Remote Sensing and Geological Interpretation

Year
1
Academic year
2019-2020
Code
02032043
Subject Area
Geology
Language of Instruction
Portuguese
Other Languages of Instruction
English
Mode of Delivery
B-learning
Duration
SEMESTRIAL
ECTS Credits
6.0
Type
Compulsory
Level
2nd Cycle Studies - Mestrado

Recommended Prerequisites

General Geology; General Physics; Mapping; Computing as user.

Teaching Methods

Lectures:oral presentation of concepts and methodologies using audiovisual media to facilitate understanding of the knowledge of the subject. Theoretical-Practical:application of theoretical knowledge to practical problems through the collection, analysis and processing of geo-spatial information using adequate methods and techniques particularly GIS software for organizing analyzing, modeling and visualization of geo-spatial data.Practical: the students will do a project work based in real data using the software aforementioned, to consolidate the knowledge acquired in the course unit.

Learning Outcomes

This unit envisages:

a) to provide the ability to understand the acquisition of spatial data by Remote Sensing technological systems;

b) to perceive and apply digital geo-spatial processing techniques to such data;

c) to understand the GIS environment as a useful tool to integrate geographic information;

d) to understand and develop the ability to manage, extract, analyze and model the digital data;

e) to apply the above methods to geological and environmental systems.

Work Placement(s)

No

Syllabus

1. Remote Sensing as a system;

2. Technological systems for the acquisition of images and the various space programs for Earth observation;

3. The LIDAR system

4. Techniques for image processing and classification;

5. GIS as system integrator for geographically-based information;

6. Techniques for management, extraction, analysis, and modeling of information in a GIS environment;

7. Practical classes with application to the geological interpretation of Timor based on LIDAR system and Landsat and ASTER image analysis.

Assessment Methods

Assessment
Project: 40.0%
Exam: 60.0%

Bibliography

Fonseca, A.D. & Fernandes, J.C. (2004) – Detecção Remota, Lidel, Lisboa, 224 p.

http://www.ldeo.columbia.edu/res/fac/rsvlab/fundamentals_e.pdf - Fundamentals of Remote Sensing - A Canada Centre for Remote Sensing Remote Sensing Tutorial

https://www.fas.org/irp/imint/docs/rst/Front/tofc.html -  Remote Sensing Tutorial;  NASA/Goddard Space Flight Center

Davis, B.E. (2001) - GIS – a visual approach, 150 p.