Comparing satellite and ground-based observations of paroxysmal degassing events at Etna volcano, Italy

Mount Etna, Italy, is one of the most active volcanoes in the world, and is also regarded as one of the strongest volcanic sources of sulfur dioxide (SO2) emissions to the atmosphere. Since October 2004, an automated ultraviolet (UV) spectrometer network (FLAME) has provided ground-based SO2 measurements with high temporal resolution, providing an opportunity to validate satellite SO2 measurements at Etna. The Ozone Monitoring Instrument (OMI) on the NASA Aura satellite, which makes global daily measurements of trace gases in the atmosphere, was used to compare SO2 amount released by the volcano during paroxysmal lava-fountaining events from 2004 to present. We present the first comparison between SO2 emission rates and SO2 burdens obtained by the OMI transect technique and OMI Normalized Cloud-Mass (NCM) technique and the ground-based FLAME Mini-DOAS measurements. In spite of a good data set from the FLAME network, finding coincident OMI and FLAME measurements proved challenging and only one paroxysmal event provided a good validation for OMI. Another goal of this work was to assess the efficacy of the FLAME network in capturing paroxysmal SO2 emissions from Etna, given that the FLAME network is only operational during daylight hours and some paroxysms occur at night. OMI measurements are advantageous since SO2 emissions from nighttime paroxysms can often be quantified on the following day, providing improved constraints on Etna’s SO2 budget.

Quickbird satellite imagery for riparian management : characterizing riparian filter strips and detecting concentrated flow in an agricultural watershed

Riparian ecology plays an important part in the filtration of sediments from upland agricultural lands. The focus of this work makes use of multispectral high spatial resolution remote sensing imagery (Quickbird by Digital Globe) and geographic information systems (GIS) to characterize significant riparian attributes in the USDA’s experimental watershed, Goodwin Creek, located in northern Mississippi. Significant riparian filter characteristics include the width of the strip, vegetation properties, soil properties, topography, and upland land use practices. The land use and vegetation classes are extracted from the remotely sensed image with a supervised maximum likelihood classification algorithm. Accuracy assessments resulted in an acceptable overall accuracy of 84 percent. In addition to sensing riparian vegetation characteristics, this work addresses the issue of concentrated flow bypassing a riparian filter. Results indicate that Quickbird multispectral remote sensing and GIS data are capable of determining riparian impact on filtering sediment. Quickbird imagery is a practical solution for land managers to monitor the effectiveness of riparian filtration in an agricultural watershed.