Remote Sensing X ray application Remote sensing can be defined as the collection of data about an object from a distance. Humans and many other types of animals accomplish this task with aid of eyes or by the sense of smell or hearing. Geographers use the technique of remote sensing to monitor or measure phenomena found in the Earth's lithosphere, biosphere, hydrosphere, and atmosphere. Remote sensing of the environment by geographers is usually done with the help of mechanical devices known as remote sensors. These gadgets have a greatly improved ability to receive and record information about an object without any physical contact. Often, these sensors are positioned away from the object of interest by using helicopters, planes, and satellites. Most sensing devices record information about an object by measuring an object's transmission of electromagnetic energy from reflecting and radiating surfaces. Remote sensing imagery has many applications in mapping land-use and cover, agriculture, soils mapping, forestry, city planning, archaeological investigations, military observation, and geomorphological surveying, among other uses. For example, foresters use aerial photographs for preparing forest cover maps, locating possible access roads, and measuring quantities of trees harvested. Specialized photography using color infrared film has also been used to detect disease and insect damage in forest trees. The simplest form of remote sensing uses photographic cameras to record information from visible or near infrared wavelengths (Table 2e-1). In the late 1800s, cameras were positioned above the Earth's surface in balloons or kites to take oblique aerial photographs of the landscape. During World War I, aerial photography played an important role in gathering information about the position and movements of enemy troops. These photographs were often taken from airplanes. After the war, civilian use of aerial photography from airplanes began with the systematic vertical imaging of large areas of Canada, the United States, and Europe. Many of these images were used to construct topographic and other types of reference maps of the natural and human-made features found on the Earth's surface. Table 2e-1: Major regions of the electromagnetic spectrum. Region Name Wavelength Comments Gamma Ray < 0.03 nanometers Entirely absorbed by the Earth's atmosphere and not available for remote sensing. X-ray 0.03 to 30 nanometers Entirely absorbed by the Earth's atmosphere and not available for remote sensing. Ultraviolet 0.03 to 0.4 micrometers Wavelengths from 0.03 to 0.3 micrometers absorbed by ozone in the Earth's atmosphere. Photographic Ultraviolet 0.3 to 0.4 micrometers Available for remote sensing the Earth. Can be imaged with photographic film. Visible 0.4 to 0.7 micrometers Available for remote sensing the Earth. Can be imaged with photographic film. Infrared 0.7 to 100 micrometers Available for remote sensing the Earth. Can be imaged with photographic film. Reflected Infrared 0.7 to 3.0 micrometers Available for remote sensing the Earth. Near Infrared 0.7 to 0.9 micrometers. Can be imaged with photographic film. Thermal Infrared 3.0 to 14 micrometers Available for remote sensing the Earth. This wavelength cannot be captured with photographic film. Instead, mechanical sensors are used to image this wavelength band. Microwave or Radar 0.1 to 100 centimeters Longer wavelengths of this band can pass through clouds, fog, and rain. Images using this band can be made with sensors that actively emit microwaves. Radio > 100 centimeters Not normally used for remote sensing the Earth. The development of color photography following World War II gave a more natural depiction of surface objects. Color aerial photography also greatly increased the amount of information gathered from an object. The human eye can differentiate many more shades of color than tones of gray (Figure 2e-1 and 2e-2). In 1942, Kodak developed color infrared film, which recorded wavelengths in the near-infrared part of the electromagnetic spectrum. This film type had good haze penetration and the ability to determine the type and health of vegetation. Figure 2e-1: The rows of color tiles are replicated in the right as complementary gray tones. On the left, we can make out 18 to 20 different shades of color. On the right, only 7 shades of gray can be distinguished. Figure 2e-2: Comparison of black and white and color images of the same scene. Note how the increased number of tones found on the color image make the scene much easier to interpret. (Source: University of California at Berkley - Earth Sciences and Map Library). Satellite Remote Sensing In the 1960s, a revolution in remote sensing technology began with the deployment of space satellites. From their high vantage-point, satellites have a greatly extended view of the Earth's surface. The first meteorological satellite, TIROS-1 (Figure 2e-3), was launched by the United States using an Atlas rocket on April 1, 1960. This early weather satellite used vidicon cameras to scan wide areas of the Earth's surface. Early satellite remote sensors did not use conventional film to produce their images. Instead, the sensors digitally capture the images using a device similar to a television camera. Once captured, this data is then transmitted electronically to receiving stations found on the Earth's surface. The image below (Figure 2e-4) is from TIROS-7 of a mid-latitude cyclone off the coast of New Zealand. Figure 2e-3: TIROS-1 satellite. (Source: NASA - Remote Sensing Tutorial). Figure 2e-4: TIROS-7 image of a mid-latitude cyclone off the coast of New Zealand, August 24, 1964. (Source: NASA - Looking at Earth From Space). Today, the GOES (Geostationary Operational Environmental Satellite) system of satellites provides most of the remotely sensed weather information for North America. To cover the complete continent and adjacent oceans two satellites are employed in a geostationary orbit. The western half of North America and the eastern Pacific Ocean is monitored by GOES-10, which is directly above the equator and 135° West longitude. The eastern half of North America and the western Atlantic are cover by GOES-8. The GOES-8 satellite is located overhead of the equator and 75° West longitude. Advanced sensors aboard the GOES satellite produce a continuous data stream so images can be viewed at any instance. The imaging sensor produces visible and infrared images of the Earth's terrestrial surface and oceans (Figure 2e-5). Infrared images can depict weather conditions even during the night. Another sensor aboard the satellite can determine vertical temperature profiles, vertical moisture profiles, total precipitable water, and atmospheric stability. Figure 2e-5: Color image from GOES-8 of hurricanes Madeline and Lester off the coast of Mexico, October 17, 1998. (Source: NASA - Looking at Earth From Space). In the 1970s, the second revolution in remote sensing technology began with the deployment of the Landsat satellites. Since this 1972, several generations of Landsat satellites with their Multispectral Scanners (MSS) have been providing continuous coverage of the Earth for almost 30 years. Current, Landsat satellites orbit the Earth's surface at an altitude of approximately 700 kilometers. Spatial resolution of objects on the ground surface is 79 x 56 meters. Complete coverage of the globe requires 233 orbits and occurs every 16 days. The Multispectral Scanner records a zone of the Earth's surface that is 185 kilometers wide in four wavelength bands: band 4 at 0.5 to 0.6 micrometers, band 5 at 0.6 to 0.7 micrometers, band 6 at 0.7 to 0.8 micrometers, and band 7 at 0.8 to 1.1 micrometers. Bands 4 and 5 receive the green and red wavelengths in the visible light range of the electromagnetic spectrum. The last two bands image near-infrared wavelengths. A second sensing system was added to Landsat satellites launched after 1982. This imaging system, known as the Thematic Mapper, records seven wavelength bands from the visible to far-infrared portions of the electromagnetic spectrum (Figure 2e-6). In addition, the ground resolution of this sensor was enhanced to 30 x 20 meters. This modification allows for greatly improved clarity of imaged objects. Figure 2e-6: The Landsat 7 enhanced Thematic Mapper instrument. (Source: Landsat 7 Home Page). The usefulness of satellites for remote sensing has resulted in several other organizations launching their own devices. In France, the SPOT (Satellite Pour l'Observation de la Terre) satellite program has launched five satellites since 1986. Since 1986, SPOT satellites have produced more than 10 million images. SPOT satellites use two different sensing systems to image the planet. One sensing system produces black and white panchromatic images from the visible band (0.51 to 0.73 micrometers) with a ground resolution of 10 x 10 meters. The other sensing device is multispectral capturing green, red, and reflected infrared bands at 20 x 20 meters (Figure 2d-7). SPOT-5, which was launched in 2002, is much improved from the first four versions of SPOT satellites. SPOT-5 has a maximum ground resolution of 2.5 x 2.5 meters in both panchromatic mode and multispectral operation. Figure 2e-7: SPOT false-color image of the southern portion of Manhatten Island and part of Long Island, New York. The bridges on the image are (left to right): Brooklyn Bridge, Manhattan Bridge, and the Williamsburg Bridge. (Source: SPOT Image). Radarsat-1 was launched by the Canadian Space Agency in November, 1995. As a remote sensing device, Radarsat is quite different from the Landsat and SPOT satellites. Radarsat is an active remote sensing system that transmits and receives microwave radiation. Landsat and SPOT sensors passively measure reflected radiation at wavelengths roughly equivalent to those detected by our eyes. Radarsat's microwave energy penetrates clouds, rain, dust, or haze and produces images regardless of the Sun's illumination allowing it to image in darkness. Radarsat images have a resolution between 8 to 100 meters. This sensor has found important applications in crop monitoring, defence surveillance, disaster monitoring, geologic resource mapping, sea-ice mapping and monitoring, oil slick detection, and digital elevation modeling (Figure 2e-8). Figure 2e-8: Radarsat image acquired on March 21, 1996, over Bathurst Island in Nunavut, Canada. This image shows Radarsat's ability to distinguish different types of bedrock. The light shades on this image (C) represent areas of limestone, while the darker regions (B) are composed of sedimentary siltstone. The very dark area marked A is Bracebridge Inlet which joins the Arctic ocean. (Source: Canadian Centre for Remote Sensing - Geological Mapping Bathurst Island, Nunavut, Canada March 21, 1996). Principles of Object Identification Most people have no problem identifying objects from photographs taken from an oblique angle. Such views are natural to the human eye and are part of our everyday experience. However, most remotely sensed images are taken from an overhead or vertical perspective and from distances quite removed from ground level. Both of these circumstances make the interpretation of natural and human-made objects somewhat difficult. In addition, images obtained from devices that receive and capture electromagnetic wavelengths outside human vision can present views that are quite unfamiliar. To overcome the potential difficulties involved in image recognition, professional image interpreters use a number of characteristics to help them identify remotely sensed objects. Some of these characteristics include: Shape: this characteristic alone may serve to identify many objects. Examples include the long linear lines of highways, the intersecting runways of an airfield, the perfectly rectangular shape of buildings, or the recognizable shape of an outdoor baseball diamond (Figure 2e-9). Figure 2e-9: Yankee stadium in Bronx, New York. Baseball stadiums have an obvious shape that can be easily recognized even from vertical aerial photographs. (Source: Google Earth). Size: noting the relative and absolute sizes of objects is important in their identification. The scale of the image determines the absolute size of an object. As a result, it is very important to recognize the scale of the image to be analyzed. Image Tone or Color: all objects reflect or emit specific signatures of electromagnetic radiation. In most cases, related types of objects emit or reflect similar wavelengths of radiation. Also, the types of recording device and recording media produce images that are reflective of their sensitivity to particular range of radiation. As a result, the interpreter must be aware of how the object being viewed will appear on the image examined. For example, on color infrared images vegetation has a color that ranges from pink to red rather than the usual tones of green. Pattern: many objects arrange themselves in typical patterns. This is especially true of human-made phenomena. For example, orchards have a systematic arrangement imposed by a farmer, while natural vegetation usually has a random or chaotic pattern (Figure 2e-10). Figure 2e-10: Black and white aerial photograph of natural coniferous vegetation (left) and adjacent apple orchards (center and right). Shadow: shadows can sometimes be used to get a different view of an object. For example, an overhead photograph of a towering smokestack or a radio transmission tower normally presents an identification problem. This difficulty can be over come by photographing these objects at Sun angles that cast shadows. These shadows then display the shape of the object on the ground. Shadows can also be a problem to interpreters because they often conceal things found on the Earth's surface. Texture: imaged objects display some degree of coarseness or smoothness. This characteristic can sometimes be useful in object interpretation. For example, we would normally expect to see textural differences when comparing an area of grass with a field corn. Texture, just like object size, is directly related to the scale of the image. Study Guide Additional Readings Internet Weblinks Citation: Pidwirny, M. (2006). "Introduction to Geographic Information Systems". Fundamentals of Physical Geography, 2nd Edition. Date Viewed. http://www.physicalgeography.net/fundamentals/2e.html

remote sensing

X-Ray Powder Diffraction

This handout provides background on

the use and theory of X-ray powder

diffraction. Examples of applications of

this method to geologic studies are

provided.

Introduction

Rocks, sediments, and precipitates are

examples of geologic materials that are

composed of minerals. Numerous

analytical techniques are used to

characterize these materials. One of

these methods, X-ray powder diffraction

(XRD), is an instrumental technique that

is used to identify minerals, as well as

other crystalline materials. In many

geologic investigations, XRD

complements other mineralogical

methods, including optical light

microscopy, electron microprobe

microscopy, and scanning electron

microscopy. XRD provides the

researcher with a fast and reliable tool for

routine mineral identification. XRD is

particularly useful for identifying finegrained

minerals and mixtures or

intergrowths of minerals that may not

lend themselves to analysis by other

techniques. XRD can provide additional

information beyond basic identification.

If the sample is a mixture, XRD data can

be analyzed to determine the proportion

of the different minerals present. Other

information obtained can include the

degree of crystallinity of the mineral(s)

present, possible deviations of the

minerals from their ideal compositions

(presence of element substitutions and

solid solutions), the structural state of the

minerals (which can be used to deduce

temperatures and (or) pressures of

formation), and the degree of hydration

for minerals that contain water in their

structure. Some mineralogical samples

analyzed by XRD are too fine grained to

be identified by optical light microscopy.

XRD does not, however, provide the

quantitative compositional data obtained

by the electron microprobe or me textural

and qualitative compositional data

obtained by the scanning electron

microscope.

Theory and Methodology

The three-dimensional structure of

nonamorphous materials, such as

minerals, is defined by regular, repeating

planes of atoms that form a crystal

lattice. When a focused X-ray beam

interacts with these planes of atoms, part

of the beam is transmitted, part is

absorbed by the sample, part is refracted

and scattered, and part is diffracted.

Diffraction of an X-ray beam by a

crystalline solid is analogous to

diffraction of light by droplets of water,

producing the familiar rainbow. X-rays

are diffracted by each mineral

differently, depending on what atoms

make up the crystal lattice and how these

atoms are arranged.

In X-ray powder diffractometry, X-rays

are generated within a sealed tube that is

under vacuum. A current is applied that

heats a filament within the tube, the

higher the current the greater the number

of electrons emitted from the filament.

This generation of electrons is analogous

to the production of electrons in a

television picture tube. A high voltage,

typically 15-60 kilovolts, is applied

within the tube. This high voltage

accelerates the electrons, which then hit a

target, commonly made of copper. When

these electrons hit the target, X-rays are

produced. The wavelength of these Xrays

is characteristic of that target. These

X-rays are collimated and directed onto

the sample, which has been ground to a

fine powder (typically to produce particle

sizes of less than 10 microns). A

detector detects the X-ray signal; the

signal is then processed either by a

microprocessor or electronically,

converting the signal to a count rate.

Changing the angle between the X-ray

source, the sample, and the detector at a

controlled rate between preset limits is an

X-ray scan (figs. 1 and 2).

When an X-ray beam hits a sample and

is diffracted, we can measure the

distances between the planes of the

atoms mat constitute the sample by

applying Bragg's Law. Bragg's Law is

Figure 1. Simplified sketch of one

possible configuration of the X-ray

source (X-ray tube), the X-ray detector,

and the sample during an X-ray scan. In

this configuration, the X-ray tube and the

detector both move through the angle

theta (q), and the sample remains

stationary.

n l = 2 d sin q, where the integer n is the

order of the diffracted beam, 1 is the

wavelength of the incident X-ray beam, d

is the distance between adjacent planes

of atoms (the d-spacings), and q is the

angle of incidence of the X-ray beam.

Since we know l and we can measure q,

we can calculate the d-spacings. The

geometry of an XRD unit is designed to

accommodate this measurement (fig. 1).

The characteristic set of d-spacings

generated in a typical X-ray scan

provides a unique "fingerprint" of the

mineral or minerals present in the

sample. When properly interpreted, by

comparison with standard reference

patterns and measurements, this

"fingerprint" allows for identification of

the material.

Applications

XRD has a wide range of applications

in geology, material science,

environmental science, chemistry,

forensic science, and the pharmaceutical

industry, among others. At the U.S.

Geological Survey, researchers use XRD

to characterize geologic materials from a

wide variety of settings; a few examples

follow.

Mineral-Environmental Studies

In studies of areas affected by acid

mine drainage, the identification of

secondary minerals and fine-grained

precipitates is a critical element. Acid is

generated when iron sulfide minerals,

such as pyrite, weather. Elements

derived from the alteration of the sulfide

minerals can form secondary minerals or

go into solution. Elements that go into

solution may form mineral precipitates as

conditions (temperature, acidity, solution

composition) change. Accurate

mineralogical characterization of the

precipitates and secondary minerals,

together with hydrogeochemical data,

helps us to better understand the

solubility, transport, and storage of

metals.

Ore Genesis Studies

Minerals form under specific ranges of

temperature and pressure. Mineralogical

identification of ore minerals and

associated minerals, including finegrained

hydrothermal alteration minerals,

provides evidence used to deduce the

conditions under which ore deposits

formed and the conditions under which,

in many cases, they were subsequently

altered.

Predictive Stratigraphic

Analysis

Mineralogical characteristics of

paleosols (ancient buried soil horizons)

and underclays (the fine-grained detrital

material lying immediately beneath a

coal bed) have been instrumental in

correlating coal zones from the

Appalachian basin into the Western

Interior basin. They have been the key to

quantifying the paleolatitudinal climate

gradient in North America during the late

Middle Pennsylvanian.

Remote-Sensing Studies

Mineralogical analysis by XRD is used

in conjunction with remotely sensed data

in several research investigations. XRD

is used to identify the minerals

composing clay-rich, hydrothermally

altered rocks that occur on several

Cascade volcanoes. Such rocks are

believed to play an important role in the

generation of large landslides and

mudflows. XRD is used to analyze

saline minerals, including borates.

Many saline hydrate minerals produce

diagnostic spectral bands, and spectral

data provide a basis for mineral

exploration using remote-sensing data.

Figure 2. Example of an X-ray powder diffractogram produced during an X-ray scan.

The peaks represent positions where the X-ray beam has been diffracted by the

crystal lattice. The set of d-spacings (the distance between adjacent planes of atoms),

which represent the unique “fingerprint” of the mineral, can easily be calculated from

the 2-theta (2q) values shown. The use of degrees 2-theta in depicting X-ray powder

diffraction scans is a matter of convention and can easily be related back to the

geometry of the instrument, shown in figure 1. The angle and the d-spacings are

related by Bragg’s Law, as described in the text.

Analysis of airborne imaging

spectrometer data can directly map

mineral occurrences by detecting

diagnostic spectral absorption bands, the

shape and position of which are

determined by individual mineral

structures. A detailed knowledge of

sample mineralogy, provided at least in

part by XRD, is required to understand

the observed spectral absorption features.

Genesis of Coal Beds

XRD is one of the primary tools used

to evaluate the lateral and vertical

variations in mineral matter and major,

minor, and trace elements in coal beds.

These data are used to help determine the

impact of geologic and geochemical

processes on coal bed formation in order

to understand and predict both inorganic

and organic variability within and among

mineable coal beds.

Mineral-Resource

Assessments

Mineralogical characterization

provides part of the data required to

determine the particular kind of mineral

deposits encountered in mineral-resource

assessment studies. XRD allows us to

identify fine-grained mixtures of

minerals found in associated gangue and

alteration assemblages, which cannot be

resolved by other methods.

-Prepared by Marta J.K. Flohr

For more information, please contact:

Frank T. Dulong

U.S. Geological Survey, MS 956

Reston, VA 20192

Telephone: (703) 648-6416

E-mail: fdulong@usgs.gov

John C. Jackson

U.S. Geological Survey, MS 954

Reston, VA 20192

Telephone: (703) 648-6321

E-mail: jjackson@usgs.gov

U.S. Department of the Interior

U.S. Geological Survey May 1997