Course syllabus
FjÀrranalys, digitala metoder
Remote Sensing, Digital Methods
EXTN15, 7,5 credits, A (Second Cycle)
Valid for: 2013/14
Decided by: Education Board D
Date of Decision: 2013-04-19
General Information
Elective for: L4-gi, Pi4, Pi4-mrk
Language of instruction: The course will be given in English
Aim
The course aims at conveying basic knowledge about theories and
methods in digital satellite remote sensing.
Learning outcomes
Knowledge and understanding
For a passing grade the student must
- describe the fundamental physical principles of remote
sensing,
- account for the basic technical principles of satellites,
sensors, and ground segments for data collection, and for
properties of available data from these systems, and
- account for principles of digital image management and
processing in remote sensing.
Competences and skills
For a passing grade the student must
- analyse digital remote sensing data with existing image
processing software independently,
- integrate remote sensing data with other data in a geographical
information system,
- actively contribute to discussions, and present the result of
remote sensing in writing, orally, and in maps for specialists and
lay persons, and
- gather knowledge within the field in a predominantly
independent and individual way.
Judgement and approach
For a passing grade the student must
- compile, appraise and discuss choice of data and analysis
method to solve a given remote sensing problem, and
- critically review, appraise and discuss the reliability of
analyses based on remote sensing data.
Contents
- fundamental physical principles and terminology for
electromagnetic radiation, and its interaction with different media
(air, water, land, vegetation etc.)
- overview of remote sensing satellites and their orbits, common
remote sensing systems and their technical principles, properties,
and data formats.
- data management from raw data to geometrically and
radiometrically corrected imagery.
- image processing methods within remote sensing, including e.g.
image enhancement, data compression, image transformation, and
basic classification methods.
- integration of field data with remotely sensed data for
classification and accuracy evaluation.
- thematic mapping with remote sensing data.
Examination details
Grading scale: TH
Assessment: Assessment takes the form of a written test at the end of the course, and evaluation of student reports. Teaching consists of lectures, practicals, field exercises, seminars, group exercises and project work. Practicals, field exercises, seminars, group exercises and project work, and the course elements associated with these are compulsory.
Admission
Admission requirements:
- 120 credits within civil engineering or equivalent
Required prior knowledge: FMS032/FMS012 Matemathical Statistics, Basic Course.
The number of participants is limited to: 20
Selection: Total number of credits on master level within specialisation of LTH program.
The course overlaps following course/s: NGEN09, NGEN08
Reading list
- Compendia and articles.
- Lillesand T., Kiefer, R.W. and Chipman, J: Remote sensing and image interpretation. Wiley , 2007, ISBN: 10-0470052457. Course book.
Contact and other information
Course coordinator: Lars Eklundh, Lars.Eklundh@nateko.lu.se
Course homepage: http://www.nateko.lu.se/extn15