Landsat-based dataset for mapping annual center-pivot irrigated cropland in Brazil

Center-pivot irrigated cropland (CPIC) is a critical component of irrigation and plays an essential role in improving water use efficiency and increasing food production. To automatically extract the spatial distribution of CPIC in Brazil based on the remote sensing technology, we constructed a trai...

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Bibliographic Details
Main Authors: Xiangyu, Liu, Wei, He, Wenbin, Liu, Guoying, Yin, Hongyan, Zhang
Format: Dataset
Language:English
Subjects:
irrigation
remote sensing
semantic segmentation
Online Access:Get full text
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Summary:Center-pivot irrigated cropland (CPIC) is a critical component of irrigation and plays an essential role in improving water use efficiency and increasing food production. To automatically extract the spatial distribution of CPIC in Brazil based on the remote sensing technology, we constructed a training dataset that supports the semantic segmentation models. The dataset were built with the  Landsat 5 , 7 and 8  images as well as the CPIC maps from ANA reference data. We used the Landsat images in 2005, 2010 and 2015 to build the dataset. The samples in train_images and train_masks were used to train and valid the Convolutional Neural Network models;  The samples in valid_data were used to test the model's prediction accuracy. Pixels with values 255 and 0 in the mask samples represent the CPIC and background categories. For technical details that used to create the dataset, please refer to https://doi.org/10.1016/j.isprsjprs.2023.10.007.
ISSN:1872-8235
DOI:10.5281/zenodo.10035903