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Estimating and Mapping Carbon Stock Using3S Technology in Bhawal National Park of Bangladesh

作　者: Yusuf Chowdury
导　师: 冯仲科
学　校: 北京林业大学
专　业: 森林经理学
关键词: Carbon Remote Sensing Shorea robusta GIS GPS linear regressionequation carbon stock model LANSAT TM image
分类号: S759.91
类　型: 硕士论文
年　份: 2012年
下　载: 8次
引　用: 0次
阅　读: 论文下载

内容摘要

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.

全文目录

ABSTRACT  4-5
TABLE OF CONTENTS  5-7
LIST OF ACRONYMS  7-8
INTRODUCTION  8-24
  1.1. Background  8-9
  1.2. Statement of the Problem  9
  1.3. Justification for the Study  9-10
  1.4. Aim of the Research  10-11
    1.4.1. Objectives  10
    1.4.2. The Specific Objectives  10-11
  1.5. The Study Area  11-13
  1.6. Review of Published Articles  13-24
    1.6.1. Biomass and carbon  13
    1.6.2. Remote sensing  13
    1.6.3. Geographic Information systems (GIS)  13-16
    1.6.4. LANDSAT TM Image  16-17
    1.6.5. Global Climate change and carbon stock  17-20
    1.6.6. Forest area of Bangladesh  20-21
    1.6.7. Status of carbon stocks in Bangladesh  21-22
    1.6.8. Remote sensing as a tool of measuring carbon stocks  22-24
2. MATERIALS AND METHOD  24-32
  2.1. Satellite Data  24
  2.2. Software Used To Process Satellite Data  24-25
  2.3. Field Equipments  25
  2.4. Image Pre-processing  25
  2.5. Image Mosaic and Subset  25-26
  2.6. Image Fusion  26
  2.7. Finding Digital Number,image characteristics and topographic factors  26-27
  2.8. Research Method  27
  2.9. Filed Work  27-29
    2.9.1. Sampling Design  27-28
    2.9.2. Data Collection from the Field  28
    2.9.3. Sampling Plots  28-29
    2.9.4. Field Data Analysis  29
  2.10. Biomass and Carbon Stock Calculation  29-30
    2.10.1. Aboveground biomass  29
    2.10.2. Belowground biomass  29-30
  2.11. Regression Analysis and Validation of the Model  30-32
3. RESULTS AND DISCUSSIONS  32-36
  3.1. Usability of LANDSAT Image  32
  3.2. Spectral Means of the Image in Every Band  32
  3.3. Model Developments and Validation  32-35
    3.3.1. Development of model  32-33
    3.3.2. The precision analysis of the model  33
    3.3.3. Model Summary  33-34
    3.3.4. Validation of the model  34-35
  3.4. Carbon stock mapping  35-36
4. RESULTS AND ANALYSIS  36-40
  4.1. Analysis of the several limiting factors of satellite images  36
  4.2. Model analysis  36-37
  4.3. Analysis of carbon stock map  37
  4.4. Allometric equations  37-38
  4.5. Limitation of the research  38-40
5. CONCLUSIONS AND RECOMMENDATIONS  40-42
  5.1. Conclusions  40
  5.2. Recommendations  40-42
REFERENCES  42-50
APPENDICES  50-54
ACKNOWLEDGEMENTS  54-56
CANDIDATE'S RESUME  56-58
SUPERVISOR'S RESUME  58

Estimating and Mapping Carbon Stock Using3S Technology in Bhawal National Park of Bangladesh

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