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A STP-HSI index method for urban built-up area extraction based on multi-source remote sensing data

Citation

Zhang, Zhengpeng (2022), A STP-HSI index method for urban built-up area extraction based on multi-source remote sensing data , Dryad, Dataset, https://doi.org/10.5061/dryad.qz612jmhr

Abstract

The changes of urban built-up areas can reflect the process of urbanization, and it can reflect the population, economy, and cultural development of the city. Therefore, accurate and timely extraction of urban built-up areas plays an important role in the dynamic management of the city. In the existing research, single-source remote sensing data is used to extract urban built-up areas, and there is a problem that the spectrum of urban areas and non-urban areas is easily confused. Multi-source remote sensing data, including luojia-1 remote sensing data, Landsat 8 OLI remote sensing data, etc., can make up for the spectrum confusing issues.

We fuse the time series information of night light remote sensing data, neighborhood information and point of interest (POI) data in spatial dimension, and propose a built-up area extraction method that integrates night light time and space information and POI information.

Funding

National Natural Science Foundation of China, Award: 41801294

National Key Research and Development Program of China, Award: 2020YFA0713503

Hunan Provincial Natural Resources Department, Award: 2022-15