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author:

Wu, Bin (Wu, Bin.) [1] | Yang, Chengshu (Yang, Chengshu.) [2] | Chen, Zuoqi (Chen, Zuoqi.) [3] (Scholars:陈佐旗) | Wu, Qiusheng (Wu, Qiusheng.) [4] | Yu, Siyi (Yu, Siyi.) [5] | Wang, Congxiao (Wang, Congxiao.) [6] | Li, Qiaoxuan (Li, Qiaoxuan.) [7] | Wu, Jianping (Wu, Jianping.) [8] | Yu, Bailang (Yu, Bailang.) [9]

Indexed by:

SSCI EI SCIE

Abstract:

As spatial and socioeconomic processes are the two key aspects of urban development, revealing the relationship between these two key aspects is critical. Previous studies attempted to explain their correlation at the city or region level using built-up area metrics and nighttime light (NTL) data. However, more comprehensive studies on urban interior spatial characteristics and their relationship to NTL intensity are lacking in a three-dimension space. Using Luojia 1-01 nighttime light data, LiDAR digital surface model data, and other auxiliary data, this study applies an extreme gradient boosting regression model and Sharpley Additive exPlanations method to model and interpret the relationship between two-dimensional (2-D)/3-D landscape patterns and NTL intensity. Two study areas were selected to investigate the landscape-NTL relationship at the parcel and subdistrict levels. The major findings of this study include the following: 1) 2-D and 3-D urban landscape patterns have a close relationship with NTL intensity at the parcel and subdistrict scales; 2) the combinational metric of 2-D and 3-D landscape patterns has a stronger relationship with NTL intensity than either the 2-D or 3-D landscape metrics alone; 3) the correlations between most landscape metrics and NTL intensity are not simply positive or negative but change as metrics grow; and 4) the urban socioeconomic level is not only related to a single landscape metric sometimes but tends to the result of metrics interaction. These findings may help urban planners and government officials make more reasonable urban landscape planning policies under the goal of sustainable development.

Keyword:

extreme gradient boosting (XGBoost) regression Landscape metrics Land surface Measurement nighttime light (NTL) data Radiometry Remote sensing Roads three-dimensional (3-D) landscape pattern Urban areas urban development Vegetation mapping

Community:

  • [ 1 ] [Wu, Bin]East China Normal Univ, Key Lab Geog Informat Sci, Minist Educ, Shanghai 200241, Peoples R China
  • [ 2 ] [Yang, Chengshu]East China Normal Univ, Key Lab Geog Informat Sci, Minist Educ, Shanghai 200241, Peoples R China
  • [ 3 ] [Wang, Congxiao]East China Normal Univ, Key Lab Geog Informat Sci, Minist Educ, Shanghai 200241, Peoples R China
  • [ 4 ] [Li, Qiaoxuan]East China Normal Univ, Key Lab Geog Informat Sci, Minist Educ, Shanghai 200241, Peoples R China
  • [ 5 ] [Wu, Jianping]East China Normal Univ, Key Lab Geog Informat Sci, Minist Educ, Shanghai 200241, Peoples R China
  • [ 6 ] [Yu, Bailang]East China Normal Univ, Key Lab Geog Informat Sci, Minist Educ, Shanghai 200241, Peoples R China
  • [ 7 ] [Wu, Bin]East China Normal Univ, Sch Geog Sci, Shanghai 200241, Peoples R China
  • [ 8 ] [Yang, Chengshu]East China Normal Univ, Sch Geog Sci, Shanghai 200241, Peoples R China
  • [ 9 ] [Wang, Congxiao]East China Normal Univ, Sch Geog Sci, Shanghai 200241, Peoples R China
  • [ 10 ] [Li, Qiaoxuan]East China Normal Univ, Sch Geog Sci, Shanghai 200241, Peoples R China
  • [ 11 ] [Wu, Jianping]East China Normal Univ, Sch Geog Sci, Shanghai 200241, Peoples R China
  • [ 12 ] [Yu, Bailang]East China Normal Univ, Sch Geog Sci, Shanghai 200241, Peoples R China
  • [ 13 ] [Chen, Zuoqi]Fuzhou Univ, Minist Educ, Natl & Local Joint Engn Res Ctr Satellite Geospat, Key Lab Spatial Data Min & Informat Sharing, Fuzhou 35002, Peoples R China
  • [ 14 ] [Chen, Zuoqi]Fuzhou Univ, Acad Digital China, Fuzhou 35002, Peoples R China
  • [ 15 ] [Wu, Qiusheng]Univ Tennessee, Dept Geog, Knoxville, TN 37996 USA
  • [ 16 ] [Yu, Siyi]Shanghai Univ Sport, Sch Econ & Management, Shanghai 200438, Peoples R China

Reprint 's Address:

  • [Yu, Bailang]East China Normal Univ, Key Lab Geog Informat Sci, Minist Educ, Shanghai 200241, Peoples R China;;[Yu, Bailang]East China Normal Univ, Sch Geog Sci, Shanghai 200241, Peoples R China

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Source :

IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING

ISSN: 1939-1404

Year: 2022

Volume: 15

Page: 478-489

5 . 5

JCR@2022

4 . 7 0 0

JCR@2023

ESI Discipline: GEOSCIENCES;

ESI HC Threshold:51

JCR Journal Grade:1

CAS Journal Grade:3

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count: 8

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 5

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