Land use information extraction and spatio-temporal variation analysis of Poyang Lake Basin based on remote sensing

Hai Liu; Huiqiong Xia; Bo Zhou

doi:10.1117/12.2035679

26 October 2013 Land use information extraction and spatio-temporal variation analysis of Poyang Lake Basin based on remote sensing

Hai Liu, Huiqiong Xia, Bo Zhou

Author Affiliations +

Proceedings Volume 8921, MIPPR 2013: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications; 892113 (2013) https://doi.org/10.1117/12.2035679
Event: Eighth International Symposium on Multispectral Image Processing and Pattern Recognition, 2013, Wuhan, China

Abstract

Poyang Lake Basin is the biggest freshwater lake in China and a significant wetland of the world. The study of the land use changes on there is a great significance for regional sustainable development. In this paper, using the RS image as the main data source, the study area was divided into six land use types. With the acquired land use data of three periods, the spatio-temporal dynamic variation characteristics were analyzed with the area changes and land use dynamic index (LUDI). The analysis shows that the largest land use type is woodland, followed by cultivated land and grassland, and area of the rest types all account for less than 10%. Through the analysis of the area transfer matrix of LUCC, it shows that woodland and construction land increased in each period while cultivated land reduced. Unused land increased a lot during 1990 to 2000 before decreased dramatically during 2000 to 2008, grassland and water experienced a significant increase after an obvious decline and came out to increase finally. The analysis of LUDI indicates that construction land changed the most quickly, followed by unused land and cultivated land, yet the other land use types changed slowly.

Citation Download Citation

Hai Liu, Huiqiong Xia, and Bo Zhou "Land use information extraction and spatio-temporal variation analysis of Poyang Lake Basin based on remote sensing", Proc. SPIE 8921, MIPPR 2013: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications, 892113 (26 October 2013); https://doi.org/10.1117/12.2035679

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available