Please wait a minute...
干旱区科学  2018, Vol. 10 Issue (2): 316-333    DOI: 10.1007/s40333-018-0003-4
  本期目录 | 过刊浏览 | 高级检索 |
Regional difference and dynamic mechanism of locality of the Chinese farming-pastoral ecotone based on geotagged photos from Panoramio
Fang WANG1,2,*(), Yixi LI1,3, Ying DONG1,3, Xiaohua ZHU4
1 Sino-German Joint Laboratory on Urbanization and Locality Research (UAL), College of Architecture and Landscape Architecture, Peking University, Beijing 100871, China
2 Key Laboratory for Earth Surface Processes, Ministry of Education, Peking University, Beijing 100871, China
3 College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
4 Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
下载:  HTML  PDF (720KB) 
输出:  BibTeX | EndNote (RIS)      
服务
把本文推荐给朋友
加入引用管理器
E-mail Alert
RSS
作者相关文章
Abstract: 

Cross-regional locality research reflects the influences of natural environment and the human activities due to the abundant land types and the multiple landscape combinations in related regions. The Chinese farming-pastoral ecotone is a typical large-scale region but few studies were conducted. This research contributed to the understanding of cross-regional locality of the Chinese farming-pastoral ecotone from different scales, including national, sectional, and provincial administrative units by utilizing geotagged photos (GTPs) obtained from the Panoramio website. The major results were as follows: (1) the locality elements of the Chinese farming-pastoral ecotone included 52 free nodes classified into 8 types of scene attributes; (2) there were huge differences between locality elements of different regions, and there was a negative correlation between the similarity degree of elements of different provinces and their spatial distances; (3) the Chinese farming-pastoral ecotone could be divided into the northern, central and southern sections, whose localities had differences in element constitution, association structure and the strength of elements, system stability and the anti-interference capability; and (4) the evolution of the localities of the northern and central sections was mainly influenced by human activities, while the locality of southern section retained more natural features. On a theoretical level, this research aimed to establish the research methodology of locality from the perspective of open data on the web with strong operability and replicability. On a practical level, this research could enrich the structuring recognition of the locality of the Chinese farming-pastoral ecotone and the comprehension of its dynamic mechanism. The results provide a reference for locality differentiation protection and the development of a cross-regional scale.

Key words:  administrative units    geotagged photos    landscape    locality    networks    regional differences
收稿日期:  2017-08-17      修回日期:  2017-10-08      接受日期:  2018-01-25      出版日期:  2018-04-10      发布日期:  2018-03-02      期的出版日期:  2018-04-10
引用本文:    
. [J]. 干旱区科学, 2018, 10(2): 316-333.
Fang WANG, Yixi LI, Ying DONG, Xiaohua ZHU. Regional difference and dynamic mechanism of locality of the Chinese farming-pastoral ecotone based on geotagged photos from Panoramio. Journal of Arid Land, 2018, 10(2): 316-333.
链接本文:  
http://jal.xjegi.com/CN/10.1007/s40333-018-0003-4  或          http://jal.xjegi.com/CN/Y2018/V10/I2/316
[1] Deng H.2005. From the Natural Landscape to the Cultural Landscape: A Historical Geography Perspective on the Evolution of Man-land Relationship in the Farming-pastoral Ecotone in the North Yanshan. Beijing: The Commercial Press, 41-106. (in Chinese)
[2] Du M H, Yan P J, Wang P T.2015. The drought disaster and its response to the warming-dry climate in the farming-pastoral ecotones in the northern China. Journal of Arid Land Resources and Environment, 29(1): 124-128. (in Chinese)
[3] Feick R, Robertson C.2015. A multi-scale approach to exploring urban places in geotagged photographs. Computers, Environment and Urban Systems, 53: 96-109.
[4] Frias-Martinez V, Frias-Martinez E.2014. Spectral clustering for sensing urban land use using Twitter activity. Engineering Applications of Artificial Intelligence, 35: 237-245.
[5] Han Y, Hou X Y.2011. Change, classification and management of agro-pastoral ecotone in north China. Chinese Journal of Agricultural Resources and Regional Planning, 32(5): 31-35. (in Chinese)
[6] Hou X H, Niu Z, Gao S, et al.2013. Monitoring vegetation phenology in farming-pastoral zone using SPOT-VGT NDVI data. Transactions of the Chinese Society of Agricultural Engineering, 29(1): 142-150. (in Chinese)
[7] Hu Y J, Gao S, Janowicz K, et al.2015. Extracting and understanding urban areas of interest using geotagged photos. Computers, Environment and Urban Systems, 54: 240-254.
[8] Jankowski P, Andrienko N, Andrienko G, et al.2010. Discovering landmark preferences and movement patterns from photo postings. Transactions in GIS, 14(6): 833-852.
[9] Kisilevich S, Keim D, Rokach L.2010. A novel approach to mining travel sequences using collections of geotagged photos. In: Painho M, Santos M Y, Pundt H. Geospatial Thinking. Berlin, Heidelberg: Springer, 163-182.
[10] Li M M, Yan J P.2013. The characteristics and response of climate change in farming-pastoral ecotone of North China. Journal of Arid Land Resources and Environment, 27(5): 100-106. (in Chinese)
[11] Li X, Stepchenkova S.2012. Chinese outbound tourists’ destination image of America: part I. Journal of Travel Research, 51(3): 250-266.
[12] Ma W Y, Wang X M, Zhou N, et al.2017. Relative importance of climate factors and human activities in impacting vegetation dynamics during 2000-2015 in the Otindag Sandy Land, northern China. Journal of Arid Land, 9(4): 558-567.
[13] Meng J J, Zhang Y R, Zhou P.2010. Ecological vulnerability assessment of the farming-pastoral transitional zone in northern China: A case study of Ordos City. Journal of Desert Research, 30(4): 850-856. (in Chinese)
[14] Salton G, Buckley C.1988. Term-weighting approaches in automatic text retrieval. Information Processing & Management, 24(5): 513-523.
[15] Sha Z Y, Xie Y C, Tan X C, et al.2017. Assessing the impacts of human activities and climate variations on grassland productivity by partial least squares structural equation modeling (PLS-SEM). Journal of Arid Land, 9(4): 473-488.
[16] Spyrou E, Mylonas P.2016. Analyzing Flickr metadata to extract location-based information and semantically organize its photo content. Neurocomputing, 172: 114-133.
[17] Steiger E, Westerholt R, Resch B, et al.2015. Twitter as an indicator for whereabouts of people? Correlating Twitter with UK census data. Computers, Environment and Urban Systems, 54: 255-265.
[18] Stepchenkova S, Zhan F Z.2013. Visual destination images of Peru: Comparative content analysis of DMO and user-generated photography. Tourism Management, 36: 590-601.
[19] Stephens M, Poorthuis A.2015. Follow thy neighbor: Connecting the social and the spatial networks on Twitter. Computers, Environment and Urban Systems, 53: 87-95.
[20] Wang F, Li W, Prominski M.2014a. The new conflicts, strategies and explorations of urbanization and locality: Overview on the Sino-German Symposium. Geographical Research, 33(11): 2205-2014. (in Chinese)
[21] Wang J S, Jin X B, Cao X, et al.2015. Changes of the northern limit of cultivation in northern agro-pastoral ecotone in Qing Dynasty. Journal of Arid Land Resources and Environment, 29(3): 20-25. (in Chinese)
[22] Wang X J, Zhou L H, Shi M J.2014b. Sustainable development of a rural economy under grazing prohibition in a desertification control region and agro-pastoral transitional zone. Resources Science, 36(10): 2166-2173. (in Chinese)
[23] Weiss S M, Indurkhya N, Zhang T, et al.2005. Text Mining: Predictive Methods for Analyzing Unstructured Information. New York: Springer, 25-35.
[24] Xu J Y, Liu W H, Chang J, et al.2010. Exploring strategies about ecological improvement based on local responses in northern agro-pastoral ecotone. Acta Ecologica Sinica, 30(22): 6126-6134. (in Chinese)
[25] Xu L, Luo W, Zhou B B.2015. Landscape ecological risk assessment of farming-pastoral ecozone based on land use change: A case study of the Yanghe Watershed, China. Journal of Natural Resources, 30(4): 580-590. (in Chinese)
[26] Yu S X, Zhao M, Chen F Z, et al.2010. Dynamic remote sensing monitoring and analysis on desertification in the northern farming-pastoral zone based on GIS: A case of Tongliao, Inner Mongolia. Journal of Arid Land Resources and Environment, 24(4): 107-111. (in Chinese)
[27] Zhao H L, Zhao X Y, Zhang T H, et al.2002. Boundary line on agro-pasture zig zag zone in north China and its problems on eco-environment. Advance in Earth Sciences, 17(5): 739-747. (in Chinese)
[28] Zhao S Q.1953. An economic geographical survey of a farming-pastoral ecozone: Caibei, Caimeng and Ximeng. Acta Geographica Sinica, 19(1): 43-60. (in Chinese)
[29] Zheng Y Y, Guo S T, Su J.2014. The climate boundary and its change in farming-pastoral ecotone of northern China. Chinese Journal of Agricultural Resources and Regional Planning, 35(3): 6-13. (in Chinese)
[30] Zhou B L, Liu L, Oliva A, et al.2014. Recognizing city identity via attribute analysis of geo-tagged images. In: Fleet D, Pajdla T, Schiele B, et al. Computer Vision-ECCV 2014. Cham: Springer International Publishing, 519-534.
[31] Zhou X L, Xu C, Kimmons B.2015. Detecting tourism destinations using scalable geospatial analysis based on cloud computing platform. Computers, Environment and Urban Systems, 54: 144-153.
No related articles found!
No Suggested Reading articles found!
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed