In this paper, the decision tree classification based on the CART algorithm (Classification and Regression Tree) is used to extract the impervious surface area of Nantong city in Jiangsu Province in China. Impervious surface dynamic change nearly 25 years in Nantong city is researched using four periods Landsat images of 1990, 2003, 2008, and 2014. The results show that the classification precision based on the CART algorithm is higher, which can more accurately extract the impervious surface. During the 25 years, the trend of the impervious surface of Nantong is increased year by year. Urban construction and expansion is one of the driving forces of the impervious surface increase.
In many interpolation methods, with its simple interpolation principle, Inverse distance weighted (IDW) interpolation is one of the most common interpolation method. There are anisotropic spatial structures with actual geographical spatial phenomenon. When the IDW interpolation is used, anisotropic spatial structures should be considered. Geostatistical theory has a characteristics of exploring anisotropic spatial structures. In this paper, spatial interpolation approach based on IDW with anisotropic spatial structures is proposed. The DEM data is tested in this paper to prove reliability of the IDW interpolation considering anisotropic spatial structures. Experimental results show that IDW interpolation considering anisotropic spatial structures can improve interpolation precision when sampling data has anisotropic spatial structures feature.
Fuxian Lake located in the middle of Yunnan Province is second deepest lake in china. The water level of Fuxian Lake descends and its water area reduces in recent years owing to the climate changing. Therefore, it is crucial for rational utilization of lake resources to study the change trend of Fuxian Lake’s area. Landsat images from 1974 to 2014 were used to monitor Fuxian Lake’s area change. Monitoring results show that there are four apparent features of Fuxian Lake’s area: (1) Years in which Fuxian Lake’s area are larger are concentrated in 2006 to 2009. (2) From 1974 to 1990, Fuxian Lake’s area change has a trend of decrease. (3) From 1990 to 2005, Fuxian Lake’s area change shows a rise trend on the whole. (4) From 2005 to 2014, there is an obvious decrease trend of Fuxian Lake’s area change.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
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.