留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

Spatial Patterns of LULC and Driving Forces in the Transnational Area of Tumen River: A Comparative Analysis of the Sub-regions of China, the DPRK, and Russia

NAN Ying WANG Bingbing ZHANG Da LIU Zhifeng QI Dekang ZHOU Haohao

NAN Ying, WANG Bingbing, ZHANG Da, LIU Zhifeng, QI Dekang, ZHOU Haohao. Spatial Patterns of LULC and Driving Forces in the Transnational Area of Tumen River: A Comparative Analysis of the Sub-regions of China, the DPRK, and Russia[J]. 中国地理科学, 2020, 30(4): 588-599. doi: 10.1007/s11769-020-1136-x
引用本文: NAN Ying, WANG Bingbing, ZHANG Da, LIU Zhifeng, QI Dekang, ZHOU Haohao. Spatial Patterns of LULC and Driving Forces in the Transnational Area of Tumen River: A Comparative Analysis of the Sub-regions of China, the DPRK, and Russia[J]. 中国地理科学, 2020, 30(4): 588-599. doi: 10.1007/s11769-020-1136-x
NAN Ying, WANG Bingbing, ZHANG Da, LIU Zhifeng, QI Dekang, ZHOU Haohao. Spatial Patterns of LULC and Driving Forces in the Transnational Area of Tumen River: A Comparative Analysis of the Sub-regions of China, the DPRK, and Russia[J]. Chinese Geographical Science, 2020, 30(4): 588-599. doi: 10.1007/s11769-020-1136-x
Citation: NAN Ying, WANG Bingbing, ZHANG Da, LIU Zhifeng, QI Dekang, ZHOU Haohao. Spatial Patterns of LULC and Driving Forces in the Transnational Area of Tumen River: A Comparative Analysis of the Sub-regions of China, the DPRK, and Russia[J]. Chinese Geographical Science, 2020, 30(4): 588-599. doi: 10.1007/s11769-020-1136-x

Spatial Patterns of LULC and Driving Forces in the Transnational Area of Tumen River: A Comparative Analysis of the Sub-regions of China, the DPRK, and Russia

doi: 10.1007/s11769-020-1136-x
基金项目: 

Under the auspices of National Natural Science Foundation of China (No. 41771094, 41871185, 41801184)

详细信息
    通讯作者:

    ZHANG Da. E-mail:zhangda@ybu.edu.cn

Spatial Patterns of LULC and Driving Forces in the Transnational Area of Tumen River: A Comparative Analysis of the Sub-regions of China, the DPRK, and Russia

Funds: 

Under the auspices of National Natural Science Foundation of China (No. 41771094, 41871185, 41801184)

  • 摘要: Understanding the spatial patterns of land-use and land-cover (LULC) and their driving forces in transnational areas is important for the sustainable development of these regions. However, the spatial patterns of LULC and their driving forces across multiple scales are poorly understood in transnational areas. In this study, we analyzed the spatial patterns of LULC and driving forces in the transnational area of Tumen River (TATR) in 2016 across two scales: the entire region and the sub-regions of China, the Democratic People’s Republic of Korea (DPRK), and Russia. Results showed that the LULC was dominated by broadleaf forest and dry farmland in the TATR in 2016, which accounted for 66.86% and 13.60% of the entire region, respectively. Meanwhile, the LULC in the three sub-regions exhibited noticeable differences. In the Chinese and the DPRK’s sub-regions, the area of broadleaf forest was greater than those for the other LULC types, while the Russian sub-region was dominated by broadleaf forest and grassland. The spatial patterns of LULC were mainly influenced by topography, climate, soil properties, and human activities. In addition, the driving forces of the spatial patterns of LULC in the TATR had an obvious scaling effect. Therefore, we suggest that effective policies and regulations with cooperation among China, the DPRK, and Russia are needed to plan the spatial patterns of LULC and improve the sustainable development of the TATR.
  • [1] Akhtar F, Awan U K, Tischbein B, 2017. A phenology based geo-informatics approach to map land use and land cover (2003-2013) by spatial segregation of large heterogenic river basins. Applied Geography, 88:48-61. doi: org/10.1016/j.apgeog.2017.09.003
    [2] Du P J, Xia J S, Zhang W et al., 2012. Multiple classifier system for remote sensing image classification:a review. Sensors, 12(4):4764-4792. doi: 10.3390/s120404764
    [3] Fang Chuanglin, 2017. The strategy and pattern of international economic cooperation in Tumen River area of China under the ‘the Belt and Road’. Northeast Asia Economic Research, 1(1):5-14. (in Chinese)
    [4] Grant J A, Quinn M S, 2007. Factors influencing transboundary wildlife management in the North American ‘Crown of the Continent’. Journal of Environmental Planning and Manage-ment, 50(6):765-782. doi: 10.1080/09640560701609323
    [5] Guo X Y, Zhang H Y, Wang Y Q et al., 2015. Mapping and as-sessing typhoon-induced forest disturbance in Changbai Mountain National Nature Reserve using time series Landsat imagery. Journal of Mountain Science, 12(2):404-416. doi: 10.1007/s11629-014-3206-y
    [6] Hansen M C, Loveland T R, 2012. A review of large area moni-toring of land cover change using Landsat data. Remote Sensing of Environment, 122(1):66-74. doi:10.1016/j.rse.2011. 08.024
    [7] He C Y, Liu Z F, Tian J et al., 2014. Urban expansion dynamics and natural habitat loss in China:a multiscale landscape per-spective. Global Change Biology, 20(9):2886-2902. doi: 10.1111/gcb.12553
    [8] Huang Qingxu, He Chunyang, Shi Peijun et al., 2009. Under-standing multi-scale urban expansion driving forces:in the case study of Beijing. Economic Geography, 29(5):714-721. (in Chinese)
    [9] Kashaigili J J, Majaliwa A M, 2010. Integrated assessment of land use and cover changes in the Malagarasi river catchment in Tanzania. Physics and Chemistry of the Earth, Parts A/B/C, 35(13-14):730-741. doi: 10.1016/j.pce.2010.07.030
    [10] Li B, Liu Z F, Nan Y et al., 2018. Comparative analysis of urban heat island intensities in Chinese, Russian, and DPRK regions across the transnational urban agglomeration of the Tumen River in Northeast Asia. Sustainability, 10(8):2637. doi: 10.3390/su10082637
    [11] Ma Q, He C Y, Wu J G, 2016. Behind the rapid expansion of ur-ban impervious surfaces in China:major influencing factors revealed by a hierarchical multiscale analysis. Land Use Policy, 59:434-445. doi: 10.1016/j.landusepol.2016.09.012
    [12] Ma Q, He C Y, Wu J G et al., 2014. Quantifying spatiotemporal patterns of urban impervious surfaces in China:an improved assessment using nighttime light data. Landscape and Urban Planning, 130:36-49. doi:10.1016/j.landurbplan.2014. 06.009
    [13] Ma Q, Wu J G, He C Y et al., 2018. Spatial scaling of urban im-pervious surfaces across evolving landscapes:from cities to urban regions, Landscape and Urban Planning, 175:50-61. doi: 10.1016/j.landurbplan.2018.03.010
    [14] Mao D H, Wang Z M, Wu J G et al., 2018. China's wetlands loss to urban expansion. Land Degradation & Development, 29:2644-2657.
    [15] Nan Ying, Ji Zhe, Dong Yehui et al., 2012. Study of land use/cover dynamic change in Tumen River across national border region during the last 30 years. Journal of Natural Science of Hunan Normal University, 35(1):82-89. (in Chinese)
    [16] Pelorosso R, Leone A, Boccia L, 2009. Land cover and land use change in the Italian central Apennines:a comparison of as-sessment methods. Applied Geography, 29(1):35-48. doi:10. 1016/j.apgeog.2008.07.003
    [17] Prishchepov A V, Müller D, Dubinin M et al., 2013. Determinants of agricultural land abandonment in post-Soviet European Russia. Land Use Policy, 30(1):873-884. doi: 10.1016/j.landusepol.2012.06.011
    [18] Sun Q L, Feng X F, Ge Y et al., 2015. Topographical effects of climate data and their impacts on the estimation of net primary productivity in complex terrain:a case study in Wuling Mountainous area, China. Ecological Informatics, 27(27):44-54. doi: 10.1016/j.ecoinf.2015.02.003
    [19] Tao H, Nan Y, Liu Z F et al., 2017. Spatiotemporal patterns of forest in the transnational area of Changbai Mountain from 1977 to 2015:a comparative analysis of the Chinese and DPRK sub-regions. Sustainability, 9(6):1054. doi: 10.3390/su9061054
    [20] Tuia D, Ratle F, Pacifici F et al., 2009. Active learning methods for remote sensing image classification. IEEE Transactions on Geoscience and Remote Sensing, 47(7):2218-2232. doi: 10.1109/TGRS.2008.2010404
    [21] Tuia D, Volpi M, Copa L et al., 2011. A survey of active learning algorithms for supervised remote sensing image classification. IEEE Journal of Selected Topics in Signal Processing, 5(3):606-617. doi: 10.1109/JSTSP.2011.2139193
    [22] Verburg P H, Neumann K, Nol L, 2011. Challenges in using land use and land cover data for global change studies. Global Change Biology, 17(2):974-989. doi:10.1111/j.1365-2486. 2010.023.07.x
    [23] Wang J W, Zhang D, Nan Y et al., 2020. Spatial patterns of net primary productivity and its driving forces:a multi-scale anal-ysis in the transnational area of the Tumen River. Frontiers of Earth Science, 14(1):124-139. doi: 10.1007/s11707-019-0759-7
    [24] Wang N H, Brown D G, An L et al., 2013. Comparative perfor-mance of logistic regression and survival analysis for detecting spatial predictors of land-use change. International Journal of Geographical Information Science, 27(10):1960-1982. doi: 10.1080/13658816.2013.779377
    [25] Wu J G, 2004. Effects of changing scale on landscape pattern analysis:scaling relations. Landscape Ecology, 19(2):125-138. doi: 10.1023/B:LAND.0000021711.40074.ae
    [26] Wu J G, 2013. Landscape sustainability science:ecosystem ser-vices and human well-being in changing landscapes. Landscape Ecology, 28(6):999-1023. doi: 10.1007/s10980-013-9894-9
    [27] Wu Jianguo, Guo Xiaochuan, Yang Jie et al., 2014. What is sus-tainability science? Chinese Journal of Applied Ecology, 25(1):1-11. (in Chinese)
    [28] Wu L, Deng F, Xie Z et al., 2016. Spatial analysis of severe fever with thrombocytopenia syndrome virus in China using a geo-graphically weighted logistic regression model. International Journal of Environmental Research and Public Health, 13(11):1125. doi: 10.3390/ijerph13111125
    [29] Wu Xue, Gao Jungang, Zhang Yili et al., 2017. Land cover status in the Koshi River Basin, Central Himalayas. Journal of Re-sources and Ecology, 8(1):10-19. doi: 10.5814/j.issn.1674-764x.2017.01.003
    [30] Yang Y M, Zhang D, Nan Y et al., 2019. Modeling urban expan-sion in the transnational area of Changbai Mountain:a scenario analysis based on the zoned Land Use Scenario Dynam-ics-urban model. Sustainable Cities and Society, 50:101622. doi: 10.1016/j.scs.2019.101622
    [31] Ye Baoying, Huang Fang, Zhang Shuwen et al., 2001. The driving forces of land use/cover change in the upstream area of the Nenjiang River. Chinese Geographical Science, 11(4):377-377. doi: 10.1007/s11769-001-0054-9
    [32] Zhang D, Huang Q X, He C Y et al., 2017. Impacts of urban ex-pansion on ecosystem services in the Beijing-Tianjin-Hebei urban agglomeration, China:a scenario analysis based on the Shared Socioeconomic Pathways. Resources, Conservation and Recycling, 125:115-130. doi:10.1016/j.resconrec.2017. 06.003
    [33] Zhang D, Huang Q X, He C Y et al., 2019. Planning urban land-scape to maintain key ecosystem services in a rapidly urbanizing area:a scenario analysis in the Beijing-Tianjin-Hebei urban agglomeration, China. Ecological Indicators, 96:559-571. doi: 10.1016/j.ecolind.2018.09.030
    [34] Zhang X P, Zhang L, Zhao J et al., 2008. Responses of streamflow to changes in climate and land use/cover in the Loess Plateau, China. Water Resources Research, 44(7):W00A07. doi: 10.1029/2007WR006711
    [35] Zhou W Q, Troy A, Grove M, 2008. Object-based land cover classification and change analysis in the Baltimore metropolitan area using multitemporal high resolution remote sensing data. Sensors, 8(3):1613-1636. doi: 10.3390/s8031613
    [36] Zhu Weihong, Guo Yanli, Sun Peng et al., 2012. Wetland ecosys-tem health assessment of the Tumen River downstream. Acta Ecologica Sinica, 32(21):6609-6618. (in Chinese)
    [37] Zhu Weihong, Miao Chengyu, Zheng Xiaojun et al., 2014. Study on ecological safety evaluation and warning of wetlands in Tumen River watershed based on 3S technology. Acta Eco-logica Sinica, 34(6):1379-1390. (in Chinese)
  • [1] Yue WANG, Chengyun WANG, Xiyan MAO, Binglin Liu, Zhenke ZHANG, Shengnan JIANG.  Spatial Pattern and Benefit Allocation in Regional Collaborative Innovation of the Yangtze River Delta, China . Chinese Geographical Science, 2021, 31(5): 900-914. doi: 10.1007/s11769-021-1224-6
    [2] TONG Huali, SHI Peiji, LUO Jun, LIU Xiaoxiao.  The Structure and Pattern of Urban Network in the Lanzhou-Xining Urban Agglomeration . Chinese Geographical Science, 2020, 30(1): 59-74. doi: 10.1007/s11769-019-1090-7
    [3] DU Yan, QIN Weishan, SUN Jianfeng, WANG Xiaohui, GU Haoxin.  Spatial Pattern and Influencing Factors of Regional Ecological Civilisa-tion Construction in China . Chinese Geographical Science, 2020, 30(5): 776-790. doi: 10.1007/s11769-020-1145-9
    [4] HUANG Xin, HUANG Xiaojun, LIU Mengmeng, WANG Bo, ZHAO Yonghua.  Spatial-temporal Dynamics and Driving Forces of Land Development Intensity in the Western China from 2000 to 2015 . Chinese Geographical Science, 2020, 30(1): 16-29. doi: 10.1007/s11769-020-1095-2
    [5] XUE Shuyan, LI Gang, YANG Lan, LIU Ling, NIE Qifan, Muhammad Sajid MEHMOOD.  Spatial Pattern and Influencing Factor Analysis of Attended Collection and Delivery Points in Changsha City, China . Chinese Geographical Science, 2019, 29(6): 1078-1094. doi: 10.1007/s11769-019-1086-3
    [6] CHU Nanchen, ZHANG Pingyu, LI He.  Transnational Economic Connection Analysis Based on Railway Class Ac-cessibility Between China and Russia . Chinese Geographical Science, 2019, 20(5): 872-886. doi: 10.1007/s11769-019-1064-9
    [7] GONG Shihan, XIAO Yang, XIAO Yi, ZHANG Lu, OUYANG Zhiyun.  Driving Forces and Their Effects on Water Conservation Services in Forest Ecosystems in China . Chinese Geographical Science, 2017, 27(2): 216-228. doi: 10.1007/s11769-017-0860-3
    [8] WANG Cheng, WANG Liping, JIANG Fuxia, LU Zhangwei.  Differentiation of Rural Households' Consciousness in Land Use Activities: A Case from Bailin Village, Shapingba District of Chongqing Municipality, China . Chinese Geographical Science, 2015, 25(1): 124-136. doi: 10.1007/s11769-014-0688-z
    [9] DI Xianghong, HOU Xiyong, WANG Yuandong, WU Li.  Spatial-temporal Characteristics of Land Use Intensity of Coastal Zone in China During 2000-2010 . Chinese Geographical Science, 2015, 25(1): 51-61. doi: 10.1007/s11769-014-0707-0
    [10] SONG Wei, CHEN Baiming, ZHANG Ying.  Land-use Change and Socio-economic Driving Forces of Rural Settlement in China from 1996 to 2005 . Chinese Geographical Science, 2014, 0(5): 511-524. doi: 10.1007/s11769-013-0633-6
    [11] MA Xiaodong, QIU Fangdao, LI Quanlin, SHAN Yongbin, CAO Yong.  Spatial Pattern and Regional Types of Rural Settlements in Xuzhou City, Jiangsu Province, China . Chinese Geographical Science, 2013, 23(4): 482-491. doi: 10.1007/s11769-013-0615-8
    [12] YAN Mi1, 2, WANG Zhiyuan2, 3, Jed Oliver KAPLAN4, LIU Jian1, 2, MIN Shen2, WANG.  Comparison Between Reconstructions of Global Anthropogenic Land Cover Change over Past Two Millennia . Chinese Geographical Science, 2013, 23(2): 131-146.
    [13] ZHU Likai, MENG Jijun, MAO Xiyan.  Analyzing Land-use Change in Farming-pastoral Transitional Region Using Autologistic Model and Household Survey Approach . Chinese Geographical Science, 2013, 23(6): 716-728. doi: 10.1007/s11769-013-0642-5
    [14] WEI Wei, CHEN Liding, YANG Lei, FU Bojie, SUN Ranhao.  Spatial Scale Effects of Water Erosion Dynamics: Complexities, Variabilities, and Uncertainties . Chinese Geographical Science, 2012, 22(2): 127-143.
    [15] DAI Junliang, WANG Kaiyong, GAO Xiaolu.  Spatial Structure and Land Use Control in Extended Metropolitan Region of Zhujiang River Delta, China . Chinese Geographical Science, 2010, 20(4): 298-308. doi: 10.1007/s11769-010-0402-8
    [16] WANG Bo, GUO Qinghai, Dou Sen.  Urbanization of Jilin Province and Its Spatial Pattern . Chinese Geographical Science, 2006, 16(4): 359-364.
    [17] CHANG Li-ping, ZHANG Shu-wen.  ANALYSIS OF THE EXPANSION OF THE BUILT-UP AREA OF DALIAN CITY . Chinese Geographical Science, 2002, 12(4): 373-377.
    [18] XU Han-qiu.  AN ASSESSMENT OF LAND USE CHANGES IN FUQING COUNTY OF CHINA USING REMOTE SENSING TECHNOLOGY . Chinese Geographical Science, 2002, 12(2): 126-135.
    [19] LIU Ji-yuan, DENG Xiang-zheng, LIU Ming-liang, ZHANG Shu-wen.  STUDY ON THE SPATIAL PATTERNS OF LAND—USE CHANGE AND ANALYSES OF DRIVING FORCES IN NORTHEASTERN CHINA DURING 1990-2000 . Chinese Geographical Science, 2002, 12(4): 299-308.
    [20] 肖笃宁, 赵羿, 郭林海.  LANDSCAPE PATTERN CHANGES IN WEST SUBURBS OF SHENYANG . Chinese Geographical Science, 1994, 4(3): 277-288.
  • 加载中
计量
  • 文章访问数:  168
  • HTML全文浏览量:  41
  • PDF下载量:  24
  • 被引次数: 0
出版历程
  • 收稿日期:  2019-12-22

Spatial Patterns of LULC and Driving Forces in the Transnational Area of Tumen River: A Comparative Analysis of the Sub-regions of China, the DPRK, and Russia

doi: 10.1007/s11769-020-1136-x
    基金项目:

    Under the auspices of National Natural Science Foundation of China (No. 41771094, 41871185, 41801184)

    通讯作者: ZHANG Da. E-mail:zhangda@ybu.edu.cn

摘要: Understanding the spatial patterns of land-use and land-cover (LULC) and their driving forces in transnational areas is important for the sustainable development of these regions. However, the spatial patterns of LULC and their driving forces across multiple scales are poorly understood in transnational areas. In this study, we analyzed the spatial patterns of LULC and driving forces in the transnational area of Tumen River (TATR) in 2016 across two scales: the entire region and the sub-regions of China, the Democratic People’s Republic of Korea (DPRK), and Russia. Results showed that the LULC was dominated by broadleaf forest and dry farmland in the TATR in 2016, which accounted for 66.86% and 13.60% of the entire region, respectively. Meanwhile, the LULC in the three sub-regions exhibited noticeable differences. In the Chinese and the DPRK’s sub-regions, the area of broadleaf forest was greater than those for the other LULC types, while the Russian sub-region was dominated by broadleaf forest and grassland. The spatial patterns of LULC were mainly influenced by topography, climate, soil properties, and human activities. In addition, the driving forces of the spatial patterns of LULC in the TATR had an obvious scaling effect. Therefore, we suggest that effective policies and regulations with cooperation among China, the DPRK, and Russia are needed to plan the spatial patterns of LULC and improve the sustainable development of the TATR.

English Abstract

NAN Ying, WANG Bingbing, ZHANG Da, LIU Zhifeng, QI Dekang, ZHOU Haohao. Spatial Patterns of LULC and Driving Forces in the Transnational Area of Tumen River: A Comparative Analysis of the Sub-regions of China, the DPRK, and Russia[J]. 中国地理科学, 2020, 30(4): 588-599. doi: 10.1007/s11769-020-1136-x
引用本文: NAN Ying, WANG Bingbing, ZHANG Da, LIU Zhifeng, QI Dekang, ZHOU Haohao. Spatial Patterns of LULC and Driving Forces in the Transnational Area of Tumen River: A Comparative Analysis of the Sub-regions of China, the DPRK, and Russia[J]. 中国地理科学, 2020, 30(4): 588-599. doi: 10.1007/s11769-020-1136-x
NAN Ying, WANG Bingbing, ZHANG Da, LIU Zhifeng, QI Dekang, ZHOU Haohao. Spatial Patterns of LULC and Driving Forces in the Transnational Area of Tumen River: A Comparative Analysis of the Sub-regions of China, the DPRK, and Russia[J]. Chinese Geographical Science, 2020, 30(4): 588-599. doi: 10.1007/s11769-020-1136-x
Citation: NAN Ying, WANG Bingbing, ZHANG Da, LIU Zhifeng, QI Dekang, ZHOU Haohao. Spatial Patterns of LULC and Driving Forces in the Transnational Area of Tumen River: A Comparative Analysis of the Sub-regions of China, the DPRK, and Russia[J]. Chinese Geographical Science, 2020, 30(4): 588-599. doi: 10.1007/s11769-020-1136-x
参考文献 (37)

目录

    /

    返回文章
    返回