Scale effect analysis of carbon emission simulation based on NPP-VIIRS images in Guangdong province

doi:10.13474/j.cnki.11-2246.2021.333

Abstract

Abstract: Carbon emission estimation is one of the most important fields of energy conservation and global climate change research. NPP-VIIRS night light image can reflect the intensity of human activities and is widely used in the spatial estimation and analysis of carbon emission. This paper constructs and compares the fitting models of energy consumption and carbon emissions estimation in Guangdong province based on NPP-VIIRS night light images in 2015, and focused on the scale effect of NPP-VIIRS images, and discussed the accuracy of model results at 500 m, 1000 m, 1500 m and 2000 m resolution. The results showed that:①The quadratic polynomial fitting model is a better method for carbon emission estimation, and the fitting results of 21 cities in Guangdong province are quite different. ②The root mean square error of Guangdong province carbon emission estimation results from NPP-VIIRS nighttime light image with 1000 m resolution is the smallest, and the absolute error of 2000 m resolution is smaller, and the model operation efficiency is improved by scaling up. ③Estimation results of carbon emissions show fluctuation from night light images with different spatial resolutions increasing continuously from 500 m to 2000 m at an interval of 100 m and tend to balance at the resolution of 1000 m. This paper analyzes the carbon emission estimation model of Guangdong province based on NPP-VIIRS night light images, and reveals the scale effect rules of different spatial resolution images, which can provide a reference for spatial scale optimization and result refinement of carbon emission estimation of night light images.

Key words: carbon emission, NPP-VIIRS nighttime light image, spatial resolution, scale effect, carbon emission estimation

CLC Number:

P237

WANG Yanjun, WANG Mengjie, LI Shaochun, LIN Yunhao. Scale effect analysis of carbon emission simulation based on NPP-VIIRS images in Guangdong province[J]. Bulletin of Surveying and Mapping, 2021, 0(11): 25-30.

References

[1] 赵荣钦,黄贤金,钟太洋.中国不同产业空间的碳排放强度与碳足迹分析[J].地理学报,2010,65(9):1048-1057.
[2] 江威,曾海鹰.能源消费、碳排放与经济增长的关系研究——以湖北省为例[J].生产力研究,2019(11):29-33.
[3] LI X, XU H M, CHEN X L, et al. Potential of NPP-VIIRS nighttime light imagery for modeling the regional economy of China[J]. Remote Sensing, 2013, 5(6):3057-3081.
[4] 卓莉,陈晋,史培军,等.基于夜间灯光数据的中国人口密度模拟[J].地理学报,2005,60(2):266-276.
[5] ZHOU Y Y, SMITH S J, ELVIDGE C D, et al. A cluster-based method to map urban area from DMSP/OLS nightlights[J]. Remote Sensing of Environment,2014, 147:173-185.
[6] WEN J Q, CHUAI X W, LI S C, et al. Spatial heterog-eneity of the carbon emission effect resulting from urban expansion among three coastal agglomerations in China[J]. Sustainability, 2019, 11(17):4590-4610.
[7] 肖建华,邬明权,周世健,等. "一带一路"重大铁路建设生态与经济影响遥感监测[J].科学技术与工程,2020,20(11):4605-4613.
[8] GHOSH T, ELVIDGE C D, SUTTON P C, et al. Creating a global grid of distributed fossil fuel CO₂ emissions from nighttime satellite imagery[J]. Energies, 2010, 3(12):1895-1913.
[9] SHI K F, CHEN Y, YU B L, et al. Modeling spatiot-emporal CO₂ (carbon dioxide) emission dynamics in China from DMSP-OLS nighttime stable light data using panel data analysis[J]. Applied Energy,2016, 168:523-533.
[10] 张永年,潘竟虎.基于DMSP/OLS数据的中国碳排放时空模拟与分异格局[J]. 中国环境科学, 2019,39(4):1436-1446.
[11] 苏泳娴,陈修治,叶玉瑶,等.基于夜间灯光数据的中国能源消费碳排放特征及机理[J]. 地理学报, 2013,68(11):1513-1526.
[12] 陈小勇,林鹏.我国红树植物分布的空间自相关分析[J].华东师范大学学报(自然科学版),2000(3):104-109.
[13] 苏理宏,李小文,黄裕霞.遥感尺度问题研究进展[J].地球科学进展,2001,16(4):544-548.
[14] MEENTEMEYER V. Geographical perspectives of space, time, and scale[J]. Landscape Ecology, 1989, 3(3-4):163-173.
[15] 陈世莉,陈浩辉,李郇.夜间灯光数据在不同尺度对社会经济活动的预测[J].地理科学,2020,40(9):1476-1483.
[16] 明冬萍,王群,杨建宇.遥感影像空间尺度特性与最佳空间分辨率选择[J].遥感学报,2008,12(4):529-537.
[17] 温兆飞,张树清,白静,等.农田景观空间异质性分析及遥感监测最优尺度选择——以三江平原为例[J].地理学报,2012,67(3):346-356.