中国耕地种植制度遥感探测及其时空特征

doi:10.3864/j.issn.0578-1752.2024.08.005

摘要/Abstract

摘要：

【目的】耕地种植制度是农业生产方式的具体体现，其形成受自然资源要素与人类土地利用行为综合影响，反映了“人类-自然”的耦合关系。本研究旨在科学掌握全国耕地种植制度格局，为优化农业生产布局、提高农业生产能力、推动农业可持续性发展提供依据。【方法】结合遥感监测与空间决策树模型等手段，构建适合我国农情的跨年度种植制度探测方法体系，并开展空间格局分析。首先，通过辨析种植强度、复种指数等概念，从长期性、周期性、稳定性等方面，定义种植制度的内涵；其次，构建连续度、频度指标，并利用基于时序遥感的2001—2018年中国复种指数监测结果，结合时间滑动窗口方法，在像元尺度分别计算两个指标的具体值；最后，评估耕地的种植强度与种植制度特征的显著性，利用决策树方法确定种植制度类型，从区域差异、动态规律等方面分析不同区域种植制度的时空异质特征。【结果】（1）面积上看，一年一熟所占面积最大，占53.52%，超过耕地总面积的一半；其次是一年两熟，占23.28%，季节性休耕（如两年三熟）与年度休耕分别占12.80%和6.94%。（2）空间上看，一年一熟、一年两熟、季节性休耕与年度休耕的集中分布区分别为东北地区、华北地区、长江以南地区与“镰刀弯”地区。（3）时间上看，动态稳定的种植制度从时间维度上揭示了静态复种指数背后的异质性，例如，2018年复种指数为1的区域，其中75.18%属于一年一熟、6.60%属于一年两熟、8.92%属于季节性休耕、8.02%属于年度休耕。【结论】本研究提出了一种结合时序遥感监测与空间决策树模型的跨年度分类体系，揭示了中国耕地种植制度分区聚集、种植强度南高北低的空间格局，直观展现了松嫩平原、“镰刀弯”等空间聚集区；分析了耕地复种与种植制度的时空差异特征，主要表现在种植制度与年度复种指数的空间不一致性，以及种植制度特有的周期性。研究结果可为合理提高耕地复种强度、推动实施“藏粮于地”战略提供案例支撑。

关键词: 耕地, 种植制度, 复种, 休耕轮作, 跨年度, 时空格局

Abstract:

【Objective】Cropping systems of cropland are the concrete embodiment of the mode of agricultural production, which reflect the coupled human-environment interactions. The formation is affected by natural resource elements and human land use behavior. This study aims to scientifically understand the spatial-temporal pattern of cropping systems, which helps to optimize agricultural distribution, improve agricultural production capacity, and realize the sustainable agriculture. 【Method】This study combined remote sensing monitoring with spatial decision tree models and other means to construct an inter-annual detection method system for cropping systems, which is designed for Chinese agricultural conditions, and then spatial pattern of cropping systems was analyzed. Firstly, the connotation of cropping systems was defined by identifying concepts such as cropping intensity, multiple cropping index, and considering of characteristics of “long-lasting” “periodicity” “stability”. Secondly, the indicators (i.e. continuity and frequency) were constructed, and were calculated at the pixel scale by the moving time window. Finally, the significance of the cropping intensity and characteristics of cropping system was evaluated. The decision tree method was also applied to determine the type of cropping systems, and the spatial-temporal heterogeneity of cropping systems in different regions was analyzed from the aspects of regional differences and dynamic laws. 【Result】 (1) Quantitatively, the largest area, 53.52%, is occupied by the single-cropping system, followed by the double-cropping system at 23.28%, the seasonal fallow system (i.e. 3 crops in 2 years) and the annual fallow system at 12.80% and 6.94%, respectively. (2) Spatially, the single-cropping system, double-cropping system, seasonal fallow system and annual fallow system are concentrated in Northeast China, North China, South of Yangtze River and “Sickle Bend” areas, respectively. (3) Temporally, it revealed the heterogeneity of cropping system and static multiple cropping index in the time dimension. For example, the regions with multiple cropping index of 1 in 2018 consist of 75.18% single-cropping system, 6.60% double-cropping system, 8.92% seasonal fallow system and 8.02% annual fallow system. 【Conclusion】This study proposed a method for mapping inter-annual cropping systems, combining remote sensing temporal monitoring and spatial decision tree models. It revealed the spatial pattern of cropping systems which is gathered by zone and cropping intensity is higher in the south and lower in the north. The Songnen Plain, “Sickle Bend” and other spatial gathering areas were intuitively displayed. Also, the differences between multi-cropping and cropping system were compared, which were mainly manifested in the spatial inconsistency between the cropping system and the annual multiple cropping index, as well as the periodicity of the cropping system. The results will provide case support for rationally increasing the cropland multi-cropping intensity and promoting the implementation of the “grain storage in the ground” strategy.

Key words: cropland, cropping system, multiple cropping, land fallow and crop rotation, inter-annual, spatial-temporal pattern

张素心, 申格, 余强毅, 吴文斌. 中国耕地种植制度遥感探测及其时空特征[J]. 中国农业科学, 2024, 57(8): 1469-1489.

ZHANG SuXin, SHEN Ge, YU QiangYi, WU WenBin. Remote Sensing Detection of Cropping System and Its Spatial-Temporal Pattern in China[J]. Scientia Agricultura Sinica, 2024, 57(8): 1469-1489.

0
/ / 推荐

导出引用管理器 EndNote|Reference Manager|ProCite|BibTeX|RefWorks

链接本文: https://www.chinaagrisci.com/CN/10.3864/j.issn.0578-1752.2024.08.005

https://www.chinaagrisci.com/CN/Y2024/V57/I8/1469

图/表 13

图1

图2

图3

图4

图5

表1

图6

图7

图8

图9

图10

表2

图11

参考文献 46

[1]	RAY D K, GERBER J S, MACDONALD G K, WEST P C. Climate variation explains a third of global crop yield variability. Nature Communications, 2015, 6: 5989. doi: 10.1038/ncomms6989 pmid: 25609225
[2]	WAHA K, MULLER C, BONDEAU A, DIETRICH J P, KURUKULASURIYA P, HEINKE J, LOTZE-CAMPEN H. Adaptation to climate change through the choice of cropping system and sowing date in sub-Saharan Africa. Global Environmental Change, 2013, 23(1): 130-143. doi: 10.1016/j.gloenvcha.2012.11.001
[3]	ZHU P, BURNEY J, CHANG J F, JIN Z N, MUELLER N D, XIN Q C, XU J L, YU L, MAKOWSKI D, CIAIS P. Warming reduces global agricultural production by decreasing cropping frequency and yields. Nature Climate Change, 2022, 12: 1016-1023. doi: 10.1038/s41558-022-01492-5
[4]	RAY D K, WEST P C, CLARK M, GERBER J S, PRISHCHEPOV A V, CHATTERJEE S. Climate change has likely already affected global food production. PLoS ONE, 2019, 14(5): e0217148. doi: 10.1371/journal.pone.0217148
[5]	COHN A S, VANWEY L K, SPERA S A, MUSTARD J F. Cropping frequency and area response to climate variability can exceed yield response. Nature Climate Change, 2016, 6: 601-604. doi: 10.1038/nclimate2934
[6]	HEINO M, KINNUNEN P, ANDERSON W, RAY D K, PUMA M J, VARIS O, SIEBERT S, KUMMU M. Increased probability of hot and dry weather extremes during the growing season threatens global crop yields. Scientific Reports, 2023, 13(1): 3583. doi: 10.1038/s41598-023-29378-2 pmid: 36869041
[7]	FU J, JIAN Y W, WANG X H, LI L, CIAIS P, ZSCHEISCHLER J, WANG Y, TANG Y H, MULLER C, WEBBER H, et al. Extreme rainfall reduces one-twelfth of China’s rice yield over the last two decades. Nature Food, 2023, 4(5): 416-426. doi: 10.1038/s43016-023-00753-6
[8]	U.S. Department of Agriculture. Action plan for climate adaptation and resilience. 2021, https://www.sustainability.gov/pdfs/usda-2021-cap.pdf.
[9]	刘巽浩, 陈阜, 吴尧. 多熟种植——中国农业的中流砥柱. 作物杂志, 2015(6): 1-9.
	LIU X H, CHEN F, WU Y. Multiple cropping: The principal part of China’s agriculture. Crops, 2015(6): 1-9. (in Chinese)
[10]	杨婷, 赵文利, 王哲怡, 陆星彤, 卢珊. 基于遥感影像NDVI数据的中国种植制度分布变化. 中国农业科学, 2015, 48(10): 1915-1925. doi: 10.3864/j.issn.0578-1752.2015.10.005.
	YANG T, ZHAO W L, WANG Z Y, LU X T, LU S. Changes of cropping system in China based on remotely sensed NDVI data. Scientia Agricultura Sinica, 2015, 48(10): 1915-1925. doi: 10.3864/j.issn.0578-1752.2015.10.005. (in Chinese)
[11]	吴文斌, 余强毅, 陆苗, 项铭涛, 谢安坤, 杨鹏, 唐华俊. 耕地复种指数研究的关键科学问题. 中国农业科学, 2018, 51(9): 1681-1694. doi: 10.3864/j.issn.0578-1752.2018.09.006.
	WU W B, YU Q Y, LU M, XIANG M T, XIE A K, YANG P, TANG H J. Key research priorities for multiple cropping systems. Scientia Agricultura Sinica, 2018, 51(9): 1681-1694. doi: 10.3864/j.issn.0578-1752.2018.09.006. (in Chinese)
[12]	WAHA K, DIETRICH J P, PORTMANN F T, SIEBERT S, THORNTON P K, BONDEAU A, HERRERO M. Multiple cropping systems of the world and the potential for increasing cropping intensity. Global Environmental Change: Human and Policy Dimensions, 2020, 64: 102131. doi: 10.1016/j.gloenvcha.2020.102131
[13]	唐华俊, 吴文斌, 余强毅, 夏天, 杨鹏, 李正国. 农业土地系统研究及其关键科学问题. 中国农业科学, 2015, 48(5): 900-910. doi: 10.3864/j.issn.0578-1752.2015.05.08.
	TANG H J, WU W B, YU Q Y, XIA T, YANG P, LI Z G. Key research priorities for agricultural land system studies. Scientia Agricultura Sinica, 2015, 48(5): 900-910. doi: 10.3864/j.issn.0578-1752.2015.05.08. (in Chinese)
[14]	POORE J, NEMECEK T. Reducing food’s environmental impacts through producers and consumers. Science, 2018, 360(6392): 987-992. doi: 10.1126/science.aaq0216
[15]	WANG X, LI X B. Impacts of land fragmentation and cropping system on the productivity and efficiency of grain producers in the North China Plain: Taking Cangxian County of Hebei Province as an example. Journal of Resources and Ecology, 2020, 11(6): 580-588. doi: 10.5814/j.issn.1674-764x.2020.06.005
[16]	UDDIN M J, HOODA P S, MOHIUDDIN A S M, SMITH M, WALLER M. Land inundation and cropping intensity influences on organic carbon in the agricultural soils of Bangladesh. Catena, 2019, 178: 11-19. doi: 10.1016/j.catena.2019.03.002
[17]	HUANG M, TIAN A L, CHEN J N, CAO F B, CHEN Y M, LIU L S. Soil bacterial communities in three rice-based cropping systems differing in productivity. Scientific Reports, 2020, 10(1): 9867. doi: 10.1038/s41598-020-66924-8 pmid: 32555234
[18]	XIONG Z Q, LIU Y L, WU Z, ZHANG X L, LIU P L, HUANG T Q. Differences in net global warming potential and greenhouse gas intensity between major rice-based cropping systems in China. Scientific Reports, 2015, 5: 17774. doi: 10.1038/srep17774 pmid: 26626733
[19]	GAO J Q, YANG X G, ZHENG B Y, LIU Z J, ZHAO J, SUN S, LI K N, DONG C Y. Effects of climate change on the extension of the potential double cropping region and crop water requirements in Northern China. Agricultural and Forest Meteorology, 2019, 268: 146-155. doi: 10.1016/j.agrformet.2019.01.009
[20]	JEONG S J, HO C H, PIAO S L, KIM J W, CIAIS P, LEE Y B, JHUN J G, PARK S K. Effects of double cropping on summer climate of the North China Plain and neighbouring regions. Nature Climate Change, 2014, 4(7): 615-619. doi: 10.1038/nclimate2266
[21]	YANG X G, CHEN F, LIN X M, LIU Z J, ZHANG H L, ZHAO J, LI K N, YE Q, LI Y, LV S, YANG P, WU W B, LI Z G, LAL R, TANG H J. Potential benefits of climate change for crop productivity in China. Agricultural and Forest Meteorology, 2015, 208: 76-84. doi: 10.1016/j.agrformet.2015.04.024
[22]	李宇, 邱炳文, 何玉花, 陈功, 叶智燕. 基于MODIS数据的2001—2018年中国耕地复种指数反演研究. 地理科学进展, 2020, 39(11): 1874-1883. doi: 10.18306/dlkxjz.2020.11.008
	LI Y, QIU B W, HE Y H, CHEN G, YE Z Y. Cropping intensity based on MODIS data in China during 2001-2018. Progress in Geography, 2020, 39(11): 1874-1883. (in Chinese) doi: 10.18306/dlkxjz.2020.11.008
[23]	YAN H M, LIU F, QIN Y W, NIU Z E, DOUGHTY R, XIAO X M. Tracking the spatio-temporal change of cropping intensity in China during 2000-2015. Environmental Research Letters, 2019, 14: 035008. doi: 10.1088/1748-9326/aaf9c7
[24]	XIANG M T, YU Q Y, WU W B. From multiple cropping index to multiple cropping frequency: Observing cropland use intensity at a finer scale. Ecological Indicators, 2019, 101: 892-903. doi: 10.1016/j.ecolind.2019.01.081
[25]	QIU B W, HU X, CHEN C C, TANG Z H, YANG P, ZHU X L, YAN C, JIAN Z Y. Maps of cropping patterns in China during 2015-2021. Scientific Data, 2022, 9(1): 479. doi: 10.1038/s41597-022-01589-8 pmid: 35931696
[26]	QIU B W, WANG Z Z, TANG Z H, CHEN C C, FAN Z L, LI W J. Automated cropping intensity extraction from isolines of wavelet spectra. Computers and Electronics in Agriculture, 2016, 125: 1-11. doi: 10.1016/j.compag.2016.04.015
[27]	RAMANKUTTY N, MEHRABI Z, WAHA K, JARVIS L, KREMEN C, HERRERO M, RIESEBERG L H. Trends in global agricultural land use: Implications for environmental health and food security. Annual Review of Plant Biology, 2018, 69: 789-815. doi: 10.1146/annurev-arplant-042817-040256 pmid: 29489395
[28]	HENRY R C, ENGSTRÖM K, OLIN S, OLIN S, ALEXANDER P, ARNETH A, ROUNSEVELL M D A. Food supply and bioenergy production within the global cropland planetary boundary. PLoS ONE, 2018, 13(3): e0194695. doi: 10.1371/journal.pone.0194695
[29]	IIZUMI T, RAMANKUTTY N. How do weather and climate influence cropping area and intensity? Global Food Security, 2015, 4: 46-50.
[30]	刘珍环, 杨鹏, 吴文斌, 李正国, 游良志. 近30年中国农作物种植结构时空变化分析. 地理学报, 2016, 71(5): 840-851. doi: 10.11821/dlxb201605012
	LIU Z H, YANG P, WU W B, LI Z G, YOU L Z. Spatio-temporal changes in Chinese crop patterns over the past three decades. Acta Geographica Sinica, 2016, 71(5): 840-851. (in Chinese) doi: 10.11821/dlxb201605012
[31]	蒋敏, 李秀彬, 辛良杰, 谈明洪. 南方水稻复种指数变化对国家粮食产能的影响及其政策启示. 地理学报, 2019, 74(1): 32-43. doi: 10.11821/dlxb201901003
	JIANG M, LI X B, XIN L J, TAN M H. The impact of paddy rice multiple cropping index changes in Southern China on national grain production capacity and its policy implications. Acta Geographica Sinica, 2019, 74(1): 32-43. (in Chinese) doi: 10.11821/dlxb201901003
[32]	冀正欣, 王秀丽, 李玲, 关小克, 蔚霖, 许月卿. 南阳盆地区耕地利用效率演变及其影响因素. 自然资源学报, 2021, 36(3): 688-701. doi: 10.31497/zrzyxb.20210312
	JI Z X, WANG X L, LI L, GUAN X K, YU L, XU Y Q. The evolution of cultivated land utilization efficiency and its influencing factors in Nanyang Basin. Journal of Natural Resources, 2021, 36(3): 688-701. (in Chinese) doi: 10.31497/zrzyxb.20210312
[33]	YAO Z Y, ZHANG L J, TANG S H, LI X X, HAO T T. The basic characteristics and spatial patterns of global cultivated land change since the 1980s. Journal of Geographical Sciences, 2017, 27: 771-785. doi: 10.1007/s11442-017-1405-5
[34]	武兰芳, 陈阜, 欧阳竹. 种植制度演变与研究进展. 耕作与栽培, 2002(3): 1-5, 14.
	WU L F, CHEN F, OUYANG Z. The evolution and research progress of cropping system. Tillage and Cultivation, 2002(3): 1-5, 14. (in Chinese)
[35]	BLANCO-CANQUI H, LAI R. Cropping systems//Principles of Soil Conservation and Management. Dordrecht: Springer, 2010: 165-193.
[36]	SHEN G, YU Q Y, ZHOU Q B, WANG C, WU W B. From multiple cropping frequency to multiple cropping system: A new perspective for the characterization of cropland use intensity. Agricultural Systems, 2023, 204: 103535. doi: 10.1016/j.agsy.2022.103535
[37]	苏康传, 杨庆媛, 张忠训, 毕国华. 中国耕地差异化休耕模式及技术措施探讨. 农业工程学报, 2020, 36(9): 283-291.
	SU K C, YANG Q Y, ZHANG Z X, BI G H. Investigation of differential fallow patterns and technical measures for cultivated land in China. Transactions of the Chinese Society of Agricultural Engineering, 2020, 36(9): 283-291. (in Chinese)
[38]	黄国勤, 赵其国. 中国典型地区轮作休耕模式与发展策略. 土壤学报, 2018, 55(2): 283-292.
	HUANG G Q, ZHAO Q G. Mode of rotation/fallow management in typical areas of China and its development strategy. Acta Pedologica Sinica, 2018, 55(2): 283-292. (in Chinese)
[39]	董金玮, 吴文斌, 黄健熙, 尤南山, 何盈利, 闫慧敏. 农业土地利用遥感信息提取的研究进展与展望. 地球信息科学学报, 2020, 22(4): 772-783. doi: 10.12082/dqxxkx.2020.200192
	DONG J W, WU W B, HUANG J X, YOU N S, HE Y L, YAN H M. State of the art and perspective of agricultural land use remote sensing information extraction. Journal of Geo-Information Science, 2020, 22(4): 772-783. (in Chinese)
[40]	石淑芹, 曹玉青, 吴文斌, 杨鹏, 蔡为民. 耕地集约化评价指标体系与评价方法研究进展. 中国农业科学, 2017, 50(7): 1210-1222. doi: 10.3864/j.issn.0578-1752.2017.07.004.
	SHI S Q, CAO Y Q, WU W B, YANG P, CAI W M. Progresses in research of evaluation index system and its method on arable land intensification: A review. Scientia Agricultura Sinica, 2017, 50(7): 1210-1222. doi: 10.3864/j.issn.0578-1752.2017.07.004. (in Chinese)
[41]	HIGO M, TATEWAKI Y, IIDA K, YOKOTA K, ISOBE K. Amplicon sequencing analysis of arbuscular mycorrhizal fungal communities colonizing maize roots in different cover cropping and tillage systems. Scientific Reports, 2020, 10(1): 6039. doi: 10.1038/s41598-020-58942-3 pmid: 32245995
[42]	YAN Z Z, ZHANG X Y, RASHID M A, LI H J, JING H C, HOCHMAN Z. Assessment of the sustainability of different cropping systems under three irrigation strategies in the North China Plain under climate change. Agricultural Systems, 2020, 178: 102745. doi: 10.1016/j.agsy.2019.102745
[43]	LIU Y, YU Q Y, ZHOU Q B, WANG C, BELLINGRATH-KIMURA S D, WU W B. Mapping the complex crop rotation systems in Southern China considering cropping intensity, crop diversity and their seasonal dynamics. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022, 15: 9584-9598. doi: 10.1109/JSTARS.2022.3218881
[44]	李忠华, 张龑, 李翠梅, 李风晶. 新疆两年三熟种植模式研究. 农村科技, 2018(12): 6-8.
	LI Z H, ZHANG Y, LI C M, LI F J. The cropping pattern of triple cropping per cycle in Xinjiang, China. Rural Science & Technology, 2018(12): 6-8. (in Chinese)
[45]	WU W B, YU Q Y, YOU L Z, CHEN K, TANG H J, LIU J G. Global cropping intensity gaps: Increasing food production without cropland expansion. Land Use Policy, 2018, 76: 515-525. doi: 10.1016/j.landusepol.2018.02.032
[46]	余强毅, 项铭涛, 谢安坤, 申格, 杨鹏, 吴文斌. 耕地复种差研究进展. 中国农业信息, 2018, 30(5): 1-12.
	YU Q Y, XIANG M T, XIE A K, SHEN G, YANG P, WU W B. Cropping intensity gap: A review. China Agricultural Informatics, 2018, 30(5): 1-12. (in Chinese)

参照 Reference		比较 Comparison	2001—2021年种植制度 Cropping systems from 2001 to 2021
2001—2018年种植制度 Cropping systems from 2001 to 2018		比较 Comparison	组内 Group (%)	全局 Overall (%)
一年一熟 Single-cropping	56.64%	一年一熟-一年一熟Single-cropping and Single-cropping	97.79	55.39
		一年一熟-一年两熟Single-cropping and Double-cropping	0.55	0.31
		一年一熟-季节性休耕Single-cropping and Seasonal fallow	0.97	0.55
		一年一熟-年度休耕Single-cropping and Annual fallow	0.44	0.25
		一年一熟-未识别Single-cropping and Unknown	0.25	0.14
一年两熟 Double-cropping	25.36%	一年两熟-一年一熟Double-cropping and Single-cropping	1.01	0.26
		一年两熟-一年两熟Double-cropping and Double-cropping	95.95	24.33
		一年两熟-季节性休耕Double-cropping and Seasonal fallow	1.27	0.32
		一年两熟-年度休耕Double-cropping and Annual fallow	1.25	0.32
		一年两熟-未识别Double-cropping and Unknown	0.53	0.13
季节性休耕 Seasonal fallow	10.49%	季节性休耕-一年一熟Seasonal fallow and Single-cropping	6.68	0.70
		季节性休耕-一年两熟Seasonal fallow and Double-cropping	4.84	0.51
		季节性休耕-季节性休耕Seasonal fallow and Seasonal fallow	85.17	8.93
		季节性休耕-年度休耕Seasonal fallow and Annual fallow	1.07	0.11
		季节性休耕-未识别Seasonal fallow and Unknown	2.21	0.23
年度休耕 Annual fallow	5.29%	年度休耕-一年一熟Annual fallow and Single-cropping	22.65	1.20
		年度休耕-一年两熟Annual fallow and Double-cropping	0.41	0.02
		年度休耕-季节性休耕Annual fallow and Seasonal fallow	0.68	0.04
		年度休耕-年度休耕Annual fallow and Annual fallow	72.59	3.84
		年度休耕-未识别Annual fallow and Unknown	3.69	0.20
总体一致性 Overall consistency			—	92.50