Index and zoning for green and low-carbon transition of cultivated land utilization in main grain-producing areas of China

FU Haiyue; WU Shudong; JIANG Penghui

doi:10.11975/j.issn.1002-6819.202304087

Volume 39 Issue 23

Dec. 2023

Turn off MathJax

Article Contents

Abstract

References

Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE) > 2023 > 39(23): 238-246. > DOI: 10.11975/j.issn.1002-6819.202304087

FU Haiyue, WU Shudong, JIANG Penghui. Index and zoning for green and low-carbon transition of cultivated land utilization in main grain-producing areas of China[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2023, 39(23): 238-246. DOI: 10.11975/j.issn.1002-6819.202304087

Citation:

PDF (851 KB)

Index and zoning for green and low-carbon transition of cultivated land utilization in main grain-producing areas of China

FU Haiyue^{1, 2, 3,},
WU Shudong¹,
JIANG Penghui^{1, 2, ,}

1.
College of Public Administration, Nanjing Agricultural University, Nanjing 210095, China
2.
China Resources & Environment and College of Public Administration Development Academy, Nanjing Agricultural University, Nanjing 210095, China
3.
Key Laboratory of Urban Land Resources Monitoring and Simulation, Ministry of Natural Resources, Shenzhen 518034, China

More Information

Received Date: April 11, 2023
Revised Date: September 14, 2023
Available Online: January 29, 2024

Graphical Abstract

Abstract

Abstract

The cultivated land environment has imposed the most serious constraints on national food and ecological security. The green and low-carbon transformation of cultivated land is of great significance to promote sustainable agriculture under the "dual carbon" goals. In this study, an input-output analysis model was established for the green and low-carbon utilization of cultivated land. The transition index was also constructed for the green and low-carbon utilization of cultivated land, according to a comparative analysis of the "status quo target". The governance areas were then grouped for the various regulation paths. A case study was conducted on 171 prefecture-level cities in the main grain-producing areas of China. Firstly, the temporal and spatial characteristics were analyzed for the green and low-carbon utilization efficiency of cultivated land from 2000 to 2020. Secondly, the indicators were predicted for the green and low-carbon utilization of cultivated land in 2030. Finally, 171 prefecture-level cities were grouped for the differentiated suggestions, according to the green and low-carbon index of cultivated land. The results indicate that there was an increasing trend in the green and low-carbon utilization level of cultivated land in the main grain-producing areas from 2000 to 2020, indicating a spatial pattern with the high in the north and the low in the south. The improved level was predicted in the green and low-carbon of cultivated land in 2030, but there were significant differences in the growth rates among regions. Strict control zones for pollution reduction and carbon reduction, control zones, and protection zones, as well as the pollution and carbon sequestration protection zones accounted for 9.36%, 39.77%, 10.52%, and 40.35% of the main grain production areas, respectively, which were distributed mainly in the southern, central and southern regions, Yantai city in Shandong Province, and cities along the eastern coast, Inner Mongolia, and Sichuan Province. Some suggestions were proposed to strengthen the efficient allocation of farmland production factors, according to the socio-economic conditions of each region. The farmland carbon sequestration and emission reduction technologies can be utilized to implement green and low-carbon production practices. Differentiated guidance of green and low-carbon transition was established for the carbon sink systems of farmland. The finding can provide strong reference and decision-making support to explore the path of green and low-carbon utilization transition of cultivated land. Differentiated regulation suggestions are also addressed to promote sustainable land use and green transition in modern agriculture.
- cultivated land,
- land use,
- index of green and low-carbon transition,
- zoning governance,
- main grain producing areas,
- sustainable development

FullText(HTML)

References (41)

References

[1]	郧文聚,吴克宁,张小丹. 中国耕地健康问题及防治对策[J]. 中国发展,2019,19(4):34-37. YUN Wenju, WU Kening, ZHANG Xiaodan. Health problems and prevention countermeasures of cultivated land in China[J]. China Development, 2019, 19(4): 34-37. (in Chinese with English abstract)
[2]	LU H, XIE H L, LV T G, et al. Determinants of cultivated land recuperation in ecologically damaged areas in China[J]. Land Use Policy, 2019, 81(1): 160-166.
[3]	张琳,张凤荣,安萍莉,等. 不同经济发展水平下的耕地利用集约度及其变化规律比较研究[J]. 农业工程学报,2008,24(1):108-112. ZHANG Lin, ZHANG Fengrong, AN Pingli, et al. Comparative study of cultivated land use intensive degree and its change law at different economic levels[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2008, 24(1): 108-112. (in Chinese with English abstract)
[4]	张荣天,焦华富. 中国省际耕地利用效率时空格局分异与机制分析[J]. 农业工程学报,2015,31(2):277-287. ZHANG Rongtian, JIAO Huafu. Spatial-temporal pattern differentiation and its mechanism analysis of using efficiency for provincial cultivated land in China[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2015, 31(2): 277-287. (in Chinese with English abstract)
[5]	陈丹玲,卢新海,匡兵. 基于随机森林的耕地利用效率测度模型构建及其应用[J]. 自然资源学报,2019,34(6):1331-1344. doi: 10.31497/zrzyxb.20190618 CHEN Danling, LU Xinhai, KUANG Bing. Measurement of cultivated land utilization efficiency: Construction and application of random forest[J]. Journal of Natural Resources, 2019, 34(6): 1331-1344. (in Chinese with English abstract) doi: 10.31497/zrzyxb.20190618
[6]	封永刚,彭珏,邓宗兵,等. 面源污染、碳排放双重视角下中国耕地利用效率的时空分异[J]. 中国人口·资源与环境,2015,25(8):18-25. FENG Yonggang, PENG Jue, DENG Zongbing, et al. Spatial-temporal variation of cultivated land’s utilization efficiency in China based on the dual perspective of non-point source pollution and carbon emission[J]. China Population, Resources and Environment, 2015, 25(8): 18-25. (in Chinese with English abstract)
[7]	王海力,韩光中,谢贤健. 基于DEA模型的西南地区耕地利用效率时空格局演变及影响因素分析[J]. 长江流域资源与环境,2018,27(12):2784-2795. WANG Haili, HAN Guangzhong, XIE Xianjian. Spatiotemporal pattern evolvement based on the DEA model and its driving factors of arable land utilization efficiency of the southwest region in China[J]. Resources and Environment in the Yangtze Basin, 2018, 27(12): 2784-2795. (in Chinese with English abstract)
[8]	刘蒙罢,张安录,文高辉. 长江中下游粮食主产区耕地利用生态效率时空格局与演变趋势[J]. 中国土地科学,2021,35(2):50-60. LIU Mengba, ZHANG Anlu, WENG Gaohui. Temporal and spatial pattern and evolution trend of cultivated land use ecological efficiency in the main grain producing areas in the Lower Yangtze Region[J]. China Land Science, 2021, 35(2): 50-60. (in Chinese with English abstract)
[9]	吴昊玥,孟越,黄瀚蛟,等. 中国耕地低碳利用绩效测算与时空分异[J]. 自然资源学报,2022,37(5):1148-1163. doi: 10.31497/zrzyxb.20220504 WU Haoyue, MENG Yue, HUANG Hanjiao, et al. Estimation and spatio-temporal divergence of the low-carbon performance of cropland use in China[J]. Journal of Natural Resources, 2022, 37(5): 1148-1163. (in Chinese with English abstract) doi: 10.31497/zrzyxb.20220504
[10]	柯楠,卢新海,匡兵,等. 碳中和目标下中国耕地绿色低碳利用的区域差异与影响因素[J]. 中国土地科学,2021,35(8):67-76. KE Nan, LU Xinhai, KUANG Bing, et al. Regional ifferences and influencing factors of green and low-carbon utilization of cultivated land under the carbon neutrality target in China[J]. China Land Science, 2021, 35(8): 67-76. (in Chinese with English abstract)
[11]	ZOMER R J, BOSSIO D A, SOMMER R, VERCHOT L V. Global sequestration potential of increased organic carbon in cropland soils[J]. Scientific Reports, 2017, 7(1): 15554. doi: 10.1038/s41598-017-15794-8
[12]	匡兵,卢新海,韩璟,等. 考虑碳排放的粮食主产区耕地利用效率区域差异与变化[J]. 农业工程学报,2018,34(11):1-8. doi: 10.11975/j.issn.1002-6819.2018.11.001 KUANG Bing, LU Xinhai, HAN Jing, et al. Regional differences and dynamic evolution of cultivated land use efficiency in major grain producing areas in low carbon perspective[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2018, 34(11): 1-8. (in Chinese with English abstract) doi: 10.11975/j.issn.1002-6819.2018.11.001
[13]	杨朔,于文海,李世平. 基于DEA非有效改进的陕西省耕地生产效率研究[J]. 中国土地科学,2013,27(10):62-68. YANG Shuo, YU Wenhai, LI Shiping. Study on the non-effective improvement of productive efficiency of cultivated land in Shaanxi Province based on DEA[J]. China Land Science, 2013, 27(10): 62-68. (in Chinese with English abstract)
[14]	XIE H L, CHEN Q R, WANG W , et al. Analyzing the green efficiency of arable land use in China[J]. Technological Forecasting and Social Change, 2018, 133(3): 15-28.
[15]	柯善淦,崔海莹,卢新海,等. 耕地利用绿色转型的时空格局及其驱动机制研究——以湖北省为例[J]. 中国土地科学,2021,35(12):64-74. KE Shangan, CUI Haiying, LU Xinhai, et al. Research on the spatial-temporal pattern and mechanisms of green transition of farmland use: A case of Hubei Province[J]. China Land Science, 2021, 35(12): 64-74. (in Chinese with English abstract)
[16]	匡兵,范翔宇,卢新海. 中国耕地利用绿色转型效率的时空分异特征及其影响因素[J]. 农业工程学报,2021,37(21):269-277. KUANG Bing, FAN Xiangyu, LU Xinhai. Spatial-temporal differentiation characteristics of the efficiency of green transformation of cultivated land use and its affecting factors in China[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2021, 37(21): 269-277. (in Chinese with English abstract)
[17]	张文慧,吕晓,史洋洋,等. 黄河流域土地利用转型图谱特征[J]. 中国土地科学,2020,34(8):80-88. ZHANG Wenhui, LV Xiao, SHI Yangyang, et al. Graphic characteristics of land use transition in the Yellow River Basin[J]. China Land Science, 2020, 34(8): 80-88. (in Chinese with English abstract)
[18]	李全峰,胡守庚,瞿诗进. 1990—2015 年长江中游地区耕地利用转型时空特征[J]. 地理研究,2017,36(8):1489-1502. LI Quanfeng, HU Shougeng, QU Shijin. Spatiotemporal characteristics of cultivated land use transition in the Middle Yangtze River from 1990 to 2015[J]. Geographical Research, 2017, 36(8): 1489-1502. (in Chinese with English abstract)
[19]	龙花楼,戈大专,王介勇. 土地利用转型与乡村转型发展耦合研究进展及展望[J]. 地理学报,2019,74(12):2547-2559. LONG Hualou, GE Dazhuan, WANG Jieyong. Progress and prospects of the coupling research on land use transitions and rural transformation development[J]. Acta Geographica Sinica, 2019, 74(12): 2547-2559. (in Chinese with English abstract)
[20]	祖健,郝晋珉,陈丽,等. 耕地数量、质量、生态三位一体保护内涵及路径探析[J]. 中国农业大学学报,2018,23(7):84-95. ZU Jian, HAO Jinmin, CHEN Li, et al. Analysis on trinity connotation and approach to protect quality and ecology of cultivated land[J]. Journal of China Agricultural University, 2018, 23(7): 84-95. (in Chinese with English abstract)
[21]	杨忍,刘彦随,龙花楼,等. 基于格网的农村居民点用地时空特征及空间指向性的地理要素识别——以环渤海地区为例[J]. 地理研究,2015,34(6):1077-1087. YANG Ren, LIU Yansui, LONG Hualou, et al. Spatial-temporal characteristics of rural residential land use change and spatial directivity identification based on grid in the Bohai Rim in China[J]. Geographical Research, 2015, 34(6): 1077-1087. (in Chinese with English abstract)
[22]	廖柳文,龙花楼,马恩朴. 乡村劳动力要素变动与耕地利用转型[J]. 经济地理,2021,41(2):148-155. LIAO Liuwen, LONG Hualou, MA Enpu. Rural labor change and farmland use transition[J]. Economic Geography, 2021, 41(2): 148-155. (in Chinese with English abstract)
[23]	宋小青,李心怡. 区域耕地利用功能转型的理论解释与实证[J]. 地理学报,2019,74(5):992-1010. SONG Xiaoqing, LI Xinyi. Theoretical explanation and case study of regional cultivated land use function transition[J]. Acta Geographica Sinica, 2019, 74(5): 992-1010. (in Chinese with English abstract)
[24]	卢新海,唐一峰,易家林,等. 基于空间计量模型的耕地利用转型对农业经济增长影响研究[J]. 中国土地科学,2019,33(6):53-61. LU Xinhai, TANG Yifeng, YI Jialin, et al. Study on the impact of cultivated land use transition on agricultural economic growth based on spatial econometric model[J]. China Land Science, 2019, 33(6): 53-61. (in Chinese with English abstract)
[25]	杨斌,杨俊,王占岐,等. 长江经济带耕地绿色低碳利用的时空格局及其成因分析[J]. 中国土地科学,2022,36(10):63-71. YANG Bin, YANG Jun, WANG Zhanqi, et al. Spatial-temporal pattern and attribution of cultivated land green and low-carbon utilization in the Yangtze River economic belt[J]. China Land Science, 2022, 36(10): 63-71. (in Chinese with English abstract)
[26]	童锐,王永强. 农产品基地认证促进农户农药安全使用了吗?——基于陕西省苹果种植户的实证研究[J]. 生态经济,2019,35(11):112-116. TONG Rui, WANG Yongqiang. Does agro-product certification promote the use of unrestricted pesticides: Based on the empirical study of apple farmers in Shaanxi Province[J]. Ecological Economy, 2019, 35(11): 112-116. (in Chinese with English abstract)
[27]	中华人民共和国财政部. 关于改革和完善农业综合开发政策措施的意见[EB/OL]. (2014-08-20)[2016-10-20]. https://code.fabao365.com/law_162366.html.
[28]	李雪,顾莉丽,李瑞. 我国粮食主产区粮食生产生态效率评价研究[J]. 中国农机化学报,2022,43(2):205-213. LI Xue, GU LIli, LI Rui. Study on evaluation of eco-efficiency of grain production in major grain-producing areas of China[J]. Journal of Chinese Agricultural Mechanization, 2022, 43(2): 205-213. (in Chinese with English abstract)
[29]	陈丽,郝晋珉,王峰,等. 基于碳循环的黄淮海平原耕地固碳功能研究[J]. 资源科学,2016,38(6):1039-1053. CHEN Li, HAO Jinmin, WANG Feng, et al. Carbon sequestration function of cultivated land use system based on the carbon cycle for the Huang-Huai-Hai Plain[J]. Resources Science, 2016, 38(6): 1039-1053. (in Chinese with English abstract)
[30]	田云,张俊飚. 中国农业生产净碳效应分异研究[J]. 自然资源学报,2013,28(8):1298-1309. TIAN Yun, ZHANG Junbiao. Regional differentiation research on net carbon effect of agricultural production in China[J]. Journal of Natural Resources, 2013, 28(8): 1298-1309.
[31]	谢光辉,王晓玉,韩东倩,等. 中国禾谷类大田作物收获指数和秸秆系数[J]. 中国农业大学学报,2011,16(1):1-8. XIE Guanghui, WANG Xiaoyu, HAN Dongqian, et al. Harvest index and residue factor of non-cereal crops in China[J]. Journal of China Agricultural University, 2011, 16(1): 1-8. (in Chinese with English abstract)
[32]	WEST T O, MARLAND G. A synthesis of carbon sequestration, carbon missions, and net carbon flux in agriculture: Comparing tillage practices in the United States[J]. Agriculture Ecosystems and Environment, 2002, 91: 217-232. doi: 10.1016/S0167-8809(01)00233-X
[33]	POST W M, KWON K C. Soil carbon sequestration and land use change: processes and potential[J]. Global Change Biology, 2000, 6(3): 317-327. doi: 10.1046/j.1365-2486.2000.00308.x
[34]	李波,张俊飚,李海鹏. 中国农业碳排放时空特征及影响因素分解[J]. 中国人口·资源与环境,2011,21(8):80-86. LI Bo, ZHANG Junbiao, LI Haipeng. Research on spatial-temporal characteristics and affecting factors decomposition of agricultural carbon emission in China[J]. China Population, Resources and Environment, 2011, 21(8): 80-86. (in Chinese with English abstract)
[35]	DUBEY A, LAL R. Carbon footprint and sustainability of agricultural production systems in Punjab, India and Ohio, USA[J]. Journal of Crop Improvement, 2009, 23(4): 332-350. doi: 10.1080/15427520902969906
[36]	中华人民共和国农业农村部. 张桃林副部长在全国农业机械化工作会议上的讲话及典型发言材料[EB/OL]. [2022-03-21].
[37]	李晨. 未来十年我国粮食产量将年均增长1.2%[N]. 中国科学报,2023-04-24(001).
[38]	张玥,代亚强,陈媛媛等. 中国耕地低碳利用效率时空演变及其驱动因素[J]. 农业工程学报,2022,38(8):234-243. ZHANG Yue, DAI Yaqiang, CHEN Yuanyuan, et al. Spatial-temporal evolution and driving factors of low-carbon use efficiency of cultivated land in China[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2022, 38(8): 234-243. (in Chinese with English abstract)
[39]	汪亚琴,姚顺波,侯孟阳,等. 基于地理探测器的中国农业生态效率时空分异及其影响因素[J]. 应用生态学报,2021,32(11):4039-4049. WANG Yaqin, YAO Shunbo, HOU Mengyang, et al. Spatial-temporal differentiation and its influencing factors of agricultural eco-efficiency in China based on geographic detector[J]. Chinese Journal of Applied Ecology, 2021, 32(11): 4039-4049. (in Chinese with English abstract)
[40]	畅华仪,张俊飚,何可. 技术感知对农户生物农药采用行为的影响研究[J]. 长江流域资源与环境,2019,28(1):202-211. CHANG Huayi, ZHANG Junbiao, HE Ke. Technology perception and biological pesticides adoption[J]. Resources and Environment in the Yangtze Basin, 2019, 28(1): 202-211. (in Chinese with English abstract)
[41]	TAN X P, WANG X Y, ZAIDI S H A. What drives public willingness to participate in the voluntary personal carbon-trading scheme? A case study of Guangzhou Pilot, China[J]. Ecological Economics, 2019, 165(3): 13-17.

[1]	NING Zhengtong, LI Jian, LI Haidong, ZHU Liangkuan, ZHAO Wen, WANG Yangwei, GUO Yanling. Edge fusion-based image segmentation model for orchard overlapping grape clusters[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2025, 41(6): 165-172. DOI: 10.11975/j.issn.1002-6819.202410095
[2]	Huang Chenglong, Ke Yuxi, Hua Xiangdong, Yang Junya, Sun Mengyu, Yang Wanneng. Application status and prospect of edge computing in smart agriculture[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2022, 38(16): 224-234. DOI: 10.11975/j.issn.1002-6819.2022.16.025
[3]	Zhu Yu, Luo Quanda, Tian Ye, Lai Jianfeng, Jiang Fangshi, Zhang Yue, Ge Hongli, Huang Yanhe, Lin Jinshi. Development of the depth measurement system for shallow flow on slopes using an edge-detection algorithm[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2022, 38(2): 157-165. DOI: 10.11975/j.issn.1002-6819.2022.02.018
[4]	Zhu Weixing, Ji Bin, Qin Feng. Detection of foreground-frame of pig using edge model based on pseudosphere-operator[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2012, 28(12): 189-194.
[5]	Fast method of egg image edge detecting based on dichotomy[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2010, 26(1): 238-242.
[6]	Zhou Zhiyu, Liu Yingchun, Zhang Jianxin. Orange edge detection based on adaptive Canny operator[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2008, 24(3).
[7]	Liang Yan, Ying Miaomiao, Lü Yinghua, Lu Xianying, Zhang Ying. Microwave-assisted technology for extracting Opuntia polysaccharide[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2006, 22(7): 159-162.
[8]	Yang Fuzeng, Wang Zheng, Han Wenting, Yang Qing. Wavelet transform-based multiscale edge detection of dehiscence furrow in Chinese date images[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2005, 21(6): 92-95.
[9]	Xu Juan, Wang Maohua. Application of Morphological Image Processing inStem Location and Edge Detection of Apple Automatic Grading[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 1999, 15(2): 177-180.
[10]	Yu Zaihe, Liu Fu, Sun Lingming, Li Tiezhu. Measurement of Edge Flaw on Metal Workpiece[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 1998, 14(1): 138-141.

Cited By

Cited by

Periodical cited type(2)

1.	柴俊，王浩陈. 基于改进Canny的水稻倒伏区域提取方法. 现代信息科技. 2025(02): 12-15 .
2.	谢强. 一种融合场景解译与面向对象分割精准识别城市边缘区域闲置地的方法. 江苏科技信息. 2024(14): 127-130+136 .