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author:

Yuan, Y. (Yuan, Y..) [1] | Chen, Z. (Chen, Z..) [2] (Scholars:陈佐旗)

Indexed by:

ESCI Scopus

Abstract:

As human activities highly depend on the land resources and changed the land cover (LC) condition, the relationship between LC and nighttime light (NTL) intensity has been widely analyzed to support the foundation of NTL applications and help explain the drivers of urban economic development. However, previous studies always paid attention to the effect of each LC type on NTL intensity, with limited consideration of the joint effects of any two LC types. To fill this gap, this study measured the land cover spatial combination (LCSC) by using a spatial adjacency matrix, and then analyzed its impacts on NTL intensity based on an extreme gradient boosting (XGBoost) regression model with the assistant of sharpley additive explanations (SHAP) method. Our results presented that the LCSC can better (R2 of 82.4% and 98.1% in 2010 and 2020) explain the relationship between LC and NTL intensity with the traditional LC metrics (e.g., area and patch count), since the LCSC is much more sensitive to the diverse land functions. It is noteworthy that the impacts, as well as their dynamics, of LCSC between any two LC types on NTL intensity are various. LCSC associated with artificial surface contributed more to NTL intensity. In detail, the LCSC of water/wetland and artificial surface can increasingly promote the NTL intensity while the LCSC of grassland/forest and artificial surface has a decreasing or inverse U-shaped contribution to NTL intensity. Whereas LCSC associated with non-artificial surface were not conducive to the increase in NTL intensity due to high vegetation density. We also provided three implications to help further urbanization process and discussed the applications of LCSC. © 2023, The Author(s).

Keyword:

Land cover spatial combination Nighttime light intensity SHAP XGBoost

Community:

  • [ 1 ] [Yuan, Y.]Key Laboratory of Spatial Data Mining and Information Sharing of Ministry of Education, National & Local Joint Engineering Research Center of Satellite Geospatial Information Technology, Fuzhou University, Fuzhou, 350108, China
  • [ 2 ] [Yuan, Y.]The Academy of Digital China, Fuzhou University, Fuzhou, 350108, China
  • [ 3 ] [Chen, Z.]Key Laboratory of Spatial Data Mining and Information Sharing of Ministry of Education, National & Local Joint Engineering Research Center of Satellite Geospatial Information Technology, Fuzhou University, Fuzhou, 350108, China
  • [ 4 ] [Chen, Z.]The Academy of Digital China, Fuzhou University, Fuzhou, 350108, China

Reprint 's Address:

  • 陈佐旗

    [Chen, Z.]The Academy of Digital China, China

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Source :

Computational Urban Science

ISSN: 2730-6852

Year: 2023

Issue: 1

Volume: 3

2 . 6

JCR@2023

2 . 6 0 0

JCR@2023

JCR Journal Grade:2

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 1

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