🛰️🌍 Geospatial Datasets
Collection
A curated collections of diverse geospatial and satellite imagery datasets.
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The PatternNet dataset is a dataset for remote sensing scene classification and image retrieval.
PatternNet is a large-scale high-resolution remote sensing dataset collected for remote sensing image retrieval. There are 38 classes and each class has 800 images of size 256×256 pixels. The images in PatternNet are collected from Google Earth imagery or via the Google Map API for some US cities. The following table shows the classes and the corresponding spatial resolutions. The figure shows some example images from each class.
To use this dataset, simply use datasets.load_dataset("blanchon/PatternNet")
.
from datasets import load_dataset
PatternNet = load_dataset("blanchon/PatternNet")
If you use the EuroSAT dataset in your research, please consider citing the following publication:
@article{li2017patternnet,
title = {PatternNet: Visual Pattern Mining with Deep Neural Network},
author = {Hongzhi Li and Joseph G. Ellis and Lei Zhang and Shih-Fu Chang},
journal = {International Conference on Multimedia Retrieval},
year = {2017},
doi = {10.1145/3206025.3206039},
bibSource = {Semantic Scholar https://www.semanticscholar.org/paper/e7c75e485651bf3ccf37dd8dd39f6665419d73bd}
}