Monitoring post-tsunami vegetation recovery in Phang-Nga province,Thailand, based on IKONOS imagery and field investigations – a contribution to the analysis of tsunami vulnerability of coastal ecosystems

A major tsunami in December 2004 devastated the coastal ecosystems along the Andaman Sea coast of Thailand. Since intact coastal ecosystems provide many important services for local communities at the Andaman Sea, it is crucial to investigate to what extent (in terms of percentage area and speed) the affected ecosystems were capable of recovering after the tsunami. Field measurements and multi-date IKONOS imagery were used to estimate the recovery and succession patterns of coastal vegetation types in the Phang-Nga province of Thailand, three years after the tsunami. Thus, this study contributes to a holistic understanding of the ecological vulnerability of the coastal area to tsunamis. A zone-based change detection approach is applied by comparing two change detection techniques: the first method involves the calculation of a recovery rate based on multi-temporal TNDVI (transformed normalized difference vegetation index) images (TNDVI approach), whereas the second approach is a combined approach of the change vector analysis (CVA). Although these two methods provide different types of information (quantitative for the TNDVI approach, qualitative for the CVA), they are comparable in terms of results and accuracies. The results reveal that recovery processes vary based on the type of the ecosystem and, furthermore, are strongly influenced by human activities. Grasslands, coconut plantations and the mixed vegetation cover could recover faster than the mangroves and casuarina forests. Among the forest ecosystems, recovery rates of casuarina forests were higher than for mangroves, but the recovery area was smaller. This study also discusses the potential and some limitations and inaccuracies of applying high-resolution optical imagery for assessing vegetation recovery at a local scale.     

Strain and temperature sensors using multimode optical fiber Bragg gratings and correlation signal processing

Multimode fiber optic Bragg grating sensors for strain and temperature measurements using correlation signal processing methods have been developed. Two multimode Bragg grating sensors were fabricated in 62/125 /spl mu/m graded-index silica multimode fiber; the first sensor was produced by the holographic method and the second sensor by the phase mask technique. The sensors have signal reflectivity of approximately 35% at peak wavelengths of 835 nm and 859 nm, respectively. Strain testing of both sensors has been done from 0 to 1000 /spl mu//spl epsiv/ and the temperature testing from -40 to 80/spl deg/C. Strain and temperature sensitivity values are 0.55 pm//spl mu//spl epsi/ and 6 pm//spl deg/C, respectively. The sensors are being applied in a power-by-light hydraulic valve monitoring system.     

Photocatalytic activity of La-doped ZnO nanostructure materials synthesized by sonochemical method

ZnO nanostructure materials doped with different La contents were synthesized by sonochemical method. The products were characterized by X-ray diffraction(XRD), scanning electron microscopy(SEM),transmission electron microscopy(TEM), Raman spectroscopy, and Fourier transform infrared spectroscopy(FTIR). In this research, XRD patterns of pure ZnO and La-doped ZnO are specified as hexagonal wurtzite ZnO structure with no detection of La2O3 phase. SEM and TEM characterization revealed the flower shape of pure ZnO built-up from petals of hexagonal prisms with hexagonal pyramid tips. Upon doping with La, the flower-shaped ZnO is broken into individual 1D prism-like nanorods. Photocatalytic activities of the as-synthesized products were determined by measuring the degradation of methylene blue(MB) under ultraviolet–visible(UV) light irradiation.Among them, the 2.0 mol% La-doped ZnO shows better photocatalytic properties than any other products.