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Study project: Remote sensing based analysis of environmental change - Single View

Basic Information
Type of Course Project course Long text
Number 148783 Short text
Term WS 2019/20 Hours per week in term 2
Expected no. of participants 10 Study Year
Max. participants 15
Credits 5 Assignment enrollment
Hyperlink
Language english
application period
Dates/Times/Location Group: [no name] iCalendar export for Outlook
  Day Time Frequency Duration Room Room-
plan
Lecturer Status Remarks Cancelled on Max. participants
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iCalendar export for Outlook
Tue. 16:00 to 18:00 weekly 15.10.2019 to 28.01.2020  Heisenbergstr. 2 - StudLab GEO1 130       08.10.2019: The course starts in the second week of the term
Group [no name]:
 


Responsible Instructor
Responsible Instructor Responsibilities
Meyer, Hanna, Prof. Dr. responsible
Curriculae
Graduation - Curricula Sem ECTS Bereich Teilgebiet
Master - Geoinformatics (88 E62 8) - 5
Master - Geoinformatics (88 E62 12) - 5
Bachelor - Geoinformatik (82 807 13) - 5
Bachelor - Geoinformatik (82 807 9) - 5
Exams / Modules
Number of exam Module
30002 Projekt - Bachelor Geoinformatik Version 2013
26003 Projekt - Bachelor Geoinformatik Version 2009
13002 Project Selected Topics in Geographic Information Science - Master Geoinformatics Version 2012
13003 Project in Interoperability - Master Geoinformatics Version 2012
18002 Project Computer Science - Master Geoinformatics Version 2012
17002 Study Project Advanced Topics in Geographic Information Science - Master Geoinformatics Version 2012
12002 Project in Interoperability - Master Geoinformatics Version 2008
Assign to Departments
Fachbereich 14 Geowissenschaften
Contents
Description

Environmental change encompasses climate- and land cover change and its consequences on ecosystems such as land degradation, forest dieback, spread of invasive species, etc.

The aim of this study project is to analyze and visualize different topics of environmental change on the basis of multi-sensor satellite data.

During the course, students will work in small groups on self-chosen topics and will be supported by practical guidance on satellite data handling, image classification, change detection or trend analysis. Methods will be exemplified using R.

The course is at the interface between geoinformatics and landscape ecology and students from landscape ecology are highly encouraged to participate as well.


Structure Tree
Lecture not found in this Term. Lecture is in Term WS 2019/20 , Currentterm: SoSe 2024