Advanced remote sensing

This web page contains the material used in the remote sensing component of the ANU course “Advanced remote sensing and GIS” (ENVS3019/ENVS6319). Each of the topics are covered by short videos and some reading material. I have posted it here for anyone who is interested in the material. ANU students can also access this through the course web site on Wattle (registered access).

TIPS:

  • ANU students can also access this through the course web site on Wattle (registered access).
  • Want to download all video slides, reading and/or tutorial materials in one step? You can, via this link.

Course content

Topic 1: Introduction to Remote Sensing

Short videos

Reading Material

Web sites and Resources

Topic 2: Optical Remote Sensing

Short videos

Reading Material

Web sites and Resources

Topic 3: Other Remote Sensing Methods

Short videos

Reading Material

Web sites and Resources

Topic 4: Interpreting remote sensing data

Short videos

Reading Material

Web sites and Resources

Topic 5: Vegetation remote sensing

Short videos

Reading Material

Web sites and Resources

Topic 6: Atmosphere and water remote sensing

Short videos

Reading Material

Web sites and Resources

  • Asia-Pacific Water Monitor, which combines satellite rainfall data and reanalysis rainfall data to monitor developing droughts (ANU WALD)
  • EarthWindMap – an amazing visualisation of reanalysis weather data (nullschool)

Tutorials 

The tutorials are available for Matlab and for Python.

MatLab is commercial software for technical computing. It offers a stable, visual and interactive analysis environment and has well-developed documentation of its functions. It is recommended you choose these tutorials if you have had no previous experience with programming or if you prefer to program in a more interactive environment.  You can download all Matlab tutorials here. There are also some introductory videos:

Python is an open-source, general-purpose programming language which is increasingly popular for scientific data analysis.  As well as in science, Python is widely used in areas from web development, to desktop utilities, to cloud- or super- computing. If you have never worked with Python you will need to invest some additional time and effort into mastering the basics. If you have never programmed in any language you may find the learning curve steep. You can find all the workshop materials, a free textbook and practice exercises, along with instructions on how to install Python at home on Github: https://github.com/Zac-HD/remote-sensing-workshops

Data download links

NOTE: some of these data use FTP, other use THREDDS (What is THREDDS?)