Material stock analysis of urban road from nighttime light data based on a bottom-up approach

Fei Zhao; Huixia Wu; Sijin Zhu; Hongyun Zeng; Zhifang Zhao; Xutao Yang; Sujin Zhang

doi:10.1016/j.envres.2023.115902

Material stock analysis of urban road from nighttime light data based on a bottom-up approach

Environ Res. 2023 Jul 1:228:115902. doi: 10.1016/j.envres.2023.115902. Epub 2023 Apr 13.

Authors

Fei Zhao¹, Huixia Wu², Sijin Zhu³, Hongyun Zeng⁴, Zhifang Zhao⁵, Xutao Yang⁶, Sujin Zhang⁷

Affiliations

¹ School of Earth Sciences, Yunnan University, Kunming, 650500, China; Engineering Research Center of Domestic High-resolution Satellite Remote Sensing Geology for Universities of Yunnan Province, Kunming, 650500, China. Electronic address: cartographer@ynu.edu.cn.
² Institute of International Rivers and Eco-Security, Yunnan University, Kunming, 650500, China. Electronic address: wuhuixia@mail.ynu.edu.cn.
³ Institute of International Rivers and Eco-Security, Yunnan University, Kunming, 650500, China. Electronic address: zhusijin@mail.ynu.edu.cn.
⁴ School of Earth Sciences, Yunnan University, Kunming, 650500, China. Electronic address: hy_zeng@ynu.edu.cn.
⁵ School of Earth Sciences, Yunnan University, Kunming, 650500, China; Engineering Research Center of Domestic High-resolution Satellite Remote Sensing Geology for Universities of Yunnan Province, Kunming, 650500, China. Electronic address: zhaozhifang@ynu.edu.cn.
⁶ School of Information Science and Engineering, Yunnan University, Kunming, 650500, China. Electronic address: yangxutao@ynu.edu.cn.
⁷ School of Earth Sciences, Yunnan University, Kunming, 650500, China. Electronic address: zsj@mail.ynu.edu.cn.

PMID: 37059324
DOI: 10.1016/j.envres.2023.115902

Abstract

In recent years, there has been an increasing focus on the dynamics of material stock, that is, the basis of material flow in the entire ecosystem. With the gradual improvement of the global road network encryption project, the uncontrolled extraction, processing, and transportation of raw materials impose serious resource concerns and environmental pressure. Quantifying material stocks enable governments to formulate scientific policies because socio-economic metabolism, including resource allocation, use, and waste recovery, can be systematically assessed. In this study, OpenStreetMap road network data were used to extract the urban road skeleton, and nighttime light images were divided by watershed to construct regression equations based on geographical location attributes. Resultantly, a generic road material stock estimation model was developed and applied to Kunming. We concluded that (1) the top three stocks are stone chips, macadam, and grit (total weight is 380 million tons), (2) the proportion of asphalt, mineral powder, lime, and fly ash is correspondingly similar, and (3) the unit area stock decreases as the road grade declines; therefore, the branch road has the lowest unit stock.

Keywords: Material stock analysis; Nighttime lights; OpenStreetMap; Remote sensing; Urban road system.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Coal Ash*
Ecosystem*
Transportation

Substances

Coal Ash