An Improved Vegetation Adjusted Nighttime Light Urban Index and Its Application in Quantifying Spatiotemporal Dynamics of Carbon Emissions in China

Remote Sensing

Cheng Huang¹  Xing Meng¹  Ji Han² 

[1] School of Geographical Sciences, East China Normal University, Dongchuan Road 500, Shanghai 200241, China;Shanghai Key Laboratory for Urban Ecological Processes and Eco-Restoration, School of Ecological and Environmental Sciences, East China Normal University, Dongchuan Road 500, Shanghai 200241, China;

关键词: nighttime light;    Vegetation Adjust NTL Urban Index (VANUI);    spatiotemporal pattern;    CO2 emissions;    China;   

DOI  :  10.3390/rs9080829

来源: DOAJ

【 摘 要 】

Nighttime Light (NTL) has been widely used as a proxy of many socio-environmental issues. However, the limited range of sensor radiance of NTL prevents its further application and estimation accuracy. To improve the performance, we developed an improved Vegetation Adjusted Nighttime light Urban Index (VANUI) through fusing multi-year NTL with population density, the Normalized Difference Vegetation Index and water body data and applied it to fine-scaled carbon emission analysis in China. The results proved that our proposed index could reflect more spatial variation of human activities. It is also prominent in reducing the carbon modeling error at the inter-city level and distinguishing the emission heterogeneity at the intra-city level. Between 1995 and 2013, CO2 emissions increased significantly in China, but were distributed unevenly in space with high density emissions mainly located in metropolitan areas and provincial capitals. In addition to Beijing-Tianjin-Hebei, the Yangzi River Delta and the Pearl River Delta, the Shandong Peninsula has become a new emission hotspot that needs special attention in carbon mitigation. The improved VANUI and its application to the carbon emission issue not only broadened our understanding of the spatiotemporal dynamics of fine-scaled CO2 emission, but also provided implications for low-carbon and sustainable development plans.

【 授权许可】

Unknown