Electronic versions

DOI

  • Yu Zeng
    Central South University of Forestry and Technology
  • Shuguang Liu
    Central South University of Forestry and Technology
  • Sheng Huang
    Central South University of Forestry and Technology
  • Sopan Patil
  • Wenyuan Gao
    Ecological Environment Monitoring Center of Hunan Province
  • Hao Li
    Ecological Environment Monitoring Center of Hunan Province
Straw burning is a significant source of atmospheric pollutants, releasing particulate matter and trace gases. Capturing the characteristics of straw burning and understanding its influencing factors are important prerequisites for regulating straw burning. Based on the fire points detected by the Moderate-resolution Imaging Spectroradiometer (MODIS) in Hunan province, China, from 2010 to 2020, this study analyzed the spatiotemporal variations of straw burning and employed Geographically Weighted Regression (GWR) models to investigate the underlying forces driving straw burning. The results show that the spatiotemporal characteristics of straw burning in Hunan Province can be categorized into two distinct periods: 2010 to 2014 and 2015 to 2020. The period from 2010 to 2014 witnessed a rapid increase, while the period from 2015 to 2020 experienced fluctuating decreases. The shift is closely linked to the implementation of the straw burning ban policy in 2015. Spatially, the areas with a high number of fire points are primarily located in the southern regions, especially in the border regions between Chenzhou, Yongzhou, Hengyang, and Shaoyang cities. A significant change was found in the impact of economic development and human activity factors on straw burning before and after 2015. These factors include crop yield, Gross Domestic Product (GDP), and road network development. From the implementation of the straw burning ban policy, increases in GDP and settlement density will have a dampening effect on straw burning in a region. Straw burning locations may shift towards regions with relatively slow economic development. The results could serve as a foundation for decision-making to address the issue of straw burning.

Keywords

  • Geographically Weighted Regression models, Hunan province, driving forces, kernel density, straw burning
Original languageEnglish
JournalRemote Sensing
Volume16
Issue number8
Early online date18 Apr 2024
DOIs
Publication statusPublished - 18 Apr 2024
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