Serwan Mj Baban

Modeling methane emission from wetlands in North-Eastern New South Wales, Australia using Landsat ETM+.

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.

Monitoring coastal wetland communities in north-eastern NSW using ASTER and Landsat satellite data

The coastal wetland communities of north-eastern New South Wales (NSW) Australia exist in a subtropical climate with high biodiversity and are affected by anthropogenic and natural stressors such as urbanization and climate change. The aim of the research is to map and monitor the coastal wetland communities in north eastern NSW using satellite data. Advanced Spaceborne Thermal Emission and Reflectance Radiometer, Landsat ETM+ and Landsat TM satellite imagery of November 2003, June 2001 and September 1989 respectively were used to identify and monitor the wetland communities. Supervised classification was performed using the maximum likelihood standard algorithm. Normalized Difference Vegetation Index was produced and the health of the wetland vegetation was evaluated. The wetland maps present significant changes in the coastal wetland communities in the months of September 1989, June 2001 and November 2003. This information could be used by coastal wetland managers in order to enhance the management of these ecosystems.