CHEN Yanlin, HAN Bo, JIN Xiaobin, ZHANG Yan. Analysis of the cropland productivity change and the impact of land consolidation in the Yangtze River Economic Zone[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2023, 39(2): 182-193. DOI: 10.11975/j.issn.1002-6819.202210144
    Citation: CHEN Yanlin, HAN Bo, JIN Xiaobin, ZHANG Yan. Analysis of the cropland productivity change and the impact of land consolidation in the Yangtze River Economic Zone[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2023, 39(2): 182-193. DOI: 10.11975/j.issn.1002-6819.202210144

    Analysis of the cropland productivity change and the impact of land consolidation in the Yangtze River Economic Zone

    • Abstract: Cropland productivity can be greatly improved to ensure national food security in China, particularly under the quantitative constraints of farmland resources. Among them, land consolidation can be an important way for the high cropland productivity in recent years. But, the spatial differentiation patterns of land consolidation can pose a great impact on cropland productivity in large-scale regions. Taking the Yangtze River Economic Zone as an example, this study aims to determine the impact of land consolidation on cropland productivity change using MODIS-EVI remote sensing data. The S-G filtering and threshold were used to extract the cropland productivity (i.e., single-crops productivity, the first and second season productivity of double crops) in the study area from 2001-2017. Then, 80 920 projects of land consolidation were collected (including land development, consolidation, and reclamation projects) with the location and attribute information using the national rural land consolidation monitoring and supervision system. The contribution rate of land consolidation was further analyzed for the cropland productivity in counties using a geographically weighted regression model, together with the spatial differentiation of the impact degree. Finally, the impact of land consolidation was spatially partitioned on the cropland productivity using the hierarchical clustering model. The optimization strategies of land consolidation were also proposed for each zone, according to the cropland utilization characteristics. The results showed that: 1) There was a significant spatial divergence trend of cropland productivity. Specifically, the productivity of single-crops and double-crops in the first and second seasons presented a decelerating increase, an accelerating increase, and an increase followed by a decrease, respectively, with the largest increase in the productivity in the upper reaches of the Yangtze River. There was a significant decrease in the productivity of the single-crops and the second season productivity of double-crops in the lower reaches; 2) The average contribution of land development, allocation, and reclamation to the change of single-crops productivity were 7.38%, 4.44%, and 2.80%, respectively; the average contribution to the change of first season productivity of double-crops were 6.21%, 5.04%, and 3.34%, respectively; and the average contribution to the change of second season productivity of double-crops were 7.10%, 7.15%, and 3.69%, respectively. 3) The Yangtze River economic belt was divided into the consolidation areas of the southwest mountain, the Sichuan basin, the southern hilly, and the lower Yangtze River plain, according to the cropland productivity and the impact mechanism of land consolidation. A better optimization was also provided for the land consolidation of each region. In addition, some findings were also needed to further explain: firstly, the land allocation was the least effective to promote cropland productivity improvement among all types of projects. The reason behind this issue can be expected to continue. Another phenomenon is that the second season productivity of double-crops was generally negatively correlated with the land consolidation indicators, has the implementation of land consolidation accelerated the phenomenon of "double to single"? What is the mechanism behind this phenomenon? Finally, it is very necessary to improve the efficiency of the causal inference using a geographically weighted regression model.
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