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2012年至2021年中国二氧化碳排放的多尺度时空分析基于核正常化差异植被指数和夜间照明数据

Rui Liu^1,2,3, Decheng Wang^4,5, Xirong Guo⁶

¹State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu, 610059, China.

Environmental monitoring and assessment

|May 14, 2025

概括

本研究引入了一种新方法,将植被和夜间光线数据结合起来,以高分辨率绘制中国二氧化碳 (CE) 排放的地图. 结果显示CE分布不均,西北地区成为高排放地区.

科学领域:

环境科学环境科学
遥感遥感遥感遥感
地理空间分析的研究.

背景情况:

准确了解二氧化碳排放 (CE) 空间分布对于实现碳中和目标至关重要.
现有的研究往往缺乏在更细微的尺度上对CE的详细时空分析.

研究的目的:

开发一种新的方法,以高分辨率地图中国的CE.
分析2012年至2021年中国CE的时空空间动态.

主要方法:

整合了内核规范差异植被指数 (kNDVI) 和NPP-VIIRS夜间照明数据 (NTL) 来创建内核植被夜间照明指数 (kVNTL).
应用地理和时间加权回归 (GTWR) 模型用于250m分辨率的CE图生成.
使用了核心密度,趋势,热点和定向分布分析.

主要成果:

与单独的NTL数据相比,拟议的kVNTL指数显著提高了CE估计的准确性.
中国的CE在2012年至2021年间呈现不均的分布和显著的集群.
区域互动和地理位置被确定为影响CE模式的关键因素.
中国西北地区显示出成为高CE地区的趋势.

结论:

新的kVNTL-GTWR方法为高分辨率的CE映射提供了一个强大的方法.
时空空间分析揭示了对中国的EC动态和地区差异的关键见解.
研究结果支持有针对性的战略,以实现碳峰值和碳中和目标.

关键词:

碳排放地图的绘制肯德维 (KNDVI) 的意思是核电站 - 维尔斯遥感是一种远程传感.空间聚类空间聚类

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