Satellite earth observation is being increasingly used to monitor forests across the world. Freely available Landsat data stretching back four decades, coupled with advances in computer processing capabilities, has enabled new time-series techniques for analyzing forest change. Typically, these methods track individual pixel values over time, through the use of various spectral indices. This study examines the utility of eight spectral indices for characterizing fire disturbance and recovery in sclerophyll forests, in order to determine their relative merits in the context of Landsat time-series. Although existing research into Landsat indices is comprehensive, this study presents a new approach, by comparing the distributions of pre and post-fire pixels using Glass's delta, for evaluating indices without the need of detailed field information. Our results show that in the sclerophyll forests of southeast Australia, common indices, such as the Normalized Difference Vegetation Index (NDVI) and the Normalized Burn Ratio (NBR), both accurately capture wildfire disturbance in a pixel-based time-series approach, especially if images from soon after the disturbance are available. However, for tracking forest regrowth and recovery, indices, such as NDVI, which typically capture chlorophyll concentration or canopy 'greenness', are not as reliable, with values returning to pre-fire levels in 3-5 years. In comparison, indices that are more sensitive to forest moisture and structure, such as NBR, indicate much longer (8-10 years) recovery timeframes. This finding is consistent with studies that were conducted in other forest types. We also demonstrate that additional information regarding forest condition, particularly in relation to recovery, can be extracted from less well known indices, such as NBR2, as well as textural indices incorporating spatial variance. With Landsat time-series gaining in popularity in recent years, it is critical to understand the advantages and limitations of the various indices that these methods rely on.

The rapid increase in the number and volume of chemical substances being used in modern society has been accompanied by a large number of potentially hazardous chemicals being found in environmental samples. In Vietnam, the monitoring of chemical substances is mainly limited to a small number of known pollutants in spite of rapid economic growth and urbanization, and there is an urgent need to examine a large number of chemicals to prevent impacts from expanding environmental pollution. However, it is difficult to analyze a large number of chemicals using existing methods, because they are time consuming and expensive. In the present study, we determined 1153 substances to grasp a pollution picture of microcontaminants in the aquatic environment. To achieve this objective, we have used two comprehensive analytical methods: (1) solid-phase extraction (SPE) and LC-TOF-MS analysis, and (2) SPE and GC-MS analysis. We collected 42 samples from northern (the Red River and Hanoi), central (Hue and Danang), and southern (Ho Chi Minh City and Saigon-Dongnai River) Vietnam. One hundred and sixty-five compounds were detected at least once. The compounds detected most frequently (>40 % samples) at μg/L concentrations were sterols (cholesterol, beta-sitosterol, stigmasterol, coprostanol), phthalates (bis(2-ethylhexyl) phthalate and di-n-butyl phthalate), and pharmaceutical and personal care products (caffeine, metformin). These contaminants were detected at almost the same detection frequency as in developed countries. The results reveal that surface waters in Vietnam, particularly in the center of large cities, are polluted by a large number of organic micropollutants, with households and business activities as the major sources. In addition, risk quotients (MEC/PNEC values) for nonylphenol, sulfamethoxazole, ampicillin, acetaminophen, erythromycin and clarithromycin were higher than 1, which indicates a possibility of adverse effects on aquatic ecosystems.

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