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-2019-200
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-2019-200
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: data description paper 21 Jan 2020

Submitted as: data description paper | 21 Jan 2020

Review status
A revised version of this preprint was accepted for the journal ESSD and is expected to appear here in due course.

Development of a global 30-m impervious surface map using multi-source and multi-temporal remote sensing datasets with the Google Earth Engine platform

Xiao Zhang1,2, Liangyun Liu1,2, Changshan Wu3, Xidong Chen1,2, Yuan Gao1,4, Shuai Xie1,2, and Bing Zhang1,2 Xiao Zhang et al.
  • 1State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China
  • 2University of Chinese Academy of Sciences, Beijing 100049, China
  • 3Department of Geography, University of Wisconsin-Milwaukee, Milwaukee, WI, USA
  • 4College of Geometrics, Xi’an University of Science and Technology, Xi’an 710054, China

Abstract. The amount of impervious surface is an important indicator in the monitoring of the intensity of human activity and environmental change. The use of remote sensing techniques is the only means of accurately carrying out global mapping of impervious surfaces covering large areas. Optical imagery can capture surface reflectance characteristics, while synthetic aperture radar (SAR) images can be used to provide information on the structure and dielectric properties of surface materials. In addition, night-time light (NTL) imagery can detect the intensity of human activity and thus provide important a priori probabilities of the occurrence of impervious surfaces. In this study, we aimed to generate an accurate global impervious surface map at a resolution of 30-m for 2015 by combining Landsat-8 OLI optical images, Sentinel-1 SAR images and VIIRS NTL images based on the Google Earth Engine (GEE) platform. First, the global impervious and non-impervious training samples were automatically derived by combining the GlobeLand30 land-cover product with VIIRS NTL and MODIS enhanced vegetation index (EVI) imagery. Then, based on global training samples and multi-source and multi-temporal imagery, a random forest classifier was trained and used to generate corresponding impervious surface maps for each 5°×5° cell of a geographical grid. Finally, a global impervious surface map, produced by mosaicking numerous 5°×5° regional maps, was validated by interpretation samples and then compared with three existing impervious products (GlobeLand30, FROM_GLC and NUACI). The results indicated that the global impervious surface map produced using the proposed multi-source, multi-temporal random forest classification (MSMT_RF) method was the most accurate of the maps, having an overall accuracy of 96.6 % and kappa coefficient of 0.903 as against 92.5 % and 0.769 for FROM_GLC, 91.1 % and 0.717 for GlobeLand30, and 87.43 % and 0.585 for NUACI. Therefore, it is concluded that a global 30-m impervious surface map can accurately and efficiently be generated by the proposed MSMT_RF method based on the GEE platform. The global impervious surface map generated in this paper are available at https://doi.org/10.5281/zenodo.3505079 (Zhang et al., 2019).

Xiao Zhang 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

Xiao Zhang et al.

Data sets

Development of a global 30-m impervious surface map using multi-source and multi-temporal remote sensing datasets with the Google Earth Engine platform X. Zhang and L. Liu https://doi.org/10.5281/zenodo.3505079

Xiao Zhang et al.

Viewed

Total article views: 900 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
625 267 8 900 7 11
  • HTML: 625
  • PDF: 267
  • XML: 8
  • Total: 900
  • BibTeX: 7
  • EndNote: 11
Views and downloads (calculated since 21 Jan 2020)
Cumulative views and downloads (calculated since 21 Jan 2020)

Viewed (geographical distribution)

Total article views: 743 (including HTML, PDF, and XML) Thereof 742 with geography defined and 1 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Saved

No saved metrics found.

Discussed

No discussed metrics found.
Latest update: 06 Jul 2020
Download
Citation