Natural wetlands constitute a major source of methane emission to the atmosphere, accounting for approximately 32 ± 9.4% of the total methane emission. Estimation of methane emission from wetlands at both local and national scale using process-based models would improve our understanding of their contribution to global methane emission. The aim of the study is to estimate the amount of methane emission from the coastal wetlands in north-eastern New South Wales (NSW), Australia, using Landsat ETM+ and to estimate emission with a temperature increase. Supervised wetland classification was performed using the Maximum Likelihood Standard algorithm. The temperature dependent factor was obtained through land surface temperature (LST) estimation algorithms. Measurements of methane fluxes from the wetlands were performed using static chamber techniques and gas chromatography. A process-based methane emission model, which included productivity factor, wetland area, methane flux, precipitation and evaporation ratio, was used to estimate the amount of methane emission from the wetlands. Geographic information system (GIS) provided the framework for analysis. The variability of methane emission from the wetlands was high, with forested wetlands found to produce the highest amount of methane, i.e., 0.0016 ± 0.00009 teragrams (Tg) in the month of June, 2001. This would increase to 0.0022 ± 0.0001 Tg in the month of June with a 1 °C rise in mean annual temperature by the year 2030 in north-eastern NSW, Australia.
Journal article
Modelling methane emission from wetlands in north-eastern NSW, Australia using Landsat ETM+
Remote Sensing, Vol.2(5), pp.1378-1399
2010
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Abstract
Details
- Title
- Modelling methane emission from wetlands in north-eastern NSW, Australia using Landsat ETM+
- Creators
- Clement E Akumu - Southern Cross UniversitySumith Pathirana - Southern Cross UniversitySerwan MJ Baban - University of KurdistanDaniel J Bucher - Southern Cross University
- Publication Details
- Remote Sensing, Vol.2(5), pp.1378-1399
- Identifiers
- 1864; 991012821466602368
- Academic Unit
- School of Environment, Science and Engineering; Marine Ecology Research Centre; Faculty of Science and Engineering
- Resource Type
- Journal article