Skip to main content

Regression and analytical models for estimating mangrove wetland biomass in South China using Radarsat images

Buy Article:

$60.90 plus tax (Refund Policy)

Abstract:

Mangrove wetlands have been rapidly diminishing because of human pressures worldwide. The Guangdong Province in South China, which has the largest area of mangrove wetlands in the nation, is under severe threat as a result of rapid urbanization and economic development. In this paper, comparisons were made between optical Landsat TM images and Radarsat fine-mode images for estimating wetland biomass. Regression and analytical models were used to establish the relationships between remote sensing data and wetland biomass. The optimal parameter values for the analytical model were determined using genetic algorithms. Experiments indicate that the models using Radarsat fine-mode images have significant accuracy improvement in terms of Root Mean-Square Error (RMSE) whereas the use of the single Normalized Difference Vegetation Index (NDVI) may produce serious errors in biomass estimation. The Radarsat images can obtain more accurate trunk information about mangrove forests because of higher resolution and side-looking geometry. The use of genetic algorithms can help to decompose backscatter into vegetation and soil backscattering, which is very useful for ecological modelling.

Document Type: Research Article

DOI: http://dx.doi.org/10.1080/01431160701227638

Affiliations: 1: School of Geography and Planning, Sun Yat-sen University, Guangzhou 510275, PR China,Guangzhou Institute of Geography, Guangzhou 510070, PR China 2: Centre of Urban Planning and Environmental Management, The University of Hong Kong, Hong Kong SAR, PR China 3: School of Geography and Planning, Sun Yat-sen University, Guangzhou 510275, PR China 4: Guangzhou Institute of Geography, Guangzhou 510070, PR China

Publication date: January 1, 2007

More about this publication?
tandf/tres/2007/00000028/00000024/art00009
dcterms_title,dcterms_description,pub_keyword
6
5
20
40
5

Access Key

Free Content
Free content
New Content
New content
Open Access Content
Open access content
Subscribed Content
Subscribed content
Free Trial Content
Free trial content
Cookie Policy
X
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more