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https://github.com/martibosch/uhi-twin-cities
https://github.com/martibosch/uhi-twin-cities
Last synced: 4 days ago
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- Host: GitHub
- URL: https://github.com/martibosch/uhi-twin-cities
- Owner: martibosch
- License: gpl-3.0
- Created: 2020-09-04T13:07:39.000Z (over 4 years ago)
- Default Branch: master
- Last Pushed: 2020-10-01T11:09:10.000Z (over 4 years ago)
- Last Synced: 2024-06-11T16:31:38.582Z (7 months ago)
- Language: Makefile
- Size: 19.5 KB
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
[](https://github.com/martibosch/uhi-twin-cities/blob/master/LICENSE)
# UHI Twin Cities
Calibration of the InVEST urban cooling model in Twin Cities, USA
## Instructions to reproduce
### 1. Clone the repository
You can use git to clone this repository as in:
```bash
git clone https://github.com/martibosch/uhi-twin-cities.git
```
or [download as a zip file](https://github.com/martibosch/uhi-twin-cities/archive/master.zip) and extract it.
### 2. Software requirements
First of all, conda is required to automatically install all the sofware dependencies. See [its installation page](https://docs.conda.io/projects/conda/en/latest/user-guide/install/) and follow the steps to install it in your operating system.
Additionally, [GNU Make](https://www.gnu.org/software/make/) is used to manage the execution of the calibration workflow, which is usually built-in with Linux and OSX systems. **Windows users** can install it from the Anaconda prompt as in:
```bash
# ACHTUNG: You only need to run this in Windows
conda install -c conda-forge make
```
Then, from the root of this repository, you can create a conda environment with all the required software dependencies as in:
```bash
make create_environment
```
and then activate it as in:
```bash
conda activate uhi-twin-cities
```
### 3. Data requirements
Copy the `UCM_CalibrationData` from the Google Drive to the `data/raw` directory of this repository so that the directory structure is of the form:
```
|─ data
| └─ raw
| └─ UCM_CalibrationData
| |─ InVEST_Inputs
| |─ Twine_UHI_2016
| └─ LandSurfaceTemperature2016
|
|─ .gitignore
|─ LICENSE
|─ Makefile
|─ README.md
└─ environment.yml
```
### 4. Calibrate the model
The calibration of the urban cooling model for the `July4-6_2012_DayTemp1.tif`, `July4-6_2012_NightTemp1.tif`, `JJA_Day_Temp1.tif`, `JJA_Night_Temp1.tif` and `lst2016_utm_c/hdr.adf` reference temperature rasters can be executed as in:
```bash
make calibrate
```
which will dump the calibrated parameters for each file in the `data/processed` directory (which will be created automatically if it does not exist).
### 5. Generate the calibration reports
Reports for the calibration of the urban cooling model for each of the reference temperature rasters can be obtained as in:
```bash
make calibration_reports
```
which will generate a PDF calibration report and dump it to the `reports` directory (which will be created automatically if it does not exist).
--------
Project based on the [cookiecutter data science project template](https://drivendata.github.io/cookiecutter-data-science). #cookiecutterdatascience