Remote Sensing and GIS Software

Code:

EGEO4021

Acronym:

EGEO4021

Keywords
Classification	Keyword
OFICIAL	Surveying Engineering

Instance: 2021/2022 - 2S

Active?	Yes
Responsible unit:	Department of Geosciences, Environment and Spatial Plannings
Course/CS Responsible:	Master in Remote Sensing

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
M:DR	12	The study plan from 2018	1	-	3	21	81

Teaching language

Suitable for English-speaking students

Objectives

It is aimed that the students acquired skills and knowledge in new GIS/ remote sensing applications and their computational development.

It is aimed to:

1. Become familiar with the graphical user environment of each application.
2. Use specific tools designed for GIS and Remote Sensing.
3. Acquire training about geospatial libraries and involved programming paradigms.
4. Automation of algorithms for data processing and analysis.

Learning outcomes and competences

Through the contact with the software and available tools, the student are stimulated to learn and explore the software. The students can follow the code presented in the python-notebook and implement the same code contributing to the consolidation of the acquired knowledge; with the classes using the software and script development, the student will finish the creation of an application / tool, integrating all the concepts learned up to that moment.

Working method

Presencial

Program

1. Exploitation of spatial data modules: GDAL / OGR.


2. Introduction to QGIS software.
   
   
   
   • Exploitation of remote sensing tools integrated in the QGIS.
     
     
     
     • Semi automatic classification plugin.
     
     
     • Orfeo-Toolbox.
     
     
     
     
   
   
   • Introduction to PyQt4 library and QGIS API (qgis.gui and qgis.core).
   
   
   • Official framework for creating applications in QGIS software.
   
   
   
   

2.4 Importing algorithms from the Processing Toolbox framework

1. Introduction to GRASS-GIS software (vector and raster layers; layer properties; visualization of geospatial information; geoprocessing; managing multispectral images).


2. Introduction to the processing of SAR-imaging products with ESA-SNAP. Radiometric calibration, noise reduction with filters and multilook technique, geometric correction. Integration of the final product in GRASS-GIS for geospatial analysis.

Mandatory literature

Lawhead, J.; QGIS Python Programming Cookbook, 2015
Markus Neteler, Helena Mitasova; Open Source GIS: A GRASS GIS Approach, Springer, 2010
Gary Sherman; Desktop GIS: Mapping the Planet with Open Source Tools, Pragmatic Bookshelf, 2008

Teaching methods and learning activities

The classes are taught essentially with a practical component and complemented with a theoretical context that will be presented in the form of worksheets integrated between the different software, and where the students follow the program interactively using the software QGIS, GRASS-GIS and ESA-SNAP.

Assessment is done at the end of the program with a practical exam where problems are proposed and students should think / reflect and implement a solution. This assessment is made with the support of the interactive notebook provided in classes.

Practical exam - 100%

Software

QGIS
GRASS-GIS

Evaluation Type

Evaluation with final exam

Assessment Components

designation	Weight (%)
Exame	100,00
Total:	100,00

Amount of time allocated to each course unit

designation	Time (hours)
Frequência das aulas	21,00
Estudo autónomo	60,00
Total:	81,00

Eligibility for exams

Assessment is done at the end of the program with a practical exam.

Calculation formula of final grade

Practical exam.

Observations

Due to the pandemic (COVID-19), part of the face-to-face assessment may be replaced by remote assessment, maintaining the same assessment criteria.