J 

Third Semi-Annuai 

Progress Report 

To: National Aeronautics and Space Administration 

Goddard Space Flight Center 

Greenbelt, Maryland 20771 

Contract: NAS5-28358 

Title: Spectral characteristics and the extent of paleosol s 

of the Palouse formation 

Principal Investigator: Dr. B. E. Frazier 

Agronomy and Soils 

Washington State University 

Pull man, WA 991 64 

Col laborators: Dr. Alan Busacca 

Yaan Cheng 

Agronomy and Soils 

David Wherry 

Judy Hart I 

Steve Gill 

Digital Image Analysis Laboratory 

( NASA -CE- 18 0357 ) S F ECTR Al C EA E ACT E RIST ICs 

AND TEE EXlIENl CF OBLECSOLS GF IhE PALCUSE 

FCRHA %IC N Se siannua 1 Progress E€ port 

(Washington State Univ.) 22 F CSCL 086 Unclas 

N87- 15 8 26 

G3/46 43668 
Introduction 

The third six month period of our work has been devoted to analysis of 

image data and verification by comparison to previously gathered transect 

samples and to aerial photographs. We report work by objective as stated 

in our proposal. 

Progress by Objective: 

I.A. Develop spectral relationships from TM data that will define 

the spatial distribution of soil areas by levels of (1) organic 

matter in the surface soil, (2) iron oxide and clay in exposed 

paleosol B horizons, and (3) lime-silica accumulations in 

exposed pal eosol B horizons. 

B. Compare areas determined by the method outlined in A to patterns 

interpreted from color aerial photographs, and to ground 

observations on bare-soil fields. 

In this reporting period we have investigated a bare-soil field with 

exposed paleosols characterized by slight enrichment of iron. Spectral 

relationships were first investigated statistically by creating a data set 

with DN values spatially matched as nearly as possible to field sample 

points. 

which also were used to locate the sample transects. Chemical data for 

each sample point included organic carbon (easily oxidizable carbon by the 

method of Nelson and Sommers, 1975), free iron oxide (dithionite-citratebicarbonate method of Kittrick and Hope, 1963), and amorphous iron content 

(hydroxylamine method of Chao and Zhou, 1983). We also included the ratio 

of amorphous iron to organic carbon because there was an apparent inverse 

relationship between them (Table 1). 

This was accomplished by correcting the scene to UTM coordinates 

The organic carbon and frea iron oxide data are the same as in our first 

semiannual report but are repeated here to show relationships to amorphous 

iron in surface samples. Table 2 shows the distribution of amorphous iron 

in some profiles from the test field. The greatest amounts of amorphous 

iron are found in the Bt horizons as compared to either C, BC, or A 

horizons. Some Ap horizons show higher values than A horizons because 

tillage overburden contains B material that has been moved down slope. 

The chemical data, ON values, and various band ratios were examined with 

the program package Statistix (NH Analytical Software) in order to find the 

combinations of reflectance data most likely to show a relationship which 

would dependably separate the exposed paleosols from other soils. 

shows correlation coefficients (R) and P-values for the TM bands used 

individually. 

levels and amorphous iron was with TM5 and TM7. 

relationship with free iron oxide. Apparently there was not enough 

difference expressed at the soil surface of the cultivated field to 

differentiate it by reflectance in these single wavebands. 

Table 3 

The best chance for success at predicting organic carbon 

There was no good 

Better results were 

potential for discr 

5/7, 5/3, 5/2, 4/7, 

obtained with band ratios (Table 4). Ratios hav 

minating organic carbon on this site were TM 1/4 

3/5, 3/7, 4/1, and 4/5. The best candidates to 

ng 

5/4, 

1 
discriminate amorphous iron were 5/4, 4/7, and 4/5. The analysis suggests 

only marginal success for free iron oxide with 3/4, 4/3, and 5/7. Since 

organic carbon and amorphous iron are inversely related, the ratio of the 

two is best modeled with the same bands indicated for organic carbon 

a1 one. 

Me also looked at combinations of three bands or three ratios to predict 

the soil properties (Table 5). The best relationships were for organic 

carbon and the ratio of amorphous iron to carbon followed by amorphous iron 

and free iron oxide in that order. 

Cl uster analyses and Fastcl as cl assi f i cati on procedures were appl ied to the 

most promising of the band ratio combinations. Figure 1 shows the 

distribution of clusters in TM 5/3 by TM 3/4 data-space used to model the 

amorphous iron/organic carbon ratio. The distribution pattern shows a soil 

line and a group of clusters from areas of mixed plants and soil. The soil 

line shows a progression from a small ratio value at cluster 20 to a large 

value at cluster 22. There is an increase in amorphous iron from cluster 

20 to 22 and a decrease in organic carbon. There is a decrease in TM5 / 

TM3 DN which matches the decrease in organic carbon. The soil line is mapped 

in Figure 2a where the print density increases with increasing carbon. 

most eroded soils are well represented by the symbols -, =, and +. Figure 

2a may be compared to Figure 2b, an aerial photograph taken near the time of 

the satellite overpass. 

The 

Figure 3 shows the cluster distribution for the best model of amorphous 

iron. TM band ratios 5/3, 3/1, and 4/5 were used to produce this data set 

and the map in Figure 4. The soil line is represented by clusters 3, 4, 5, 

8, and 10 representing decreasing amounts of amorphcus iron from three to 

10. This produces a map similar to the one shown in Figure 2a, but with less 

detail. Again, the eroded soils are well represented; however, it is not 

clear which if any of these clusters in either data set represent B 

horizons from Holocene soils and which represent Bt horizons from 

paleosols. The exposed paleosols are well mapped but may include some of 

the younger soil B horizons. Final evaluation of these models cannot be 

carried out until the field drys later in spring. 

Figures 5 and 6 show the cluster distribution and Fastclas map for organic 

carbon in of the same area. These were derived by using band ratios 5/4, 

3/4, and 1/4. The striking similarity to the previous maps as well as the 

statistical data suggest that carbon is by far the most important soil 

property being mapped. If the small amount of iron in these soils has 

enough i nf 1 uence on ref 1 ectance to a1 low separation of eroded pal eosol s 

from eroded Holocene soils we have not yet found a way to do it. We feel 

that more conclusive evidence may be found by combining-data sets from this 

area and from the carbonate soil area reported in our second semiannual 

report. The carbonate soil area had clusters to represent the carbonateenriched paleosols, iron-enriched paleosols, and a sequence of organic 

carbon contents. Any clusters which are separable but which have similar 

low carbon values may be the ones associated with the various B horizons. 

.I.C. Define, on the basis of results of A and B to the extent 

possible, where exposed paleosols exist within fields that 

are not bare, but have a crop cover, and the distribution of 

2 
desi rabl e and undesirable soi 1 properties i n each field. 

We have studied this problem by using imagery from 1985, which covers the 

same fields that we worked on with 1984 imagery, to analyze the patterns of 

bare soil. On the field of interest, the 1984 summer fallow operation was 

followed by a winter wheat crop. Imagery for 1985 was acquired on June 15 

and July 17. Thus far, we have studied the June 15 image. The crop was 

nearing maturity, but had not ripened. An aerial photograph taken July 1 

(figure 7) shows a complete range of colors from green in the valleys to 

golden brown on south-facing slopes. 

was in the field on the date of the satellite overpass two weeks earlier. 

This photograph shows less green than 

Me have used two techniques to study this problem, a clustering and 

classification routine, and principal components analysis. The chosen data 

set included the winter wheat field to be mapped and several adjacent 

fields with bare soil, spring wheat, and winter barley. Clustering was 

done using TM band ratios of 5/4, 3/4, and 2/4. 

clusters (Figure 8) was very similar in shape to the one acquired from the 

1984 data for the same area; with the exception that the June 15, 1985 

scene has clouds and cloud shadows in it. The soil line forms a flat side 

in the upper right corner of the graph which has TM 5/4 as the y axis and 

TM 3/4 as 'the x axis. 

origin. 

ends of the soil line and the tip of greenness. By studying the Fastclas 

map of these clusters (Figure 9) and comparing it to an aerial photograph 

of the bare soil (Figure 10) and to the aerial photograph of the crop 

(Figure 7) we can find the locations of clusters which represent known 

locations of paleosol exposures or near exposures. 

The distribution of 

Greenness clusters are tightly grouped toward the 

Clouds and cloud shadows fall below the triangle formed by the two 

Clusters 24, 27, 26, and 28 in Figure 9 which form the upper right end of 

the greenness block of clusters are the ones which match the known 

locations of the paleosols. 

/, =, and - for clusters 24 and 27, 26, and 28, respectively (Figure 9). 

The pattern which forms on the map is similar to the lightest colored areas 

of the aerial photographs (figures 7, 10) and to the patterns found earlier 

on the bare-soil field made from the 1984 data. 

These are mapped by Fastclas with the symbols 

Principal components analysis was used based on the idea that nonuniform 

areas of the crop canopy would be separted because they exhibit greater 

variation in reflectance values. Less than complete cover by plants means 

that soil and plant reflectances are mixed. The analysis was run with TI4 

bands 2, 3, 4, 5, and 7. The first three vectors accounted for 99.8% of 

the variance in the scene. These were printed and on visual evaluation 

showed that the areas of nonuniformity were associated with known locations 

of the paleosols. Some aspects of the paleosol patterns were visible in 

each of the three components so we decided to combine them using the 

cluster/Fastclas routine. This resulted in clusters being separated on the 

basis of variance. 

paleosols, roads, clouds and cloud shadows. A Fastclas map (Figure 11) is 

supplied for comparison to the other maps and aerial photographs. 

Those with high values were associated with the 

We have not completed these analyses yet. We would like to continue with 

an analysis of correlation statistics to establish some degree of agreement 

between the images with crop cover and the images of bare soil. We would 

3 
i 

also like to study how the ratio clusters shift in the distribution field 

as a result of introducing various amounts of plant cover. It is evident 

in Figure 8 that cluster 28 was near the equivalent position of cluster 44 

at the lower end of the soil line when we analyzed the 1984 data. It would 

be of interest to know where the rest of the soil line would be located if 

partially covered with plants and plotted in TM ratio data-space. We would 

also like to try other kinds of image enhancement routines on the principal 

components and on the output from cluster and Fastclas. 

References 

Chao, T. T., and Liyi Zhou. 1983. Extraction techniques for selective 

dissolution of amorphous iron oxides from soils and sediments. Soil 

Sci . SOC. Am. J. 47 925-232. 

Kittrick, 3. A., and E. W. Hope. 1963. A procedure for the particle-size 

separation of soils for X-ray diffraction analysis. Soil Sci. 96:319- 

325 * 

Nelson, D. W., and L. E. Sommers. 1975. A rapid and accurate procedure for 

estimation of organic carbon in soils. Indiana Acad. of Sci. Proc. 

84:456-462. 

NH Analytical Software, 801 West Iowa Avenue, St. Paul MN 55117 

4 
Table 1. Content of organic carbon, amorphous iron, free 

iron oxide, and the ratio of amorphous iron to organic 

carbon in surface soils of the test site. 

Soi 1 Organ i c Amorphous Free Am. Fe/OC 

Sample Carbon Iron Iron 

P1-1 

2 

3 

4 

5 

6 

7 

8 

9 

10 

P2-1 

2 

3 

4 

5 

6 

7 

8 

9 

10 

11 

12 

P3-1 

2 

3 

4 

5 

6 

7 

8 

9 

10 

13.7 

10.2 

7.2 

17.5 

15.1 

9.1 

12.4 

17.2 

14.4 

16.7 

13.8 

17.6 

12.5 

11.4 

20.6 

17.8 

20.7 

18.2 

8.2 

14.4 

14.9 

20.0 

15.7 

14.8 

9.7 

12.6 

20.5 

17.4 

21.4 

12.9 

13.3 

17.1 

3.68 

4.51 

6.80 

3.91 

3.51 

6.49 

5.67 

4.50 

3.79 

2.92 

5.56 

3.79 

5.23 

4.74 

4.40 

3.78 

3.82 

4.61 

6.35 

4.76 

3.16 

3.65 

3.31 

4.08 

6.28 

5.44 

4.19 

4.35 

3.45 

3.53 

5.15 

3.21 

5.55 

8.03 

8.51 

7.70 

8.11 

9.18 

7.65 

8.88 

6.83 

5.92 

9.66 

8.76 

8.44 

7.49 

7.89 

7.73 

7 -92 

8.41 

7.59 

7.27 

8.39 

6.34 

8.25 

7.76 

7.73 

9.14 

8.40 

6.69 

6.31 

8.54 

7.78 

6.17 

26.9 

44.2 

94.4 

22.3 

23.2 

71.3 

45.7 

26.2 

26.3 

17.5 

40.3 

21.5 

41.8 

41.6 

21.4 

21.2 

18.5 

25.3 

77.4 

33.1 

21.2 

18.3 

21.1 

27.6 

64.7 

43.2 

20.4 

25.0 

16.1 

27.4 

38.7 

18.8 
Table 2. Vertical distribution of iron 

oxides in soils from the test 

site. 

Thatuna series 

AP 0-50 

A 50-63 

A/B 63-115 

E 115-140 

Btb 140-260 

Naff series 

AP 0-24 

A 24-52 

BA 52-77 

Btbl 77-120 

btb2 120-210 

4.63 

4.55 

4.53 

5.36 

5.91 

6.17 

5.50 

6.03 

7.17 

7.18 

8.15 

8.35 

8.93 

8.67 

9.21 

8.45 

7.66 

6.18 

9.48 

8.64 

Pal ouse seri s 

A 0-35 4.29 9.55 

B/E 35-40 5.57 9.60 

Btb 40-100 7.44 10.81 

BC 100-135 5.81 10.74 

Garfield series 

AP 0-13 5.69 . 9.44 

Btb 13-33 8.46 10.57 

C 33-87 5.14 10.50 
Table 3. Comparison of R and P values for reflectance and 

chemical data. 

1 (Blue) R 0.210 -0.271 -0.085 -0.286 

P 0.266 0.111 0.805 0.086 

2 (Green) R -0.151 -0.085 -0.113 0.005 

P 0.504 0.805 0.684 0.999 

3 (Red) R -0.194 -0.059 -0.160 0.064 

P 0.324 0.900 0.462 0.883 

4 (IR1) R -0.257 0.011 -0.034 0.136 

P 0.138 0.996 0.966 0.573 

5 (IR2) R 0.398 -0.396 -0.072 -0.471 

P 0.008 0.009 0.856 0.001 

7 (IR3) R 0.538 -0.435 -0.172 -0.568 

P 0.000 0.003 0.411 0.000 
* " , 

Table 4. . Comparison of R and P values for TM band ratios and 

chemi cal data. 

1/4 

3/4 

5/4 

5/7 

5/3 

5/ 1 

5/2 

3/1 

3/2 

4/7 

3/5 

3/7 

R 

P 

R 

P 

R 

P 

R 

P 

R 

P 

R 

P 

R 

P 

R 

P 

R 

P 

R 

P 

R 

P 

R 

P 

0.557 

0.000 

0.094 

0.768 

0.703 

0.000 

-0.533 

0.000 

0.538 

0.000 

0.415 

0.005 

0.609 

0.000 

-0 -412 

0.006 

-0 - 211 

0.264 

-0.696 

0.000 

-0.519 

0.000 

-0.611 

0.000 

-0- 238 

0.182 

-0.151 

0.506 

-0.437 

0.003 

0.271 

0.110 

-0.283 

0.090 

-0.366 

0.018 

-0.372 

0.015 

0.090 

0.786 

0.005 

0.999 

0.425 

0.004 

0.283 

0.091 

0.333 

0.035 

-0.032 

0.969 

-0.323 

0.043 

-0.046 

0.939 

0.302 

0.064 

0.103 

0.726 

-0.042 

0.948 

0 -034 

0.966 

-0.184 

0.363 

-0.222 

0.229 

0.133 

0.589 

-0.085 

0.807 

0.011 

0.997 

-0.433 

0.003 

-0.123 

0.637 

-0.651 

0.000 

0.464 

0.001 

-0.472 

0.001 

-0.463 

0.002 

-0.552 

0.000 

0.278 

0.199 

0.152 

0.498 

0.655 

0.000 

0.464 

0.001 

0.550 

0.000 
I 

.. 

Table 4. Comparison of R and P values For TM Band Ratios and 

cherni cal data (continued) . 

4/1 R 

P 

4/2 R 

P 

4/3 R 

P 

4/5 R 

P 

-0.531 

0.000 

-0.341 

0.030 

-0.098 

0.749 

-0.677 

0.000 

0.203 

0.292 

0.223 

0.224 

0.173 

0.405 

0.435 

0.003 

0.024 

0.982 

0.162 

0.456 

0 - 307 

0.058 

0.035 

0.964 

0.403 

0.007 

0.340 

0.031 

0.155 

0.489 

0.651 

0.000 
Table 5. Selected combinations for mapping organic carbon, 

amorphous iron ,free iron oxide, and ratio of Am Fe/OC. 

Soi 1 Properties Combination R Square P-val ue 

(TM Bands) 

Organic Carbon 1-4-7 

1/4-5/2-311 

Amorphous Iron 3-4-5 

5/3-3/1-4/5 

Free Iron Oxide 3-5-7 

5/3-3/5-4/7 

Ratio of Am.Fe/OC 3-4-5 

3/4-5/4-5/3 

0.562 

0.586 

0.300 

0.301 

0.190 

0.193 

0.517 

0.524 

0.000 

0.000 

0.011 

0.011 

0.096 

0.092 

0.000 

0.000 
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ORIGINAL PAGE IS 

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Figure 7. Ripening winter wheat field shows white color where paleosols 

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