• DocumentCode
    2880544
  • Title

    Remote Sensing Based Land Use Change and Landscape Pattern Analysis in Taicang County, China

  • Author

    Li Weilin ; Feng Yongjiu ; Chen Yao

  • Author_Institution
    Coll. of Marine Sci., Shanghai Ocean Univ., Shanghai, China
  • fYear
    2012
  • fDate
    1-3 June 2012
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    Based on Landsat TM images, the land use change and landscape pattern of Taicang County, Jiangsu Province in 1995 to 2008, have been investigated using the supervised classification and Fragstats. Images processing including study area resizing, radiometric correction, geometric correction, and supervised classification have been conducted. The land use categories in Taicang were classified into four types, including built land, vegetation land with high water, vegetation land with low water, and water body. The overall accuracies of the supervised classification are 97.58% and 89.35% for 2001 and 2008, respectively. Using eight landscape metrics proposed by the FRAGSTATS, i.e. NP, PD, LPI, TE, LSI, PAFRAC, SHDI, and SIDI, the landscape pattern of Taicang County have been analyzed in detail.
  • Keywords
    geophysical image processing; image classification; land use planning; pattern recognition; radiometers; terrain mapping; vegetation; vegetation mapping; AD 1995 to 2008; China; Fragstats; Jiangsu Province; LPI; LSI; Landsat TM images; NP; PAFRAC; PD; SHDI; SIDI; TE; Taicang County; geometric correction; high water vegetation land; image processing method; land use change; landscape metrics; landscape pattern analysis; low water vegetation land; radiometric correction; remote sensing; supervised classification method; Cities and towns; Economics; Feature extraction; Indexes; Remote sensing; Vegetation mapping; Water resources;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Remote Sensing, Environment and Transportation Engineering (RSETE), 2012 2nd International Conference on
  • Conference_Location
    Nanjing
  • Print_ISBN
    978-1-4673-0872-4
  • Type

    conf

  • DOI
    10.1109/RSETE.2012.6260680
  • Filename
    6260680