s892197704 / frnet-2022-isprs

Implementation of

A full resolution deep learning network for paddy rice mapping using Landsat data

1. Requirements

(a). Tensorflow/Keras > 2.6
(b). GDAL

We suggest using Conda to set the environment.

2.Run

python shuidao.py

We will upload some training samples so anyone downloads the codes and run them directly.

3.Dataset

The training dataset locates in the folder of the dataset. For each image, 1 indicates paddy, 0 indicates nonpaddy, and 3 means background which should be masked when you generate the training samples, e.g. size of 256*256.

For better visualization, ArcGIS is suggested to open the image, and Layer Properties -> Symbology -> Unique values should be employed. One demo is shown below.