Introduction to Remote Sensing and Mineral Exploration


This article was first published on Gold Investing News on May 16, 2011.

By Leia Michele Toovey-Exclusive to Gold Investing News


Remote sensing involves gathering data and information about the physical “world” by detecting and measuring signals composed of radiation, particles, and fields emanating from objects. This data is collected without direct contact with the object and can be used to identify and categorize objects of interest. Remote sensing has a variety of applications. It is used in medical applications, environmental applications- and in mineral exploration. In terms of mineral exploration, remote sensing is a rapidly advancing, and extremely valuable tool. It allows mineral explorers to more accurately pin-point a resource at a reduced cost. According to Anglo-American (LON:AAL), in terms of diamond exploration the average cost per ‘traditional’ kimberlite discovery is US $1 million per kimberlite. By using HyMap (Hyperspectral Mapping) the cost per kimberlite discovery drops down to around US$300,000.

Remote sensing is best used for the discovery of high-value rare commodities such as diamonds and gold which are becoming more and more difficult to locate. This is due to the fact that remote sensing, in its simplest sense, can help narrow down a search area. When used in gold exploration, remote sensing is the science of acquiring, processing, and interpreting images and related data acquired from aircraft and satellites. Remote sensing utilizes a variety of sophisticated technology to record the interaction between matter and electromagnetic energy. Remote sensing images are used for mineral exploration in two applications: (1) map geology and the faults and fractures that localize ore deposits; (2) recognize hydrothermally altered rocks by their spectral signatures.

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The history of remote sensing

While remote sensing has been around since before World War II, it has rapidly advanced in the past few years. In the beginning, the primary use of remotely gathered data was comparative. If gold was found in a particular area, aerial photos of that particular area would be compared with aerial photos from other locales to find places that had similar surface features hoping they too would be covering a valuable gold deposit. Once satellite imagery became commercially available, the same compare and contrast was used with satellite images. To date, aerial photography still is used as an exploration tool. Aerial photographs are used to identify topographic surface features which may imply the subsurface geology. Such telling surface features as differential erosion, outcropping rock, drainage patterns, and folds/faults can be identified. Faults fractures and contacts often provide a conduit or depositional environment for hydrothermal or magmatic fluids in regions of known mineralization, and thus make excellent targets for further investigation.

The advent of multispectral imaging and thematic mapping has allowed surface mapping to be performed remotely, thereby enabling vast areas to be mapped in a short time at a fraction of the cost of traditional geologic mapping. Different scanning spectrums enabled researchers to begin cataloguing various reflection and adsorption properties of soils, rock, and vegetation. These spectra could be utilized to interpret actual surface lithologies from remote images. Among the most valuable data collected are the weathering and alteration products of mineral deposits, especially clays. Clays and oxides can be readily differentiated by the spectra utilized for remote sensing. By correlating the alteration products to parent materials, potentially valuable ores may by distinguished without the need for extensive soil sampling programs.

Today, there are a variety remote sensing tools available to the exploration geologist. By far, the greatest advancement in mineral exploration has been the ability to synthesize various forms of data. Known drilling results can be integrated with topographic maps, air photos, structural maps, and ore grade data, greatly increasing the accuracy and effectiveness of an exploration program.

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Remote mineral data is collected from one of two ways- via low-lying aircraft, or from satellites. Two main sensor types are used in remote sensing, optical sensors and synthetic aperture (SAR) sensors. Optical sensors that measure the spectral data of sunlight reflected from the Earth’s surface, and (SAR) sensors sense electromagnetic data by transmitting microwaves and receiving the back scatter waves from the Earth’s surface.

Collecting the data in the field is the just the first step in coming up with a product that is useful in exploration. The next step is to translate the data into a form that is useful for explorers. There are a variety of techniques and manipulations that can be used, but one of the more useful, and one of the first applied techniques I learned in school was image classification. Remote Sensing makes use of spectral signatures. For any given material, the amount of solar radiation that it reflects, absorbs, transmits, or emits varies with wavelength. When that amount coming from the material is plotted over a range of wavelengths, the connected points produce a curve called the material’s spectral signature.  All objects have a unique spectral signature- and similar objects share a spectral signature. Once you have identified the spectral signature of that object- you can look for the same spectral signature on other data sets to pin-point what could be, in fact, the same object. This, of course, is an overly simplified explanation. To determine an objects “spectral signature” the data must be manipulated- in terms of remote sensing most of the manipulation is accomplished by playing around with the spectral colour bands in the imagea.  We will go more in-depth into this technology in part 2 of this feature, when we address multi-spectral imagery.

Current remote sensing techniques

While this is a rapidly advancing field, currently,  most remote sensing is performed through the following technologies: Landsat, ASTER, Hyperspectral, Field Spectrometry and Thermal Infrared (TIR).

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