融合多源遥感数据的长株潭城市群碳排放时空差异分析

doi:10.13474/j.cnki.11-2246.2023.0011

测绘通报 ›› 2023, Vol. 0 ›› Issue (1): 65-70.doi: 10.13474/j.cnki.11-2246.2023.0011

融合多源遥感数据的长株潭城市群碳排放时空差异分析

王孟杰^1,2,3, 王艳军^1,2,3, 李少春^1,2,3, 林云浩^1,2,3, 滕菲^1,2,3, 蔡恒藩^1,2,3

1. 湖南科技大学测绘遥感信息工程湖南省重点实验室, 湖南湘潭 411201;
2. 湖南科技大学地理空间信息技术国家地方联合工程实验室, 湖南湘潭 411201;
3. 湖南科技大学地球科学与空间信息工程学院, 湖南湘潭 411201

收稿日期:2022-02-14 发布日期:2023-02-08
通讯作者: 王艳军。E-mail:wongyanjun@163.com
作者简介:王孟杰(1998-),男,硕士生,研究方向为遥感数据处理与地理建模。E-mail:541662474@qq.com
基金资助:
国家自然科学基金(41971423;31972951;41771462);湖南省自然科学基金(2020JJ3020;2020JJ5164);湖南省科技计划(2019RS2043;2019GK2132);湖南省研究生科研创新项目(CX20210991);湖南科技大学测绘遥感信息工程湖南省重点实验室开放基金(E22102;E22134)

Spatio-temporal difference analysis of carbon emissions in Chang-Zhu-Tan urban agglomeration based on multi-source remote sensing data

WANG Mengjie^1,2,3, WANG Yanjun^1,2,3, LI Shaochun^1,2,3, LIN Yunhao^1,2,3, TENG Fei^1,2,3, CAI Hengfan^1,2,3

1. Hunan Provincial Key Laboratory of Geo-Information Engineering in Surveying, Mapping and Remote Sensing, Hunan University of Science and Technology, Xiangtan 411201, China;
2. National-local Joint Engineering Laboratory of Geo-spatial Information Technology, Hunan University of Science and Technology, Xiangtan 411201, China;
3. School of Earth Science and Spatial Information Engineering, Hunan University of Science and Technology, Xiangtan 411201, China

Received:2022-02-14 Published:2023-02-08

摘要/Abstract

摘要： 碳排放时空分布监测与评估是城市可持续发展的重点研究课题之一。面向长株潭城市群碳排放的时空分布和差异分析,本文基于NPP-VIIRS夜间灯光影像和不透水面数据,结合县级碳排放数据,构建长株潭城市群碳排放估算模型,并定量分析了长株潭城市群碳排放时空分布特征及变化趋势。结果表明:①不透水面、夜间灯光均值和总值数据能够反映长株潭城市群区域碳排放水平;②2013—2017年长株潭城市群碳排放具有聚集性,主要分布在长株潭城市群北部的中间区域,碳排放区域逐年扩大但强度减弱;③2013—2017年长株潭城市群碳排放变化趋势为中心区域呈现负增长,城市扩张的边缘区域承接了部分碳排放量。本文融合多源遥感数据对2013—2017年长株潭城市群县级碳排放进行估算与监测分析,揭示了长株潭城市群碳排放时空分布变化规律,可为该区域碳减排和区域可持续发展提供科学参考。

关键词: 碳排放, NPP-VIIRS夜间灯光影像, 不透水面数据, 时空分布特征, 长株潭城市群

Abstract: The spatio-temporal distribution monitoring and evaluation of carbon emissions is one of the key research topics for sustainable urban development. For the analysis of the differences in the spatio-temporal distribution of carbon emissions in the Chang-Zhu-Tan urban agglomeration, this paper applies the NPP-VIIRS nighttime light images and impervious surface data, combined with county-level carbon emissions data to construct the carbon emission estimation model for the Chang-Zhu-Tan urban agglomeration, and analyzes the spatial and temporal distribution characteristics and changing trends of carbon emissions in this urban agglomeration. The results show that: ① The average and total value of nighttime lights and impervious surfaces data can better reflect the regional carbon emission level of the Chang-Zhu-Tan urban agglomeration.②From 2013 to 2017, the carbon emissions of the Chang-Zhu-Tan urban agglomeration were concentrated, mainly distributed in the middle area of the northern part. The carbon emissions areas expand year by year but the intensity weakened. ③ From 2013 to 2017, the changing trend of carbon emissions in the Chang-Zhu-Tan urban agglomeration was that the central area mainly has negative carbon emissions growth, while the peripheral areas have undertaken some carbon emissions. This study monitors the county-level carbon emissions of the Chang-Zhu-Tan urban agglomeration from 2013 to 2017 based on multi-source remote sensing data, and reveals the changes in the spatio-temporal distribution of carbon emissions, which can provide a scientific reference for carbon emission reduction and regional sustainable development.

Key words: carbon emissions, NPP-VIIRS nighttime light images, impervious surface data, spatio-temporal distribution features, Chang-Zhu-Tan urban agglomeration

中图分类号:

P237

王孟杰, 王艳军, 李少春, 林云浩, 滕菲, 蔡恒藩. 融合多源遥感数据的长株潭城市群碳排放时空差异分析[J]. 测绘通报, 2023, 0(1): 65-70.

WANG Mengjie, WANG Yanjun, LI Shaochun, LIN Yunhao, TENG Fei, CAI Hengfan. Spatio-temporal difference analysis of carbon emissions in Chang-Zhu-Tan urban agglomeration based on multi-source remote sensing data[J]. Bulletin of Surveying and Mapping, 2023, 0(1): 65-70.

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融合多源遥感数据的长株潭城市群碳排放时空差异分析

Spatio-temporal difference analysis of carbon emissions in Chang-Zhu-Tan urban agglomeration based on multi-source remote sensing data

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