CoolingCapacityIndex

A short script generating Cooling Capacity Index made for Landsat 8 images as main part of master thesis. Based on InVEST Natural Capital project by Standford University.

Specifications

Python 3 (originally made for Python 3.8.8 using Miniconda3)
Input folder with subfolders containing unzipped images with all bands
Output folder
Digital Elevation model in meters for your region of interest
Sensor data for air temperature and humidity in CSV
Short Wave Incoming Radiation in CSV

Obtaining satellite images

Landsat 8 images can be obtained from EarthExplorer by USGS , where you need to register and then download image bundle, unzip it and locate in input folder:

Sensor Data in CSV

Your sensor data should look a bit like this:

Sensor -- name of the sensor
Value -- actual value of temperature in °C/humidity in %
Time -- Timestamp in RRRR-MM-DD HH:MM:SS
Id -- Id of each value (can be ommited)

Short Wave Incoming Radiation CSV

Date -- Date in format of RRRRMMDD
Value -- actual value of radiation in watts per square meter

Running with Miniconda3

All kinds of env activation with miniconda are available here. If your conda is connected to another env you should deactivate it first using:

conda deactivate

and then create new env using conda create env from file:

conda env create -f environment.yml

Conda asks to procees, press Y

proceed ([y]/n)?

If you are using Miniconda3 in MicrosofT Visual Code Studio, Conda may have not been recognized, you need to connect it manually in JSON settings:

{
    ... # any other settings you have already added (remove this line)

    "terminal.integrated.shell.windows": "<path-to-conda-cmd.exe>\\cmd.exe",
    “terminal.integrated.shellArgs.windows”: [“/K”, “C:\\<path-to-conda-installation>\\Scripts\\activate.bat C:\\<path-to-conda-installation>”]
    "python.condaPath": "C:\\<path-to-conda.exe>conda.exe"
}

Running the script

Conda should be able to start using:

python CCi.py