Coursework notes for Geog 2021
See below for notes on how to use these notes, or jump to the course pages
Whilst you will need to order and download the data yourselves in this practical, a test dataset is available for you.
You should make a directory to work in, e.g.:
bash% mkdir -p ~/DATA/where_I_put_the_notes
bash% cd ~/DATA/where_I_put_the_notes
Then, download (selecting from menu) the test data file LT51220441995364-SC20150217103827.tar.gz, or do one of the following:
bash% wget http://www2.geog.ucl.ac.uk/~plewis/Geog2021_Coursework/LT51220441995364-SC20150217103827.tar.gz
or, if you are on the UCL Geography system, you can simply copy the file:
bash% cp ~plewis/p/Geog2021_Coursework/LT51220441995364-SC20150217103827.tar.gz ~/DATA/where_I_put_the_notes
These coursenotes are available as web pages (html) from the Geog 2021 course overview page or more directly from the practical introduction page.
The notes are also available on github. You can directly download the notes from github, either using some git software, e.g:
bash% mkdir -p ~/DATA/where_I_put_the_notes
bash% cd ~/DATA/where_I_put_the_notes
bash% git clone https://github.com/profLewis/Geog2021_Coursework.git
or by downloading the course notes as a zip file.
If you use git, you can apply any updates to the notes:
bash% mkdir -p ~/DATA/where_I_put_the_notes
bash% cd ~/DATA/where_I_put_the_notes/Geog2021_Coursework
bash% git reset --hard HEAD
bash% git pull
You can also fork the notes and create your own version.
You can of course just read and digest the html notes, but you will find that there are snippets of computer code (in Python) at times. Note that you do not need to use the Python codes to do this coursework: you can do everything you need in ENVI and Excel. That said, you will be processing quite a number of images, and you may find the Python codes useful for at least semi-automating the tasks.
Assuming you are on a unix system (including OS X, linux etc.), then first change directory to where the notes are:
bash% mkdir -p ~/DATA/where_I_put_the_notes
bash% cd ~/DATA/where_I_put_the_notes/Geog2021_Coursework
Then start an [ipython] session:
bash% ipython
Then, for example, folling the code in the Download section, type or paste the following at the ipython prompt (In [1]:):
import sys
sys.path.insert(0,'python')
from uncompress_ls import uncompress_ls
from sort_landsat import sort_landsat
This will load some python codes from the local python directory that you can use.
Again, following the example, we can specify a Landsat data file:
dirname = 'LT51220441995364-*.tar.gz'
which assumes there is one or more files that match the pattern LT51220441995364-*.tar.gz in the current directoy (‘folder’) (see section above on downloading a test dataset).
Then, uncompress this file with:
files = uncompress_ls(dirname)
The variable files then contains a list of the files:
print files
[array(['/tmp/tmp0ImQHU/LT51220441995364CLT00_cfmask.tif',
'/tmp/tmp0ImQHU/LT51220441995364CLT00_sr_adjacent_cloud_qa.tif',
'/tmp/tmp0ImQHU/LT51220441995364CLT00_sr_atmos_opacity.tif',
'/tmp/tmp0ImQHU/LT51220441995364CLT00_sr_band1.tif',
'/tmp/tmp0ImQHU/LT51220441995364CLT00_sr_band2.tif',
'/tmp/tmp0ImQHU/LT51220441995364CLT00_sr_band3.tif',
'/tmp/tmp0ImQHU/LT51220441995364CLT00_sr_band4.tif',
'/tmp/tmp0ImQHU/LT51220441995364CLT00_sr_band5.tif',
'/tmp/tmp0ImQHU/LT51220441995364CLT00_sr_band7.tif',
'/tmp/tmp0ImQHU/LT51220441995364CLT00_sr_cloud_qa.tif',
'/tmp/tmp0ImQHU/LT51220441995364CLT00_sr_cloud_shadow_qa.tif',
'/tmp/tmp0ImQHU/LT51220441995364CLT00_sr_ddv_qa.tif',
'/tmp/tmp0ImQHU/LT51220441995364CLT00_sr_fill_qa.tif',
'/tmp/tmp0ImQHU/LT51220441995364CLT00_sr_land_water_qa.tif',
'/tmp/tmp0ImQHU/LT51220441995364CLT00_sr_snow_qa.tif'],
dtype='|S61')]
Now, you can subset the data:
ofiles = sort_landsat(files)
which will produce the extracted files you need. You can now quite ipython (^D and confirm y).
You should see that the python codes have generated two files LT51220441995364CLT00_mask.tif and LT51220441995364CLT00_refl.tif:
bash% ls -l *tif
-rw-rw-r--. 1 plewis plewis 10768420 Feb 26 10:32 LT51220441995364CLT00_mask.tif
-rw-rw-r--. 1 plewis plewis 42996634 Feb 26 10:31 LT51220441995364CLT00_refl.tif
In many ways a better approach is to use the ipython notebooks:
bash% mkdir -p ~/DATA/where_I_put_the_notes
bash% cd ~/DATA/where_I_put_the_notes/Geog2021_Coursework
Then start a browser (e.g. firefox, safari etc) and start an [ipython notebook] session:
bash% ipython notebook
This should open a page in your browser, e.g. http://localhost:8889/tree
If you then e.g. click on the link Download.ipynb, this should run the notebook in a new tab in the browser.
You can now go through the notes, and run (and/or edit) the python codes as they appear on the page.
The various images, text etc. are in ‘cells’ on the web page. To ‘run’ a cell select the cursor in that cell and then either do Shift Return (i.e. Shift and Return keys at the same time), or click the ‘play’ button.