REMOTE SENS. ENVIRON. 27:1-10 (1989)11f4

Measurements of Short-Term ThermalResponses of Coniferous ForestCanopies Using Thermal Scanner Data

J. C. LuvallH. R. HolboScience and Technology Laboratory,NASA Stennis Space Center

Thermal Infrared Multispectral Scanner . (TIMS)data were collected over the H. J. Andrews Experi-mental Forest, a coniferous forest in western Ore-gon. TIMS flights were timed to coincide with solarnoon. Flight lines were overlapped with a 28-mintime difference between flight lines. Concurrentradiosonde measurements of atmospheric profilesof air temperature and moisture provided inputs toLOWTRAN6 for atmospheric radiance correctionsof the TIMS data. Surface temperature differencesmeasured by the TIMS over time between flightlines were combined with surface radiative energybalance estimates to develop thermal responsenumbers (TRN). These numbers characterized thethermal response (kJ m- 2 °C —1)) of the differentsurface types. Barren surfaces had the lowest TRNwhereas the forested surfaces had the highest.

Address correspondence to Dr. J. C. Luvall, Science and Tech-nology Lab., HA10, Stennis Space Center, MS 39529.

Received 4 February 1988; revised 28 October 1988.

INTRODUCTION

Investigations using thermal infrared measure-ments to study the biophysical response of vege-tated surfaces to environmental factors have beenconducted since the 1960s (Gates, 1962). Mostresearch since then has focused on agriculturalcrops and soils. Estimates of soil moisture, plantmoisture stress, crop yields, and evapotranspirationhave been made using a wide variety of satellite-,aircraft-, and ground-based thermal sensors (Soer,1980; Price, 1980, 1982; Idso et al., 1975; Seguinand Itier, 1983; Stone and Horton, 1974; Hatfieldet al., 1984, Heilman et al., 1976; Reginato et al.,1985; Jackson et al., 1977; Idso et al., 1977).

Applications of aircraft-based thermal sensorsin forestry have primarily involved spotting forestfires and the use of uncalibrated imagery for de-tecting cold air drainage patterns in mountainterrain (Hirsh et al., 1971; Fritschen et al., 1982;Balick and Wilson, 1980). Recent work by Sader(1986) used the calibrated aircraft-mounted sensorTIMS (Thermal Infrared Multispectral Scanner) tomeasure the effective radiant temperatures ofconiferous forests in western Oregon.

0034-4257/89/$0.00

2 Luvall and flolho

On a global scale, climate modelers are begin-ning to include the important linkages betweendifferent kinds of land surface and the atmosphereas factors influencing global patterns of rainfall,of temperature, and of atmospheric circulation(Shukla and Mintz, 1982). These linkages have yetto be fully characterized in global models of atmo-spheric processes. Global Climate Models (GCM)suffer from a lack of detail about how differentsurfaces respond thermally, and, hence, affect localclimatic processes. These models could be im-proved by using thermal infrared measurements toquantify the biophysical response of the surface inrelation to environmental energy fluxes (radiative,latent, conductive, and convective). Information atlarger spatial resolution is also needed by the globalmodelers for improving their predictive capabili-ties (Carson, 1982), since the heterogeneity insurface types makes it difficult to characterize av-erages over the smaller spatial resolution used inglobal climate models (Dickinson, 1983).

The thermal response of a land surface is de-pendent on complex interactions between manyphysical and vegetation factors. In agricultural ar-eas and grasslands, the amount of vegetation cover,its composition, and soil moisture all influence thethermal response (Carlson, 1986). Forested land-scapes result in a very complex situation. Thethermal response of a forested landscape may in-volve as little as a few centimeters of soil, such asin clearcuts, to as much as tens of meters of air andbiomass above the soil, such as in old growthforests. These differences in forest structure pre-sent a complex range of surfaces for which thethermal response may depend primarily upon soilproperties, at one extreme, and upon forest canopytype, depth, and architecture, at the other. Also,many forests occur in rugged mountain terrain, sothat ground slope and aspect become importantdeterminants, particularly in controlling radiantenergy fluxes.

In remote sensing, temporal changes in theamount of *mined thermal radiation, i.e., tempera-ture differences, have often been employed toestimate surface properties (Pohn et al., 1974;Kahle, 1987; Schieldge et al., 1980; Ho, 1987). Thesurface property addressed by these workers iscalled the thermal inertia (Price, 1977):

(1) Thermal inertia (cal / cm 2 ° C s° 5):

P =(1/pcX)° 5,

where p is density (g/cm3 ), c is specific heat(cal/g °C), and A thermal conductivity (cal/cm s °C). As can be seen, P includes three funda-mental properties of soils (Sellers, 1965; Monteith,1973).

The time difference between surface tempera-ture observations used in these earlier studies wasusually preestablished by the orbital mechanics ofthe satellite, typically 12 h. Thus, all of the Pestimation algorithms are needed to make al-lowances for surface dynamics during the interven-ing portion of the diurnal (cyclic) period. Thisinvolved either flux estimates using surface mea-surements, or modeling of the surface energy fluxes,including the fluxes of sensible and latent heat, thenet radiation balance, and the subsurface heatconduction. Fourier techniques were commonlyinvoked in describing the cyclic nature of thesevariables.

In terms of the types of surface they couldaccommodate, these approaches are limited to sur-faces for which the models could be formulated,where suitable values for the specific heat capacityand thermal conductivity can be chosen or de-rived, and which were homogeneous in these prop-erties at the spatial scale of the estimate. As aresult, P estimates for partially vegetated orcanopied surfaces were not generally attempted.

It is recognized that total heat storage can bean important term (up to 10% of daily net radia-tion and > 50% near sunrise and sunset) in theenergy budget of forest canopies and canopy heatstorage can equal soil heat storage when soil mois-ture is < 20% (Moore, 1976; Moore and Fisch,1986; McCaughey, 1985). However, it is difficultto determine heat storage rates in forested terrain(Moore and Fisch, 1986; McCaughey, 1985; Stew-art and Thom, 1973; Thom, 1975). The directmethod used for estimating canopy heat storage isto integrate temperature change rates from a largenumber of air and biomass temperature measure-ments throughout the canopy space (Aston, 1985).An alternative method relies on fewer canopy tem-perature measurements in combination with soilheat flux estimates, estimated specific heats of thebiomass, and net radiation measurements (Mc-Caughey, 1985; Moore and Fisch, 1986). Thesetechniques for determining canopy heat storageand temperature response are limited to site-specific studies employing intensive ground-basedmeasurements, and cannot be extrapolated to other

Thermal Response of Conifer Forests 3

forests with differing canopy structure and biomass(Moore and Fisch, 1986).

However, Sader (1986) used TIMS to demon-strate that thermal radiation measures were linkedto the physical structure of forest stands. He foundthat different Douglas-fir forest stands at the An-drews Experimental Forest yielded different sur-face temperatures, depending on their compositionand amount of green biomass. His work indicatedthat forest stands greater than 25 years of age hadlower canopy temperatures than younger, lessdense stands. Also, aspect and slope were foundmore important in determining canopy tempera-tures for younger stands than for older stands.

OBJECTIVE

A technique is needed to examine forest cano-py thermal response which avoids the dynamiccomplexity of the modeling approaches and/orthe intensive temperature measurements takenthroughout the forest canopy, yet accounts for theeffects of the canopy structure and the environ-mental energy fluxes. The approach should notrequire site-specific measurements and be able toexamine many surface types throughout a forestedlandscape. The objective of this study was to usethe change in surface temperature as measured bythe TIMS over short time periods, coupled withsolar and long-wave radiation measurements, toexpress the effects of surface heat storage rates,from various surface types to characterize the ther-mal response of forested landscapes.

METHODS

A Thermal Response Number

We_will assume that a change in surface tempera-ture can be regarded as an aggregate expression ofboth surface properties (canopy structure andbiomass, age, and physiological condition) and en-vironmental energy fluxes (solar and long waveradiation; sensible and latent heat). Over shorttime intervals, it is not unreasonable to assumethat environmental energy fluxes proceed at con-stant, unchanging rates, at least during periods of

fair weather. This relieves the need to model fluxdynamics during the TIMS measurement interval.Making this assumption, we can use surface netradiation as the value which essentially integratesthe effects of the nonradiative fluxes, and the rateof change in surface temperature as the valuewhich reveals how those nonradiative fluxes arereacting to radiant energy inputs. Their ratio canbe used to define a surface property we call aThermal Response Number (TRN):

Thermal response number m - 2 o — 1) :

E te2 (R„ * At)TRN =

AT •

Mean polygon temperature for each surfacetype:

(TT= Pn

where E tt2 ( ri * At) (Jm') is the total net radia-tion of the site between flights t 1 and t2 , At timebetween flights, and T the mean surface tempera-tures (spatially averaged), Tp the pixel tempera-ture, n the number of pixels in the surface type,and AT its change in surface temperature for thesame period of time.

Radiation Balance

One minute averages of incoming solar (Li-Corpyranometer 0.4-1.1 ,um) and longwave radiation(Eppley pyrgeometer 2 5-50 ,um) were measuredduring the flight period. The net all-wave radiationbalance (Wm -2 ) of each surface was estimated forthe TRN time period using:

Net solar:

K* = (1— a)15(K 4.).

Net longwave:

L* =L — E{G(T )41.

(6) Net allwave radiation:

R„= K* + L* .

Li-Cor, Lincoln, NE.'Eppley Lab, Newport, RI. Use of trade names implies

no endorsement by NASA.

4 Luvall and Holbo

Here K is the measured incoming solarradiation, szi5 a site-dependent slope and aspect solar gain coefficient (Gamier and Ohmura,1968), a site albedo, L I measured incominglongwave radiation, L T calculated outgoing long-wave radiation using € the surface emis-sivity (0.99), a the Stefan-Boltzman constant(5.7*10 -8 Wm-T2 -4,,) and T average surfacetemperature in degrees Kelvin. Site albedo for theclearcut was determined for clearcuts similar tothose at the Andrews (Holbo and Childs, 1987).Other albedos were obtained from literature values(Jarvis et al., 1976; McCaughey, 1987; Dickinson,1983). The range of emissivity of vegetationcanopies ranges from 0.94 to 0.99 (Monteith, 1973)and soils from 0.95 to 0.99 (Taylor, 1979). Gener-ally values of emissivity in the 8-14 pm range forvegetated surfaces do not deviate significantly fromunity (Oke, 1978; Dickinson, 1983; Carlson, 1986).

(7) The thermal energy budget (Wm -2) can beexpressed:

R = H + LE + G.

In this equation, R„, net radiation, is the amountof energy transformed at the surface into nonradia-tive processes at the surface, H sensible heat flux,LE latent heat flux, and G energy flux into thesoil. From Eq. (7) it can be seen that R„ expressesthe combined energies of the nonradiative surfaceprocesses, making it the appropriate referencevalue for AT in the TRN.

TIMS Data Collection and Analysis

The Thermal Infrared Multispectral Scanner(TIMS) is an aircraft mounted instrument(Palluconi and Meeks, 1985). It was employed toobtain the measurements needed for investigatingforest canopy thermal response, and in the devel-opment of an analytical modeling technique ofthat thermal response. The TIMS has six thermalchannels in the wavelength regions of 8.2-12.2

The 4TIMS usable swath width is + 30° ofnadir. Sinee radiance measures from all six chan-nels were highly correlated, only Channel 2(8.4-9.2 µm) was used in this study. The TIMS isa calibrated thermal scanner with a noise equiva-lent temperature (NEST) of 0.09°C for Channel2. A precision of 0.2°C is obtained over the tem-perature range of 10-65°C. Preflight optical benchcalibrations were obtained for the TIMS spectral

response and blackbody temperature settings. Cal-ibrated temperature readings are possible becauseof on-board low and high temperature blackbodies.The blackbody temperatures are selected to bracketthe expected range of surface temperatures tooptimize TIM temperature resolution.

On 5 August 1985, TIMS overflights wereflown at 13:37 local time (solar noon 13:12) withan average nadir ground resolution of 10 m pixelsize. Flights were planned to cover the area duringthe time of maximum solar irradiance. Flight pathswere overlapped with 28.3 min time differencebetween flight lines to examine the short termchanges in surface temperatures. All areas fromwhich forest types were chosen were within 10° ofTIMS nadir.

An atmospheric profile from 436 to 10912 m oftemperature, pressure (altitude), and relative hu-midity was measured by radiosonde after the TILLSflights. The atmospheric profile was incorporatedin the LOWTRAN6 model for calculation of atmo-spheric radiance (Kneizys et al., 198.3). Atmo-spheric longwave radiance values calculated by anearlier version, LOWTRAN5, have been shown tobe in excellent agreement with measured atmo-spheric radiance values (Sweat and Carroll, 1983).Wilson and Anderson (1986) indicated the validityof using LOWTRAN5 for atmospheric radiancecorrections of aircraft thermal data collected overshort atmospheric path lengths.

' The output from LOWTRAN6 was combinedwith calibrated TIMS spectral response curves andblackbody information recorded during the flightto produce a lookup table for pixel temperatures asa function of TIMS values (Anderson, 1985).

Flight lines were georeferenced to assure corn-paribility of each of the five areas between theflights. Areas representing the five surface typeswere extracted for further processing.

STUDY AREA

The H. J. Andrews Experimental Forest is 6500ha. watershed located in the central-western Cas-cade Mountains of Oregon east of Eugene, OR. Itis one of the National Science Foundation'slongterm ecological research sites. It represents thedense coniferous forests of Douglas fir, westernhemlock, and common true firs of the westernslopes of the Cascade Mountains (Hawk et al.,

0

0cc

t--10 --

cc

a.—20

—30z0a. —40 --

3

CL. —50 —

Cz —60 --4cc

—70

—80 —

Thermal Response of Conifer Forests 5

1978). Geological parent materials range from olderandesites to younger basalts. Prior to selection asan ecological site, it had been used as a U.S. ForestService Experimental Forest since 1948. It pro-vides a wide range of forest stand ages, as well aslogging, thinning, regeneration, and other kinds offorest land management practices.

Five forest stands were selected for this study,representing a range of forest canopy types andtreatments for which different thermal responsescould be expected. They are:

A mature forest stand (MATUREF) with acanopy dominated by dense crowns of Pseu-dotsuga menziesii (Mirb.) Franco, a sec-ondary canopy of dense Tsuga heterophylla(Raf.) Sarg., and a tall shrub layer of Acercircinatum Pursh. (Hawk et al., 1978). Theaverage aspect of this site is southeast, 17%slope, at an elevation of 1080 m.

A recent clearcut area (CLRCUT) that washarvested in the summer 1981 and was origi-

nally classified in the Tsuga heterophylla-Ahies amabilis (Dougl.) species zone. Siteaspect is south-southwest with a 20% slope,and an elevation of 853 m. It was burned toclear logging debris in August 1982, andplanted in March 1983 with 1-year-old Dou-glas-fir seedling stock on a 3 X 3 m spacing.Fireweed (Epilobiuin augustifolium L.) is thepredominant vegetative cover. The Douglas-fir seedlings are not yet a significant part ofthe site's cover. Logging debris constitutesabout 10% of the emitting surface.

A naturally regenerating forest (NATREG) thatwas clearcut-logged in 1955 and was origi-nally in the Tsuga heteraphylla-Abies ama-bilis species zone. The aspect is south withan 40% slope at a elevation of 869-1082 m.The site is the lower end of a small water-

- shed, and supports a canopy of about 40% A.circinatum and 60% P. menziesii. There areopenings in the canopy, exposing dry organicmaterials, and occasional rock outcroppings.

Figure 1. Atmospheric profiles of air and dew point temperatures from radiosonde data and used in LO\VTRAN6 modelsfor atmospheric radiance.

RADIOSONDE PROFILE

ALTITUDE (m)

6 Luvall and Holbo

A Douglas-fir plantation (PLANT) that was First, the forest canopy provides a mechanism

clearcut-logged in the summer of 1953, and for moderating solar irradiance to the soil surface

was originally classified within the Tsuga het- beneath the canopy (Childs et al., 1985; Holbo

erophylla-Ahies amabilis species zone. It was et al., 1985). Vanderwaal and Holbo (1984) showed

planted in the fall of 1953 at a stocking rate that Douglas-fir needle temperatures tracked air

of about 700 trees per acre, and interplanted temperatures very closely (within 3°C), regardless

to fill gaps in November 1963. The aspect is of radiant fluxes and stomatal conductances. How-

southeast with a 20% slope at a elevation of ever, sunlit soil surface temperatures directly un-

838-914 m. Canopy coverage is fairly corn- der the seedlings were 30-50°C higher than nee-plete, although crown closure has not oc- dle temperatures. Without a forest canopy as cover,curred, and thickets of Snowbrush (Ceanothus the CLRCUT site surface temperatures would becordulatus Kell.) are common. greater than a forested surface for a given energy

A quarry (QUARRY) is an area of barren rock input.used for road gravels. This exposed outcrop is Second, L T (T) was greater for the CLRCUTcomposed of altered andesites at an elevation and QUARRY sites than for the forested sitesof 807 m. (NATREG, PLANT, and MATUREF), reducing

the amount of R,, which would be available forpartitioning among LE and G. Since the QUARRY

RESULTS AND DISCUSSION site had no vegetative cover and the CLRCUT wasmostly bare soil, LE was not a significant energy

The data collection period was a clear and cloud- flux. It was apparent that only a small amount of

less day (Figs. 1 and 2). K 1 was approximately energy was partitioned into G for these sites be-

75% of the solar constant at the time of TEAS cause of the magnitude of AT between flights. The

overflights. L 1. from the atmosphere was about forested sites had a greater R „, yet T and AT

37% of the amount contributed by solar radiation. were much smaller. It was evident that the sites

The atmospheric profiles of air and dew point with a forest canopy efficiently dissipated the en-

temperature showed boundary layer gradients of ergy. With large canopy biomass and surface area,

- 0.007°C m -1 and - 0.003°C m -1 , respec- forest R „ would be dissipated through either LE

tively. Profile slopes also showed no evidence of or H. However in coniferous forests, LE can pro-

clouds or inversions. These conditions maximized ceed without producing much drop in T, and it is

daytime solar loading and provided uniform, nearly possible that H is the dominant mechanism fOr

constant K .1, flux to all study sites. Thus the T and dissipating R„ (Jarvis et al., 1976). It is also possi-

AT of the various surface types depended entirely ble that G could be significant, given the large

on how their R„ was partitioned among LE, H, canopy biomass of the forested sites. In coniferousand G. forests, up to 10% of R„ can be allocated to G

Surfaces exhibited considerable differences in (Moore, 1976; McCaughey, 1985).

their radiation balances, average temperature, and This study represents the first time that short

changes in average temperatures (Table 1). The term (e.g., 28 min) surface thermal response

forested surfaces had greater R„ values than the changes have been measured on a "landscape

clearcut or quarry. The mean surface temperature scale" for forests using remote thermal sensors.

T and surface temperature change AT were dif- Each surface type produced a characteristically

ferent for each type of surface. One can note the different TRN (Table 1). The sites could be ranked

inverse relationship between the amount of energy by using the TRN value. The TRN for the forested

required to change surface temperature and fac- sites was much greater than for the QUARRY and

tors like forest type, forest canopy volume, and the CLRCUT sites. The TRN even differentiatedcompleteness of canopy cover. Both T and AT among the forested sites. It was evident that one

tended to increase with decreasing forest cover. It could not distinguish between the PLANT and

was evident that the presence of a forest canopy NATREG sites by using only T. It is possible for

cover could significantly alter the thermal re- two different forest canopies to have the same T,sponses of the surfaces in two ways. but partition the energy differently. Only when

0.5 -

0.4 -

0.3 -

0

500

Thermal Response of Con k! t,

RADIATION FLUX DENSITY

0.9 -

1

longwave

0.8 -

0.7 -

0.6 -

shortwave

0.2 -

0.1 -

I

700 900 1100 1300 1500 1700 1900 2100 2300

TIME

Figure 2. Shortwave and longwave radiation flux density during study period.

Table 1. Radiation Balance Estimates and Thermal Response Numbers for Various ForestSurface Types'

Quarry Clrcut Plant Natreg Maturef

Albedo a 0.25 0.22 0.15 0.15 0.08Solar gain 4) 1.00 1.07 1.05 1.10 1.05K 1 (W m -2 ) 957 1024 1005 1053 1005K S (W m -2 ) 718 799 854 895 924L .1. (w m- 2 ) 353 353 353 353 353LT (W rn -2 ) 626 634 477 477 448L* (w m- 2 ) - 273 - 281 - 124 - 124 - 95R„(W m -2 ) 445 517 730 771 830T (°C) 50.7 51.8 29.5 29.4 24.7AT (°C) 4.50 2.16 0.76 1.66 0.91

4 AT/At (°C min -1 ) 0.16 0.08 0.03 0.06 0.03TRN (kJ m -2 °C) - I 168 406 1631 788 1549

"Incoming solar (K 1.) and longwave (L flux densities W m -2 measured at quarry site, given for the 28.3-mintime period (At) during the overflights. Standard deviation for K.1 was 6 W m -2 , and for L 1, 2 W m-2.

Luvall and Holho

Table 2. Sensitivity Analysis for the Variables Used To Calculate the ThermalResponse Number

Variable"

Quarry Clrcut Plant Natreg Nfattlref

Da = 0.05 7.5 7.4 6.0 6.1 5.8Ae = 0.01 1.4 1.2 0.6 0.7 0.5AR„-- 50 Wm-2 11.2 9.7 6.5 6.9 6.0AT — 0.2°C 0.3 0.3 0.2 0.2 0.1

"Results are given in percent change in TRN for a given change (error) in a single variable.

the canopy is warming or cooling would differ-ences in I partitioning among LE, H, and Gbecome evident. Therefore, the TRN, which is anexpression of energy required to change T, coulddistinguish the site types.

A sensitivity analysis was performed on theTRN (Table 2) to identify what effect errors in theinput variables (a, E, R„, AT) would have on theTRN. Generally the percent change in the TRNwas small for a given change in all the variables.The TRN is most sensitive to changes in a and

n . However, surface type influenced the sensitiv-ity of the TRN most. Surfaces which had the leastcanopy cover were very sensitive to changes in allthe variables. There was little difference amongthe forested surfaces. A reduction in E of 0.02would result in only a 1% change in the TRNfor the NIATUREF site.

There are various implications of using theTIMS in studying landscape ecology and forestmanagement. Effects of altering the land's surfaceon the microclimate and hydrologic cycle havebeen difficult to evaluate at a regional or water-shed type scale.Gossmann (1986) calculated statis-tics of surface temperature for a combination offorested, agricultural, and urban land-use typesusing the uncalibrated thermal band on the HeatCapacity Mapping Mission (HCMM) satellite. Heestimated that a 20% change in area from oneland-use type to another would give a temperaturechange of up to 2.6-2.8°C. Another is the well-documented urban heat island effect which hasbeen found to influence precipitation and regionalenergy balances (Oke, 1978). The variability insuch areas is so great that conventional micromete-orologic techniques could not adequately charac-terize the thermal response of these surfaces.

CONCLUSIONS

Results of this study indicate that the TRN, de-rived from average surface temperatures and radi-

ation balance estimates, is a site-specific surfaceproperty which can discriminate among varioustypes of coniferous forest stands. The TRN pro-vides an analytical framework for studying theeffects of surface thermal response for large spatialresolution map scales that can be aggregated forinput to smaller scales, as needed by global climatemodels. The sensitivity analysis showed that evenwith minimal ground based measurements, theTRN could separate the thermal response of sev-eral different forest types. With the advent ofcalibrated multipass satellite thermal sensors, andwith the required atmospheric correction, it will bepossible to study the thermal response of manyother forest types. These landscape studies mightinclude forest thermal cover type classification,cold air drainage patterns, examinations of theimpact of drought, of excess moisture, or of insectdamage on forests. In tropical areas, the effects oflarge scale deforestation on regional water andthermal balances could be examined. Future stud-ies using the TRN should include various types ofdeciduous and tropical forests combined with moredetailed information on stand characteristics suchas basal area, leaf area index, and canopy biomassin order to identify their influence on the TRN.

This work was funded by NASA's Terrestrial Ecosystemsprogram (RTOP 677-21-29-03). The authors wish to thankthe following Lockheed-LESC employees for their numerousand valuable contributions to this project; Bill Colliver, pilot;Duane O'Neal, TIMS operator; Julius Baham, data processing;and Sharon Hatch, data preparation.

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