Description
Objectives
To acquire fundamental knowledge to: - manipulate remotely sensed data of varied characteristics and distinct planetary bodies. - select the most adequate tecnhiques in each processing step. - identify and analyse the image contents in different application areas.
Syllabus
1. Fundamentals. Plataforms and sensors and adequation by application area. 2. Image processing and analysis. Filtering. Spectral indices as indicators of the relative abundance of landscape features. Segmentation and identification of the homogeneous regions of the images. 3. Unmanned aerial vehicles. Mission planning and image acquisition. Processing and analysis of 3D cloud points. Algorithms to build image mosaics and elevation models. 4. Machine learning. Selection and evaluation of features and samples. Object- based classification. Performance evaluation metrics. 5. Multitemporal image analysis and quantitative change detection. Application to natural resources evaluation, natural hazards and risk management, ecossystems dynamics and biodiversity.
Prerequisites
Geographical information systems, programming and computing, geo-spatial data analysis.
Cross Competence Component
Critical and innovative thinking: strategies to solve problems in TR (15%) and MP (15%) Intrapersonal skills: decision making in TR (10%) and MP (10%) Interpersonal skills: oral communication in MP (10%), written communication in TR (15%) and AMP (15%), work-team in TR (20%) and MP (20%) Information and media literacy: information search and management in TR (5%) and MP (5%)
Laboratorial Component
Solving applied exercises in LTI. Practical testing of unammned aerial vehicles in the field.
Programming And Computing Component
Use of commercial software of remote sensing to process and analyse the datasets in the applied exercises and the project. Development of small routines to solve specific tasks, using other computation and programming skills (for instance, Matlab or R). The total weight of the programming and computing component will be equal to 50%.
Ethical Principles
All members of a group are responsible for the group's work. In any assessment, every students shall honestly disclose any help received and sources used. In an oral assessment, every students shall be able to present and answer questions about the entire assignment and solution.