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Analyzing the spatiotemporal differences of carbon emission in the Pearl River Delta using DMSP/OLS nighttime light images

  • role： First author第一作者
  • Affiliation：

    Hunan Provincial Key Laboratory of Geo-Information Engineering in Surveying, Mapping and Remote Sensing, Hunan University of Science and Technology, Xiangtan 411201, China

    National-local Joint Engineering Laboratory of Geo-spatial Information Technology, Hunan University of Science and Technology, Xiangtan 411201, China

  • Email：wongyanjun@163.com
  • Introduction：王艳军，研究方向为多源遥感数据处理与空间环境建模分析。E-mail：wongyanjun@163.com
WANG Yanjun12,  
  • Affiliation：

    Hunan Provincial Key Laboratory of Geo-Information Engineering in Surveying, Mapping and Remote Sensing, Hunan University of Science and Technology, Xiangtan 411201, China

    National-local Joint Engineering Laboratory of Geo-spatial Information Technology, Hunan University of Science and Technology, Xiangtan 411201, China

WANG Mengjie12,  
  • Affiliation：

    Hunan Provincial Key Laboratory of Geo-Information Engineering in Surveying, Mapping and Remote Sensing, Hunan University of Science and Technology, Xiangtan 411201, China

    National-local Joint Engineering Laboratory of Geo-spatial Information Technology, Hunan University of Science and Technology, Xiangtan 411201, China

LIU Lin,  
  • Affiliation：

    Hunan Provincial Key Laboratory of Geo-Information Engineering in Surveying, Mapping and Remote Sensing, Hunan University of Science and Technology, Xiangtan 411201, China

    National-local Joint Engineering Laboratory of Geo-spatial Information Technology, Hunan University of Science and Technology, Xiangtan 411201, China

LI Shaochun12,  
  • Affiliation：

    Hunan Provincial Key Laboratory of Geo-Information Engineering in Surveying, Mapping and Remote Sensing, Hunan University of Science and Technology, Xiangtan 411201, China

    National-local Joint Engineering Laboratory of Geo-spatial Information Technology, Hunan University of Science and Technology, Xiangtan 411201, China

LIN Yunhao12

resumen

The temporal and spatial distribution of carbon emissions and their heterogeneity are important topics in the study of ecological environment protection and climate change monitoring.Based on the fine analysis of the spatial distribution of carbon emissions in the Pearl River Delta urban agglomeration, this paper studies the spatial-temporal differences of carbon emissions in the area from 2000 to 2013 based on DMSP/OLS nighttime light images and land use data. This paper also reveals the spatial-temporal distribution characteristics, growth trend, and intensity trend of carbon emissions in different cities and land types.Results show the following. (1) The total carbon emissions of the Pearl River Delta urban agglomerations from 2000 to 2013 have been in the growth stage, but due to the 2008 financial crisis, the growth has turned from a high-speed growth stage to a slow growth stage. (2) The growth rate of per capita carbon emission intensity slowed down after the 2008 financial crisis. (3) The carbon emission intensity per unit of GDP experienced a small growth stage from 2005 to 2008, and then the overall trend is decreasing. (4) In terms of carbon emission intensity per square kilometer, the average carbon emission intensity of industrial and mining land transited from the growth stage before the 2008 financial crisis to the post-crisis reduction phase, while the average carbon emission intensity of urban land has been in a continuous growth phase. The carbon emissions of the Pearl River Delta urban agglomeration have obvious temporal and spatial differences before and after the 2008 financial crisis, and the continuous growth of carbon emissions from urban land will become a key issue for carbon emission reduction.This study can provide a scientific reference for carbon emission estimation and prediction, energy conservation and emission reduction, and ecological environment protection.

palabra clave

carbon emission;spatial and temporal distribution;DMSP/OLS nighttime light image;land use data;refinement

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