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Zürcher Hochschule für Angewandte Wissenschaften

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n.MA.ENR.RSE.18FS (Remote Sensing for Ecology) 
Modul: Remote Sensing for Ecology
Diese Information wurde generiert am: 21.11.2024
Nr.
n.MA.ENR.RSE.18FS
Bezeichnung
Remote Sensing for Ecology
Credits
3

Beschreibung

Version: 6.0 gültig ab 01.08.2023
Studiengang
Degree Program		 MSc in Environment and Natural Resources
Arbeitsaufwand
Workload		 90 hours (35 h contact lessons, 55 h self-study)
Modulleitung
Module Coordinator		 Michael Döring
Dozierende
Lecturers		 Michael Döring, various internal and external lecturers
Eingangskompetenzen
Entry Requirements		 Students are able to
  • explain the basic functions and interrelationships in ecosystems,
  • perform simple, stand-alone field recordings in ecosystems,
  • explain the theoretical foundations of Geographic Information Systems (GIS),
  • carry out basic, spatial ecosystem analyses using GIS.
    A written proof of skills/GIS certificate is required.
Ausgangskompetenzen
Learning Outcome and Competences		 Students will learn to
  • recognise and evaluate the potential of remote sensing for ecosystem assessment and evaluation,
  • perform spatio-temporal data and analyses by means of remote sensing (e.g. drone) and GIS,
  • interpret and critically assess remote sensing data and products for ecosystem assessment and evaluation,
  • integrate remote sensing data and products into their own research or practical projects and carry out such a project.
Inhalte
Module Content		 Ecological systems are diverse and spatially heterogeneous areas characterized by interacting natural and impacted terrestrial and aquatic mosaics, which consist of features, such as forests, grasslands, rivers or lakes. Key research topics in these landscape mosaics include the analyses, quantification and scaling of ecological flows, land-use and land-cover change, relating landscape pattern analysis with ecological processes, conservation and sustainability.

In this context GIS analyses in concert with  remote sensing using unmanned aerial or aquatic vehicles (UAVs), autonomously or remotely operated and equipped with various sensors such as NIR (Near infrared), TIR (Thermal infrared) or ADP (Acoustic Doppler Profiler) offer new opportunities for scale appropriate measures of ecological phenomena at high spatial- temporal resolutions.
 
The goal of this proposed class is to introduce and expose students to close range remote sensing in ecosystems with the focus on aquatic and terrestrial components of floodplains and adjacent areas such as agricultural land. Students will be gain knowledge of basic spatial analysis through GIS and remote sensing techniques.  In addition, students will learn basic application of drones and ADP, two remote sensing instruments of fast growing interest in ecological research and application. The students will learn about the essentials to operate drones and ADPs, the initial post processing of data products and examples how to integrate these data into ecological research and application.
 
Lehr-/Lernmethoden
Teaching / Learning Methods		 Lectures, GIS excercises, Project work
Leistungsnachweis
Assessment of Learning
Outcome		 The assessment of learning outcome is composed as follows
  • written proposal
  • project work
  • project presentation
Bibliographie
Bibliography		 Carbonneau and Piegay (2012). Fluvial Remote Sensing for Science.
Unterrichtssprache
Language		 English
Bemerkungen
Comments		 -

Hinweis

  • Weitere verfügbare Versionen: 1.0 gültig ab 01.02.2018, 2.0 gültig ab 01.02.2019, 4.0 gültig ab 01.08.2020, 5.0 gültig ab 01.08.2021, 7.0 gültig ab 01.02.2025