The extraction of mangrove within intertidal zone based on multi-temporal HJ CCD images

The coastal zone in Beibu Gulf is dominated by diurnal tide and there exists the largest mangrove community in China. The frequently used mangrove extraction methods seldom took the tide influence into account which would lead to extracted area loss on single instantaneous remote sensing image. The loss cannot be ignored when the mangrove submerged time is long. This study took one portion of Beibu gulf coastline as research site. Four temporal HJ CCD images with different tide levels were selected for inundation mangrove extraction and coastal terrain classification. Based on the analysis of targets image-spectra, several decision factors were proposed, and subsequently a multi-layer decision tree was constructed. After the classification, target distributions at research site including the submerged mangrove were acquired. The overall classification precision was high up to 91.79%, and the Kappa coefficient was 0.9064. The obtained submerged mangrove area was 2.155 km2, which comprised 4.5% of total mangrove area and would be lost if the extraction were only applied on single image.

[1]  James H. Everitt,et al.  Evaluation of Airborne Video Imagery for Distinguishing Black Mangrove (Avicennia germinans) on the Lower Texas Gulf Coast , 1991 .

[2]  Liang Shi-chun Annotation of Mangrove Plant , 2003 .

[3]  P. Mayaux,et al.  An object-based method for mapping and change analysis in mangrove ecosystems , 2008 .

[4]  Cheng Hao-hao Decision Tree Model in Extraction of Mangrove Community Information Using Hyperspectral Image Data , 2007 .

[5]  D. Alongi Present state and future of the world's mangrove forests , 2002, Environmental Conservation.

[6]  Fethi Ahmed,et al.  Comparison of remote sensing techniques for alien vegetation mapping , 1998, Proceedings of the 1998 South African Symposium on Communications and Signal Processing-COMSIG '98 (Cat. No. 98EX214).

[7]  B. G. Long,et al.  A Technique for Mapping Mangroves with Landsat TM Satellite Data and Geographic Information System , 1996 .

[8]  C. Brodley,et al.  Decision tree classification of land cover from remotely sensed data , 1997 .

[9]  Tian Qing-jiu Vegetation Classification Based on High-resolution Satellite Image , 2007 .

[10]  S. Hay,et al.  Mapping land-cover over large areas using multispectral data derived from the NOAA-AVHRR: a case study of Nigeria , 1997 .

[11]  Bin-Yuan He,et al.  Critical tidal level for forestation with hypocotyl of Rhizophora stylosa Griff along the Guangxi coast of China , 2007, Ying yong sheng tai xue bao = The journal of applied ecology.

[12]  Li-hua Xia,et al.  Mangrove Wetland Changes in the Pearl River Estuary Using Remote Sensing , 2006 .

[13]  Jay Gao,et al.  A hybrid method toward accurate mapping of mangroves in a marginal habitat from SPOT multispectral data , 1998 .

[14]  N. Loneragan,et al.  Mapping and characterising subtropical estuarine landscapes using aerial photography and GIS for potential application in wildlife conservation and management , 2005 .

[15]  N. Loneragan,et al.  Spatial and temporal variation in distribution of mangroves in Moreton Bay, subtropical Australia: a comparison of pattern metrics and change detection analyses based on aerial photographs , 2003 .