Journal cover Journal topic
Earth System Science Data The data publishing journal
Journal topic

Journal metrics

Journal metrics

  • IF value: 9.197 IF 9.197
  • IF 5-year value: 9.612 IF 5-year
    9.612
  • CiteScore value: 12.5 CiteScore
    12.5
  • SNIP value: 3.137 SNIP 3.137
  • IPP value: 9.49 IPP 9.49
  • SJR value: 4.532 SJR 4.532
  • Scimago H <br class='hide-on-tablet hide-on-mobile'>index value: 48 Scimago H
    index 48
  • h5-index value: 35 h5-index 35
Preprints
https://doi.org/10.5194/essd-2019-65
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-2019-65
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: data description paper 25 Jul 2019

Submitted as: data description paper | 25 Jul 2019

Review status
This preprint was under review for the journal ESSD but the revision was not accepted.

A 30-meter resolution national urban land-cover dataset of China, 2000–2015

Wenhui Kuang1, Shu Zhang1,2, Xiaoyong Li1,2, and Dengsheng Lu3 Wenhui Kuang et al.
  • 1Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
  • 2College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 10049, China
  • 3College of Geographical Sciences, Fujian Normal University, Fuzhou 350117, China

Abstract. Accurate urban land-cover datasets are essential for mapping urban environments. However, a series of national urban land-cover data covering more than 15 years that characterizes urban environments is relatively rare. Here we propose a hierarchical principle on remotely sensed urban land-use/cover classification for mapping intra-urban structure/component dynamics. China's Land Use/cover Dataset (CLUD) is updated, delineating the imperviousness, green surface, waterbody and bare land conditions in cities. A new data subset called CLUD-Urban is created from 2000 to 2015 at five-year intervals with a medium spatial resolution (30 m). The first step is a prerequisite to extract the vector boundaries covered with urban areas from CLUD. A new method is then proposed using logistic regression between urban impervious surface area (ISA) and the annual maximum Normalized Difference Vegetation Index (NDVI) value retrieved from Landsat images based on a big-data platform with Google Earth Engine. National ISA and urban green space (UGS) fraction datasets for China are generated at 30-meter resolution with five-year intervals from 2000 to 2015. The overall classification accuracy of national urban areas is 92 %. The root mean square error values of ISA and UGS fractions are 0.10 and 0.14, respectively. The datasets indicate that the total urban area of China was 6.28 × 104 km2 in 2015, with average fractions of 70.70 % and 26.54 % for ISA and UGS, respectively. The ISA and UGS increased between 2000 and 2015 with unprecedented annual rates of 1,311.13 km2/yr and 405.30 km2/yr, respectively. CLUD-Urban can be used to enhance our understanding of urbanization impacts on ecological and regional climatic conditions and urban dwellers' environments. CLUD-Urban can be applied in future researches on urban environmental research and practices in the future. The datasets can be downloaded from https://doi.org/10.5281/zenodo.2644932.

Wenhui Kuang et al.

Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement

Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement

Wenhui Kuang et al.

Data sets

A national urban land use/cover change dataset (CLUD-Urban) in China, 2000-2015 W. Kuang, S. Zhang, X. Li, and D. Lu https://doi.org/10.5281/zenodo.2644932

Wenhui Kuang et al.

Viewed

Total article views: 1,220 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
1,047 160 13 1,220 14 19
  • HTML: 1,047
  • PDF: 160
  • XML: 13
  • Total: 1,220
  • BibTeX: 14
  • EndNote: 19
Views and downloads (calculated since 25 Jul 2019)
Cumulative views and downloads (calculated since 25 Jul 2019)

Viewed (geographical distribution)

Total article views: 989 (including HTML, PDF, and XML) Thereof 977 with geography defined and 12 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Saved

No saved metrics found.

Discussed

No discussed metrics found.
Latest update: 06 Jul 2020
Download
Short summary
Urban land use/cover dynamics datasets play a vital role in urban planning and management. However, a series of national urban land-cover data covering more than 15 years is relatively rare. Here we developed a new data subset called CLUD-Urban from 2000 to 2015 at five-year intervals with a 30 m resolution. The total urban area of China was 62800 km2 in 2015, with average fractions of 70.70 % and 26.54 % for ISA and UGS, respectively. CLUD-Urban will be useful in urban environment.
Urban land use/cover dynamics datasets play a vital role in urban planning and management....
Citation