Remote Sensing (Mar 2023)

Spatial Correlations of Land Use Carbon Emissions in Shandong Peninsula Urban Agglomeration: A Perspective from City Level Using Remote Sensing Data

  • Lin Zhao,
  • Chuan-hao Yang,
  • Yu-chen Zhao,
  • Qian Wang,
  • Qi-peng Zhang

DOI
https://doi.org/10.3390/rs15061488
Journal volume & issue
Vol. 15, no. 6
p. 1488

Abstract

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The spatial and temporal characteristics of land use carbon emissions are relevant to the sustainable use of land resources. Although spatial and temporal studies have been conducted on land use carbon emissions, the spatial correlation of land use carbon emissions at the city level still requires further research. Here, we estimated the distribution of carbon emissions at the city level in Shandong Peninsula urban agglomeration in spatial and temporal terms based on land use remote sensing data and fossil energy consumption data during 2000–2019. The results showed that the land use change in the 16 cities in the study area was the conversion of cropland to construction land. Carbon emissions from land use had an upward trend for all 16 cities overall during the period of 2000–2019, but the incremental carbon emissions trended downward after 2010. Among them, Jinan and Qingdao had higher carbon emissions than other cities. In addition, we also found that land use carbon emissions at the city level were characterized by stochasticity, while per capita carbon emissions displayed geospatial aggregation. Among them, Yantai displayed a spatial pattern of high–high clustering of carbon emissions, while Jining presented a spatial pattern of low–low clustering in terms of land-average carbon emissions and carbon emissions per capita during 2000–2019. The results of the study are important for guiding the achievement of urban carbon emission reduction and carbon neutrality targets at the city level.

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