Rural settlement Planet remote sensing image datase

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Authors: Yanlin Han
Cited by: 0

Abstract

This dataset is a deep learning training dataset used for remote sensing automatic extraction of rural settlements. The data core consists of high-resolution satellite images from Planet and their corresponding manually interpreted annotation masks. This dataset is specifically designed for training and evaluating semantic segmentation models for remote sensing images, with the aim of automatically and accurately extracting settlement spatial ranges from complex rural backgrounds. The task challenges include dealing with the diversity of settlement forms, spectral confusion with background features, and small target detection. The dataset is organized in the form of "image mask" pairing, usually stored in separate newjpg and newmask directories, ensuring strict file name correspondence for easy programmatic reading and batch loading.

Fields of Study & Subjects

Remote-Sensing Image Classification Automated Road and Building Extraction Remote Sensing and Land Use

Publication details

Journal / source
Figshare
Publication date
11 March 2026
Language
EN
Document type
Dataset