M. LEONARD BRYANW. D. STROMBERG

THOMAS G. F ARRJet Propulsion Labomtory

Pasadena, CA 91103

Computer Processing of SARL-Band Imagery

Digital filtering and thresholding were applied to SAR scenesof sea ice and fresh-water lakes.

INTRODUCTION

T HE INTERPRETATION of side-looking air­borne radar (SLAR) images obtained

from either real aperture radar (RAR) or homsynthetic aperture radar (SAR) systems hasbeen progressing for the past decade (Dun­bar, 1975; Page and Ramseier, 1975). Todate, data from a variety of systems operatingat numerous frequencies (e.g., K (18-26.5GHz); K u (12.5-18 GHz); x (8-12.5 GHz);

The wavelength of the operating radar is ofequal importance in defining these returns.

Present imaging radars lack both a calibra­tion within the entire system and a quantifi­able measure of their stability. The formerrefers to the inability to determine absolutevalues (such as 0-°) of targets and the latter tothe repeatability of the values which, al­though not absolute, may be obtained onsubsequent flights over a given target area.

ABSTRACT: A continuing problem with the interpretation ofsyntheticaperture radar (SAR) data, especially in the image format, is the factthat such radar systems genemlly are not calibmted. This tends toreduce the validity of computer processing in the form of automaticinterpretation as it may be applied to SAR imagery. However, forsome classes of targets, i.e., those which have especially constantand high or low returns, such automatic discrimination can be at­tained easily and quickly by digitally filtering and thresholding thedata. We have applied such procedures to two scenes, one of sea iceand the other offresh-water lakes. The orientation of leads (througha Fourier transform) together with the percentage of open water inthe entire sea ice scene is quickly attained. For the lake scene theareas of lakes were determined with a high accuracy by using thestandard library routines in a General Electric Image 100 system.These techniques demonstrate the validity ofmachine processing forobtaining quantitative data for some classes of targets as seen byuncalibrated synthetic aperture radars.

L(I-2 GHz)) have been interpreted visually.Although there is not a direct transfer of in­terpretations £i'om one system to that of thenext, there is apparently a direct transfer ofinterpretation methodologies. Hence, it isgenerally agreed that surface roughness andelectrical properties and look and depres­sion angle of the radar are the primary factorsconb'olling the backscatter of incident radarenergy and therefore the image brightness.

Primarily for these reasons, radar interpreta­tion has been largely confined to the mode ofphoto interpretation dealing with shape, lo­cation, time, texture, and relationships tosurrounding features. In such a situation,computer processing of radar data is primar­ily concerned with the enhancement of thetarget features (e.g., edge enhancement, con­trast stretching of intensity).

This does not mean, however, that compu-

1283PHOTOGRAMMETRIC EGINEERING AND REMOTE SENSING,

Vol. 43, No. 10, October 1977, pp. 1283-1294.

1284 PHOTOGRAMMETRIC ENGINEERING & REMOTE SENSING, 1977

TABLE 1. JPL RADAR SYSTEM PARAMETERS

L-Band

FIG. 1. Location of the study sites used in thiswork.

ter processing techniques, in and of them­selves, cannot be a major contributor to radarimage interpretation (Larson et ai., 1974). Insome cases the information obtained fromcomputer processing may directly yield re­sults which are either unattainable withother methods or available only throughlaborious and time-consuming work. Thispaper describes some of our work in theareas of hydrology and polar ice which de­fine possible uses of automatic picture pro­cessing of uncalibrated radar imagery.

THE RADAR SYSTEM AND STUDY AREAS

The data used in this study were collectedby the Jet Propulsion Laboratory's (JPL)L-band synthetic aperture radar mounted in

/

Transmitted Peak PowerFrequency (wavelength)Pulse Rep. Frequency

Pulse WidthBandwidthAntenna

Polarization

Recorder

Areas Resolution

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4 kw1215 MHz (25 cm)1 KHz at platformV=250 m/sec. velocity1.25/JLsec.10 MHzPhased array75 x 25 x 5 cmHH, HV; or VV, VH.Range beamwidth 90°centered 45° off vertical.Azimuth 18° centered onzero doppler.Goodyear 102, dualchannel, 5" film.Nominally 25 m x 25 m.

the NASA CV-990 aircraft. This radar, thespecifications for which are presented inTable I, was operated at approximately30,000 feet altitude. Two study areas, onelocated at 73°30' N, 140° 00' W in theBeaufort Sea and consisting of sea ice andthe other at 70°30' N, 156° 00' W near Admi­ralty Bay and composed primarily oflakes onthe Alaskan North Slope, were used (Figure1). All were L(HH) data collected on100CT75 and 260CT75 (for the sea-icescene) and 200CT75 for the fresh water lakescene.

ApPROACH

From the earlier discussion it follows thatpicture processing with uncalibrated SARdata is of limited utility although, for certaintypes or classes of targets, such efforts canyield good results. The targets selected forstudy should have constant returns almost ir­respective of the wavelength or the depres­sion angle of the radar. Because smooth sur­faces (e.g., unrippled water surfaces, playalakes, and mud Hats) are always imaged asblack "no return" areas (specular reHectors),their automatic discrimination should bequite easy. Other areas of the imagery arealso black (e.g., radar shadows) and to dis­criminate these two classes (smooth homshadows) would be impossible if one were towork only in the automatic picture process­ing mode. Alternatively, in areas wherethere is very little topographic relief, and inwhich the interpreter has some basic con­ception of the nature of the surface and itsconfiguration, the discrimination of suchblack areas is relatively simple. Hence, thetwo areas which have been selected forstudy consist of some lakes of the Alaskan

COMPUTER PROCESSING OF SAR L-BAND IMAGERY 1285

North Slope and open water of the Arctic seaice; both scenes are of areas having very lit­tle topographic relief.

In both study areas, following data digiti­zation and thresholding, the percentage ofthe area which is at any given quantitizedgrey level can be determined. Also, for thesea-ice study area, through a Fourier trans­form, it is possible to prepare a rose diagramgiving the orientation of the leads.

Difficulties in such a study are few, but areof major importance and must be consideredby the interpreter. In the sea-ice case, as icemoves and opens, the water surface is di­rectly visible to the radar imagery and is eas­ily identified. However, if the ice remainsstagnant, this water will begin to h'eeze andthus a thin ice cover, often indistinguishablefrom the open water on the SAR imagery,will form. It then requires additionalamounts of movement to form small ridges(which appear as bright linears) within thethin ice cover to properly identify this newsurface. In these cases it is the smoothness ofthe sea surface (or the smooth surface of thenew sea ice) rather than the nature of thesurface which is controlling the radar imagetone (Bryan, 1976). For such scenes, sequen­tial data are of great importance (Johnsonand Farmer, 1971; Ketchum and Tooma,1973). Seasonality of the data also plays animportant role for during the summermonths of July to September, when there issurficial melting of the sea ice, smooth meltponds and increased dampness of the uppersurface often combine to give very dark re­turns. Such returns can be distinguished byusing a simple level slicing technique as inthis study, but proper identification couldnot be so easily f~lcilitated.

In the case of the hesh-water lakes andrivers, for data collected at any season otherthan late winter or spring (February-June),the surface of the water or of the ice willgenerally be physically smooth. Therefore,imagery of the lake will be black on the SARdata. The oriented lakes, which have re­sulted hom the wind-induced erosion ofpermafrost on the North Slope, will, duringthe winter season, have approximately 2meters of ice on their surfaces. In these areaswhere the lake has been frozen to the bottomthe radar returns will be low; returns will behigh for those areas of the lake which areunderlain by a water layer. (Elachi et al.,1976; Sellman et al., 1974; Campbell et al.,1975). In the spring, when low density snowice has developed, and later in the summerwhen the ice on the small lakes is candelingand disintegrating, the resulting roughness

of the lake surface should cause brighter re­turns on the SAR data. Hence, seasonality ofthe data collection continues to be of pri­mary importance and the technique we use isbest exploited when the lakes are com­pletely ice h'ee, or have new, smooth, andthin covers of crystalline ice. In October,when our data were collected, the lakeswere not fi'ozen to the bottom and only verythin and quite homogenous ice covers con­sisting primarily of black ice overlain by athin layer of snow existed. Snow ice, whichoften causes considerable scattering of theradar energy, was not sufficiently developedto affect the backscattering.1

A final problem, resulting £i'om the use ofuncalibrated SAR data, is that the minimumsignal return may be below the radar systemnoise . .Thus, due to variations in the dark­room procedures, it may be possible thatsystem noise appears on the photographicimagery. Such areas, which are physicallysmooth and theoretically dark on SAR imag­ery, may have a very low grey tone on thephotographic product (Larson et al., 1974).

STUDY Of ARCTIC SEA ICE

One of the major problems of studyingArctic sea ice is the lack of high-resolutiondata which have been collected duringperiods of inclement weather ancIJor dark­ness. Efforts at modeling sea-ice movementsand at understanding the heat balance prob­lem over the Arctic Ocean are thus ham­pered by the lack of very basic data concern­ing the gross movements of the ice and thepercentage of open water of the ArcticOcean. For example, it is noted that seasonalvariations in the areal extent of the icecoverage of the Arctic Ocean is about 15 per­cent (for the Antarctic it approaches 80 per­cent). These ice-covered sea surfaces thusrepresent one of the most rapidly movingand varying solid surfaces of the earth, andfor studies of ice and ocean dynamics it is ofprimary importance to know the nature ofthese movements in both the spatial andtemporal domains.

Thus, as stated by Fletcher (1971, pp. lO-ll), there is a need:

... to achieve quantitative understanding ofthe interaction between the fields of motionof the atmosphere, the pack ice, and the liquid

1 Such scattering is of major importance in pas­sive microwave remote sensing, especially for thedetection of aufeis on northern rivers as theSagavanirktok, Ivishak, and Echooka (Hall, 1976).Discussion of interpretation of SAR data for freshwater lakes is given in Bryan and Larson (1975).

1286 PHOTOGRAMMETRIC ENGINEERING & REMOTE SENSING, 1977

SLANT RANGE

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FIG,2. Geometry of the data obtained by the JPLL-Band Radar.

ocean and to develop the capability to simu­late this interaction by means of a mathemati­cal model. The ultimate goal is to predict icemovement and deformation and heat ex­change between the ocean and the atmosphere.

The National Aeronautics and Space Ad­ministration, in cooperation with severalother national agencies and specific projects,has been involved in an Arctic ExperimentProgram in an effOit to obtain such remotelysensed information by using, among othersensors, the JPL SAR. Data presented in thispaper were collected during one such proj­ect, the Arctic Ice Dynamics Joint Experi­ment sponsored by the National ScienceFoundation (Untersteiner, 1974; Weeks etal., 1974; Campbell et al., in press). In orderto obtain sufficient areal coverage it was nec­essary to make multiple passes with the SAR.The SAR views only the right of the aircraft,at an angle extending from nadir to approxi­mately 55°. Thus, from a flight altitude of30,000 ft. (9144 m) a slant range swathwidth of approximately 50,800 ft. (15.5 km)would be imaged with each pass. The result­ing data were in the slant range mode fromwhich a ground range (map correct) data setcould be generated (Thompson et al., 1972)(Figure 2). For this portion of the study wedid not conduct that correction; rather, wevisually mosaicked all adjacent passes tomake the complete (but uncorrected)mosaics of the sea-ice study site which arepresented as Figures 3a,3b2 . As can be seen

2 Because the sea ice drifts at approximately 0.3to 0.5 Ian per day, it is noted that the geographic

in these figures, there are some imperfec­tions in the mosaics in that the adjacentstrips do not always have sufficient overlapto avoid gaps, and especially in the southernfour strips of the 260CT75 mosaic (Figure3b) the image outputs of the several dataruns were quite different from those of theremai nder of the study area. These completeand uncorrected mosaics (Figures 3a, 3b)were optically scanned, digitized on a mi­crodensitometer with a 50 /Lm sample spac­ing, and subjected to digital processing tofacilitate flnther analyses.

DIGITAL PROCESSING

Digital processing was performed in theImage Processing Laboratory at JPL with animage processing language and applicationssoftware known as VICAR, implemented onan IBM 360/65 computer. The objectives ofthis work were to:

• improve the subjective appearance (reducethe differences between strips and elimi­nate the brightness gradient within thesb'ips),

• compute the percentage area comprised ofleads and other open water, and

• provide a quantitative measure of theorientation of the leads.

In order to reduce the brightness gradientacross each component strip and to equalizetheir average brightnesses, the mosaics were"high pass" filtered. In general, this opera­tion removes all low spatial frequency varia­tions (i.e., the slowly varying brightness gra­dient) and sets the average data value to aspecified level. However, in the case ofthese mosaics, the high contrast present be­tween the floes and the leads and also at theedges of the mosaics would have producedan undesirable effect in the filtered images.The effect, sometimes referred to as "ring­ing," consists of the introduction of oppositepolarity shadows on either side of a bright ordark feature. While "ringing" always occursin "high pass" filtering, its appearance isusually negligible. Only in the presence ofhigh amplitude and abrupt variations, as atthe edges of leads or across ridges, does itbecome objectionable. To avoid "ringing" itwas necessary to employ a recently de­veloped, computationally lengthy version ofthe "high pass" filter which modifies itselfin the presence of sharp discontinuities(Schwartz and Soha, 1976). Generally quite

coordinates of the sea-ice test site have changedbetween lOOCT75 and 260CT75. Close exam­ination of the mosaics reveals that the same area ofice is covered on the two data flights.

COMPUTER PROCESSING OF SAR L-BAND IMAGERY 1287

I138"W

I139'W

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~ AIDJEX TEST SITE SYNTHETIC APERTURE RADAR MOSAIC"If - L-BAND -HH POLARIZATION (UNCORRECTED)

10 OCTOBER 1975

ARCTICEXPERIMENTPROGRAM- III

(a)

I139'W

I140'W

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IARCTIC ~ AIDJEX TEST SITE SYNTHETIC APERTURE RADAR MOSAICEXPERIMENT B L-BAND -HH POLARIZATION (UNCORRECTED)

PROGRAM - III . 26 OCTOBER 1975I

(b)FIG. 3. Sea Ice Study Site, L(HH) SAR imagery: (a) uncorrected mosaic forlOOCT75, (b) uncorrected mosaic for 260CT75.

successful results, Figure 4(a,b), were ob­tained with this adaptive filter. However,some residual "ringing" is apparent at theright of both mosaics near the locations ofthe geographic coordinates seen in Figure 3.Further adjustment of the control parametersin an additional application of the filter

could have reduced the severity of the effect,but the cost was not felt to be warranted inview of the limited extent of the phenome­non.

Application of the "high pass" filter madepossible the isolation of the leads by simplebrightness thresholding. In order to deter-

1288 PHOTOGRAMMETRIC ENGINEERING & REMOTE SENSING, 1977

(b)FIG. 4. The results of high pass filtering Figure 3: (a) filtering of Figure 3a, IOOCT75, (b)filtering of Figure 3b, 260CT75.

mine a level which would separate openwater and thin ice £i'om other ice types, im­ages thresholded at several candidatebrightness values were generated and com­pared with the filtered mosaics. An intensitytransformation which mapped all brightnessvalues less than the threshold to one valueand those above to another value was thenundertaken. The binary images thus gener­ated are displayed in Figure 5. The percen­tage of area occupied by leads was obtainedfrom histograms of the binary images withadjustments to compensate for the irregularmarginal areas surrounding the mosaics. Thearea imaged and represented in Figure 5aand 5b are 8,472 km 2 and 8,020 km 2 respec­tively. Leads comprised 1.6 percent of thearea for lOOCT75 (Figure 5a) or 136 Km 2

and 1.1 percent or 88 Km2 for the study areafor 260CT75 (Figure 5b).

A measure of the orientation of the leadswas obtained through automated examina­tion of the Fourier transforms of the binarylead pictures. The relative contribution of

Fourier components within one degree in­tervals was determined by integrating theamplitude of the Fourier transform over con­secutive one degree pie-shaped wedges. Alinear feature produces a long narrowmound, oriented in the same direction as thefeature, in the amplitude of its Fourier trans­form. The cumulative effect of a non­uniformly distributed, randomly oriented setof features is to generate a transformamplitude surface which has largeramplitude along some radii than others.Therefore, by radially integrating in thetransforms of the binary lead images, theproportion of components at each orientation'was obtained. Polar plots of these integralsare displayed in Figures 6(a,b). The radialdistance to the curve represents the propor­tion of leads parallel to the radius.

APPLICATIONS OF PROCESSING OF SEA ICE

SCENES

Because a satellite borne imaging radarsystem will have predetermined orbits, and

---- --------------------------------------------

COMPUTER PROCESSING OF SAR L-BAND IMAGERY 1289

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,.~~'>

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<,.,

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.. ".~.'~~<:jI

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(b)FIG. 5. The results of thresholding the high pass filtered images shown in Figure 4: (a) forlOOCT75, dark areas representing leads and other open water areas, constitute 1.6 percent ofthe entire scene, (b) for 260CT75, dark areas representing leads and other open water areas,

given that such a system will be polar orbit­ing, radar imagery of sea ice similar to thatused in this study will become available.These data will be available for each satel­lite pass, assuming the sufficient collectionand storage abilities of the orbiting radar.Seasat radar, for example, will probably pro­vide better data than we have used becauseits swath width will be approximately 199km. This will yield a coverage similar to thatprovided by our entire mosaic and reducethe processing problems by removing theneed for the first (brightness equalization)picture processing operation.

Through the remaining digital processingtechniques we can obtain information con­cerning the gross movements of sea icethrough time. Changes in both the percen­tage of dark areas (which represent openwater and recently refi'ozen leads) and theorientation of these areas will allow theoceanographer to quickly identifY areas of

major ocean and ice dynamics. By creating aset of sequential data for several geographicareas of the polar seas a hierarchy of zones ofprogressively intense oceanic activity inboth the space and time dimensions can bedeveloped. An increased understanding .ofocean dynamics will be available to sci­entists developing mathematical modelsdealing with heat balance, physical oceanog­raphy, and oceanic circulation of the polarseas by using such data sets.

As an example of the nature of the synopticenergy budgets over the Beaufort Sea, wesummarize Vowinckel and Orvig (1971):

• The "oasis effect," that is, irregularities inconditions over even the most uniform sur­face types are quite pronounced in thePolar Oceans;

• For polar oceans, absorbtion of short-waveradiation is higher over open water thanover ice; but the total energy losses aregreater over open water than over ice, and

1290 PHOTOGRAMMETRIC ENGINEERING & REMOTE SENSING, 1977

180"10 OCT 75

have used in this study, will help fill theseinformation gaps.

One additional comment must be made.We note that the discrimination of the areasyielding very low backscatter is relativelysimple, but the correct identiflcation of suchareas is somewhat more difficult. Althoughdata concerning microwave emissivity fromice and open water are quite unambiguous(open water having emissivities approxi­mately 50 percent of that of ice at 3.0 and 1.0cm wavelengths (Wilheit et ai., 1972)), suchdata collected from satellite altitude by mi­crowave radiometers have low resolutions (inthe neighborhood of 32 km).3 Thus it ap­pears that the best system for correct iden­tification of ice types and percentage of openwater is to combine the all-weathercapabilities of the two (active and passive)microwave systems in which the SAR pro­vides the very high resolution whileradiometers provide accurate surface typeidentification (Campbell et ai., 1975). Thiswill allow the development of algorithms forinterpretation of pixels having intermediatebrightness temperatures in the radiometerdata (such as presently received by the Nim­bus satellite series), with the SAR beingused to give data concerning percentage ofice coverage of the given Nimbus data pixel.

STUDY OF NORTH SLOPE LAKES

The radar cross-section ofland is generallyhigher and more varied than that of theocean's surface (Long, 1975). This createssome basic problems with respect to compu­ter processing of uncalibrated radar data ofland scenes. The wide variety of returns, andthe close juxtaposition of the strength of thebackscatter in both space and intensity, re­quires that we again seek features whichhave fairly constant returns. As discussedpreviously, fresh-water surfaces, liquid orfrozen (assuming that the latter are not ho­zen to the bottom), are very good candidatesurfaces for this study.

Such features, even on the Alaskan NorthSlope, are of both practical and scientific in­terest. With the development of this area,especially with respect to oil exploration,there is a need for water supplied for bothindustrial and domestic use. Also, becausesurface travel during the summer is quiterigorous, it has been suggested that it wouldbe economical to use frozen lakes as airfields

3 Mircowave radiometers on Nimbus G and theSeasat SMMR, operating at 37 GHz, will have aresolution of25 km by 16 km for the elliptical foot­print.

26 OCT 75

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this additional loss is supplied by the oceanwater itself(e.g., the sensible heat flux overwater is 63 times that over ice at the sametime, and of an opposite sign (for Feb­ruary));

• Open water areas are not negligible withrespect to the assessment of regional valuesfor the turbulent flux, and under celtainconditions the direction of the areal netflux may be detelmined by a few percent ofopen water (Table 2);

• Compared to the importance of open water,the ice thickness is of minor consequence;and

• Thus, it is concluded that, u ••• the ice co­vered Polar Ocean is a heat sink during thewhole year as are also the open water areasduring summer. During winter, however,the open water spots present great heatsources."

The implications with respect to synopticair mass meteorology are obvious.

At present, vast areas of the open ocean,and for extensive periods of time, are essen­tially unknown with respect to their trueocean dynamics. The inclusion of satelliteborne active microwave data, such as we

(b)FIG. 6. Polar plots of the Fourier h'ansfonn per­f0l111ed on Figure 5. Radial distances to the curvefrom the origin represent the proportion of leadsand other open water areas within the scenewhich are parallel to that radius: (a) for lOOCT75,(b) for 260CT75.

COMPUTER PROCESSING OF SAR L-BAND IMAGERY 1291

TABLE 2. THE PERCENTAGE OF THE OCEAN SURFACE, IF OPEN WATER, WHICH WILL GIVE AN ENERGYLoss EQUAL TO THAT FROM THE REMAINING IcE COVERED SURFACE

(VOWI CKEL AND ORWIG, 1971, p. 156).

OCTOBER NOVEMBER DECEMBER JANUARY FEBRUARY MARCH

5.2 2.4 0.8 0.1 0.1 0.2 %

to support winter drilling and explorationpeuties (O'Lone, 1975). Hence, we feel thatthere are needs for continuing the study ofthe information extractable from remotelysensed data, including SAR data, of theseareas.

DIGITAL PROCESSING

For this portion of the study the originalSAR data were scanned at 40 ILm aperture,geometrically corrected (Figure 7), and pro­cessed by using a General Electric Image100 multispectral analyzer. The returns homthe lakes were low (being horizontal specu­lar reflectors). These were enhanced, withrespect to the surrounding terrain, by thelinear contrast stretch program. The lakeswere then separated from the surroundingterrain by a density slicing technique andstored in the theme storage areas. Nineteenlakes within the candidate scene, varying insize hom 0.54 km 2 to 6.09 km 2 , were selectedand isolated for study'. Each lake was indi­vidually measured using a pixel count and amap of the several lakes printed. Figure 8shows the print-out of the selected lakes asidentified on the Image 100. The question tobe answered deals with the accuracy withwhich this method, using a simplethresholding technique applied to uncali­brated L-band SAR data, can be used to mea­sure the area of each of the several lakes. Itwas determined, given the resolution of theradar, the aperture size used for scanning,and the processing system, that each pixel onthe Image 100 represented an area of900 m2 •

Hence, we were able to determine directlythe areal extent of each lake. As a check, the1:250,000 map of the study area (Teshekpuk,Alaska) was used to obtain surface areas ofthe lakes. Figure 9 gives these relationships.

APPLICATION OF PROCESSING OF LAKE SCENES

The technique of using the Image 100 and

• Lakes of smaller sizes were easily measuredfrom the SAR data using the Image 100, but theaccuracies of the planimeter measurements forsuch small areas, and at the scale of 1:250,000,were in doubt. Therefore, these were not includedin this study.

the thresholding programs to analyze un­calibrated SAR L-band data has provided uswith an accurate and quick measurement ofthe surface areas of the lakes of the northernAlaskan tundra. The differences betweenthe areas detected by the computertechnique and that using the manual(planimeter) technique can be partially at­tributed to the scale of the map used and thefact that the 1:250,000 map was 15 yearsolder than the SAR data. Ideally, aerialphotography would have been the bestsource of comparative data, but these werenot available for this study. Also, Landsat(especially Bands 6 and 7) would provide ac­curate comparative data.

If we consider these lakes as floodedareas, it is suggested that uncalibratedL-band SAR data similar to that used in thisstudy and which will be available from satel­lites (such as Seasat) can be used to identifysuch areas in many land scenes. Because ofthe all-weather capabilities of radar, studiesof floods can be conducted, in an automaticprocessing mode, while the floods are inprogress. Some difficulties can arise (e.g.,diflerentiating shadows and similar dark orno-return areas from floods in rough terrain,and possibly separating nat terrain from ad­jacent flooded areas) and it is in such situa­tions that both sequential data and the pre­vious knowledge of the interpreter of thegeneral scene will be of major importance infacilitating accurate interpretation. Earlierwork in the comparison of inhared photog­raphy, bands 6 and 7 of Landsat data, andsynthetic aperture radar has shown the rela­tionships of these data sets with respect toflooded terrain. By combining these addi­tional sets, accuracy of interpretation, eitherautomatic or manual, can be improved(Bryan, 1975b).

CONCLUSIONS

Because the strength of radar backscatterfor a variety of scenes is quite varied, it isdesirable that calibrated SAR data be madeavailable for earth resources purposes.Nonetheless, certain types of features, thosewhich have very constant returns which are

1292 PHOTOGRAMMETRIC ENGINEERING & REMOTE SENSING, 1977

TOPOMAP

L-BANDSAR

ORIGINALGEOMETRICALLY L ES3 d M'L'S

CORRECTED h H d mOMmRS

(a) (b) (c)FIG. 7. Data used in the study of north slope lakes: (a) raw SAR L(HH)imagery, (b) geometrically corrected SAR L(HH) data, and (c) portion of1:250,000 topographic map used for comparison.

also very high or very low in intensity,S canbe efficiently studied by using simple au­tomatic picture processing techniquesapplied to uncalibrated radar data. Thus, inareas which are generally inaccessible or inwhich monitoring of the changes of sometypes of earth's surfaces (such as polar seaice, arctic tundra, or areas of Hooding) arerequired, such uncalibrated SAR data canprovide emth scientists with valuable infor­mation for modeling and mapping functions.Obviously, combinations of multiti'equency,multipolarization, sequential, and calibratedSAR data will allow the extension of thesetechniques. Similarly, the inclusion of addi­tional wavelengths beyond the microwave oradditional modes of microwave remote sens­ing (i.e., passive) together with additionaland more sophisticated digital processingtechniques may be employed and will ob­tain accurate results.

5 Examples of high backscatter scenes for whichthis technique may be employed are the commer­cial and industrial (including strip commercial)areas within urban scenes. The high point returnsand their close proximity to one another in spaceand time renders these areas easily identifiable(BIyan, 1974, 1975a).

, ..,. uAlI ~IJ-

(a)

, J;a.

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FIG. 8. Identification, using Image 100, of 'theseveral lakes selected for study. (a) Northern por­tion of study site seen in Figure 7c, (b) Southernportion of study site seen in Figure 7c.

COMPUTER PROCESSING OF SAR L-BAND IMAGERY 12937000

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FIG. 9. Comparison of areas oflakes within studysite as detennined by planimetric measurementson 1:250,000 maps and using the Image 100. Leastsquares relationship is shown.

ACKNOWLEDGMENTS

The authors wish to thank R. O. Ramseier,Canadian Department of Environment; D.K. Hall of Goddard Space Flight Center; andD. Harrison, S. Scott, E. McMillian, D.Baker, and K. Borger (all of JPL) for theircontributions and helpful comments duringthe conduct of this work. They also wouldlike to thank the Ames Airborne ScienceProgram Office for the SUppOlt in the datacollection. The work has been funded by theEODAP othce as part of the AIDJEX sup­port.

This paper presents the results of onephase of research carried out at JPL, Califor­nia Institute of Technology, under contractNAS7-100, sponsored by the NationalAeronautics and Space Administration.

REFERENCES

Bryan, M. L., 1974. Exb'action of Urban LandCover Data from Multiplexed Synthetic Aper­ture Radar. Proceedings, 9th IntI. Symp. Re­mote Sensing of Environment, Ann Arbor,MI., Env. Res. Inst. MI., pp. 271-288.

----, 1975a. Interpretation of an UrbanScene Using Multichannel Radar Imagery.Remote Sensing of Environment, V. 4, No.1,pp.49-66.

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