Remote estimation of leaf transpiration rate and stomatal resistance based on infrared thermometry

Agricultural and Forest Meteorology, 51 (1990) 21-33

21

Elsevier Science Publishers B.V., Amsterdam - - Printed in The Netherlands

R E M O T E E S T I M A T I O N OF L E A F T R A N S P I R A T I O N R A T E A N D STOMATAL RESISTANCE BASED ON INFRARED THERMOMETRY

YOSHIO INOUE*, BRUCE A. KIMBALL, RAY D. JACKSON, PAUL J. PINTER JR., and ROBERT J. REGINATO

U.S. Department o[ Agriculture, Agricultural Research Service, U.S. Water Conservation Laboratory, 4331 East Broadway Road, Phoenix, AZ 85040 (U.S.A.) (Received June 21, 1989; revision accepted November 24, 1989)

ABSTRACT Inoue, Y., Kimball, B.A., Jackson, R.D., Pinter Jr., P.J. and Reginato, R.J., 1990. Remote estimation of leaf transpiration rate and stomatal resistance based on infrared thermometry. Agric. For. Meteorol., 51: 21-33. A remote method was developed for monitoring leaf transpiration rate and stomatal resistance on a realtime base. The method utilizes leaf temperatures measured with an infrared radiometer as integral inputs for a model to compute those parameters. The model is based on the energy balance of a plant leaf, accounting for moisture transfer processes in the stomata and boundary layer. Remotely determined transpiration rates and stomatal resistances were compared with those measured with a steady state porometer. The corresponding values obtained from the two methods were linearly related (r=0.79"* and 0.93** for transpiration and stomatal resistance, respectively); but the porometer transpiration rates were somewhat higher than those obtained by the "remote" method, probably because the air in the porometer cuvette was drier than the ambient air. On the other hand, the stomatal-resistance values from the two methods fell on the 1 : 1 line with a high correlation coefficient, suggesting that the "remote" method produces excellent estimates of actual stomatal resistance.

INTRODUCTION

Future improvement of irrigation scheduling practices may require monitoring of appropriate crop parameters indicating the physiological activity or response of the crop to the environmental stresses. However, measurements such as leaf water potential or stomatal resistance on a large number of individual leaves are not only labor intensive but also subject to substantial errors (Meyer et al., 1985). Thus, non-destructive and instantaneous methods are desirable for assessing the physiological status of an entire crop in the field. *Permanent address: National Agricultural Research Centre, Tsukuba 305, Japan.

0168-1923/90/$03.50

© 1990 Elsevier Science Publishers B.V.

92

'~ I N O / J E E T A t .

In arid or semi-arid regions, a linear relationship can be obtained between canopy-air temperature differential and air vapor pressure deficit (Ehrler, 1973: Idso et al., 1981 ) or extractable water remaining in the soil (Jackson, 1982 } On the basis of this fact, Jackson et al. (1981) and Idso et al. {1981,) have successfully developed a practical index (Crop Water Stress Index) for esti~ mating crop water stress. Jackson et al. ( 1981 ) also reviewed pertinent energ3 balance considerations and presented a theoretical basis for the CWSI. A number of experiments have shown that evapotranspiration or transpiration is closely correlated with crop yield (StanhiU, 1986; Hanks, 1983). The relationship, also, has been incorporated into many simulation models ( T a n ner and Sinclair, 1983 ). Moreover, recent work has shown that stomatal resistance is more closely correlated to soil water status than to leaf water potential or leaf turgor (Schulze et al., 1987), which suggests that stomatal resistance could be a direct indicator of soil-induced water stress. Therefore, the actual estimates of transpiration rate and stomatal resistance or the ratios of' them to the potential values will be useful bases of physiological diagnosis or yield predictions. Inoue (1986) and Inoue et al. (1989) showed that a thermal image of a crop canopy could provide the spatial differences in canopy surface temperatures which significantly reflected the differences in physiological activity of indi vidual leaves. They obtained surface temperature data from 122 800 points i1~ a crop canopy at the same time, remotely and instantaneously. The differences in photosynthetic and transpiration rates and stomatal resistances of plants could easily be detected by means of infrared image analysis, since the micro meteorological conditions were exactly the same. This experimental fact im~ plies that a great number of leaves could be monitored simultaneously if in frared leaf temperatures were interrelated quantitatively with transpiratio~ rates and stomatal resistances. The objective of this paper is thus to examine a remote monitoring method for evaluating transpiration rates and stomatal resistances of crops under field conditions. The method is based on the energy balance model of a single leaf and utilizes infrared leaf temperature as one of the important inputs to th~:~ model. MATERIALSAND METHODS The model

A model was developed to calculate transpiration (Et) and stomatal resistance (rsv) using equations for the energy balance of a plant leaf which account for moisture-exchange processes in the stomata and the boundary layer. Jackson et al. (1981) elucidated the energy balance considerations for a whole canopy which play a role in calculating CWSI from measured dry-bulb, wet-bulb.

REMOTE SENSING OF STOMATAL RESISTANCE

23

and infrared canopy temperatures with some assumptions concerning solar radiation and aerodynamic and canopy resistances. Jackson et al. (1987) and Inoue (1987) further demonstrated that remote-sensing techniques based on the same theory were applicable for estimating the evapotranspiration from agricultural fields and from a corn canopy, respectively. On a similar theoretical basis, the present model estimates leaf transpiration and stomatal resistance, accounting for changes in solar radiation, windspeed, and therefore, the boundary-layer resistance explicitly. In the case of an individual leaf, we can use stomatal resistances measured with a steady state porometer for model validation. Et can be described as a part of the energy balance of a leaf as follows (Monteith, 1973 and Jackson et al., 1981)

Et-~ (Rn-H)/2~

(1)

where: E t is the mean one-sided value of leaf transpiration rate; ~ is the latent heat of vaporization; Rn is net radiation, and division by 2 is required to obtain a one-sided E t value. H is the rate of sensible heat transfer from both sides of the leaf to the ambient air; and it is expressed, based on the heat-exchange process in the boundary layer, as

H=2pCp(6 - ta)/rah

(2)

where: p is the density of air; Cp is the heat capacity of air; t~is leaf temperature; t a is air temperature; rah is the boundary-layer resistance of the leaf to sensible heat transfer; and the 2 ensures that H represents the sensible heat transfer from both sides of the leaf. Since rah is relatively small and varies little when the windspeed is greater than around 0.5 m s-1 (Horie, 1979), we simply assumed rah varies as in the next equation for an ideal flat plate r~h =300 (L/u) °~

(3)

where L is the mean width of a leaf, and u is windspeed. Net radiation can be expressed as

Rn =aR~ --Rl

(4)

where R~ is the impinging shortwave radiation, a is leaf absorptance for solar radiation, and R~ is the longwave radiation budget of the leaf. An absorptance of approximately 0.50 is a good estimate for a (Gates, 1980). R~ is calculated using the following equations, assuming that the uppermost leaves are receiving longwave radiation from the sky (Brutsaert, 1975) and from lower leaves with the same temperature as ambient air:

R~=a{2e~(t~+ 2 7 3 ) 4 - e~(t~ + 273 P - ee(ta +273) 4}

(5)

where a is the Stefan-Boltzmann constant, el and ee are the emissivities of

24

Y INOUEET AL

leaves and atmosphere, respectively. Hence, substituting eqns. (2) and (3~ into (1), we obtain the following equation Et = {Rn - 6.67 X 10- ~pCp ( u / L )o.~( t~ - ta ) }/22

{6

Another expression for leaf transpiration rate is

Et = t ~ ( e * - e a ) /

(rsv +rav )

(7~

where: e* is the saturated vapor pressure at the leaf temperature; e~ is the actual vapor pressure of the ambient air; rsv is the stomatal resistance for water vapor transport; r~v is the boundary-layer resistance for water vapor transport; k~ is the factor needed to convert from vapor pressure to vapor concentration, which is defined as k~ = M ~ / R ( t a + 2 7 3 )

~I

where M~ is the molecular weight of water, and R is the gas constant. Since diffusion processes for heat and water vapor are similar, ray can consequently be expressed as r~v = (to~D,,)2/3rah

=

0.921r~h

(9 i

where ~ and D~ are diffusion coefficients for heat and water vapor, respectively (Thorn, 1968). Et can be computed using eqn. (6) from remotely sensed data. Then, using E~ from eqn. (6) and r~v from eqn. (9), the stomatal resistance, r~v, can be obtained from a rearrangement of eqn. (7) as the following equation: r~v - k v ( e ~ - e a ) / E t - r,,v

(10)

22kv (e* - e a ) - a R ~ - R , - 2pCp( t~ - t ~ ) /r.h - r . . Experimental

The experiment was conducted in the s u m m e r of 1987 at Phoenix, Arizona. Cotton (Gossypium hirsutum L. ) was planted during mid-April in a 22 m × 40 m experimental field. The soil type of the field was Avondale loam. T r e a t m e n t s in 16 randomly allocated plots included two levels of irrigation, as well as two levels of fertilizer nitrogen. Stomatal resistance and transpiration rate were measured with a steady state transpiration porometer (Li-Cor, LI-1600) 1 on five leaves near the top of the canopy, which oriented approximately on horL zontal planes. Before and after the porometer measurements, 10 temperature measurements of each leaf were obtained with a handheld infrared thermom1Trade names and company names are included for the benefit of the reader. No e n d o r ~ m e n t is implied.

REMOTE SENSING OF STOMATALRESISTANCE

25

eter (Everest Interscience, Model-110)~, which has a 4 ° field of view, a stated accuracy of _+0.5°C, and a resolution of +0.1°C. Air dry and wet bulb temperatures (by aspirated psychrometers), solar radiation (by Eppley solarimeters), and windspeed (by Young cup anemometers) were automatically recorded every 30 s at a position about 0.5 m above the plant canopy, in the central part of the field. The infrared leaf temperatures and micro-meteorological data were averaged for each cycle of measurement and used for model calculations. The ranges of meteorological conditions are shown in Fig. la and b, which shows those averaged raw data as well as the time of each measurement. Measurements were made on 12 days from July to September for which a wide range of plant conditions were provided by the irrigation and nitrogen treatments. However, those treatments were not distinguished, because any treatments and time of measurements were also regarded as among varying environments resulting in a wide range of plant status which should be monitored. The effect of each treatment on plant parameters is to be reported elsewhere with statistical methods based on systematically replicated measurements. lOOO

~2~ 800 .~ 6QO ~

oo

4

o

@o °

oo

o

o

x

400

~ 2QO ©

~ :~ t 1 ~×

i;

8

;2

;4

16

18 i0

44 3 ~

40

d $

~6

~

32

(b)

~oo

o

~Z~

o

8 6~

o

x

x

~

4>

x~ x~k

x

2 0

28

8

,

,

L

.

i0

12

14

16

Time

of day

O

18

(hr)

Fig. 1. Measured micro-meteorological conditions and time of measurements; (a) solar radiation and windspeed, (b) air temperature and vapor pressure deficit. All raw data from different days were developed in the axis of time of day.

26

Y [NOUEET A[.

RESULTS AND DISCUSSION

In the first place, the behavior of the model was examined. The responses oi the final outputs, transpiration and stomatal resistance, to the leaf temperature were calculated under various simulated conditions of solar radiation, air temperature, humidity and windspeed. Figures 2 and 3 show representative responses to the leaf temperature under different solar radiation intensities and air humidities. The selected ranges of leaf temperature along the x-axis were substantially reasonable since the observed ambient air temperatures varied from 30.1 to 42.0 ° C (as shown in Fig. lb ) while the leaf-air temperature differentials varied from - 10.5 to 1.8 ° C. The effects of solar radiation on them were relatively great compared with those of air humidity and other factors. In fact, windspeed had little influence on outputs when it was greater than 1.0 m s - l. Changes in air temperature also just shifted the simulated line with little change in shape toward the x-axis, based on the relative difference from the

m

'~

]

""

\~ -

i

fj

ZS,., i000

~o 800

gO

--~--~ ..

';2

o ~ ~ (~,: = . 9 " c >

'

600

-8

34

36

. . . . .

38

40

)

~

1/.~.

;//f,/l," /'--

40LC

~

~200 0

28

30

32 34 Leaf temperature

Fig. 2. Simulated responses of (a) transpiration rate and perature under different conditions of solar radiation.

36 (°C)

--~

~8

40

(b) stomatal resistance to the leaf tern

REMOTE SENSING OF STOMATAL RESISTANCE

27

]

200 R H = 2 0 % u)

'7

E

4O ta

50

L.

I00

70

i

1 ] ]

35

4O

(G) ta = 38"C R s = 700 W m- e

L

u

0 20 1000

= 2.0ms

-~

. . . .

r

,

i

i

25 . . . .

I

i

I

{

i

i

30 . . . .

I

=

. . . .

I

(b) u)

ta= 36 ~3

800

RS

= 700

W

j i -~

/

600

1

Q,)

400

o

200

0 2O

=

=

L i i

=

25

30 Leof temperoture

35 (°C)

i

4O

Fig. 3. S i m u l a t e d r e s p o n s e s of (a) t r a n s p i r a t i o n rate a n d (b) s t o m a t a l resistance to the leaf temperature under different c o n d i t i o n s of a m b i e n t air h u m i d i t y .

fixed leaf temperature. Both transpiration rate and stomatal resistance were very sensitive to the changes in measured leaf temperatures in all cases. Stomatal resistances were more sensitive under lower solar radiation and high humidity conditions. The model indicates that the sensitivity of stomatal resistance to leaf temperature increases with the leaf temperature. These results suggest that the higher the relative leaf temperatures, the more serious the effects of errors in leaf temperature measurements become. Calculated values of sensible heat, H, and longwave radiation, R~, are shown in Fig. 4. Sensible heat varied from 50 to - 400 W m -2 (negative values signify heat transfer from air to leaf), depending on the windspeed and temperature differential between the leaf and air; while longwave radiation ranged from 60 to 250 W m -2, which means that energy was transferred from the leaf to the surroundings. Since the amount of longwave radiation emitted from a leaf was approximately half of the sensible heat that flowed to it, the energy exchange process was apparently determined mainly by solar radiation and transpirao

28

~ INOUEE'FA i , (W n1-2} r--200 ~-

,

--~" lau, , ~' n ra ~n u

1

Q tl annul

?o ..~_&,,

r ca

'

' --7

,:¢_,~.~2=

1

° °

,

,.

.'...

°

°

•% ° :

•,.

°

.°* °

..~"

,

-;.

. •..,',.

- iS." i

•

":.....;

-200 ~

°

°°'o

! i

I

-400

t

Fig. 4. S e n s i b l e

heat

16

12 14 Time of day (hr)

jcl

18

(O) and longwave radiation budget [] ) estimated by the modei

5001

,,

, ,

.

,.

,

t

E &

1O0

°0

r

/;

i

200

, -

~

/

400!

E 300i

,

i

I

I

,2",

/

I

~

Ft

•• / • • t ///i 2"

ida

18.H , Zi!!X 'l II 79"*1n 165J I

20(}

t'CIlIO[~-

~t

300 (II1~

Ill'

460 ~

J

t !

t

] 500

'J

Fig. 5. A c o m p a r i s o n b e t w e e n t h e " r e m o t e " t r a n s p i r a t i o n E t estimated by the model and the measured Et with a s t e a d y s t a t e p o r o m e t e r . ** S i g n i f i c a n t a t t h e 1% level.

tion. The boundary-layer resistance to vapor diffusion, ray, varied from 40 to 130 s m-1, which was an order of magnitude smaller than stomatal resistance r~v. However, under well-watered and low-windspeed conditions when r~v becomes relatively small, ray could be significant in regulating the vapor-ex* change process. E t and r~ values computed by the remote method were compared with values measured by the steady state porometer in Figs. 5 and 6. The correlation coefficient was 0.79** for Et and 0.93** for r.~v, respectively. On a particular day

REMOTE SENSING OF STOMATAL RESISTANCE

1500

.

i

i

i

i

29

i

i

1000

i

•

i

i

i

i

i

i

i

• •

"-2 • 500

• •

$

Y=33.1 +0.88X

•

2 ~'4t •

. . . .

5;0

. . . .

lO;O . . . .

soo

remote-rsv (s m ~) Fig. 6. A c o m p a r i s o n b e t w e e n t h e " r e m o t e " s t o m a t a l r e s i s t a n c e rs,, b y t h e m o d e l a n d t h e m e a s u r e d r~v w i t h a s t e a d y s t a t e p o r o m e t e r . ** S i g n i f i c a n t a t t h e 1% level.

under relatively stable conditions (e.g. DOY = 212 ) the correlation coefficient was 0.71"* for Et and 0.96** for r+v. Respectable linear regression lines were obtained between calculated and measured values. The regression line for r+v was very close to the 1:1 line and the "remote" r~v could be a good estimate of actual r+v. In the case of Et, however, the regression line was far from the 1 : 1 line, with the porometer Et consistently higher than the "remote" Et. This p h e n o m e n o n seems attributed to the drier air and higher windspeed in the cuvette of the porometer. The lower humidity and relatively great air flow in the cuvette resulted in higher cuvette Et values because of greater evaporative demand and smaller boundary-layer resistance. In fact, the cuvette humidity was always higher than ambient humidity with a correlation coefficient of 0.69**. This fact implies that porometer Et values are generally higher than actual values of Et in the free-air environment of the field. Nevertheless, this type of steady state porometer uses the initial value of "open" air humidity in calculations, which is measured each time just before clumping a leaf. Also, the boundary layer resistance within the cuvette was estimated from 15 to 45 s m-1 based on measurements for filter papers with various wetnesses. Those values were not extremely lower than values calculated by the model. Consequently, transpiration values measured by the porometer could not behave without system, but possibly reflect the actual values of Et. Thus, E t by the porometer seems competent in the case of relative comparisons. Smith et al. (1988) proposed a two-layer model based on energy partitioning to calculate the mean stomatal resistance of a sparse crop. They tested their

~0

Y. IN(}UE ET AI.

model against measured data from well-watered and water-stressed wheat crops, showing the feasibility of their model for inferring the mean stomatal resistance of a whole canopy from infrared foliage temperatures. Generally, however, the fully developed leaves near the top of a canopy have the highest physiological activity and account for most of the productivity of the canopy. In fact, photosynthetic rates in those leaves are much higher than in lower leaves, not only because of high light intensity but also because of age (e.g. Hesketh, 1963; Thomas and Stoddart, 1980). Thus, the activity or responses to e n v i r o n mental stresses evaluated for those leaves may provide representative inibrmation on the physiological status of the whole canopy. The model used here could basically be applicable to various crops, because it consists of equations about biophysical processes containing few empirical or statistical parameters. The results obtained here suggest that this model, combined with remotely sensed data, could provide fairly good estimations fbr diagnosis, which is also suggested by extra experiments using the several other crops under different climates such as in Japan. Several problems, however, remain in both the direct and remote methods discussed in the following sections, which must be the cause of disagreement or scattering of points in the diagrams of results. Owing to limitations of the porometer used, Et and r~v were obtained only for the bottom (abaxial) surface of each leaf, while calculated values were averages for both sides. This type of steady state porometer could properly be used only to measure the bottom surface, because of the necessity to keep the upper surface sunlit and exposed to the open air. The stomatal density is not necessarily the same on both sides of a leaf, being, in general, greater on the abaxial side than on the adaxial side. Hence, values by porometry may not. always directly validate the "remote" values, which suggests that values from the two methods should not necessarily fall on the 1 : 1 lines, both in transpiration and stomatal resistance. Nevertheless, stomatal behavior is presumably similar on both sides of a leaf, so that trends measured on one side should be representative of the stomatal behavior of the whole leaf. Micro-meteorological conditions in the cuvette of the steady state transpiration porometer were different from those in the ambient air, which undoubtedly caused the porometer Et values to be consistently higher than the calculated ones. Specifically, leaf temperatures measured with a fine thermocouple. as well as air humidities within the cuvette, were somewhat different from those observed in the ambient air. Indeed, Meyer et al. (1985) showed that leaf temperatures are more properly measured with an infrared thermometer than with a thermistor in a water vapor diffusion porometer. Idso et al. (1988) also showed the same kind of problem with porometry, indicating that the relationship between foliage-air temperature differential and air vapor pressure deficit (VPD) was significantly different between the inside and outside of the cuvette. However, realistic stomatal resistance values can probably be calculated

REMOTE SENSING OF STOMATAL RESISTANCE

31

using such data inside the chamber, because the time constant of stomatal response to changing environmental factors is generally much longer than the time necessary for measurements (van Bavel et al., 1965; Horie, 1979; Shackel and Brinckmann, 1984), and also because parameters such as leaf temperature and air humidity should be regarded just as provisional measurements for calculating the stomatal resistance and should not necessarily be the same as those before the leaf was clamped in the cuvette. Indeed, Schulze et al. (1987) showed that a step-like change in air humidity caused a simultaneous great change in transpiration rate but caused only small and slow change in stomatal resistance. Thus, the stomatal resistance seems to be the parameter most likely to be representative of "open" conditions among all those measured with the instrument. Also, the discussions above suggest that "remote" E t may be more realistic than "porometer" Et. The model used instantaneous data and did not account for the time constant of each variable. Windspeed, in particular, must be averaged for some period, because of its rapid fluctuations. Therefore both stomatal resistances and transpiration rates should give more reliable estimates when averaged over an appropriate period. The boundary-layer resistance was expressed theoretically in a simple form assuming that the boundary layer is laminar, which might not be the case in nature. Although the effect of wind in calculating ray is presumably smaller than calculated values because of turbulent flow or convection, the effect, especially in low windspeed conditions, should be examined. The temperature and humidity of air above a canopy measured by sensors may not be exactly the same as those outside the boundary layer of each leaf because of their spatial gradients. Therefore, as long as the present version of the model is concerned, it must be assumed that the micro-meteorological conditions near a canopy are approximately the same as those outside the boundary layers of the uppermost leaves. Some partial model might be incorporated into the model in order to account for the effect. For simplicity, values at 25°C were used for several physical parameters which vary somewhat depending on air temperature a n d / o r vapor pressure. This approximation, however, should have caused little difference in the results. Although further testing and improvement in accuracy are warranted in order to account for the several points discussed above, we have demonstrated the feasibility of estimating the transpiration rate and the stomatal resistance with a remote method. This method could prove useful for agronomic water management, as well as for assessing plant behavior in physiological or ecological studies in the field. ACKNOWLEDGMENTS

The authors appreciate the valuable advice of Prof. Takeshi Horie, Kyoto University, and of Prof. Edward T. Kanemasu, Kansas State University.

Thanks also are due to Dr. Sherwood B. Idso and Dr. Stephen G. Allen for their helpful comments and suggestions.

REFERENCES Brutsaert, W.H., 1975. On a derivable formula for long-wave radiation from clear skies. W'aLer Resour. Res., 11: 742-744. Ehrler, W.L., 1973. Cotton leaf temperatures as related to soil water depletion and meteorological factors. Agron. J.; 65: 404-409. Gates, D.M., 1980. Biophysical Ecology. Springer-Verlag, New York, NY, 611 pp. Hanks, R.J., 1983. Yield and water-use relationships: An overview. In: H.M. Taylor, W.R. Jordan and T.R. Sinclair {Editors), Limitations to Efficient Water Use in Crop Production. Americai~ Society of Agronomy, U.S.A., pp. 393-411. Hesketh, J.D., 1963. Limitations to photosynthesis responsible for differences among species Crop Sci., 3: 493-496. Horie, T., 1979. Studies on photosynthesis and primary production of rice plants in relation t , meteorological environments. II. Gaseous diffusive resistances, photosynthesis and transpir ation in the leaves as influenced by atmospheric humidity, and air and soil temperatures. J. Agric. Meteorol., 35:1 - 12. Idso, S.B., Jackson, R.D., Reginato, R.J., Pinter Jr., P.J. and Hatfield, J.L., 1981. Normalizing the stress degree day for environmental variability. Agric. Meteorol., 24: 45-55. Idso, S.B., Allen, S.G. and Choudhury, B.J., 1988. Problems with porometry: measuring stomatal conductances of potentially transpiring plants. Agric. For. Meteorol., 43: 49-58. Inoue, Y., 1986. Remote-monitoring of the physiological and ecological status of crops. 1. Analysis of thermal image of crop canopy. Jpn. J. Crop Sci., 55: 261-268. Inoue, Y., 1987. Remote-monitoring of the physiological and ecological status of crops. III. Estimating remotely the transpiration in corn canopy by means of multi-sensing of infrared canop~ temperature and micro-meteorological data. Jpn. J. Crop Sci., 56: 337-344. Inoue, Y., Oyanagi, A. and Ishii, T., 1989. Remote detection of crop stresses based on infrared thermometry - - relationship of infrared leaf temperature with photosynthetic and transpira tion rates and stomatal resistance. Jpn. J. Crop Sci., 58 (Extra issue 2): 145-146. Jackson, R.D., 1982. Soil moisture inferences from thermal-infrared measurements of vegetation temperatures. IEEE Trans. Geosci. Remote Sens., Vol. GE-20: 282-286. Jackson, R.D., Idso, S.B., Reginato, R.J. and Pinter Jr., P.J., 1981. Canopy temperature as a crop water stress indicator. Water Resour. Res., 17:1133-1138. Jackson, R.D., Moran, M.S., Gay, L.W. and Raymond, L.H., 1987. Evaluating evaporation from field crops using airborne radiometry and ground-based meteorological data. Irrig. Sci., 8:81 90. Monteith, J.L., 1973. Principles of Environmental Physics. Arnold, London, 147 pp. Meyer, W.S., Reicosky, D. and Schaeffer, N.L., 1985. Errors in field measurement of leaf diffusive conductance associated with leaf temperature. Agric. For. Meteorol., 36: 55-64. Shackel, E.D. and Brinckmann, E., 1984. In-situ measurement of epidermal cell turgot, leaf water potential and gas exchange in Tradescantis virginiana (L.). Plant Physiol., 78: 66- 70. Schulze, E.D., Turner, N.C., Gollan, T. and Shackel, K.A., 1987. Stomatal responses to air humidity and to soil drought. In: E. Zeiger, G.D. Farquhar and I.R. Cowan (Editors), Stomatal Function. Stanford University Press, Stanford, CA, pp. 311-321. Smith, R.C.G., Barrs, H.D. and Fischer, R,A., 1988. Inferring stomatal resistance of sparse crops from infrared measurements of foliage temperature. Agric. For. Meteorol., 42: 183-198. Stanhill, G., 1986. Water use efficiency. Adv. Agron., 39: 53-85.

REMOTESENSINGOF STOMATALRESISTANCE

33

Tanner, C.B. and Sinclair, T.R., 1983. Efficient water use in crop production: Research or re-search?. In: H.M. Tayler, W.R. Jordan and T.R. Sinclair (Editors), Limitations to Efficient Water Use in Crop Production. American Society of Agronomy, U.S.A., pp.l-27. Thom, A.S., 1968. The exchange of momentum, mass and heat between an artificial leaf and the airflow in a wind tunnel. Q. J. R. Meteorol. Soc., 94: 44-55. Thomas, H. and Stoddart, J.L., 1980. Leaf senescence. Annu. Rev. Plant Physiol., 31: 83-111. van Bavel, C.H.M., Nakayama, F.S. and Ehrler, W.L., 1965. Measuring transpiration resistance of leaves. Plant Physiol., 40: 535-540.