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Spring wheat-leaf phytomass and yield estimatesfrom airborne scanner and hand-held radiometermeasurements†J. K. AASE a , F. H. SIDDOWAY a & J. P. MILLARD ba USDA-ARS , P.O. Box 1109, Sidney, Montana, 59270, U.S.Ab NASA, Ames Research Center , Moffett Field, California, 94035, U.S.APublished online: 27 Apr 2007.

To cite this article: J. K. AASE , F. H. SIDDOWAY & J. P. MILLARD (1984) Spring wheat-leaf phytomass and yield estimates fromairborne scanner and hand-held radiometer measurements†, International Journal of Remote Sensing, 5:5, 771-781

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INT. J. REMOTE SENSING, 1984, VOL. 5, No.5, 771-781

Spring wheat-leaf phytomass and yield estimates from airbornescanner and hand-held radiometer measurements]

J. K. AASE, F. H. SIDDOWAY

USDA-ARS, P.O. Box 1109, Sidney, Montana 59270, U.S.A.

and J. P. MILLARD

NASA, Ames Research Center, Moffett Field, California 94035, U.S.A.

(Received 9 August 1983: in final form 10 November 1983)

Abstract. Our objective was to relate radiance measurements from a hand-heldradiometer (Exotech 100-A) and an airborne multispectral scanner (DaedalusDEI 1260) to different wheat (Triticum aestiuum L.) stand densities (simulatedwinter wheat winterkill) and to grain yield. The field experiment was locatedII km north-west of Sidney, Montana (47°45'N, 104°16'W) on a Williams loamsoil (fine-loamy, mixed Typic Argiborolls). Three rates-67, 27 and 13kg/ha-of'Len', a semidwarf, hard red spring-wheat cultivar, were seeded to representstands of 100, 40 and 20 per cent. Radiances were measured with a hand-heldradiometer on clear mornings throughout the growing season. Aircraft overflightmeasurements were made at three growth stages: tillering, stem extension andheading period.

The near-l R/red ratio was used in the. analysis. Both aircraft and groundmeasurements made it possible to differentiate and evaluate wheat stand densitiesat an early enough growth stage to make management decisions. The aircraftmeasurements also corroborated hand-held radiometer measurements whenrelated to yield prediction. Although there was some growth dependency, thencar-l R/red ratio correlated with yield when measured from just past tilleringuntil about the watery-ripe stage. The results reinforce the potential of remotesensing for estimating grain yields and evaluating winterkill.

1. IntroductionConsiderable research has been conducted to relate remotely sensed agricultural

spectral data to crop condition and potential yield. Wheat (Triticum aestivum L.) hasbeen the chief benefactor of remote-sensing research on pre-harvest crop-conditioninformation and yield prediction. Tucker et al. (1980) reviewed some of the variousmethods and approaches used for wheat. In addition to wheat, relationships betweenspectrally measured data and agronomic variables have been reported for othercrops as well. Green-leaf-area index and green-leaf phytomass are agronomicvariables best correlated with spectral data (Kimes et al. 1981, Markham et al. 1981,Tucker et al. 1979, Holben et al. 1980).

Various combinations, referred to as vegetation indices (VIs), of radiance orreflectance measured in the four wavebands corresponding to the LANDSATmultispectral scanner (MSS) bands have been used when studying crop development

t Contribution from the USDA, Agricultural Research Service, and NASA/AmesResearch Center, in co-operation with the Montana Agricultural Experiment Station, JournalSeries No. 1309.

© Copyright u.s. Government 19&4

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and yield. The most commonly used spectral measurements have involved red andnear-infrared (lR) radiances which correspond to LANDSAT bands 5 and 7 (0·6-0·7and 0·8-1,1 )lm, respectively). Tucker (1979) concluded that the TRjred ratio andlinear combinations of the IR and red radiances estimated the photosyntheticallyactive phytomass to about the same degree of precision. Lautenschlager and Perry(1981) concluded that many of the VIs found in the literature are statistically similar.

Aase and Siddoway (1980, 1981 a, b), using a hand-held radiometer, found thatthe IRjred ratio and the normalized difference VI [ND =(lR - red)j(IR + red)] ofRouse et al. (1973) and Deering et al. (1975) could be used to estimate wheat standdensities, total dry-matter production and grain yield. Jackson et al. (1983)concluded that no one VI will give all the information desired.

The objective of this study was to relate radiance measurements from a hand-heldradiometer and an airborne MSS to wheat stand densities (or leaf phytomass) andgrain yields from large fields of wheat with three seeding densities.

2. Methods and materialsThe field experiment was located on a Williams loam soil (fine-loamy, mixed

typic Argiborolls) II km north-west of Sidney, Montana (47°45'N, 104°16'W). The32 ha field with dimensions of 800 m north-south and 400 m east-west was summerfallowed in 1980. The field was divided into three equal-area plots, with 6 meast-west summer-fallowed alleys separating each plot. Because the field was notavailable early enough to seed winter wheat (Triticum aestivum L.) as originally'intended, 'Len', a semidwarf, hard red spring-wheat cultivar was seeded. The wheatwas seeded with a double disk opener drill in an east-west direction in 30·5 em rows.The north plot was seeded at a rate of 67 kgjha (100 per cent) on 15 April 1981; themiddle third was seeded on 16 April at 27 kgjha (40 per cent); and the south plot wasseeded on 17 April at 13 kgjha (20 per cent). Diammonium phosphate (18-46-0) wasbroadcast with the drill at rates of 121, 67 and 13kgjlia for the north, middle andsouth plots, respectively.

The resultant stand densities, as measured on 15 May from six 1·0 m2 samplesfrom each plot, were 104,41 and 17plants/rn? on what, for convenience of reference,will be designated the 100,40 and 20 per cent plots, respectively.

Weekly throughout the growing season, six 1·0m2 plant samples were clipped atground level from each plot. Green leaves, senescent leaves, stems and heads wereseparated, oven dried at- 57°C and weighed to determine dry matter. Growth stagewas determined according to the Feekes scale (Large 1954).

An Exotecht Model IOO-A radiometer with a 15° field of view (FOV) was used tomeasure radiances corresponding to the LANDSAT MSS bands 4, 5, 6 and 7,representing O' 5-0·6, 0'6-0·7, O' 7-0'8 and 0,8-1·1 )lm wavelengths, respectively. Allchannel outputs were read simultaneously and recorded on a portable, battery­operated digital printer, and later manually read and transferred for analysis.Because scattered cumulus clouds commonly begin to move in from the west afterabout 10.00 hours M.S.T. (Mountain standard time), the sampling time was set for08.30hours M.S.T. Measurements were generally completed within 20min. Themeasurements were taken on clear days and on days when apparent haze or distancthorizon cumulus clouds were judged not to interfere with the solar beam. Readingswere obtained on 19 days during the growing season.

t Trade and company names are included for the benefit of the reader and do not implyany endorsementor preferential treatment by the USDA of the product listed.

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Leafphytomass and yield estimates of wheat 773

Measurements were made by walking the field once in each direction, each timeobtaining two dark-level readings (background reading allowing no light to enterlenses), four readings from a pressed barium sulphate standard (not used in thisanalysis) placed on pre-levelled wooden stakes, six readings from each of the plots,and three from bare soil in the alleys in the following sequence: dark level, standard,20 per cent plot, standard, bare soil, 40 per cent plot, bare soil, standard, 100 percent plot, 100 per cent plot, standard, bare soil, 40 per cent plot, bare soil, standard,20 per cent plot, standard and dark level.

The original intent, although not realized, was to also obtain LANDSAT data inconjunction with the other measurements. To coincide with a pure LANDSAT pixel(no border effects) of each plot, the middle of each plot was selected for hand-heldradiometer measurements. To facilitate the radiance measurements, walkways wereprovided by placing planks perpendicularly to the rows and supported 20cm aboveground by cement blocks. A worker standing on the planks took radiance readingsfrom the east side of the planks. The radiance readings subtended an area about50ern in diameter.

An Aerocommander 500B twin-engine aeroplane equipped with two down ports,one for a Daedalus DEI 1260 MSS and one for an RC-IO, 23cm format camera,made three overflights during the season on 28 May, 10 June and 25 June and weretimed to coincide with the hand-held radiometer measurements. The flights tookplace near the following growth stages as given by the Feekes scale (Large 1954): 4(leaf sheaths lengthen), 6 (first node of stem visible), 10 (ear swollen but not yetvisible) (figure I).

..:r

"

RIPENING

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STAGE5

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3 teet-. sbectbs~~:~:d Itngthtn

STAGE STAGEI 2

ant: tdlnlngshoot btgH'l'5

I------TILLERING· .. -----+jUl..;:

Figure I. Illustration of the Feekes wheat growth stage (after Large 1954) withcorresponding aircraft overflights indicated.

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774 J. K. Aase et al.

~ 50:

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The flights were at 610 m above ground level and were repeated twice, first in awest-east direction, then in a south-north direction. The instantaneous field of view(I FOY) of the aircraft scanner was 2·5 mrad, corresponding to about 1·5 m groundresolution. Each plot was approximately 400 m x 263 m, resulting in nearly 50000pixels per plot. Channels 6 and 10 (0,60-0'65 and 0·92-1,10 J.lm, respectively), of theDEI 1260 scanner were used for data analysis. The DEI 1260 scanner and theExoteeh 100-A radiometer were calibrated relative to the same radiance transferstandard consisting of a plate coated with Kodak White Reflectance Standard and aquartz iodine calibration lamp traceable to National Bureau of Standards.

As a guide to evaluating the results, the Honestly Significant Difference (HSD),one of the most conservative of all mean separation procedures, was used (Steel andTorrie 1960). Since we did not replicate the large fields used for the experiment, theuse ':of the HSD was based on the assumption that within-plot variation was themajor source of experimental variation rather than among replicated plots.

3. Results and discussionFigure 2 illustrates the seasonal progression of the IR/red ratio as calculated

from the hand-held radiometer data. Although the data are from spring-seededwheat, inferences regarding winter-wheat winterkill and reseeding decisions can bemade since winter-wheat development is 3-4 weeks ahead of spring-wheatdevelopment in the early season. The data verify earlier findings and conelusions ofAase and Siddoway (1980, 1981 a) that wheat stand densities, and thus winterkill of

AIRCRAFT DATA~ S-N PASS

6 W-E PASS

STEM EXT. FLOWER

61__~1' 'I.-~-I-_

T1LLERING HEADING RIPENING

0

!:~ II I~ d ,I I I, ,I ! I I10 20 30 10 20 30 10 20

MAY JUNE JUL Y

Figure 2. IR/rcd radiance ratio versus time for bare soil (0) and three spring-wheat seedingrates-20,40, 100 per cent (100 per eent=67kg/ha}--as measured by a hand-heldradiometer. The individual symbols represent values obtained from airborne MSS inwest-cast and south-north flight directions. The symbol pairs in ascending orderrepresent 0, 20, 40 and 100per cent seeding rates.

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Leafphytomass and yield estimates of wheat 775

winter wheat, can be detected early enough in the spring to make reseeding decisionsprior to a nominal cut-off data of 15 May. The statistical analyses in table 1 showthat 100 and 40 per cent plots could be separated from each other and from the 20and 0 per cent plots at the first sampling date, the 20 per cent plot separated out fromthe 0 per cent plot during the first days in June. The difference among the plotspersisted well into flowering after which time any difference vanished.

The data points from the aircraft-mounted sensor (superimposed on figure 2) areaverages of the whole field with inherent greater variation than data points from thehand-held radiometer. Although they are not identical to those obtained with thehand-held radiometer, they are grouped in the same order and show the same

Table I. Growth stage for each sampling date, means of IR/red ratio and HSD for hand-held radiometer measurements. Plots represent 0, 20, 40 and 100 per cent seeding rate(100 per cent =67 kg/hal.

IR/red

Date Plot HSD1981 Growth stage 0 20 40 100 (P=0'05)

\9 May Tillers formed 0·95 0·96 1·07 1·15 0·0521 May Beginning erection

of pseudostem 0·89 0·91 1·01 1'!7 0·0828 May Pseudostem strongly

erected 0·95 ],09 1·49 1·74 0·1630 May Pseudostem strongly

erected 0·95 1·01 ],32 1·69 0·125 June First node of stem

visible 0·99 1·07 ),52 236 0·2410 June First node of stem

visible 1·00 1·34 [·62 2·93 0·2616 June Second node of stem

formed to last leafvisible 0·95 J·52 2·22 4·03 0·43

24 June First ears visible tohalf of heading complete 0·89 1·67 2·37 3'65 0·62

25 June Quarter of heading tothree-quarters complete 0·96 \·76 2-47 3·23 0-46

29 June Three-quarters headingto beginning flowering 0·94 2·30 3·14 4·41 0·72

30 June Three-quarters headingto beginning offlowering 0·92 2·17 2-86 4·66 0·81

2 July Three-quarters headingto beginning offlowering 0·89 1·74 2-64 HI 0·71

6 July All ears out to floweringcomplete 0·89 2·28 3·19 3·63 0·68

9 July Beginning flower to milkyripe 0·92 2·27 2'95 3097 0·65

14 July Watery ripe to milky ripe 0·90 2·54 2-62 2-80 0·6015 July Milky ripe to medium ripe 0·94 2·64 2·74 2-42 0·5116 July Milky ripe to medium ripe 0·91 2·12 2·16 2·07 0·5421 July Milky ripe to kernel hard 0·90 1·72 1·73 1·58 0·3823 July Milky ripe to kernel hard 0·93 ],78 1·61 1·38 0·31

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776 J. K. Aase et al.

relationship to wheat stand densities as do the data points from the hand-heldradiometer measurements. However, when looking at the statistics in table 2 andcomparing with the visual image of figure 2, there are obvious differences among thefields that cannot be discerned by the statistical process.

Table 2. Growth stage for eaeh sampling date, means of IR/red ratio and HSD for airborneMSS measurements. Plots represent 0, 20, 40, and 100 per cent seeding rate (100 percent = 67kg/ha)

Flight IR/red. Date direc- Growth Plot HSD

1981 tion stage 0 20 40 luu (P=0'05)

28 May S-N Pseudostem strongly 0·79 0·84 0·94 1·34 0·54W-E erected 0·82 0·83 0·92 1·29 0·48

10June S-N First node of stem 0·82 1·02 ],48 2·36 0·92W-E visible 0·84 1·09 1·44 2021 0·95

25 June S-N Quarter of heading to \·03 2·37 3·50 4-61 2-43W-E three-quarters complete 1·18 2·56 3·02 4·33 1·98

The dips in the curves in figure 2 apparently illustrate wheat suffering from waterstress. Stress seems particularly obvious for the 100 per cent plot between 16 Juneand 28 June. The thinner-seeded plots apparently did not require as much water asdid the 100 per cent plot. However, the sharp rise in the curves following the rain on28 June indicate that all plots had been under some water stress. The increase in the20 and 40 per cent curves prior to 6 July remain unexplained.

A combination of aircraft digital data, as illustrated in figure 2, along with colourimages of the scanner data shown in figure 3 complement each other and facilitateinterpretation. The 100 and 40 per cent plots are readily discernible from a fallowfield to the west on the first flight date. On the last two flight dates, all three plots areindividually discernible and different from the fallow field. Some detail in standvariation and weed infestation is also visible.

In figure 4, we illustrate the relationship of green-leaf phytomass (throughflowering growth stage) versus hand-held radiometer and airborne scannermeasurements of IR/red ratio. These types of relationships are potentially importantfor plant-growth models requiring either leaf area or leaf-phytomass as inputs. Thedata points calculated from the airborne scanner measurements do not necessarilymatch those from hand-held radiometer measurements; however, the relationshipsare similar and the hand-held radiometer measurements support those of theairborne scanner. Because of the sampling procedure employed, there wasnecessarily some variation in phytomass samples as evidenced in figure 4; butbecause the aeroplane scanner covered the entire field, the relationship between thescanner measurements and leaf phytomass was better than between the hand-heldradiometer measurements and leaf phytomass. Total phytomass, leaf phytomass and

Figure J. Colour image or experimental area on three dates showing detail and contrast ofthe three fields with a fallow field on the west. The data were obtained from an aircraftoverflight in a west-east direction at 610m above ground level. The coloursrepresenting values of the IR/red ratio are shown on the right.

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Leafphytomass and yield estimates ofwheat 777

5-28·81 958 MOST

PLOT 2.0

1.8

1.6

100 1.4

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.420 .2

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778 J. K. Aase et al.

leaf area have all been related to spectral radiometric measurements. However,green-leaf-area index and green-leaf phytomass have been found to be the agronomicvariables best correlated with spectral data (Aase and Siddoway 1981 a, Kimes et al.1981, Holben et al. 1980, Wiegand et al. 1979).

Another potential use for seasonal spectral radiometric measurements is forgrain-yield prediction. There is a good linear relationship between grain yield andvegetation indices measured between approximately the end of tillering growth stagethrough the watery-ripe growth stage (Aase and Siddoway 1981 a, Tucker et at. 1980,Colwell et al. 1977). The relationship is growth-stage dependent, and, as Tucker et al.(1980) discussed, some type of normalizing factor must be found so that onerelationship can be developed for use throughout the useful yield-predictive period.

On figure 5, we have plotted data obtained with the hand-held radiometer overthree seasons. The data encompass two spring-wheat cultivars, 'Olaf' in 1979 (Aaseand Siddoway 1981 a), 'Len' in 1981 (this paper) and one winter-wheat cultivar,'Roughrider' in 1980 (Aase, unpublished data). It was not possible to find data at thesame growth stage for all years; therefore, the nearest to the same was used: in 1979at flowering complete, and in 1980 and 1981 at quarter of heading complete. Thedata seem to be cultivar independent and reasonably uniform during the headinggrowth period.

HANDHELDRADIOMETER

oo<I

AIRCRAFT SEEDING RATE.SCANNER percent

\l 100

o 40

C> 20

5

" AIRCRAFT SCANNERY = -0.03 + 0.22 XA2 '"0.89

2 3IAIRED RATIO

1.0

.9

.8

.7

" 0:r;:: .6 '"l:l.

" 0

"0 .5 D.....>:r~

~.4

w-'

.3

.2

.1

0

Figure 4. Green-leaf phytomass versus IR/red ratio for hand-held radiorreter and airborneMSS measurements as determined for three seeding rates of wheat.

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Leafphytomass and yield estimates of wheat 779

The data from 1980 were obtained from a winter-wheat experiment designed thesame as the spring-wheat experiment from which the 1979 data were taken (Aase andSiddoway 1981 a). The difference was that a severe drought occurred in 1980 andyields were about half of those expected under more nearly 'normal' conditions. Thedata from the 3 years were combined and one line drawn as shown in figure 5. Thisline was drawn on figure 6 and there compared with 1981 data obtained from theairborne scanner when flown in the west-east direction. The 1981 data obtained withthe hand-held radiometer is also repeated on figure 6. As expected, the IRjred ratiodata from the airborne scanner showed nearly the same relationship as the IRjredratio data from the hand-held radiometer. Wiegand et al. (1983) have found a similarstraight-line relationship between the perpendicular VI (Richardson and Wiegand1977) derived from LANDSAT bands 5 and 7 and sorghum iSorqhum bicolor L.,Moench) grain yields. Their findings are remarkable inasmuch as the dataencompassed 4 years and a wide diversity in growing conditions, soils, culturalpractices and plant genetics.

4. ConclusionWe demonstrated that wheat stand density differences (simulated winterkill) can

be detected at an early growth stage by airborne MSS. The airborne-scannermeasurements were supported by data collected with a hand-held radiometer.Airborne-scanner measurements as well as hand-held radiometer measurements were

o 1979 -- STAGE 10.5.2Y = 0.30 ... 0.63 XR2 = O.Bl

6 19BO - - - - STAGE 10.2Y = 0.34 + 0.74 XR2 = 0.89

o 1981 -. - STAGE 10.2Y '" 0.78 + 0.54 XR2 '" 0.99

3

1979 - __

19BO1981

AVERAGE OFHANDHELD RADIOMETERy '" 0.54 +-a.5axR2 = 0.84

'"~ 2

0'-'w>2",«:to

o 2 3IRIRED RATIO

4 5

Figure 5. Grain yield versus IR/red ratio at given growth stages as obtained by a hand-heldradiometer during three growing seasons, plus an average of the three.

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780 J. K. Aase et al.

o 1981 AIRCRAFT SCAN~IER

STAGE 102Y"D.77+0.41XR2.O.89

6 1981 ---- HANDHELD RADIOMETERSTAGE 10.2Y '"0.78 • 0.54 XR2. 0.99

1979 AVERAGE OF1980 HANDHELD RADIOMETER1981 Y '" 0.54 + 0.58 X

R2 • 0.84

3

~ 2;::ci...w>­z<1~ 1

o 2 3IRIRED RATIO

4 5

Figure 6. Grain yield versus IRrred ratio for readings from hand-held radiometer andairborne MSS. The curve representing the average in figure 5 is included here forcomparison purposes.

linearly related to grain yield and both demonstrated similar sensitivity for grain-, yield estimation. Care must be exercised when interpreting relationships among

combinations of reflectance or radiance measurements and yield because suchthings as disease, weeds, water stress and hail could reduce yield and not beaccounted for. A combination of the above and independent estimates of disease andweed infestations, along with meteorological observations, could be used to predictyields more precisely or to make timely crop management decisions.

AcknowledgmentsWe thank Messrs. Jerome V. Braaten and Theodore M. Bernard for help with the

field work, and Messrs. Kirk Cumming and Bari S. Brown for help with datareduction.

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spectral reflectance measurements. Aqron. J., 72, 149.AASE, J. K., and SIDDOWAY, F. H.. 1981 a, Spring wheat yield estimates from spectral

reflectance measurements. 1.£.£.£. Trans. Geosci. remote Sensinq, 19,78.AASE, J. K., and SIDDOWAY, F. H., 1981 h, Assessing winter wheat dry matter production via

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"

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JACKSON. R, D.. SLATER. P, N.. and PINTER. P, J.. 1983. Discrimination of growth and waterstress in wheat by various vegetation indices through clear and turbid atmospheres, RemoteSensing Environ" 13, 187,

KIMES, D, S" MARKHAM, B. 1.., TUCKER C J" and McMURTREY. J, E.. III, 1981. Temporalrelationships between spectral response and agronomic variables of a corn canopy,Remote Sensing Environ" 11,401.

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