Geophysical mapping of the sediment architecture in the Orkhon Valley, Mongolia

Ground penetrating radar (GPR) and capacitive coupled resistivity (CCR) measurements were conducted in order to image subsurface structures in the Orkhon Valley, Central Mongolia. The data are extended by information from drill cores to the entire transects distinguishing different sedimentary environments in the valley. The Orkhon Valley is part of the high sensitive Steppe region in Central Mongolia, one of the most important cultural landscapes in Central Asia. There, archaeological, geoarchaeological and sedimentological research aims to reconstruct the landscape evolution and the interaction between man and environment during the last millennia since the first settlement. In May 2009 and 2010 geophysical surveys have been conducted including transects with lengths between 1.5 and 30 km crossing the entire valley and a kilometre-scaled grid in the southern part of the investigation area. The geoelectrical and GPR data revealed the existence of two layers characterized by different resistivity values and radar reflectors. The two layers do not only represent material contrasts, but also reflect the influence of sporadic permafrost which occurs in several areas of Mongolia. The results help to reconstruct the evolution of the braided Orkhon River and therefore give important hints to understand the environmental history of the Orkhon Valley.

Avaliação multitécnica em hidrogeologia ambiental e suas implicações na gestão de recursos hídricos subterrâneos

Mestrado em Engenharia Geotécnica e Geoambiente

Mapping the Pasture Steppe in Bayankhongor, Mongolia: comparison of classification methods, using Landsat-8 and geophysical data

Grasslands in semi-arid regions, like Mongolian steppes, are facing desertification and degradation processes, due to climate change. Mongolia’s main economic activity consists on an extensive livestock production and, therefore, it is a concerning matter for the decision makers. Remote sensing and Geographic Information Systems provide the tools for advanced ecosystem management and have been widely used for monitoring and management of pasture resources. This study investigates which is the higher thematic detail that is possible to achieve through remote sensing, to map the steppe vegetation, using medium resolution earth observation imagery in three districts (soums) of Mongolia: Dzag, Buutsagaan and Khureemaral. After considering different thematic levels of detail for classifying the steppe vegetation, the existent pasture types within the steppe were chosen to be mapped. In order to investigate which combination of data sets yields the best results and which classification algorithm is more suitable for incorporating these data sets, a comparison between different classification methods were tested for the study area. Sixteen classifications were performed using different combinations of estimators, Landsat-8 (spectral bands and Landsat-8 NDVI-derived) and geophysical data (elevation, mean annual precipitation and mean annual temperature) using two classification algorithms, maximum likelihood and decision tree. Results showed that the best performing model was the one that incorporated Landsat-8 bands with mean annual precipitation and mean annual temperature (Model 13), using the decision tree. For maximum likelihood, the model that incorporated Landsat-8 bands with mean annual precipitation (Model 5) and the one that incorporated Landsat-8 bands with mean annual precipitation and mean annual temperature (Model 13), achieved the higher accuracies for this algorithm. The decision tree models consistently outperformed the maximum likelihood ones.

Determination of in situ uniaxial compressive strength of coal seams based on geophysical data

The central issue for pillar design in underground coal mining is the in situ uniaxial compressive strength (sigma (cm)). The paper proposes a new method for estimating in situ uniaxial compressive strength in coal seams based on laboratory strength and P wave propagation velocity. It describes the collection of samples in the Bonito coal seam, Fontanella Mine, southern Brazil, the techniques used for the structural mapping of the coal seam and determination of seismic wave propagation velocity as well as the laboratory procedures used to determine the strength and ultrasonic wave velocity. The results obtained using the new methodology are compared with those from seven other techniques for estimating in situ rock mass uniaxial compressive strength.

Spatial modeling techniques for mapping and characterization of acid sulfate soils

Acid sulfate (a.s.) soils constitute a major environmental issue. Severe ecological damage results from the considerable amounts of acidity and metals leached by these soils in the recipient watercourses. As even small hot spots may affect large areas of coastal waters, mapping represents a fundamental step in the management and mitigation of a.s. soil environmental risks (i.e. to target strategic areas). Traditional mapping in the field is time-consuming and therefore expensive. Additional more cost-effective techniques have, thus, to be developed in order to narrow down and define in detail the areas of interest. The primary aim of this thesis was to assess different spatial modeling techniques for a.s. soil mapping, and the characterization of soil properties relevant for a.s. soil environmental risk management, using all available data: soil and water samples, as well as datalayers (e.g. geological and geophysical). Different spatial modeling techniques were applied at catchment or regional scale. Two artificial neural networks were assessed on the Sirppujoki River catchment (c. 440 km2) located in southwestern Finland, while fuzzy logic was assessed on several areas along the Finnish coast. Quaternary geology, aerogeophysics and slope data (derived from a digital elevation model) were utilized as evidential datalayers. The methods also required the use of point datasets (i.e. soil profiles corresponding to known a.s. or non-a.s. soil occurrences) for training and/or validation within the modeling processes. Applying these methods, various maps were generated: probability maps for a.s. soil occurrence, as well as predictive maps for different soil properties (sulfur content, organic matter content and critical sulfide depth). The two assessed artificial neural networks (ANNs) demonstrated good classification abilities for a.s. soil probability mapping at catchment scale. Slightly better results were achieved using a Radial Basis Function (RBF) -based ANN than a Radial Basis Functional Link Net (RBFLN) method, narrowing down more accurately the most probable areas for a.s. soil occurrence and defining more properly the least probable areas. The RBF-based ANN also demonstrated promising results for the characterization of different soil properties in the most probable a.s. soil areas at catchment scale. Since a.s. soil areas constitute highly productive lands for agricultural purpose, the combination of a probability map with more specific soil property predictive maps offers a valuable toolset to more precisely target strategic areas for subsequent environmental risk management. Notably, the use of laser scanning (i.e. Light Detection And Ranging, LiDAR) data enabled a more precise definition of a.s. soil probability areas, as well as the soil property modeling classes for sulfur content and the critical sulfide depth. Given suitable training/validation points, ANNs can be trained to yield a more precise modeling of the occurrence of a.s. soils and their properties. By contrast, fuzzy logic represents a simple, fast and objective alternative to carry out preliminary surveys, at catchment or regional scale, in areas offering a limited amount of data. This method enables delimiting and prioritizing the most probable areas for a.s soil occurrence, which can be particularly useful in the field. Being easily transferable from area to area, fuzzy logic modeling can be carried out at regional scale. Mapping at this scale would be extremely time-consuming through manual assessment. The use of spatial modeling techniques enables the creation of valid and comparable maps, which represents an important development within the a.s. soil mapping process. The a.s. soil mapping was also assessed using water chemistry data for 24 different catchments along the Finnish coast (in all, covering c. 21,300 km2) which were mapped with different methods (i.e. conventional mapping, fuzzy logic and an artificial neural network). Two a.s. soil related indicators measured in the river water (sulfate content and sulfate/chloride ratio) were compared to the extent of the most probable areas for a.s. soils in the surveyed catchments. High sulfate contents and sulfate/chloride ratios measured in most of the rivers demonstrated the presence of a.s. soils in the corresponding catchments. The calculated extent of the most probable a.s. soil areas is supported by independent data on water chemistry, suggesting that the a.s. soil probability maps created with different methods are reliable and comparable.

Use of a portable topographic mapping millimetre wave radar at an active lava flow

A ground-based millimetre wave radar, AVTIS (All-weather Volcano Topography Imaging Sensor), has been developed for topographic monitoring. The instrument is portable and capable of measurements over ranges up to similar to 7 km through cloud and at night. In April and May 2005, AVTIS was deployed at Arenal Volcano, Costa Rica, in order to determine topographic changes associated with the advance of a lava flow. This is the first reported application of mm-wave radar technology to the measurement of lava flux rates. Three topographic data sets of the flow were acquired from observation distances of similar to 3 km over an eight day period, during which the flow front was detected to have advanced similar to 200 m. Topographic differences between the data sets indicated a flow thickness of similar to 10 m, and a dense rock equivalent lava flux of similar to 0.20 +/- 0.08 m(3) s(-1).

Topographic and thermal mapping of volcanic terrain using AVTIS ground-based 94-GHz dual-mode radar/radiometric imager

The All-Weather Volcano Topography Imaging Sensor remote sensing instrument is a custom-built millimeter-wave (MMW) sensor that has been developed as a practical field tool for remote sensing of volcanic terrain at active lava domes. The portable instrument combines active and passive MMW measurements to record topographic and thermal data in almost all weather conditions from ground-based survey points. We describe how the instrument is deployed in the field, the quality of the primary ranging and radiometric measurements, and the postprocessing techniques used to derive the geophysical products of the target terrain, surface temperature, and reflectivity. By comparison of changing topography, we estimate the volume change and the lava extrusion rate. Validation of the MMW radiometry is also presented by quantitative comparison with coincident infrared thermal imagery.

High Royds: an integrated, analytical approach for mapping the unmarked burials of a pauper cemetery

Applying geophysical techniques to detect and map the physical extent of individual unmarked graves proves difficult in many cases. The success of individual geophysical techniques for detecting unmarked graves may be due to a poor understanding of the nature of the graves themselves, the context in which they lie in, and temporal changes to the burial state. Given the unpredictability of these variables, it is surprising that grave prospection is often undertaken using only a single method. This paper presents a multi-methodological survey strategy for detecting unmarked burials and utilises an analytical approach for visualising and evaluating survey results.

Still searching for graves: an analytical strategy for interpreting geophysical data used in the search for “unmarked” graves

Searching for and mapping the physical extent of unmarked graves using geophysical techniques has proven difficult in many cases. The success of individual geophysical techniques for detecting graves depends on a site-by-site basis. Significantly, detection of graves often results from measured contrasts that are linked to the background soils rather than the type of archaeological feature associated with the grave. It is evident that investigation of buried remains should be considered within a 3D space as the variation in burial environment can be extremely varied through the grave. Within this paper, we demonstrate the need for a multi-method survey strategy to investigate unmarked graves, as applied at a “planned” but unmarked pauper’s cemetery. The outcome from this case study provides new insights into the strategy that is required at such sites. Perhaps the most significant conclusion is that unmarked graves are best understood in terms of characterization rather than identification. In this paper, we argue for a methodological approach that, while following the current trends to use multiple techniques, is fundamentally dependent on a structured approach to the analysis of the data. The ramifications of this case study illustrate the necessity of an integrated strategy to provide a more holistic understanding of unmarked graves that may help aid in management of these unseen but important aspects of our heritage. It is concluded that the search for graves is still a current debate and one that will be solved by methodological rather than technique-based arguments.

Geological and geophysical data integration for delimitation of mineralized areas in a supergene manganese deposits

Geophysical methods are widely used in mineral exploration. This paper discusses the results of geological and geophysical studies in supergene manganese deposits of southern Brazil. Mineralized zones as described in geological surveys were characterized as of low resistivity (20 Omega.m) and high chargeability (30ms), pattern found also in oxides and sulfite mineral deposits. Pseudo-3D modeling of geophysical data allowed mapping at several depths. A relationship between high chargeability and low resistivity may define a pattern for high grade gonditic manganese ore. Large areas of high chargeability and high resistivity may result in accumulation of manganese and iron hydroxides, due to weathering of the gonditic ore, dissolution, percolation and precipitation.