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II. Instrumentation for Reflectance Measurements

II. Instrumentation for Reflectance Measurements

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Normal to sample

Incident flux


Viewed flux

FIG. 1. Geometric parameters describing reflection from a surface: 0, zenith angle; 4,

azimuth angle; o,beam solid angle; a prime on a symbol refers to viewing (reflected)conditions.

Figure 1 illustrates the basic geometric relationships between incoming

radiation and outgoing radiation using the previously described terminology.

The reflecting properties of a surface are most precisely described using a

parameter called the bidirectional rejectance distribution function (BRDF).

The defining equation for the BRDF is

The angles are shown in Fig. 1. The BRDF is the ratio of a radiance to an

irradiance; therefore, it has the units of sr-'. If the numerator and denominator of the expression are spectral quantities, then a spectral BRDF has been

defined and is usually denoted by the symbol A. A careful examination of Fig.

1 reveals that the BRDF is the ratio of two differential solid angles. This is a

mathematical abstraction that is closely realized by many physical situations

in which the incident and reflective solid angles are small enough to

approximate the differential case. The physically measured BRDF is therefore an average fr value over the parameter intervals. The incident and

reflected solid angles, however, need to be small to obtain a good estimate of

the true BRDF.

The measurement of the BRDF is, however, a particularly difficult

problem. It would be necessary to place a sensor at the surface to measure the

incoming radiation and then take that sensor, or another sensor, and place it

in the viewing position necessary to measure the reflected radiation. Although this represents a possible approach, an experimentally more convenient method uses a reflectance standard in the measurement procedure. The





FIG.2. Illustration of procedure for measuring the reflectance factor. The response of the

sensor to a perfectly diffuse, ideal reference is recorded, and then the response of the sensor to a

target of interest is recorded under the same illumination conditions.

geometry of this method is illustrated in Fig. 2. In this method a single sensor

located in the viewing position is used to view the reflected radiation from a

perfectly diffuse ideal reflector as well as that from the scene of interest. If the

scene and the perfectly diffuse ideal reflecting surface are viewed and

illuminated under identical conditions, the ratio of the two measurements is

referred to as the reflectance factor of the scene (Nicodemus et al., 1977).

If the geometry of the situation resembles that of Fig. 1, then the quantity

we are measuring is referred to as the bidirectional reflectance factor (BRF). If

differential solid angles are not assumed and real conical solid angles are the

case, then the quantity being measured is called the biconical reflectance

factor. If the conical solid angles for both incident and reflected radiation

include all directions, i.e., the hemisphere, then the measurement is referred to

as the bihemispherical rejectance factor. Also, the measurement may be

referred to as the directional-hemispherical reflectance factor, hemisphericalconical reflectance factor, etc., depending on the instrumentation setup. In

many real measurement situations the magnitudes of the solid angles

involved are small enough so as to approximate the differential situation. For

this reason, the results of the reflectance factor measurement are referred to as

the bidirectional reflectance factor, whereas in reality they are actually the

results of a biconical reflectance factor measurement.

The principal advantage of the reflectance factor method of measurement

is that the sensor can be kept in its viewing position and it is only necessary to



measure the radiation from the reflectance standard and that from the scene

of interest within a short time period and then take the ratio to obtain the

desired reflectance factor measurement. The method is amenable to both

laboratory and field measurement situations.

An important part of the measurement procedure just discussed is the

reflectance standard. A perfectly diffuse reflecting surface is one that reflects

equally in all directions. An ideal reflector is a surface in which all of the

energy falling on the surface is reflected. Again, this is an abstraction, but

physical surfaces have been prepared which approximate this ideal situation.

Examples of some of the reflecting materials and coatings used for diffuse

surfaces include magnesium oxide, barium sulfate (Grum and Luckey, 1968;

Billmeyer et al., 1971; Shai and Schutt, 1971; Young et al., 1980), homopolymers and copolymers with fluorine substitution (Schutt et al., 1981),

and canvas panels (Robinson and Biehl, 1979). Barium sulfate surfaces have

received the widest acceptance.

Specially prepared barium sulfate surfaces approximate a perfect diffuser at

angles within 45" of a normal to the surface. The reflectance of properly

prepared barium sulfate surfaces is over 0.9 for most wavelengths in the

reflective spectrum. Departures from perfectly diffuse or ideally reflecting

properties of the reflectance standard can be documented and accounted for

during the analysis of the measurement data (Robinson and Biehl, 1979).

Primary reflectance factor calibration measurements are usually made with

tablets that are fabricated out of pressed barium sulfate powder. The results

of these measurements are referred to standard data that have been made

available by the manufacturers of this special barium sulfate reflectance

powder. The resulting measurements are then used to calibrate painted

barium sulfate reflectance standard panels. The pressed barium sulfate tablets

can often be directly used in the laboratory, but for field situations 1.25 x

1.25 m painted panels are usually prepared. The panels are covered when not

in use and are otherwise handled very carefully to avoid contamination from




Figure 3 is a schematic diagram of the angles involved in a physically

realizable measurement situation. In this case, the source and the sensor have

real apertures which produce conical solid angles rather than differential

angles as indicated in Fig. 1. In addition, the sensor has a field of view

determined by its internal optics and indicated on the diagram by the angle p.

The amount of reflected power gathered by the sensor is proportional to the

square of the field of view, the sensor aperture area, the irradiance, the





'sensor field of view


azimuth angle

FIG. 3. Schematic diagram of illumination and viewing angles involved in a physically

realizable measurement situation.

irradiance angles, the sensor view angles, and, of course, the bidirectional

reflectance distribution of the target. The angular relationships of the source,

target, and sensor can significantly affect the measured reflectance of the

target. For example, the reflectance measured by a sensor vertically viewing

the soil in a plowed field with deep furrows will be higher when the solar

azimuth angle is parallel with the furrow (no shadows) than when the solar

azimuth is perpendicular to the furrows (shadows present). If the target is

smooth, then the azimuthal orientation of the sensor (or source) is irrelevant.

Usually laboratory samples of a soil are prepared in such a way as to be free

of azimuthal variation. Most field observations are usually made at a sensor

zenith angle of 0" and the data are taken at a variety of solar illumination

angles. Laboratory observations are, again, usually made at a sensor zenith

angle of 0" and an illumination zenith angle of 10 to 30".

As previously stated, the signal power received by the sensor is proportional to the square of the field of view of the sensor. However, this is not the sole

factor in the choice of the particular field of view that is going to be used in a

measurement situation. As shown in Fig, 4, a narrow field of view may not

properly integrate the geometric features of the scene into the signal received

by the sensor. A "wide enough" field of view is necessary in order to represent

properly the geometric features of a target to the sensor. Examples of such

structure are the plant rows in a row crop and the roughness of a plowed field.

However, if the field of view is "too wide," then it is difficult to characterize

properly the sensor zenith angle. In field situations, an appropriate compromise is a field of view of approximately 15". In laboratory situations where

the surface roughness of the target can be controlled, a narrow field of view

such as 1" may be properly used.



FIG.4. Illustration of a field of view (FOV) which is large enough to represent properly the

geometric features of the target and a FOV which is too small to integrate the geometricfeatures.

In some cases, the surface roughness of the target may be so extreme as to

make it impossible to characterize properly the reflectance properties with

one measurement. In this case, several observations of the target are made at

a variety of illumination angles or viewing angles to characterize the target

completely. In this way, shadowing effects which might otherwise obscure the

reflectance properties of the target can be taken into consideration. This

method is available only in a low-altitude field instrumentation situation.

Extreme surface roughness may seriously complicate high-altitude observations from aircraft or satellites.

Another factor that enters into the instrumentation geometric problem is

that of the ratio of direct to diffuse illumination. On a very clear, lowhumidity day, most of the incoming illumination (in a field situation) is

directly from the sun. On hazy days, a significant amount of incident

illumination may be indirect due to atmospheric scattering. This is generally

referred to as the diffuse component of the incident illumination. Moreover,

the diffuse component is a function of the wavelength, being proportionally

more at shorter wavelengths. If the diffuse component of incident illumination is a significant part of the total illumination, then it is difficult to

characterize properly the zenith angle of the incident illumination. In a

laboratory situation, the instrumentation system is arranged so as to negate

the effects of diffuse component illumination. In a field situation, it is often

possible to reduce diffuse effects by restricting data acquisition times to those

in which atmospheric conditions do not give rise to extreme diffuse effects. If

it is necessary to take data under hazy atmospheric conditions, then the

diffuse component may be determined by shadowing the target (and standard) from direct illumination and making a reflectance factor measurement.



This diffuse component is then subtracted from the total illumination in

order to obtain the reflectance factor associated with the direct illumination



Instruments that have been used to measure the reflectance of soil can

generally be divided into two broad classes-spectroradiometers and multiband radiometers. The discussion that follows is a brief summary of the

instrumentation. More detailed information can be found in Robinson and

DeWitt (1983) and Zissis (1979).

Multiband radiometers contain several optical filters to define the spectral

bandpasses. These spectral bandpasses are selected to sample discrete portions of the optical spectrum, e.g., the Landsat multispectral scanner (MSS)

or the thematic mapper (TM) bands. Multiband radiometers can be of two

types-nonchopping (dc) or chopping (ac). The detectors in dc multiband

radiometers are directly coupled to the output amplifiers. The most reliable

dc multiband radiometers are limited to the spectral range of the silicon

detector because detectors such as lead sulfide, which are sensitive beyond

1 pm, are not sufficiently stable.

Many dc multiband radiometers being used to measure the reflectance of

soils in situ contain the Landsat MSS spectral bands or the first four TM

spectral bands. Some companies have built multiband radiometers that make

it relatively easy for researchers to interchange different sets of optical filters.

ac multiband radiometers contain a chopper in front of the detectors to

allow the field of view of the detector to be alternately filled with the internal

reference source and the target. The signal measuring the radiance from the

target is now the ac signal. The dc signal, which is due to the instability of the

detector, is removed. ac multiband radiometers generally use lead sulfide

detectors to measure the radiant power in spectral bands from 1.0 to 3.0 pm,

such as the last three reflective TM bands.

Spectroradiometers.are distinguished from multiband radiometers because

they measure flux in much narrower, continuous spectral bands. Spectroradiometers can also be chopping or nonchopping. Similar to multiband radiometers, the most reliable nonchopping spectroradiometers are limited to the

silicon detector spectral range.

In spectroradiometers, optical dispersion devices replace the simple optical

filters. The dispersion device may be a segmented filter wheel, a circular

variable filter (CVF), a prism, or grating. The differences in dispersion devices

relate to wavelength resolution and spectral scan speed. Circular variable

filter spectroradiometers that operate from 0.4to 2.4 pm have been widely



used for laboratory and in situ reflectance measurements. The wavelength

resolution of these CVF instruments is generally 1-2 % of the wavelength.

Spectroradiometers and multiband radiometers may also have an integrating sphere and an artificial light source attached to allow for the measurement of the directional-hemispherical reflectance factor. Many of the

reflectance data cited in the literature are directional-hemispherical reflectance factor measurements.

The systems described above have their own set of advantages and

disadvantages. Multiband radiometers tend to be less costly to buy and

operate. They are lighter and therefore easier to mount on simple pickup

truck booms. Generally, one can obtain a set of multiband radiometer

measurements much faster than a set of spectroradiometer measurements

-fractions of a second compared to 10-120 sec. However, the spectral range

and resolution of multiband radiometers are limited. For example, one can

use reflectance measurements from a multiband radiometer with Landsat

MSS bands to help interpret Landsat MSS data; however, the measurement

could not be easily used to interpret TM data.

Spectroradiometers, on the other hand, lend themselves well to obtaining

sets of reflectance data which can be used to interpret many different sets of

broadband satellite data, e.g., Landsat MSS and TM, the National Oceanic

and Atmospheric Administration’s advanced very-high-resolution radiometer (NOAA AVHRR), and the Nimbus 7 coastal zone color scanner

(CZCS). Spectroradiometers, however, tend to be costly to operate, require

significant time to obtain a set of spectral measurements, and are cumbersome to move in the field. Recent advances in multilinear arrays, however,

may negate some of these disadvantages in the near future.

Instrumentation systems that have been used to measure the reflectance of

soil can be divided into laboratory and in situ or field systems. The laboratory

systems can be further divided into bidirectional reflectance factor systems

and directional-hemispherical reflectance factor systems. Reflectance measurements were initially done in the laboratory using directional-hemispherical spectroradiometer systems. I n situ measurements were made of soil

reflectance as field-worthy spectroradiometer systems were developed during

the late 1960s and early 1970s. With the launch of the Landsat MSS scanners

and the attention given to the Landsat MSS bands, multiband radiometers

became a primary source of field measurements during the late 1970s and

early 1980s. Laboratory measurements of reflectance also continued during

this time. Instrument systems were developed to measure the bidirectional

reflectance factor of soils in the laboratory (DeWitt and Robinson, 1976).

Many instrumentation systems are now available to make reflectance

measurements. However, to utilize and compare measurements from different

systems, researchers need to follow well-defined calibration procedures and



describe adequately their measurements relative to illumination and viewing

angle, sensor field of view, reference surface, illumination and viewing solid

angles, and target surface preparation. Also, one needs to be cautious about

comparing bidirectional measurements and directional-hemispherical

measurements. Directional-hemispherical measurements are an integration

of bidirectional measurements across all possible viewing angles.



With the development of new laboratory and field spectroradiometers

during the past two decades, it is now possible to measure quantitatively the

effects of soil constituents on soil reflectance. One of the early studies to

quantify soil reflectance and to define differences between soil reflectance

spectra was conducted by Condit (1970, 1972). He made directional-hemispherical reflectance factor measurements over the range from 0.32 to 1.0 pm

for 160 soil samples from 36 states in the United States. From these results he

classified the spectral soil curves into three general types (Fig. 5). No attempt

was made to relate quantitatively these spectral properties to other physical

and chemical properties of the soils.

By the mid-1970s laboratory and field instruments were available for

obtaining bidirectional reflectance factor measurements over an extended

range of the reflectance spectrum. Stoner and Baumgardner (1981) and

Stoner et al. (1980a) reported the results of visible and infrared reflectance

(0.52-2.38 pm) measurements for duplicate surface samples of more than 240

soil series obtained from 17 different temperature-moisture regimes in the 48

contiguous states in the United States. From these spectra and a limited

50 -





10 0









Wavelength (pm)






FIG.5. Soil spectral curve types defined by Condit (1970, 1972); reflectance is recorded as

the directional-hemispherical reflectance factor.







Wavelength (pm)

FIG.6. Soil spectral curve forms defined by Stoner and Baumgardner (1981); reflectance is

recorded as the bidirectional reflectance factor. curve a, Organic dominated; curve b, minimally

altered; curve c, iron affected; curve d, organic affected; curve e, iron dominated.

number of reflectance spectra of soils from other parts of the world, they

derived five soil spectral curve forms (Fig. 6 ) to which they established some

general genetic, physical, and chemical relationships to each spectral curve

form (Table I).

This capability to obtain calibrated data across the visible and infrared

reflectance spectrum provides an important new tool to soil scientists (Cipra

et al., 1971a). The remainder of this section will present the results of

observations made on those soil constituents which account for most of the

variation in soil reflectance.


It is a common observation that most soils appear darker when wet than

when dry. This results from decreased reflectance of incident radiation in the

visible region of the spectrum. Evans (1948), who presented reflectance curves

for three soils in both the wet and dry state, found that the wet samples

showed lower reflectance. Unfortunately, he provided no information about

the soil series or moisture contents of the soils. Brooks (1952) reported 10%

reflectivity of moist Yo10 fine sandy loam over the wavelength range of 0.4 to

2.5 pm but did not indicate the moisture content; for the dry condition, he

reported a reflectivity of 30%. Kojima (1958b) studied the effect of moisture

content on the color of 16 soils. His results, reported in Munsell color

notation, also showed a decrease in reflectance with an increase in moisture.

He made no reference to energy changes related to reflectance and moisture


In “Soil Taxonomy,” the Soil Conservation Service standard for soil

survey over much of the world, the range of change in soil color upon wetting

is given as varying between 1/2 and 3 Munsell color steps (Soil Survey Staff,

1975). No formulas are proposed for predicting change in color between the

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II. Instrumentation for Reflectance Measurements

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