Aboveground biomass and carbon stocks modelling using non-linear regression model

8th IGRSM International Conference and Exhibition on Geospatial & Remote Sensing

地球科学;计算机科学

Mohd Zaki, Nurul Ain^1 ; Abd Latif, Zulkiflee^1 ; Suratman, Mohd Nazip^2 ; Zainal, Mohd Zainee^3

Applied Remote Sensing and Geospatial Research Group, Centre for Studies Surveying Science and Geomatics, Faculty of Architecture, Planning and Surveying, Universiti Teknologi MARA, Selangor, Shah Alam

40450, Malaysia^1

Faculty of Applied Sciences, Universiti Teknologi MARA, Selangor, Shah Alam

40450, Malaysia^2

Centre for Studies Surveying Science and Geomatics, Faculty of Architecture, Planning and Surveying, Universiti Teknologi MARA, Perlis, Arau

02600, Malaysia^3

关键词: Biophysical parameters;    Canopy Height Models;    Coefficient of correlation;    Crown projection areas;    Non-linear regression;    Nonlinear regression models;    Remotely sensed data;    Tropical rain forest;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/37/1/012030/pdf
DOI  :  10.1088/1755-1315/37/1/012030

学科分类：计算机科学（综合）

来源: IOP

【 摘 要 】

Aboveground biomass (AGB) is an important source of uncertainty in the carbon estimation for the tropical forest due to the variation biodiversity of species and the complex structure of tropical rain forest. Nevertheless, the tropical rainforest holds the most extensive forest in the world with the vast diversity of tree with layered canopies. With the usage of optical sensor integrate with empirical models is a common way to assess the AGB. Using the regression, the linkage between remote sensing and a biophysical parameter of the forest may be made. Therefore, this paper exemplifies the accuracy of non-linear regression equation of quadratic function to estimate the AGB and carbon stocks for the tropical lowland Dipterocarp forest of Ayer Hitam forest reserve, Selangor. The main aim of this investigation is to obtain the relationship between biophysical parameter field plots with the remotely-sensed data using nonlinear regression model. The result showed that there is a good relationship between crown projection area (CPA) and carbon stocks (CS) with Pearson Correlation (p