Estimating and Mapping Carbon Stock Using3S Technology in Bhawal National Park of Bangladesh
【摘要】：Estimation of carbon stock is important for understanding the global carbon cycle. All countries committed to UNFCCC and Kyoto Protocol and participating in REDD should update the inventories of emissions of the greenhouse gases and estimate the amount of carbon stock. But accurate carbon stock estimation from satellite imagery is still a challenge. Thus, this study aims to develop a method to estimate amount of carbon stock in the Bhawal National park of Gazipur, Bangladesh.
LANDSAT TM images were used for the study. Spectral features of satellite images were used based on the required bands and topographic factors. Total carbon stock (both above ground and below ground carbon stock) was estimated using allometric equation from the DBH and height measured in the field. Total30plots were surveyed in the field and of those20plots were used to develop linear regression model of the carbon stock of Shorea robusta species. The relationship between field data (estimated) and image data (predicted carbon) was established using carbon stock of20plots and spectral characteristics derived from the image. Object based image analysis was carried out in the satellite image to obtain Digital Number (DN). A linear regression model was developed between the calculated carbon, and required spectral characteristics of the image and topographic factors (slope, elevation and aspect) in the study area.
The study was done only with Shorea robusta and that's why classification was not carried out with other species available in the study area. So, carbon stock derived from LANDSAT images was used to develop a linear regression model of Shorea robusta. The model was applied to validate carbon stock of the rest10plots. The developed regression model was significant and yield high coefficient of determination in Shorea robusta. The model was applied to estimate carbon map with carbon stock approximately61.40MgCha-1. The linear model explained61.66%of the predicted carbon. Shadow content, use of general allometric equation and time lag in data collection and also image download, inconsiderable solar angle, etc. are the major sources of error for this study to estimate carbon stock. Therefore, carbon stock estimation in tropical forest is practicable applying LANDSAT TM satellite images.