Estimating forest canopy density using LANDSAT TM data based on sub-compartment objects

Author

Cunjian Yang ; He Huang ; Shaou Han ; Jing Ni

Author_Institution

Res. Center of Remote Sensing & GIS Applic., Sichuan Normal Univ., Chengdu, China

fYear

2013

fDate

21-26 July 2013

Firstpage

999

Lastpage

1002

Abstract

Remote sensing opens a new method for obtaining forest canopy density. The forest resource field inventory data and simultaneous LANDSAT TM data were used to discover the model of estimating forest canopy density based on remote sensing here in Shimian county, Sichuan province, P.R.of China. A lot of derivative data were created from LANDSAT TM data. 1204 forest sub-compartments with inner homogeneity were used as samples for correlation analysis. According to the correlation analysis, TM7, P3, MVI3 and TM_7/2 value of 804 forest sub-compartment samples were used to formulate the model of estimating the forest canopy density by using stepwise regression analysis. The accuracy of the model was 68.69%. which was gotten by using 400 sub-compartment samples.

Keywords

correlation methods; forestry; regression analysis; vegetation mapping; China; LANDSAT TM data; MVI3 data; P3 data; Shimian county; Sichuan province; TM7 data; TM_7/2 data; correlation analysis; forest canopy density estimation; forest resource field inventory data; forest subcompartments; remote sensing; stepwise regression analysis; subcompartment objects; Biological system modeling; Correlation; Earth; Indexes; Remote sensing; Satellites; Vegetation mapping; Correlation analysis; Forest canopy density; Forest sub-compartment; LANDSAT TM; Regression analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Geoscience and Remote Sensing Symposium (IGARSS), 2013 IEEE International

Conference_Location

Melbourne, VIC

ISSN

2153-6996

Print_ISBN

978-1-4799-1114-1

Type

conf

DOI

10.1109/IGARSS.2013.6721331

Filename

6721331