Arctan (United States)

In the Mediterranean basin, where forest fires are dominant, the number of fires increased primarily in summer, dry spring and autumn.Regarding the latest researches, the period between June and September is the fire season in the Mediterranean basin, where the Mediterranean climate is mainly observed.According to mentioned studies, increased atmospheric instability caused by the effect of climate change, increased temperature within heat waves, and increased drought elevated the number of wildfires in the world.In this study, the forest fires that took place in the Summer of 2021, in Mula, Turkey will be analyzed under the scope of the capabilities of new-generation meteorological satellites to understand the effects of wildfires.With the sample data of Meteosat Third Generation (MTG) and Metop-SG satellites, which are planned to be placed in orbit at the end of 2022 and become operational in 2023, new capabilities for monitoring active fires were analyzed.

Induced Polarisation (IP) and Transient Electromagnetism (TEM) are among the most widely used ground electrical geophysics methods in Australia, being specialised in detecting conductive and chargeable targets such as sulphide deposits. A key challenge of IP T often a chargeable body is not a sulphide deposit but a graphite-rich formation of black shale or clays. As these shale deposits are undesirable targets, distinguishing by physical methods such as drilling is exhaustive on exploration resources. Graphite-rich shales, which plague induced polarisation surveys, cannot be distinguished from sulphide mineralisatio by existing electrical methods. The effect of disseminated sulphide grains acting as a diode in the presence of two electrical signals of nonharmonically related frequencies was originally studied in the 1970s. There is some evidence that shales produce a strictly linear response. This contrasts to the non-linear response of sulphide-rich rocks which generates additional signals in the frequency domain. A laboratory-based reinvestigation into non-linear properties of sulphides has been undertaken with a view towards field application. Variable frequencies and signal strengths were used to validate the method, based initially on the processes described in White (1974). The intermodulation mixing terms produced as a response by sulphide mineralised deposits in this laboratory-based investigation may allow for electrical distinction of sulphides from non-mineralised shales and clays. The application of a direct current (DC) bias to either signal increased the detectability of non-linear responses, allowing for a lower current density threshold for measurement. The magnitude of the non-linear signal detected provides a basis for field testing of this previously unutilised electrical property, with the eventual aim to providing a method for greatly reducing the number of drill targets barren of mineralisation.

This paper describes methods to affordably improve the robustness of distributed fusion systems by opportunistically leveraging non-traditional data sources. Adaptive methods help find relevant data, create models, and characterize the model quality. These methods also can measure the conformity of this non-traditional data with fusion system products including situation modeling and mission impact prediction. Non-traditional data can improve the quantity, quality, availability, timeliness, and diversity of the baseline fusion system sources and therefore can improve prediction and estimation accuracy and robustness at all levels of fusion. Techniques are described that automatically learn to characterize and search non-traditional contextual data to enable operators integrate the data with the high-level fusion systems and ontologies. These techniques apply the extension of the Data Fusion & Resource Management Dual Node Network (DNN) technical architecture at Level 4. The DNN architecture supports effectively assessment and management of the expanded portfolio of data sources, entities of interest, models, and algorithms including data pattern discovery and context conformity. Affordable model-driven and data-driven data mining methods to discover unknown models from non-traditional and ‘big data’ sources are used to automatically learn entity behaviors and correlations with fusion products, [14 and 15]. This paper describes our context assessment software development, and the demonstration of context assessment of non-traditional data to compare to an intelligence surveillance and reconnaissance fusion product based upon an IED POIs workflow.

With the advent of fast three dimensional inversion software for IP and resistivity data, attempts have been made to optimise survey techniques to maximise the quality and quantity of 3D field data for a given survey cost. The result has been the development of the Offset Pole-dipole array.This survey geometry has now been used on many mineral exploration projects and a considerable degree of expertise in the execution of these surveys has been gained and some of the pitfalls associated with the technique have been discovered.Three short case histories which involve this technique are presented which demonstrate the effectiveness of the technique and some of the problems encountered in its execution.The Pegmont and Maronan prospects lie in the Eastern Succession of the Mount Isa Inker in Northwest Queensland. The Mineral Hill Mine is in Central NSW.The Pegmont Prospect is presented as this was the first prospect surveyed with the technique. The Maronan and Mineral Hill surveys illustrate both the relative efficiency of the Offset Pole-dipole survey technique and some of its more serious limitations.