Package to classify crops based on sentinel images.
Project description
Crop classification
This is a collection of scripts that can help to classify crops using Sentinel data.
Installation manual
- Install conda
As the scripts are written in Python, you need to use a package manager to be able to install the packages the scripts depend on. The rest of the installation manual assumes you use anaconda and python 3.6+. The installer for anaconda can be found here: https://www.anaconda.com/download/.
If you need some more installation instructions, have a look here: https://conda.io/docs/user-guide/install/index.html
- Create new environment and install dependencies
Once you have anaconda installed, you can open an anaconda terminal window and follow the following steps:
1. Create and activate a new conda environment
```
conda create --name cropclassification python=3.6
conda activate cropclassification
```
2. Install the dependencies for the crop classification scripts:
```
conda install --channel conda-forge scikit-learn keras tensorflow rasterio rasterstats geopandas pyarrow psutil
```
3. Possibly you need to restart your computer now, especially if it was the first time you installed anaconda/geopandas
4. Start the anaconda terminal window again and activate the environment
```
conda activate cropclassification
```
- Update the configuration to your situation
You can now open the scripts in eg. visual studio code, and check out especially the .ini files in the config dir. You need to update those to match your environment, eg. set the paths as you want them,...
- Calculate the time series
To calculate time series, you need to run the calc_dias.py
script on a server that has access to the sentinel CARD images.
- Start a crop classification
Run run_job.py
.
Sample data
Sample data can be downloaded from the following location. If you don't change the default paths in the scripts in needs to be put in the directory C:\temp\CropClassification\InputData https://drive.google.com/open?id=1eN9cBcWyvM0msNMCD6nivcGuZfYyqV5q
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
File details
Details for the file cropclassification-0.0.6.tar.gz
.
File metadata
- Download URL: cropclassification-0.0.6.tar.gz
- Upload date:
- Size: 82.1 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/2.0.0 pkginfo/1.5.0.1 requests/2.24.0 setuptools/49.2.0.post20200714 requests-toolbelt/0.9.1 tqdm/4.47.0 CPython/3.8.3
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 3ce71446e6f3145715da0495e19c72e3a0aeb1590b6b7a2f7cbfdceb686cb38c |
|
MD5 | 443c6a0f4e064894fc908080e4bb8bf3 |
|
BLAKE2b-256 | 4d565d687201f689cc575b0a42d912dab58f881fd7311bf41d170da881cc97e5 |
File details
Details for the file cropclassification-0.0.6-py3-none-any.whl
.
File metadata
- Download URL: cropclassification-0.0.6-py3-none-any.whl
- Upload date:
- Size: 95.8 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/2.0.0 pkginfo/1.5.0.1 requests/2.24.0 setuptools/49.2.0.post20200714 requests-toolbelt/0.9.1 tqdm/4.47.0 CPython/3.8.3
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | d3fe0888ace63c4f73509253163a4c96b11cb02a891f12d4125b03959a079e32 |
|
MD5 | 8447e73ea6143b1357f6e663f117e32f |
|
BLAKE2b-256 | 5388e2a0d022dd8faf4b0080d49ffc25b29e3f87fcbae3b0beabe3229dbf255c |