D point clouds: Rasterization and Voxelization
- Filtering, segmentation and classification of 3D point clouds
4. 3D point clouds: Advanced processing and applications
- Practical implementation of 3D point cloud processes
Course schedule
The course is designed to be developed in 12 weeks after the presentation that is scheduled in September 2021.
Orientative schedule by topic:
1. Satellite image: Week 1 to Week 3
2. Satellite image: Advanced processing and applications: Week 4 to Week 6
3. 3D Point Clouds: Introduction: Week 7 to Week 9
4. 3D Point Clouds: Advanced processing and applications: Week 10 to Week 12
Teachers of the subject:
- Teacher: Pedro Arias
- Teacher: Suzanna Laguela