Title :
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
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 TM7/2 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; TM7/2 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;
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2013 IEEE International
Conference_Location :
Melbourne, VIC
Print_ISBN :
978-1-4799-1114-1
DOI :
10.1109/IGARSS.2013.6721331
