Unsupervised Crop Classification using Micro-spectral satellite imagery
Project description
Unsupervised Crop-Classification using Multi-Spectral Satellite Imagery
This Project is used for crop classification using unsupervised Machine Leaning (K-Means clustering)
Installation - Install the package (python 3.0 and above):
pip install crop-classifier
How to use - from unsupcc import executer
# getting indices layer stack for an AOI
ie = executer.IndexExecuter()
ie.get_layer_stack()
#provide the asked input and it will return the path where layer stack is stored
# get crop clusters from layer stack of multiple dates
ce = executer.ClusterExecuter()
ce.crop_classifier(indice_stack_path, date_bands, number_of_clusters)
#It will return a raster containing clusters of multiple crops
For a manual installation get this package:
wget https://github.com/Dehaat/crop-classification
cd crop-classification
Install the package (python 3.0 and above):
python setup.py install
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
crop-classifier-0.1.5.tar.gz
(3.8 MB
view hashes)
Built Distribution
Close
Hashes for crop_classifier-0.1.5-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | edf63b3e0f127c9d3ea4f7ca8a8c1972f030546737a382f372cf8d3019460397 |
|
MD5 | 7703edc797461f5857e8549197bf0386 |
|
BLAKE2b-256 | ed53a3dff0d84610cbee8a7ebcd8ba34ccd35c2b81c1bd366ddedbec5fceebd1 |