Vacant land of 36 major Chinese cities

Published: 24 February 2022| Version 1 | DOI: 10.17632/3c8myvygjj.1
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Description

This is the supplementary data to the paper "Large-scale Automatic Identification of Urban Vacant Land Using Semantic Segmentation of High-Resolution Remote Sensing Images", which shows the identification results in 36 major cities in China. The files include the shapefiles of the vacant land and the boundary of each city. The filename formats are as follows: (1) vacant land: [abbr. of city name]_VL (2) boundary: [abbr. of city name]_BD The abbreviations of the city name are as follows: abbr. city name BJ Beijing CC Changchun CD Chengdu CQ Chongqing CS Changsha DL Dalian FZ Fuzhou GY Guiyang GZ Guangzhou HE Harbin HF Hefei HH Hohhot HK Haikou HZ Hangzhou JN Jinan KM Kunming LS Lhasa LZ Lanzhou NB Ningbo NC Nanchang NJ Nanjing NN Nanning QD Qingdao SH Shanghai SJ Shijiazhuang SY Shenyang SZ Shenzhen TJ Tianjin TY Taiyuan WH Wuhan WL Urumqi XA Xi’an XM Xiamen XN Xining YC Yinchuan ZZ Zhengzhou The code is available at https://github.com/SkydustZ/Large-scale-Automatic-Identification-of-Urban-Vacant-Land.

Files

Steps to reproduce

To reproduce the data, one can refer to the paper "Large-scale Automatic Identification of Urban Vacant Land Using Semantic Segmentation of High-Resolution Remote Sensing Images". The code is available at https://github.com/SkydustZ/Large-scale-Automatic-Identification-of-Urban-Vacant-Land.

Institutions

Tsinghua University

Categories

Urban Land Use

Licence