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V. Applications of Soil Reflectance Measurements

V. Applications of Soil Reflectance Measurements

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Fig. 13. Spectral mapgenerated from digital analysis of Landsat MSS data for use in the soil survey of Jasper County, Indiana (Lacustrine area; Atlas

sheet No. 68) (Weismiller et a!., 1979). The area covered in the figure is approximately 17.5 km. The original scale was 1: 15,840.



REFLECTANCE PROPERTIES OF SOIL



35



Fifty years after the first use of black-and-white aerial photographs for soil

surveys, digital analysis of Landsat reflectance data was first used to prepare

a spectral base map to assist in the detailed soil survey (1:15,840) of Jasper

County, Indiana (Hinzel et al., 1980; Weismiller et al., 1979). Field surveyors

found the spectral maps (Fig. 13) useful in delineating boundaries between

soils and in assessing the homogeneity of soil map units.

In the late 1960s and early 1970s, prior to the launch of Landsat 1, several

soil scientists began to investigate the possibility of using MSS data as a tool

for delineating differences in surface soils. Kristof (1971) and Kristof and

Zachary (1971) reported that computer-implemented pattern recognition

analysis of aircraft MSS data could be used to map some soil surface

conditions over small areas with a reasonable degree of accuracy. Soon

thereafter Kristof and Zachary (1974) reported partial success in delineating

soil series in an Alfisol-Mollisol region by digital analysis of aerial MSS data.

A new era in the availability of multispectral reflectance data for soil

surveys began with the launch of Landsat 1 in July 1972. Since that data four

more satellites in the Landsat series have been placed in sun-synchronous

orbit for earth observation purposes (Table 11). One of the earlier reports on

the use of Landsat data for soil survey was by Lewis et al. (1975). They

Table I1

Specifications of the Multispectral Scanner and Thematic

Mapper on Landsats 1-5



Landsat"



Sensor



1,2,3,4, 5



MSS



3

4, 5



TM



Spectral

bands (pm)



Spatial

resolution (m)



0.5-0.6

0.6-0.7

0.7-0.8

0.8- 1.1

10.4-12.6

0.45-0.52

0.52-0.60

0.63-0.69

0.76-0.90

1.55-1.75

2.08-2.35

10.40-12.50



80

80

80

80

240

30

30

30

30

30

30

120



'(launch date)/(termination of sensor operation):

Landsat 1 , (07/72)/(01/78); Landsat 2, (01/75)/(01/80);

Landsat 3, (03/78)/(09/83); Landsat 4, (07/82)/(MSS

operational; TM 02/83); Landsat 5, (03/84)/(MSS and

TM operational).



36



MARION F. BAUMGARDNER ET AL.



concluded that soil associations within the Sand Hills region of Nebraska can

be interpreted on the basis of image patterns resulting from differences in

vegetation and related drainage conditions and from topography enhanced

by continuous snow cover and relatively low solar elevation angles.

During the first 4 years of the Landsat program, the majority of the soil

survey work using Landsat reflectance data was accomplished through visual

interpretation of images to delineate soil boundaries (Frazee et al., 1974;

Hilwig, 1976; Hilwig et al., 1974; Lewis et al., 1975; Parks and Bodenheimer,

1973; Seevers and Drew, 1973; Seevers et al., 1974; Steinhardt et a!., 1975;

Westin, 1973, 1974; Westin and Myers, 1973). During this same period a

limited number of papers reported the use of digital analysis of Landsat data

for identifying and delineating soil differences (Baumgardner et al., 1973;

Mathews et at., 1973a; May and Petersen, 1975). By 1980 the number of soil

scientists having access to computer-implemented image processing capabilities had grown considerably.

Two Landsat image mosaics (scale 1: 1,000,000) for the state of South

Dakota were prepared by Westin and Frazee (1976) from 20 late spring 1973

Landsat scenes, each scene covering an area of 34,000 km2. They used one

mosaic to prepare a land value map (soil associations keyed to land sale

prices from 1967 to 1972); on the second they keyed soil associations to soil

test results from the previous 25 years.

Weismiller et al. (1977) used computer-implemented pattern recognition

analysis of Landsat MSS data as an aid in the soil inventory of Chariton

County, Missouri. They found that by combining digitized ancillary data

(township, watershed, and physiographic boundaries) with Landsat MSS

data, a more detailed delineation of soils could be obtained than with MSS

data alone.

Analyzing Landsat reflectance data obtained on 9 June 1973 over Clinton

County, Indiana (Alfisol-Mollisol area), Kirschner et al. (1978) found a close

correlation between spectral classes and soil drainage characteristics. They

found the spectral map (scale 1:20,000) produced from digital analysis of

Landsat reflectance data to be useful in assessing map unit composition, or

homogeneity of the soils within a map unit.

Several studies have reported positive results in the use of Landsat MSS

data in delineating and mapping important soil differences in arid and

semiarid regions (Horvath, 1981; Horvath et al., 1980, 1983, 1984; Kornblau,

1979; Kornblau and Cipra, 1983; Mimms, 1982).

Horvath et al. (1984) examined the possibility of using Landsat reflectance

data to determine important properties of Arizona rangelands. They found

that satellite reflectance data added valuable information for the determination of soil map unit definition and distribution. They concluded that site

characteristics (canopy cover, elevation) were more important in predicting



REFLECTANCE PROPERTIES OF SOIL



37



MSS reflectance of rangeland test sites than were the properties of soils, but

vegetation and soil characteristics could be used in combination with

reflectance data to delineate soil map units.

Results have also been reported on the use of Landsat data as an aid to soil

surveys in India (Hilwig, 1976; Hoore et al., 1982; Rao et al., 1982), Bolivia

(Valenzuela, 1979), Spain (Hilwig et al., 1974), and the USSR (Andronikov

and Liverovski, 1982).

The launch of Landsat 4 in July 1982 made available for the first time

Landsat TM reflectance data with 30-m spatial resolution. Since that launch

several papers have reported the application of TM data to soil studies.

Thompson et al. (1984) examined TM reflectance data acquired over

Mississippi County, Arkansas, to determine the sensitivity of TM reflectance

to soil properties under growing soybeans (Glycine rnax L.). They found that

TM data provide information that is related to soil properties within a field.

Thompson and Henderson (1984) examined reflectance data from an

aircraft TM simulator and the Landsat 4 TM for their relative accuracy in

separating soils from an intensely cultivated agricultural area. They used

reflectance data from five different dates throughout the 1982 growing season

obtained over Central Iowa. The results of their study indicated that the

improved spectral and spatial resolution of TM (over MSS) data offers the

potential to separate important soil properties even in regions with similar

soils and under a dense corn (Zea mays L.) or soybean (Glycine max L.)

canopy.

A summary of the conclusions reported in the literature during the past

decade suggest that the following aspects of and possibilities with satelliteacquired reflectance data provide a significant new tool to aid in soil surveys

(Imhoff and Peterson, 1980; Kirschner et al., 1978; Longlois et a/., 1976; van

Sleen, 1982; Weismiller et a]., 1977; Weismiller and Kaminsky, 1978; Westin

and Frazee, 1976):

1.

2.

3.

4.

5.

6.

7.

8.



Synoptic view of survey area and surroundings

Quantitative assessment of homogeneity of map unit

Near orthographic quality of MSS and TM data

Multispectral data set

Repetitive coverage

Digital format for tabular or image information

Computer-implemented image processing possibilities

Possibilities for registering, overlaying, and combining multiple data

sets



The sources and uses of reflectance data from aerospace sensors have been

summarized and reported by Baumgardner et al. (1983). Appropriate sources



38



MARION F. BAUMGARDNER ET AL.



I

Survey type

Suwey scale

Size of mapping unit



-



Order of soil survey



5th order

I 4thorder

Reconnaissance1 :300,0001:125,0001:300,000

1:1,000,000

35-50 km2

500-500,000 ha



Kind of mapping unit Associations of phases Associations of

of subgroupdgreat

families of soil

groups, suborders,

series

orders



Use in development

planning



Common or potential

remote sensing data

sources



I



3rd order

Semidetailed

1:32,0001:125,000

10-1 000 ha



I



1s t order

Intensive

1: 10001: 12,000

0.5 ha or smaller

Phases of soil

series



-- -



-



Landsat



2nd order

Detailed

1: 12,0001:32,000

1.O-1.6 ha



Associations of Consociations of

phases of

phases of soil

soil series

series



Resource inventory

Proiect location



4



I



c



Feasibi!ity suweysManagement surveys



MSS and TM (images)



-



c



Landsat MSS t T M (digitall-Landsat



t

-



NOAA 617

4



c



-



TM (digital)-



Aerial photography (high altitude)

c

Aerial photography (low altitude)



-



FIG.14. Use of soil reflectance data derived from aerospace sensors as an aid for preparing

different orders of soil surveys. (Adapted from Baumgardner et nl., 1983.)



of reflectance data can be used in the preparation of different orders of soil

survey (Fig. 14).

B. SOILDEGRADATION

ASSESSMENT



The global and repetitive coverage of polar-orbiting earth observation

satellites offers the possibility of monitoring changes in earth surface phenomena. With the increasing human demands on the land resources of the

earth, an appropriate application of repetitive Landsat reflectance data is to

measure quantitatively the rates of soil degradation caused by wind erosion,

water erosion, salinization, flooding, and other processes. Several limited

studies have made use of Landsat data to inventory and monitor soil

degradation (Bleeker, 1978a,b; Hellden and Stern, 1980; Latz et al., 1984;

Mainguet et al., 1978; Mitchell and Ghorashian, 1978; Mitchell and Howard,

1978; Mitchell et al., 1978; Pacheco, 1978; Parada and Pinto, 1983).

As high-quality, repetitive multispectral data from earth observation

systems become more readily available, it should be possible to assess

quantitatively changes in soil conditions caused by soil degradation.

C. SOILINFORMATION

SYSTEMS



The capability to acquire and store very rapidly large volumes of data

about the earth’s surface has hastened the need for data management systems.



REFLECTANCE PROPERTIES O F SOIL



39



What is emerging for soils and other natural resources is an array of

georeferenced information systems (GIs). The concept suggests that remotely

sensed (e.g., reflectance, thermal, microwave), cartographic, climatic, chemical, physical, topographic, socioeconomic, and other data related to the

earth’s surface can be digitized, registered, and overlaid such that all data are

related to specific geographic coordinates on the earth’s surface. This data

base can then be used for ready retrieval of information for resource decisionmaking and policy-making.

Several papers have reported applications of the GIS concept to soil data

management (Biehl et al., 1982; Dangermond, 1983; Hitchcock et al., 1975;

Imhoff et al., 1982; Stoner et al., 1983).

Soil scientists will be presented many new opportunities and challenges in

the years ahead to utilize these new technologies to inventory and monitor

our soil resources.

REFERENCES

Al-Mahawili, S. M. H. 1983. M.S. thesis, Purdue University, West Lafayette, Indiana.

Andronikov, V. L., and Liverovski, Y. A. 1982. Ahstr. Trans. lnt. Congr. Soil Sci., J2th, New Delhi

p. 132.

Angstrom, D. 1925. Geograf. Ann. 7, 323.

Baumgardner, M. F., and Stoner, E. R. 1982. Trans. lnt. Congr. Soil Sci., IZth, New Delhi 5,

419-441.

Baumgardner, M. F., Kristof, S. J., Johannsen, C. J., and Zachary, A. L. 1970. Indiana Acad. Sci.

Proc. 79,413-422.

Baumgardner, M. F., Kristof, S. J., and Henderson, J. A,, Jr. 1973. Proc. Syrnp. Significant Results

Obtained Earth Resources Techno]. Satellite-I, 1973 NASA SP-327, pp. 213-221.

Baumgardner, M. F., Crosson, P. R., Dregne, H., Drosdoff, M., and Westin, F. C. 1983. In

“Resource Inventory and Baseline Study Methods for Developing Countries” (F. Conant,

P. Rogers, M. Baumgardner, C . McKell, R. Dasmann, and P. Reining, eds.), pp. 187-305.

Amer. Assoc. Adv. Sci. 83-3. Washington, D.C.

Beck, R. H., Robinson, B. F., McFee, W. H., and Peterson, J. B. 1976. Info. Note 081 176. Lab.

Applic. Remote Sensing, Purdue Univ., West Lafayette, Indiana.

Biehl, L. L., Bauer, M. E., Robinson, B. F., Daughtry, C . S. T., Pitts, D. E., and Silva, L. F. 1982.

Proc. lnt. Symp. Machine Process. Remotely Sensed Data pp. 169-177.

Bigham, J. M., Golden, D. C., Buol, S. W., Weed, S. B., and Bowen, L. H. 1978. Soil Sci. SOC.Am.

J . 42, 825-830.

Billmeyer, F. W., Jr., Lewis, D. L., and Davidson, J. G . 1971. Color Eng. May-June, 31-36.

Bleeker, P. 1978a. The application of Landsat imagery to soil degradation mapping at

1:5,000,000 of Cambia, Guinea, Sierra Leone, and parts of Senegal, Liberia and Ivory

Coast. Remote Sensing Unit, FAO, Rome.

Bleeker, P. 1978b. The application of Landsat imagery to soil degradation mapping of Sierra

Leone at 1:1,000,000. Remote Sensing Unit, FAO, Rome.

Bowers, S. A,, and Hanks, R. 3. 1965. Soil Sci. 100, 130-138.

Bowers, S. A., and Smith, S. J. 1972. Soil Sci. Sac. Am. Proc. 36,978-980.

Bowers, S. A., Smith, S. J., Fisher, H. D., and Miller, G . E. 1975. Soil Sci. Sac. Am. Proc. 39,

391-393.

Brooks, F. A. 1952. J . Meteorol. 9, 41-52.



40



MARION F. BAUMGARDNER E T A L .



Bushnell, T. M. 1929. Indiana Acad. Sci. Proc. 39,229-230.

Carneggie, D. M., Poulton, C. E., and Roberts, E. H. 1967. The evaluation of rangeland resources

by means of multispectral imagery. Annu. Prog. Rep., Earth Resources Survey Program,

OSSAJNASA. Univ. Gal$, Berkeley.

Cipra, J. E., Baumgardner, M. F., Stoner, E. R., and FJacDonald, R. B. 1971a. Soil Sci. SOC.Am.

Proc. 35, 1014-1017.

Cipra, J. E., Silva, L., and Hoffer, R. 1971b. Proc. Int. Symp. Remote Sensing Environ. 7th pp.

1509-1 518.

Cipra, J. E., Franzmeier, D. P., Bauer, M. E., and Boyd, R. K. 1980. Soil Sci. SOC.Am. J . 44,80-84.

Condit, H. R. 1970. Photogr. Eng. 36,955-966.

Condit, H. R. 1972. Appl. Opt. 11, 74-86.

Coulson, K. L., and Reynolds, D. W. 1971. J . Appl. Meteorol. 10, 285-1295.

Crist, E. P. 1983. Proc. Int. Symp. Machine Process. Remotely Sensed Data pp. 357-363.

Crouse, K. R., Henninger, D. L., and Thompson, D. R. 1983. Proc. Int. Geosci. Remote Sensing

Symp. 1, 2.1-2.8.

Crown, P. H., and Pawluk, S. 1974. Proc. Can. Symp. Remote Sensing, 2nd 1,450-462.

DaCosta, L. M. 1979. Ph.D. dissertation, Univ. of Missouri, Columbia.

Dangermond, J. 1983. Dig. Int. Symp. Geosci. Remote Sensing 1, 3.1-3.5.

DeWitt, D. P., and Robinson, B. F. 1976. Tech. Rep. 091576. Lab. Applic. Remote Sensing,

Purdue Univ., West Lafayette, Indiana.

Driscoll, R. S. 1971. Forest Service Research Paper, RM-67. US. Dept. of Agriculture.

Evans, R. M. 1948. “An Introduction to Color.” Wiley, New York.

Everitt, J. H., Gerbermann, A. H., and Cuellar, J. A. 1977. Photogr. Eng. Remote Sensing 43,

1041 - 1047.

Everitt, J. H., Gerbermann, A. H., and Alaniz, M. A. 1981. Photogr. Eng. 47, 1357-1362.

Frazee, C. J., Rahn, P. H., Westin, F. C., and Myers, V. I. 1974. South Dakota Agric. Exp. Sta.

Bull. 1276.

Gates, D. M. 1962. “Energy Exchange in the Biosphere.” Harper, New York.

Gates, D. M. 1963. Am. Sci. 51, 327-348.

Gates, D. M. 1965. Proc. Symp. Remote Sensing Environ., 3rd, pp. 573-600.

Gausman, H. W., Gerbermann, A. H., Wiegand, C. L., Learner, R. W., Rodriguez, R. R., and

Noriega, J. R. 1975. Soil Sci. SOC.Am. Proc. 39, 752-755.

Gausman, H. W., Learner, R. W., Noriega, J. R., Rodriguez, R. R., and Wiegand, C. L. 1977. Soil

Sci. SOC.Am. Proc. 41, 793-796.

Gerberman, A. H., and Neher, D. D. 1979. Photogr. Eng. Remote Sensing 45, 1145-1151.

Girard-Ganneau, C. M. 1975. Docteur Ingenieur dissertation, University of Paris-Sud, Center

&Orsay.

Grum, F., and Luckey, G. W. 1968. Appl. Opt. 7, 2289-2294.

Hellden, U., and Stern, M. 1980. Monitoring land degradation in Southern Tunisia: A test of

Landsat imagery and digital data. Lab. Remote Sensing, Lund Univ., Sweden.

Hilwig, F. W. 1976. 1 T C J . 1,26-42.

Hilwig, F. W., Goosen, D., and Kateieris, D. 1974. ITC J . 3, 289-312.

Hinzel, E. J., Weismiller, R. A., and Franzmeier, D. P. 1980. Tech. Rep. 080979. Lab. Applic.

Remote Sensing, Purdue Univ., West Lafayette, Indiana.

Hitchcock, H. C., Cox, T. L., Baxter, F. P., and Smart, C. W. 1975. Photogr. Eng. Remote Sensing

41, 1519-1524.

Hoffer, R. M., and C. J. Johannsen. 1969. In “Remote Sensing in Ecology” (P.L. Johnson, ed.),

pp. 1-29. Univ. Of Georgia Press, Athens.

Hoore, J. L. D., H. S. Teotia, and R. Goombeer. 1982. Abstr. Trans. Int. Congr. Soil Sci., 12th New

Delhi p. 134.



REFLECTANCE PROPERTIES O F SOIL



41



Horvath, E. H. 1981. Ph.D. dissertation, University of Arizona, Tucson.

Horvath, E. H., Post, D. F., Lucas, W. M., and Weismiller, R. A. 1980. Proc. Znt. Symp. Machine

Process. Remotely Sensed Data, 6th pp. 235-240.

Horvath, E. H., Klingebiehl, A. A,, Moore, D. G., and Fosnight, E. A. 1983. USGS Open-File

Rep. 83-880.

Horvath, E. H., Post, D. F., and Kelsey, J. B. 1984. Soil Sci. SOC.Am. J . 48, 1331-1334.

Hunt, G. R., and Salisbury, J. W. 1970. Mod. Geol. 1, 283-300.

Hunt, G. R., and Salisbury, J. W. 1971. Mod. Geol. 2, 23-30.

Hunt, G. R., and Salisbury, J. W. 1976a. Mod. Geol. 5, 211-218.

Hunt, G. R., and Salisbury, J. W. 1976b. Mod. Geol. 5, 219-228.

Hunt, G. R., Salisbury, J. W., and Lenhoff, C . J. 1971a. M o d . Geol. 2, 195-205.

Hunt, G. R., Salisbury, J. W., and Lenhoff, C. J. 1971b. Mod. Geol. 3, 1-14.

Hunt, G. R., Salisbury, J. W., and Lenhoff, C. J. 1973a. M o d . Geol. 4, 85-106.

Hunt, G. R., Salisbury, J. W., and Lenhoff, C . J. 1973b. M o d . Geol. 4, 217-224.

Hunt, G. R., Salisbury, J. W., and Lenhoff, C. J. 1973c. M o d . Geol. 4, 237-244.

Hunt, G. R., Salisbury, J. W., and Lenhoff, C. J. 1974. M o d . Geol. 5, 15-22.

Hutton, J. G. 1928. Proc. Int. Congr. Soil Sci., 1st 4, 164-172.

Hutton, J. G. 1932. Report of the Color Standards Committee. Am. Soil Survey Assoc. Bull. 13,

179-180.

Idso, S. B., Baker, D. G., and Gates, D. M. 1966.In“Advances in Agronomy 18” (A. G. Norman,

ed.), pp. 171-218. Academic Press, New York.

Imhoff, M. L., and Petersen, G. W. 1980. The role of Landsat products in soil surveys. Final

Report for Contr. No. NAS5-25667. NASA, Goddard Space Flight Center.

Imhoff, M. L., Petersen, G. W., Sykes, S. G., and Irons, J. R. 1982. Photogr. Eng. Remote Sensing

48, 133771342,

Johannsen, C . J. 1969. Ph.D dissertation, Purdue Univ., West Lafayette, Indiana.

Judd, D. B., and Kelly, K. L. 1939. U.S. NBS Jour. Res. ( R P 1239) 23, 355-385.

Karmanov, I. I. 1970. Sou. Soil Sci. 4, 226-238.

Kauth, R. J., and Thomas, G. S. 1976. Proc. Symp. Machine Process. Remotely Sensed Data pp.

41-51.

Kellogg, C. E. 1937. Soil survey manual. Misc. Publ. No. 274, US.Dept of Agriculture.

Kirschner, F. R., Kaminsky, S. A,, Weismiller, R. A,, Sinclair, H. R., and Hinzel, E. J. 1978. Soil

Sci. SOC.Am. J . 42, 768-771.

Kohnke, Helmut. 1968. In “Soil Physics,” pp, 39-54. McGraw-Hill, New York.

Kojima, M. 1958a. Soil Plnnt Food 3, 204.

Kojima, M. 1958b. Abstr. Soil Plant Food 3, 206.

Kornblau, M. L. 1979. M. S. thesis, Colorado State University, Fort Collins.

Kornblau, M. L., and Cipra, J. E. 1983. Remote Sensing Environ. 13, 103-1 12.

Kristof, S. J. 1971. J . Soil Water Conserv. 26, 15-18.

Kristof, S. J., and Baumgardner, M. F. 1975. Agron. J . 67, 317-321.

Kristof, S. J., and Zachary, A. L. 1971. Proc. Symp. Remote Sensing Environ., 7th pp. 20952108.

Kristof, S. J., and Zachary, A. L. 1974. Photogr. Eng. 40, 1427-1434.

Latz, K., Weismiller, R. A,, Van Scoyoc, G. E., and Baumgardner, M. F. 1984. Soil Sci. SOC.Am. J .

48, 1130-1134.

Lewis, D. T., Seever, P. M., and Drew, J. V. 1975. Soil Sci. SOC.Am. Proc. 39,330-335.

Lindberg, J. D., and Snyder, D. G. 1972. Am. Mineral. 57,485-493.

Longlois, K. H., Osterholz, L. C., and Kirschner, F. R. 1976. Indiana Acad. Sci. Proc. 85,

126.

.

Am. J. 44,667-676.

LOW,P. F. 1980. Soil S C ~SOC.



42



MARION F. BAUMGARDNER ET A L .



Mainguet, M. M., Spiers, B., Canon, L. B., and Langeraar, W. D. 1978. Application of Landsat

imagery to soil degradation assessment and mapping at 1:5,000,000: Niger, Upper Volta,

Eastern Mali, Northern Nigeria, Chad, and Central African Empire. FAO, Rome.

Mathews, H. L., Cunningham, R. L., and Petersen, G . W. 1973a. Soil Sci. SOC. Am. Proc. 37,

421 -424.

Mathews, H. L., Cunningham, R. L., Cipra, J. E., and West, T. R. 1973b. Soil Sci. SOC.Am. Proc.

37, 88-93.

May, G. A,, and Petersen, G. W. 1975. Remote Sensing Enuiron. 4, 21 1-220.

Meyer, M. P., and Calpouzos. L. 1968. Photogr. Eng. Remote Sensing 36, 11 16-1125.

Mimms, D. L. 1982. M.S. thesis, Pennsylvania State Univ., State College.

Mitchell, C. W., and Ghorashian, K. 1978. The application of Landsat imagery to soil

degradation mapping of Iran at 1:5,000,000. FAO, Rome.

Mitchell, C. W., and Howard, J. A. (eds). 1978. The application of Landsat imagery to soil

degradation mapping at 1: 1,000,000. FAO, Rome.

Mitchell, C. W., Pacheco, R., and Howard, J. A. 1978. The application of Landsat imagery to the

soil degradation mapping of Jordan, Syria, and Iraq at 1 :5,000,000. FAO, Rome.

Montgomery, 0. L. 1976. Ph.D. dissertation, Purdue University, West Lafayette, Indiana.

Montgomery, 0. L., and Baumgardner, M. F. 1974. Tech. Rep. 112674. Lab. Applic. Remote

Sensing, Purdue Univ., West Lafayette, Indiana.

Munsell, A. H. 1947. “A Color Notation,” 10th Ed. Munsell Color Co., Baltimore.

Munsell Color. 1975. “Munsell Soil Color Charts.” MacBeth Division of Kollmorgen Corp.

Baltimore.

Myers, V. I., and Allen, W. A. 1968. Appl. Opt. 7, 1819-1838.

Myers, V. I., Carter, D. L., and Rippert, W. J. 1966. J . Irrig. Drain. 92, 59-68.

Nickerson, D. 1940. Opt. SOC.Am. J . 30, 375-386.

Nickerson, D. 1946. Color measurement and its application to the grading of agricultural

products. Misc. Publ. No. 580, U S . Dept. of Agriculture.

Nicodemus, F. E., Richmond, J. C., Hsia, J. J., Ginsberg, 1. W., and Limperis, T. 1977. NBS

Monograph 160. U S . Govt. Printing Office, Washington, D.C.

Obukhov, A. I., and Orlov, D. S . 1964. Sou. Soil Sci. 2, 174-184.

O’Neal, A. M. 1923. Soil Sci. 16, 275-279.

Orlov, D. S . 1966. Sou. Soil Sci. 13, 1495-1498.

Pacheco, R. 1978. The use of Landsat imagery for assessing soil degradation in Morocco. Proc.

Int. SOC. Soil Sci. Rome.

Page, N. R. 1974. Agron. J . 66, 652-653.

Parada, N., and Pinto, S. 1983. Utilizacao de tecnicas de sensoriamento para a characterizacao

de erosao do solo no sw do estado de Sao Paulo. Instituto de Pesquisas Espaciais, Sao Jose

dos Campos, Brazil.

Parks, W. L., and Bodenheimer, R. E. 1973. Proc. Symp. Signif: Results Obtained Earth Resources

Technol. Satellite-1 N A S A SP-327 pp. 121-125.

Pazar, S. E. 1983. M.S. thesis, Purdue University, West Lafayette, Indiana.

Pendleton, R. L., and Nickerson, D. 1951. Soil Sci. 71, 35-43.

Peterson, J. B. 1980. Use of spectral data to estimate the relationship between soil moisture

tensions and their corresponding reflectances. Annu. Rep. O W R T Purdue Uniu. pp. 1-18.

Peterson, J. B., Robinson, B. F., and Beck, R. H. 1979. Proc. Symp. Machine Process. Remotely

Sensed Data pp. 264-273.

Planet, W. G. 1970. Remote Sensing Enuiron. 1, 127-129.

Ranzani, G. 1969. “Manual de Levantamento de Solos. Editora Blucher, Sao Paulo.

Rao, R. G . S., and Ulaby, F. T. 1977. Remote Sensing Enuiron. 6, 289-301.

Rao, K. V. S., Karale, R. L., and Singh, A. N. 1982. Abstr. Trans. Int. Congr. Soil Sci., 12th, New

Delhi. p. 132.



REFLECTANCE PROPERTIES O F SOIL



43



Resende, M. 1976. Ph.D. dissertation, Purdue University, West Lafayette, Indiana.

Rice, T. D., Nickerson, D., ONeal, A. M., and Thorp, J. 1941. Preliminary color standards and

color names for soils. Misc. Publ. No. 425, U.S. Dept. of Agriculture.

Robinson, B. F., and Biehl, L. L. 1979. Proc. Annu. Int. Tech. Symp., 23rd, SPIEE, Bellington,

Washington. 196, 16-26.

Robinson, B. F., and DeWitt, D. P. 1983. I n “Manual of Remote Sensing” (R. N. Colwell, ed.),

pp. 293-333. Amer. SOC.of Photogr., Falls Church, Virginia.

Schreier, H. 1977. Proc. Can. Symp. Remote Sensing, 4th I, 106-112.

Schutt, J. B., Holben, B. N., Shai, C. M., and Henninger, J. H. 1981. Appl. Opt. 20, 2033-2035.

Seevers, P. M., and Drew, J. V. 1973. Proc. Symp. Sign$ Results Obtained Earth Resources

Technol. Satellite-I, NASA SP-327 pp. 87-89.

Seevers, P. M., Lewis, D. T., and Drew, J. V. 1974. Proc. Earth Resources Technol. Satellitel, 3rd

pp. 225-232.

Shai, C. M., and Schutt, J. B. 1971. NASA X-762-71-266. Goddard Space Flight Center.

Shaw, C. F. 1937. Soil Sci. SOC. Am. Proc. 2,431-436.

Singh, A. N., Kristof, S. J., and Baumgardner, M. F. 1977. Lab. Applic. Remote Sensing, Purdue

Univ. Tech. Rep. 1 1 1477.

Soil Survey Staff, Soil Conservation Service, U.S. Dept. Agric. 1951. Soil survey manual. Agric.

Handb. (18).

Soil Survey Staff, Soil Conservation Service, U.S. Dept. Agric. 1975. Soil Taxonomy. Agric.

Handbook 436. U.S. Govt. Print. Office, Washington, D.C.

Steinhardt, G. D., Franzmeier, D. P., and Cipra, J. E. 1975. Indiana Acad. Sci. Proc. 84,463-468.

Stoner, E. R. 1979. Ph.D. dissertation, Purdue Univ., West Lafayette, Indiana.

Stoner, E. R., and Baumgardner, M. F. 1981. Soil Sci. SOC. Am. J . 45, 1161-1165.

Stoner, E. R., and Horvath, E. H. 1971. Proc. Int. Symp. Remote Sensing Enuiron., 7th pp.

2109-21 13.

Stoner, E. R., Baumgardner, M. F., and Swain, P. H. 1976. Agron. J . 68, 55-59.

Stoner, E. R., Baumgardner, M. F., Biehl, L. L., and Robinson, B. F. 1980a. Purdue Uniu. Agric.

Exp. Sta. Res. Bull. (962).

Stoner, E. R., Baumgardner, M. F., Weismiller, R. A,, Biehl, L. L., and Robinson, B. F. 1980b. Soil

Sci. SOC. Am. J . 44, 572-574.

Stoner, E. R., Joyce, A. T., and Hogg, H. C. 1983. Dig. Int. Symp. Geosci. Remote Sensing 1,

8.1 -8.7.

Strandberg, C. H. 1968. I n “Manual of Color Aerial Photography” (T. Smith and A. Abraham,

eds.), pp. 3-11. Amer. SOC.of Photogr., Falls Church, Virginia.

Thompson, D. R., and Henderson, K. E. 1984. Soil Sci. SOC.Am. J . 48, 1316-1319.

Thompson, D. R., Pitts, D. E., and Henderson, K. E. 1983. Soil Sci. SOC.Am. J . 47, 542-546.

Thompson, D. R., Henderson, K. E., Houston, A. G., and Pitts, D. E. 1984. Soil Sci. SOC.Am. J .

48, 137-142.

Valenzuela, C . R. 1979. Estudio integrado de 10s recursos naturales del departamento de Oruro,

La Paz, Bolivia, Programa ERTS/GEOBOL, pp. 240-384.

van Sleen, L. A. 1982. Landsat data: Their use and accuracy for small scale soil surveys and their

time and cost efficiency. Proc. Int. ConJ Remote Sensing Arid Semiarid Lands, Cairo.

Vinogradov, B. V. 1981. Sou. Soil Sci. 11, 114-123.

Weismiller, R. A,, and Kaminsky, S. A. 1978. J . Soil Water Conseru. 33, 287-289.

Weismiller, R. A,, Kirschner, F. R., Kaminsky, S. A,, and Hinzel, E. J. 1979. Lab. Applic. Remote

Sensing, Purdue Univ. Tech. Rep. 040179.

Weismiller, R. A., Persinger, I. D., and Montgomery, 0. L. 1977. Soil Sci. SOC.Am. J . 41,

1 166- 1170.

Westin, F. C. 1973. ERTS 1 imagery: A tool for identifying soil associations. Proc. Earth Survey

Problems through Use Space Tech., Gen. Assembly, Comm. Space Res., Konstanz.



44



MARION F. BAUMGARDNER ET AL.



Westin, F. C. 1974. Proc. Earth Resources Technol. Satellite-1 Symp., 3rd pp. 183-204.

Westin, F. C., and Frazee, C. J. 1976. Soil Sci. Soe. Am. J. 40, 81-89.

Westin, F. C., and Lemme, G . D. 1978. Photogr. Eng. Remote Sensing 44, 315-325.

Westin, F. C., and Myers, V. I. 1973. Proc. Symp. Sign$ Results Obtained Earth Resources

Technol. Satellite-1, NASA SP-327 pp. 973-980.

Young, E. R., Clark, K. C., Bennett, R. B., and Houk, T. L. 1980. Appl. Opt. 7, 3500-3505.

Zissis, G . J. 1979. In “The Infrared Handbook” (W. L. Wolfe and G. J. Zissis, eds.). Env. Res.

Inst. Michigan, Ann Arbor.

Zwerman, C. H., and Andrews, A. I. 1940. J . Am. Ceram. SOC.23,93-102.



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