DocumentCode :
2877978
Title :
Dynamic Monitoring of Golf Course Land in Beijing Based on Remote Sensing Technology
Author :
Jingfang Zhang ; Yun Liu ; Shanshan Cui ; Zhiying Wang ; Qun Zhao
Author_Institution :
Beijing Key Lab. of new Technol. in Agric. Applic., Beijing Univ. of Agric., Beijing, China
fYear :
2012
fDate :
1-3 June 2012
Firstpage :
1
Lastpage :
4
Abstract :
In order to study the change dynamics of golf course land in Beijing nearly 30 years, firstly, we corrected and registered the geographical coordinates of TM image data in different time by ERDAS software, and enhanced the images to classify the images by using the supervised classification and unsupervised classification method, at the same time, reference with the Google Earth maps and the actual survey, and then extracted the information of the land change of golf course under the ARCGIS. The results indicated that over the past 20 years, the total areas of golf course land that underwent changes during the periods 1987-1998 and1999-2009 respectively were from 185.49 Ha to 337.41 Ha and from519.75 Ha to5275.98Ha. The dynamic change of golf course land in Beijing was quite obvious, and showed an increasing trend. In the initial period (1987-1999), the growth rate was 6.57%, in the rapid development period (2000-2003) and in the illegal development period (2004-2009), growth rate respectively was 31.02% and 62.42%. According to the transition matrices of golf course land change in Beijing for the period 2000~2009, it found that the transition area of golf course land from other land was very different: 1013.31ha from Built-up land, 534.24 ha from Woodland, 162.9 ha from Lawn irrigation, 377.01 ha from Grasslands, 1559.34 ha from Cultivated land and Orchard, 1628 ha from Other land, corresponding transferring rates were 19.21%, 10.13%, 3.09%, 7.15%, 29.56% and 30.86%. The conversion from Cultivated land and Orchard to the golf course land were the main transition. It could be concluded that the development process of golf course land had occupied the large Cultivated land and Orchard.
Keywords :
geophysical image processing; image classification; terrain mapping; vegetation mapping; AD 1987 to 2009; ARCGIS; Beijing; China; ERDAS software; Google Earth maps; Orchard; TM image data; cultivated land; dynamic change analysis; dynamic monitoring method; geographical coordinates; golf course land change matrices; grasslands; image classification; lawn irrigation; remote sensing technology; supervised classification method; unsupervised classification method; woodland; Cities and towns; Data mining; Feature extraction; Industries; Monitoring; Remote sensing; Software;
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.2012.6260544
Filename :
6260544
Link To Document :
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