摘要
基于珞珈一号夜间灯光数据和西安市能源统计数据,结合ArcGIS空间分析方法,运用高—低聚类模型,分区县对2018年西安市碳排放量进行空间化模拟,并对全市各区县碳排放强度进行计算和分类,研究西安市各区县碳排放量分布特性。结果表明:珞珈一号灯光数据与碳排放量存在较好的相关性,线性相关系数为0.7203,四次函数多项式的相关系数最高,为0.8435;在年度碳排放量上,西安市碳排放量呈现中心主城区高、周围县区低的空间分布特点,为聚类状态分布,且聚类结果在高值区域内聚类;全市低碳排放强度区县较多,存在少量高碳排放强度区县,对实现绿色发展模式还需要进一步调整产业结构。
Based on the night lighting data of Luojia 01 and the energy statistics of Xi'an,combined with the Arc⁃GIS spatial analysis method,this paper uses the high oligomeric model to spatially simulate the carbon emission of Xi'an in 2018,calculate and classify the carbon emission intensity of all districts and counties in the city,and study the distribution characteristics of carbon emission of all districts and counties in Xi'an.The results show that there is a good correlation between Luojia-01 light data and carbon emissions,the linear correlation coeffi⁃cient is 0.7203,and the correlation coefficient of quartic function polynomial is the highest,which is 0.8435;In terms of annual carbon emissions,Xi'an's carbon emissions show the spatial distribution characteristics of high in the central main urban area and low in the surrounding counties,which is a cluster distribution,and the clustering results are clustered in the high value area;There are many low-carbon emission intensity districts and counties in the city,and there are a few high-carbon emission intensity districts and counties.The industrial structure needs to be further adjusted to realize the green development model.
作者
张瑶
张宇鑫
张勇建
弓超
孔雅倩
ZHANG Yao;ZHANG Yuxin;ZHANG Yongjian;GONG Chao;KONG Yaqian(College of Mechanical and Electrical Engineering,Shaanxi University of Science and Technology,Xi'an 710021,China)
出处
《遥感技术与应用》
CSCD
北大核心
2023年第4期869-879,共11页
Remote Sensing Technology and Application
基金
国家自然科学基金项目“可再生能源环境下智能电网需求响应策略及商业运营机制研究”(51806133)。
关键词
夜间灯光数据
高-低聚类
空间化
碳排放强度
Night light data
High oligomers
Spatialization
Carbon emission intensity
