Skip to main content

Study on Spatio-Temporal Change of Land Use in Tianjin Urban Based on Remote Sensing Data

  • Conference paper
  • First Online:
Geo-Informatics in Resource Management and Sustainable Ecosystem ( 2015, GRMSE 2015)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 569))

  • 2340 Accesses

Abstract

Understanding of development law and trend for land use change can provide effective data and decision support for the sustainable development of the region. Taking Tianjin Urban as the study area, Landsat TM/OLI images were used. Based on RS and GIS, unsupervised classification and normalized indexes were combined to interpret images. Using single dynamic degree, comprehensive dynamic degree, transfer matrix, and choosing separating index, diversity index, evenness index, spatio-temporal change of land use was analyzed. Results showed that farmland area decreased dramatically. The area of residential land significantly increased. The farmland transformed mainly into the residential land, which showed that rapid urbanization took up a large amount of farmland. The separation degree of residential land reduced. The growth of residential land was more concentrated, and expanded outward from the city center gradually. The comprehensive dynamic degree, diversity index and evenness index of land use decreased.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Institutional subscriptions

References

  1. Badreldin, N., Goossens, R.: Monitoring land use/land cover change using multi-temporal Landsat satellite images in an arid environment: a case study of El-Arish. Egypt. Arab. J. Geosci. 7(5), 1671–1681 (2014)

    Article  Google Scholar 

  2. Yang, Y.J.: Studies on land use/land cover of Wushan county based on RS and GIS. Southwest University (2009)

    Google Scholar 

  3. Vittek, M., Brink, A., Donnay, F., Simonetti, D., Desclée, B.: Land cover change monitoring using Landsat MSS/TM satellite image data over west Africa between 1975 and 1990. Remote Sens. 6(1), 658–676 (2014)

    Article  Google Scholar 

  4. Xian, G., Homer, C., Fry, J.: Updating the 2001 national land cover database land cover classification to 2006 by using Landsat imagery change detection methods. Remote Sens. Environ. 113(6), 1133–1147 (2009)

    Article  Google Scholar 

  5. Hulley, G., Veraverbeke, S., Hook, S.: Thermal-based techniques for land cover change detection using a new dynamic MODIS multispectral emissivity product (MOD21). Remote Sens. Environ. 140(1), 755–765 (2014)

    Article  Google Scholar 

  6. Cockx, K., Voorde, T.V.D., Canters, F.: Quantifying uncertainty in remote sensing-based urban land-use mapping. Int. J. Appl. Earth Obs. Geoinf. 31(9), 154–166 (2014)

    Article  Google Scholar 

  7. Beykaei, S.A., Zhong, M., Zhang, Y.: Development of a land use extraction expert system through morphological and spatial arrangement analysis. Eng. Appl. Artif. Intell. 37, 221–235 (2015)

    Article  Google Scholar 

  8. Khalifa, I.H., Arnous, M.O.: Assessment of hazardous mine waste transport in west central Sinai, using remote sensing and GIS approaches: a case study of Um Bogma area. Egypt. Arab. J. Geosci. 5(3), 407–420 (2012)

    Article  Google Scholar 

  9. Zhao, W.W.: International comparison of land use research. J. Earth Environ. 1(3), 249–256 (2010)

    Google Scholar 

  10. Yu, X.X., Yang, G.S.: The advances and problems of land use and land cover change research in China. Progress Geogr. 21(1), 51–57 (2002)

    Google Scholar 

  11. Liu, J.Y.: Study on national resources & environment survey and dynamic monitoring using remote sensing. J. Remote Sens. 1(3), 225–230 (1997)

    Google Scholar 

  12. Wang, S.Y.: Study on land use/land cover change based on geo-spatiotemporal database in China. Institute of Remote Sensing Applications, Chinese Academy of Sciences (2002)

    Google Scholar 

  13. Rouse, J.W., Haas, R.H., Schell, J.A., Deering, D.W.: Monitoring Vegetation Systems in the Great Plains with ERTS, vol. 351, p. 309. Nasa Special Publication, Washington, D.C. (1974)

    Google Scholar 

  14. Zha, Y., Gao, J., Ni, S.: Use of normalized difference built-up index in automatically mapping urban areas from TM imagery. Int. J. Remote Sens. 24(3), 583–594 (2003)

    Article  Google Scholar 

  15. Xu, H.Q.: A study on information extraction of water body with the modified normalized difference water index (MNDWI). J. Remote Sens. 9(5), 589–595 (2005)

    Google Scholar 

  16. Wang, A.Z., Zhang, G.B., Zheng, J., Zhao, J.J.: Analysis on land use change in Xinxiang city. Res. Soil Water Conserv. 15(1), 163–165 (2008)

    Google Scholar 

  17. Wang, S.Y., Zhang, Z.X., Zhou, Q.B., Wang, C.Y.: Study on spatial-temporal features of land use/land cover change based on technologies of RS and GIS. J. Remote Sens. 6(3), 223–228 (2002)

    Google Scholar 

  18. Zhao, D.B., Liang, W., Yang, Q.K., Liu, A.L.: Analysis of dynamic landuse changes of past 30 years in the hilly area of Loess plateau. Bull. Soil. Water Conserv. 28(2), 22–26 (2008)

    Google Scholar 

  19. Li, Y.J.: Spatio-temporal changes analysis of land use in Pingdu county on RS and GIS. Shandong University (2008)

    Google Scholar 

  20. Chen, L.D., Fu, B.J.: The ecological significance and application of landscape connectivity. Chin. J. Ecol. 15(4), 37–42 (1996)

    Google Scholar 

  21. Guo, Q.Z., Jiang, W.G., Li, J., Chen, Y.H., Yi, W.B.: Evolvement of urban landscape pattern and its driving factors in Haidian district, Beijing from 1985 to 2006. Urban Environ. Urban Ecol. 21(1), 18–21 + 25 (2008)

    Google Scholar 

  22. Romme, W.H.: Fire and landscape diversity in subalpine forests of Yellowstoin national park. Ecol. Monogr. 52(2), 199–211 (1982)

    Article  Google Scholar 

  23. Wang, X.L., Xiao, D.N., Bu, R.C., Hu, Y.M.: Analysis on landscape patterns of Liaohe delta wetland. Acta Ecologica Sinica 17(3), 317–323 (1997)

    Google Scholar 

Download references

Acknowledgements

This research is financially supported by the Natural Science Foundation of Tianjin, China (Grants No. 13JCQNJC08600).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Qiaozhen Guo .

Editor information

Editors and Affiliations

Rights and permissions

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 2.5 International License (http://creativecommons.org/licenses/by-nc/2.5/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

The images or other third party material in this chapter are included in the chapter's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the chapter's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.

Reprints and permissions

Copyright information

© 2016 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Guo, Q., Luo, L., Zhao, H., Pan, Y., Bing, Q. (2016). Study on Spatio-Temporal Change of Land Use in Tianjin Urban Based on Remote Sensing Data. In: Bian, F., Xie, Y. (eds) Geo-Informatics in Resource Management and Sustainable Ecosystem. GRMSE 2015 2015. Communications in Computer and Information Science, vol 569. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-49155-3_23

Download citation

  • DOI: https://doi.org/10.1007/978-3-662-49155-3_23

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-49154-6

  • Online ISBN: 978-3-662-49155-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics