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    Spatio-temporal evolution and spatial correlation of carbon emissions in Guiyang City based on land use change
    ZHOU Wei-ting
    HUBEI AGRICULTURAL SCIENCES    2023, 62 (5): 8-13.   DOI: 10.14088/j.cnki.issn0439-8114.2023.05.003
    Abstract358)      PDF (3383KB)(309)       Save
    Taking Guiyang City as an example, based on the 30 m land cover remote sensing data from 2000 to 2020, the land use transfer matrix, carbon emission calculation model and spatial auto-correlation were used to analyze the spatio-temporal evolution and spatial correlation of land use types and carbon emissions in Guiyang City, to provide reference for the realization of regional “dual carbon” goal and the development of the green and low-carbon economic model. The results showed that from 2000 to 2020, the total carbon emission of land use in Guiyang City had a rapid growth rate on the whole, and the carbon source showed an increasing trend. The carbon source mainly consisted of construction land, and the carbon sink mainly consisted of forest land with only slight fluctuation. In terms of the spatial differences of carbon emissions from 2000 to 2020, the heavy carbon emission areas were mainly concentrated in Yunyan District and Nanming District, and showed a westward expansion trend; the moderate carbon emission areas were mainly concentrated in the southwest and northeast wings of Guiyang City, and showed a northeast shift trend. In terms of spatial correlation, the carbon emission of land use in Guiyang City showed a positive spatial correlation in 2000, and a negative spatial correlation with increasing correlation from 2005 to 2020. The pattern of land use carbon emission in Guiyang City was not optimistic, and the structure and intensity of land use were in urgent need of adjustment. Therefore, feasible low-carbon emission reduction policies should be formulated according to the actual situation of Guiyang City to promote the low-carbon, efficient and sustainable utilization of regional land resources.
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    Analysis of influencing factors of farmland fragmentation based on geographical detector: A case study of Guangzhou City
    CHEN Jun-tao, LIN Jin-yao
    HUBEI AGRICULTURAL SCIENCES    2023, 62 (5): 14-21.   DOI: 10.14088/j.cnki.issn0439-8114.2023.05.004
    Abstract338)      PDF (2192KB)(312)       Save
    Guangzhou was selected as the research area. The landscape pattern index method, comprehensive index method and principal component analysis method were used to construct the evaluation system of farmland fragmentation degree, and the comprehensive index of farmland fragmentation degree of each town and street unit in the region was calculated. Ten quantifiable factors of natural conditions and human social activity were selected, and the geographical detector model was used to detect the impact of 10 factors on farmland fragmentation. The results showed that all 10 factors were the influencing factors of farmland fragmentation in Guangzhou City. The influence of the single factor on farmland fragmentation from strong to weak was urban administrative center distance factor, temperature factor, GDP factor, slope factor and altitude factor, precipitation factor, construction land distance factor, road distance factor, water body distance factor and population density factor. The interaction of any two of the 10 factors showed two-factor enhancement or nonlinear enhancement. Based on the research conclusions, some suggestions were put forward to provide valuable decision-making reference for reducing the level of farmland fragmentation in Guangzhou City.
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