The Relationship between Urban 2-D/3-D Landscape Pattern and Nighttime Light Intensity

Bin Wu, Chengshu Yang, Zuoqi Chen, Qiusheng Wu, Siyi Yu, Congxiao Wang, Qiaoxuan Li, Jianping Wu, Bailang Yu

Research output: Contribution to journalArticlepeer-review

20 Scopus citations

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.

Original languageEnglish
Pages (from-to)478-489
Number of pages12
JournalIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Volume15
DOIs
StatePublished - 2022

Keywords

  • Landscape metrics
  • extreme gradient boosting (XGBoost) regression
  • nighttime light (NTL) data
  • three-dimensional (3-D) landscape pattern
  • urban development

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