“双碳”目标下的湘西州土地利用碳排放变化及预测研究

doi:10.6046/zrzyyg.2024185

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摘要土地利用碳排放研究对实现国家“双碳”目标具有重要意义,进行湘西州土地利用碳排放变化及预测研究对湘西州地区制定“双碳”政策、平衡发展与保护提供理论参考。该文基于2000—2020年共5期土地利用数据对湘西州土地利用情况以及历史碳排放时空演变进行分析,运用脱钩模型以及对数平均迪氏指数(logarithmic mean Divisia index,LMDI)模型对其土地利用碳排放影响因素分解,并设定自然发展、耕地保护优先和生态保护优先3种土地利用情景,对2030年土地利用情况以及碳排放情况进行预测。结果表明: ①林地是湘西州最主要的土地类型,在土地转化方面,2000—2020年20 a间建设用地面积大幅增加,占用了大量林地和耕地,水域和草地的面积减少并转换成了林地和耕地,从碳排放角度,整体上碳汇用地向碳源用地转化; ②20 a间土地利用碳排放总量持续增加,建设用地是主要的碳源土地类型,林地是主要的碳汇土地类型; ③20 a间仅有花垣县碳排放量减少,其他县市均为增加,2010年后,原本碳排放增加地区碳排放量均开始减少,而其他地区碳排放量则出现不同程度的增加,建设用地碳排放量增加是引起地区碳排放量变化的关键因素; ④湘西州整体上一直保持弱脱钩效应,各县市主要是在弱脱钩和强脱钩状态之间变化,经济产出效应和能源效率效应是影响碳排放的主要因素; ⑤3种土地利用情景中总体土地格局未发生大的变化,碳排放量上,生态保护优先情景<自然发展情景<耕地保护优先情景,在未来建设用地仍然是引起整体碳排放量变化的主导因素,林地仍然是主要的碳汇来源。

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	夏思盈
	李静芝
	郑玉佳

关键词 ：土地利用, 碳排放, LMDI, CA-Markov, 情景预测, 湘西土家族苗族自治州

Abstract：

Investigating land-use-related carbon emissions (LCE) plays a vital role in achieving goals of peak carbon dioxide emissions and carbon neutrality (also referred to as the “dual carbon” goals). Research on the changes and prediction of LCE in Xiangxi Tujia and Miao Autonomous Prefecture (also referred to as the Xiangxi Prefecture) can provide a theoretical reference for the region to develop policies on the achievement of the “dual carbon” goals and for local balanced development and protection. Based on five sets of land use data from 2000 to 2020, this study analyzed the land use conditions and the spatiotemporal evolution of historical carbon emissions in Xiangxi Prefecture. The factors influencing LCE were determined using a decoupling model and a logarithmic mean Divisia index (LMDI) model. Furthermore, three land use scenarios were established: natural development, priority of cultivated land protection, and ecological protection priority. Using these scenarios, this study predicted the land use and carbon emissions in Xiangxi Prefecture in 2030. The results indicate that forest land represents the dominant land use type in Xiangxi Prefecture. Regarding land use transition, the period from 2000 to 2020 witnessed a significant increase in construction land, which encroached into substantial areas of forest land and cultivated land. Concurrently, water bodies and grassland decreased in area, being converted into forest land and cultivated land. From the perspective of carbon emissions, land use in the region exhibited a transformation from carbon sinks to carbon sources in general. During the 20-year span, the total LCE continued to increase. Construction land was identified as the primary land type as a carbon source, while forest land was the main land type as a carbon sink. Within the 20 years, carbon emissions decreased only in Huayuan County but increased in all other counties and cities. After 2010, the original regions with elevated carbon emissions showed a decrease in carbon emissions, while other regions witnessed growing carbon emissions to varying degrees. These regional changes in carbon emissions were largely attributed to the increased carbon emissions from construction land. Xiangxi Prefecture maintained a weak decoupling effect generally, with counties and cities fluctuating between weak decoupling and strong decoupling states. The economic output effect and energy efficiency effect served as the primary factors influencing carbon emissions. The overall land pattern remained relatively stable across the three scenarios. The carbon emissions of the three scenarios increased in the order of ecological protection priority, natural development, and priority of cultivated land protection. In the future, construction land will still represent the dominant factor causing overall changes in carbon emissions, while forest land will remain as the primary carbon sink.

Key words： land use carbon emission logarithmic mean Divisia index (LMDI) CA-Markov scenario forecasting Xiangxi Tujia and Miao Autonomous Prefecture

收稿日期: 2024-05-27 出版日期: 2025-09-03

ZTFLH:	TP79
	X820

基金资助:湘基金委自然科学基金面上项目“生态文明背景下湘西州社会经济-土地利用-生态系统交互耦合机制及国土空间格局优化调控研究”(2023JJ30023)

作者简介: 夏思盈(2002-),女,本科生,研究方向为城乡规划。Email: 19985352953@163.com。

引用本文:

夏思盈, 李静芝, 郑玉佳. “双碳”目标下的湘西州土地利用碳排放变化及预测研究[J]. 自然资源遥感, 2025, 37(4): 220-231.
XIA Siying, LI Jingzhi, ZHENG Yujia. Changes in land-use-related carbon emissions in Xiangxi and their prediction. Remote Sensing for Natural Resources, 2025, 37(4): 220-231.

链接本文:

https://www.gtzyyg.com/CN/10.6046/zrzyyg.2024185 或 https://www.gtzyyg.com/CN/Y2025/V37/I4/220

Fig.1 研究区位置及范围示意图

Tab.1 土地利用碳排放系数

Tab.2 能源碳排放系数

脱钩状态	脱钩类型	$M C$	$M G$	$T$
脱钩	强脱钩	<0	>0	<0
	弱脱钩	>0	>0	[0,0.8)
	衰退脱钩	<0	<0	>1.2
负脱钩	强负脱钩	>0	<0	T<0
	弱负脱钩	<0	<0	[0,0.8)
	扩张负脱钩	>0	>0	>1.2
连接	扩张连接	>0	>0	[0.8,1.2)
连接	衰退连接	<0	<0	[0.8,1.2)

Tab.3 脱钩类型分类

Fig.2 2000—2020年湘西州土地利用图

Tab.4 2000—2020年土地利用动态度

Fig.3 土地利用类型转移图

Tab.5 2000—2020年土地利用碳排放量

Tab.6 8个县市碳排放量

Fig.4 碳排放时空分布图

影响因素	2000— 2005年	2005— 2010年	2010— 2015年	2015— 2020年
$M C$	0.033	0.102	0.053	0.014
$M G$	0.829	1.470	0.647	0.401
$T$	0.040	0.069	0.082	0.036
脱钩类型	弱脱钩	弱脱钩	弱脱钩	弱脱钩

Tab.7 湘西州脱钩系数

地区	2000—2005年		2005—2010年		2010—2015年		2010—2015年
地区	$T$	状态	$T$	状态	$T$	状态	$T$	状态
吉首市	-0.071	强脱钩	0.341	弱脱钩	-0.037	强脱钩	-0.021	强脱钩
泸溪县	-0.116	强脱钩	0.168	弱脱钩	-0.314	强脱钩	-0.469	强脱钩
凤凰县	-0.052	强脱钩	-0.104	强脱钩	0.269	弱脱钩	0.262	弱脱钩
花垣县	-0.007	强脱钩	0.297	弱脱钩	-1.591	强脱钩	0.598	弱脱钩
保靖县	0.100	弱脱钩	-0.047	强脱钩	0.082	弱脱钩	0.113	弱脱钩
古丈县	-0.191	强脱钩	-0.096	强脱钩	3.044	扩张负脱钩	-0.265	强脱钩
永顺县	0.217	弱脱钩	-0.158	强脱钩	0.412	弱脱钩	-0.039	强脱钩
龙山县	0.230	弱脱钩	-0.111	强脱钩	0.565	弱脱钩	0.139	弱脱钩

Tab.8 各县市土地利用碳排放脱钩指数

Tab.9 土地利用碳排放LMDI因素分解

Tab.10 情景类型及转换原则

Fig.5 2030年情景预测土地利用占比

Tab.11 2030年情景预测土地利用情况

Tab.12 能源消耗预测检验

Tab.13 2030年情景预测土地利用碳排放情况

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