n.BA.AD.RSGA.23HS (Remote Sensing and Geodata Acquisition) 
Module: Remote Sensing and Geodata Acquisition
This information was generated on: 09 May 2024
No.
n.BA.AD.RSGA.23HS
Title
Remote Sensing and Geodata Acquisition
Credits
2

Description

Version: 1.0 start 01 August 2023

 

Study Programme Applied Digital Life Sciences
Regulations Applicable RPO, 29 January 2008, School of Life Sciences and Facility Management Academic Regulations, 15 Dec. 2009, Annex for the Bachelor of Applied Digital Life Sciences degree programme
Module Type  
  Compulsory Module  X Elective Module    Optional Module
Planned Semester 4th Semester
Module Coordinator Johann Junghardt
Telephone / E-Mail +41 (0)58 934 50 13 / johann.junghardt@zhaw.ch
Lecturer(s),
Speaker(s),
Associate(s)		 Johann Junghardt, Pascal Ochsner, Nils Ratnaweera
Entrance Requirements -
Learning Outcomes and Competencies Technical skills:
The students
  • acquire basic knowledge of remote sensing optics and physics
  • develop an applied expertise in remote sensing sensor systems and data
  • will execute their individual acquisition and processing of open and free remote sensing data in an environmental context
  • design and implement IT infrastructures for managing big remote sensing data volumes, integrating previously acquired competencies in database management and spatial databases
  • learn GIS-based processing and analysis of remote sensing data using proprietary and free software and scripting languages
  • apply image classification and automatization processes in image processing in GIS and with scripting languages
  • have insight in basic processing, visualization and analysis of 3D data and point clouds with specialized open software solutions and scripting languages.
  • are introduced to independent planning, processing and analysis of drone-based surveying
Transferable skills:
The students
  • work on their own holistic projects guided by the content of the module.
  • have to navigate, address and judge different datasets and their properties.
  • are introduced to different kinds of data quality and data origin and have to assess and choose their own sample data.
Module Content
  • Basics of physics of remote sensing ·
  • Sensors and airborne/spaceborne systems
  • Types and applications of remote sensing data
  • Interfaces and databases for managing (big) remote sensing data
  • Scripting approaches to server-based remote sensing analysis (Google Earth Engine)
  • Digital image processing and interpretation of remote sensing data
  • Image classification
  • Multitemporal analysis of geodata
  • 3D Data / point clouds / Visualization and Analysis
  • Data quality and uncertainty
  • Remote sensing and artificial intelligence
Follow-up Modules GISc and Geodatabases, Spatio-temporal Data Science, Image Processing for Remote Sensing
Methods of Instruction  Paper club

Individual and group assignments (most of the exercises will be held in collaborative and mixed forms of digital communication and collaboration).

Applied field work (drone remote sensing)

Input by external experts from the swiss remote sensing ecosystem
Digital Resources Example:
  • Videomanuals
  • Screencasts for exercises and solutions
  • Academic papers on specific content
  • Practical Exercises in Google Earth Engine, QGIS and R
Lesson Structure / Workload  
 Contact Hours 28
 Guided Self-Study 14
 Independent Self-Study 18
 Total Workload 60
Classroom Attendance No
Assessment Coursework 100%: (50% 2 small individual assignments concerning an individual project; 50% project report, semester project in groups of 2, individual contributions must be declared)
Language of Instruction  English
Comments -

 

Course: Remote Sensing and Geodata Acquisition
No.
n.BA.AD.RSGA.23HS.V
Title
Remote Sensing and Geodata Acquisition

Note

  • No module description is available in the system for the cut-off date of 09 May 2024.