The objective of this study is to exploit the new features of ALOS PALSAR dual polarization mode data and to develop
novel classification method for forest mapping in heterogeneous areas. A test site was selected in Fujian province in
southeast of China. Traditionally, forest is detected by its low coherence, low temporal variability of the backscattering
intensity and mediate backscattering intensity. However, the analyses in this paper indicate that it is not possible to
discriminate forest from nonforest by any single PALSAR feature in this test site. After examination the dependences of
the multitemporal backscatter intensity, the polarimetric parameters and the interferometric coherence on different land
cover types, a hierarchical classification method is proposed for coastal forest and hilly forest mapping. The forest maps
are validated by forest inventory data and SPOPT-5 images. The results show that multitemporal PALSAR dual
polarization data can accurate maps for coastal forest in flat areas using the proposed method. The capability to map
forest in hilly regions is still limited.
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.