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The Influence of Vegetation Cover
Density and Topographic Parameters
on the Thermal Emission of the
Beech Forests of Simbruini Mountains
(Central Italy)
Carlo Ricotta, Giancarlo Avena and Fernando Ferril
Abstract. - Numerous studies have noted a strong negative correlation
between radiometric surface temperature and spectral ratio-based
vegetation indices. Since vegetation, through the process of
transpiration, considerably enhances evaporative fluxes to the
atmosphere, greater vegetation biomass should be associated with
increased reduction in surface temperature. In irregular terrains with
variable sun-sensor-surface geometry one of the major problems
concerning the evaluation of surface temperatures of vegetation from
remotely sensed data is that the thermal response of the earth surface is
strongly influenced by topographic factors, such as altitude and
insolation angle. In this paper, which uses remotely sensed inputs of
surface temperature and vegetation fractional cover, the relations
between the surface temperatures of the beech forests of Simbruini
Mountains (Central Italy) and the main vegetation cover density and
topographic parameters are discussed. According to the results obtained,
79.0% of the thermal response variance of the beech forests is due to
variations of the topographic parameters.
INTRODUCTION
Thermal infrared measures of the Earth's surface from terrestrial and airborne
sensors have been used since the 1960s to investigate energy budget conditions of
vegetation. With the launch of Landsat 4 and 5 plant ecologists now have access
to a wide-area synoptic and multitemporal thermal infrared band TM6 with a
emote Sensing Laboratory, Department of Plant Biology, University of Rome "La Sapienza", Rome, Italy.
623
relatively high resolution (Lathrop e Lillesand 1987). A number of authors (Asrar
et al. 1988, Smith and Choudhury 1990, Smith and Choudhury 1991, Hope and
McDowell 1992) had focused on the widely observed negative correlation
between radiometric surface temperature and remotely sensed measures of
actively transpiring vegetation such as vegetation indices.
One hypothesis to explain this observation is that variability in transpiring leaf
area produces spatial variability in surface temperature by modulating evaporative
cooling at the land-surface-atmosphere interface (Fried1 and Davis 1994). In
mountainous regions, however, this relationship may be complicated by the effect
of topography since a variation in altitude and insolation angle should also result
in variated surface heating. The combined effect of topography and
evapotranspiration in the energy exchange process at the surface produces a
complex problem in the interpretation of observed thermal emissions (Conese et
al. 1989). The present work aims at estimating by Landsat 5 TM data the
variability of the beech forest surface temperatures located on the Simbruini
Mountains (Central Italy) depending on the major remotely sensed vegetation
cover density and topographic parameters, such as the Normalized Difference
Vegetation Index (NDVI), altitude and insolation angle.
STUDY AREA
The beech forests of the Municipalities of Trevi nel Lazio and Filettino
(Central Italy) were selected for analysis. There are dense 5600 ha forests located
in the watershed of the Aniene River with elevational extent from about 900 to
1700 m. Due to environmental importance, the area was designated in 1983 as
part of the Natural Park of Simbruini Mountains.
The study area belongs to the Mountainous/Sub-alpine bio-climatic belt (Blasi
1994). The climate is strongly influenced by the position of the Simbruini
Massive, which forms a transversal barrier to the western sea-winds.
Meteorological data came from the station of the Ministero dei Lavori Pubblici
located in Filettino (1062 metres above sea level.). The average annual
temperature is 10.7 "C. The average annual rainfall is 1413.9 rnm with a principal
maximum in winter and a secondary maximum during fall. The average rainfall in
the quarter June-August is 155.7 mm with a consequent lack of summer aridity. A
short period of summer sub aridity is still possible during particularly dry years.
The range of relief is approximately 1,600 metres.
The maximum elevation above sea level is 2,156 metres (MSL). The
topography of the area is complex with a variety of site exposures. The beech
forests represent a nearly continuous formation with high cover density values due
to the absence of intense grazing and cutting activities. The dominant tree species
is Fagus sylvatica. More rare arboreal species are Acer pseudoplatanus, Taxus
baccata, Tilia platiphyllos and Ulmus glabra.
MATERIALS AND METHODS
The study area was extracted from a Landsat TM 190/31 I1 Q scene from 29
July 1993. Collateral information consisted of the vegetation map of the study
area at 1:25,000 scale obtained through photointerpretation of infrared aerial
photographs. Minimal and maximal air temperatures were respectively 12.8 "C
and 26.8 OC at Filettino on 29 July 1993. In the month prior to satellite overpass
there was 79.4 mm of rain. 17 July was the last rainy day prior to satellite
overpass with 70.0 mm of rain. On 29 July 1993 the atmosphere was clear and
any atmospheric attenuation was assessed to be systematic across the study area.
The TM data were rectified to a Universal Transverse Mercator grid using a
nearest neighbour resampling method. A digital terrain model (DTM) was created
by acquiring on a digitizer the contour lines every 25 m of the national
cartography mapping sheets at 1:25,000 scale of the study area. Relative sun
incidence was calculated from the DTM. Relative sun incidence displays direct
illumination which is equal to the cosine of the angle between the surface normal
and the incident beam for each pixel. The solar azimuth and altitude angles at the
time of satellite overpass (10:09 local time) necessary to calculate this
illumination model were read from the header file of the computer compatible
tape (CCT).
In order to test the hypothesis that thermal emissions are related to the
topographic parameters, such as altitude and insolation angle and the amount of
vegetative cover, a systematic sampling (Congalton 1988) of 216 pixels was
performed on the vegetated areas of the image. To avoid autocorrelation effects
particularly on band TM 6 the starting point was located at random and each
successive unit was taken at an interval of 10 lines and 10 columns thereafter.
For each of those pixels the values of altitude (MSL), relative sun incidence
(COS Z), NDVI (TM4-TM3/TM4+TM3) and surface temperatures were extracted
from the data set.
THERMAL DATA CALIBRATION
The satellite-derived normalized difference vegetation index (NDVI) is used as
the index for the vegetation density. The physical quantity that is measured
remotely is the spectral radiance reaching the sensor [ m ~ / c m 2sr pm] quantized
in digital numbers (DN) over a 8-bit brightness range. Digital counts of the bands
TM3, TM4 and TM6 were converted to spectral radiances according to the
method proposed by Markham and Barker (1 986).
The improved darkest object subtraction technique described by Chavez (1988)
was used to correct digital numbers from the red and near-infrared bands for
differences in atmospheric scattering in these two bands. This simple correction
was applied to minimize compression in the NDVI values which results from
unequal atmospheric effects on the red and near-infrared radiances (Hope and
McDowell 1992). Spectral radiance L in the thermal-infrared band and surface
temperature Ts are related in the form (Singh 1988):
Note that the accuracy of Eq. 1 decreases with the increase of the range of
temperature chosen. For this reason the parameters a and b were determined for
temperature range of 40 OK only and are reported by Singh (1988).
This technique does not account for atmospheric attenuation of the thermal
radiance. However, although the 8-14 pm atmospheric window is far from being
transparent, Landsat TM thermal IR data collected under clear atmospheric
conditions can be correctly calibrated in surface temperatures with acceptable
accuracy even when corrections for atmospheric effect are not applied. This is
possible because under clear atmospheric conditions the amount of atmospheric
path radiance is nearly equal to the amount of attenuated target radiance
(Bartolucci et al. 1988). Moreover, since the objective of this study was to
investigate the correlation coefficients of the relationships between Ts and the
examined independent variables, a systematic offset in the values would not affect
the interpretation of the results. The relationship between the surface temperature
of the beech forests (Ts) and the three independent variables MSL, COS Z and
NDVI were investigated. Linear correlation coefficients were calculated to
quantify the magnitude of the hypotesized relationships, and scattergrams were
constructed to indicate the nature of the relationships.
RESULTS AND DISCUSSION
Scattergrams depicting the relationship between surface temperatures of the
beech forests and the independent variables are presented in figure 1 and 2, and
the associated correlation coefficients are given in table 1.
Table 1. - Correlation coefficients (R) and coefficients of determination (R~)
for surface
temperatures of vegetation versus values from MSL, COS Z and NDVI. *) Not significant at
the 0.001 level.
MSL
COS Z
NDVI
These linear correlation coefficients show that at time of satellite overpass
COS Z has the strongest association with surface beech forests temperatures. This
fact can be explained with the obvious warming of vegetation surfaces caused
after sunrise on illuminated slopes. It is very likely that at the time of satellite
overpass (10:09 local time) the temperature difference between illuminated and
shaded surfaces is near its daily maximum (Conese et al. 1989). On 29 July 1993,
the relationship between MSL and the surface temperature of the beech forests
was weaker with a negative correlation coefficient. Moreover, including MSL
along with COS Z in the calculation of a bivariate correlation coefficient did
explain 79% of the variance of the surface temperature of the beech forests (table
2). On the contrary, according to Smith and Choudhury (1991), the simple linear
regression of the surface temperature of the beech forests with the corresponding
remotely sensed vegetation index amount had no significant correlation
coefficient. In fact, no strong inverse relationships between surface temperatures
and vegetation cover density indexes are evident for homogeneous forests with
complete ground cover. This relationships exist only for crop and pasture lands
where fractional vegetation cover varies from bare soil trough to crops with
complete ground cover giving a wide range of surface temperature and NDVI
values.
Table 2. - Bivariate and multivariate coefficients of determination ( R ~ )for surface
temperatures of vegetation versus values from MSL, COS Z and NDVI. All coefficients are
significant at the 0.001 level.
MSL
COS Z
MSL
NDVI
NDVI
COS Z
MSL
COS Z
NDVI
A week relationship between NDVI and surface temperature of the beech
forests is still evident in combination with the topographic variables. The multiple
correlation coefficient of the surface temperature of the beech forests with the
three independent variables MSL, COS Z and NDVI increase their explained
variance by less than 1% with respect to the bivariate correlation coefficient of the
topographic variables alone with surface temperature.
CONCLUSIONS
This study has defined some of the problems encountered when attempting to
use remote sensed data to estimate surface temperatures of vegetation in complex
vegetated mountainous regions. In irregular terrains the influence of topography
can strongly affect the thermal levels of vegetation. The comprehension of the
sources of this influence is thus determinant for a correct interpretation of
remotely sensed thermal data.
Results of the correlation analysis on 29 July 1993 in mid-summer sub-aridity
conditions reveal that at time of satellite overpass COS Z alone accounted for
41.0% of the variance in surface temperature of the beech forests. This results
indicate that insolation angle was, under the conditions of this experiment, a more
important factor controlling surfaces temperatures of the beech forests than
altitude or vegetation cover density. Moreover, the combined effect of differential
heating and altitude explains 79.0% of the variance of surface temperature of the
beech forests of Simbruini Mountains. On the contrary, the hypothesized negative
relationship between NDVI and surface temperature is not significant due to the
limited range of surface temperatures and fractional vegetation cover density
values of the beech forests of the study area.
However, remotely sensed data provide only an instantaneous assessment of
thermal conditions and the use of remote sensed thermal data is just a first step to
describe surface temperatures of vegetation. Future works towards accurately
define thermal trends of vegetation, should necessarily include field
measurements to convert instantaneous satellite-derived thermal data to daily
predictions.
Figure 1. - Scattergram of surface temperatures versus MSL
628
COS
Z
Figure 2. - Scattergram of surface temperatures versus COS Z
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BIOGRAPHICAL SKETCH
Carlo Ricotta is a Ph.D. candidate in Botanical Sciences at the Department of
Plant Biology of the University of Rome "La Sapienza", Italy, where he graduated
in Geology in 1992. His research interests include the extraction of spatial
information from remotely sensed imagery to study vegetation dynamic and
landscape change.
Giancarlo Avena is Full Professor of Phytogeography and Director of the
Department of Plant Biology at the University of Rome "La Sapienza". He
graduated in Geology from the University of Rome "La Sapienza" in 1962 and
specialized in Physical Geography and Geobotany. His current research interests
include the application of remote sensing and associate techniques for the study of
vegetation.
Fernando Ferri is technical co-ordinator of the Remote Sensing Laboratory of
the Department of Plant Biology at the University of Rome "La Sapienza", where
he graduated in Geology in 1981. Mr. Ferri provides technical consultation on
GIs and remote sensing projects that affect vegetation mapping.