Articles

Kaybarkuh (Mount Kaybar) consists of intrusive igneous bodies with two age periods, located in North of Dasht-e-Bayaz left-lateral fault terminal. The spatial and structural analysis of fractures and dike networks may allow for the accurate identification of mineralization zones in the area. This study aims to characterize lineament network in the study area by automatic method using multispectral satellite images from Landsat 8 Operational Land Imager (OLI), visual extraction of lineaments from Landsat-8 and SENTINEL-2 images, and extraction of drainage network as lineament based on digital elevation models (DEMs) and their validation, compared with fault network of the area. The results showed that there is a significant relationship between the trend of studied lines in the region by the three methods mentioned and the overall trend is about N330⁰. This can indicate a tensile regime with a trend perpendicular to the mentioned orientation, which results from the activity of the Dasht-e-Bayaz fault. Finding more evidences requires further studies.

The Murray Darling Basin Authority (MDBA) currently has been using a discrete field sampling technique for water quality monitoring that is expensive, time consuming and may not adequately represent the spatial variability of water quality relative to the entire water body. A pilot project was executed to assess the effectiveness of using earth observation data, supported by archived field-based observations for quantitative estimation of Water Quality Parameters (WQP) and detection of algal blooms in the River Murray. The selected pilot study area includes a 100km stretch of the River Murray between the Hume Dam and Yarrawonga Weir. The time frame for the archived field samples was between November 2008 and March 2011, when major algal blooms were occurring in this stretch of the Murray River.Analysis of the 2009 data shows that waters in sites in the Murray River downstream of the Hume Dam to the Yarrawonga Weir show more temporal than spatial variability in Chl-a and PC levels. The Chl-a concentration is relatively less in the Yarrawonga Weir than in the Murray River. The scatter plot of PC vs. Turbidity suggests that PC is a more significant parameter for the detection of Cyanobacteria than Chl-a. The field data represents the temporal bio-optical variability across the 2009 algal bloom events by successfully capturing the co-variations among Chlorophyll-a, Chycocyanin and turbidity at pre, during and post bloom conditions. The methodology has proved that the usefulness of an integrated earth observation and field based WQP technique to accurately map algal bloom events. The long term MDBA RMWQMP data for the 2009 bloom event is found partially compatible to the NOW Pilot study data in that only the data for the Heywood site that was used together for testing the WQP monitoring technique. The incompatibility of the RMWQMP data downstream of Yarrawonga Weir may be due to differing techniques used for determining Chlorophyll. The 2010 data was suitable for testing the technique for complex spatial bio-optical variability during the peak of the bloom in a large water storage. Lack of Chlorophyll measurements in 2010 data poses challenges in interpreting the relationship of bio-optical variability with the spatial distributions of bio-optical parameters. As relational parameters are absent, local information and expert advice will be required to develop plausible assumptions between the Chlorophyll - Phycocyanin relationship. The field sampled data for the 2010 bloom event acquired from the Hume Dam was used for comparative investigation of both moderate resolution sensors (MODIS and MERIS) and high resolution sensors (TM/TM+). The 2009 bloom event field samples of sites in the Yarrawonga Weir was used as an input with MODIS and MERIS and the data from all the sites was applied with TM/TM+. This paper will present an integrated earth observation and field based WQP technique to accurately map algal bloom events, and discuss challenges for real time earth observation data initiatives and future collaborative projects.