Field Emissivity Measurements during the ReSeDA Experiment

Transcription

1 Field Emissivity Measurements during the ReSeDA Experiment C. Coll, V. Caselles, E. Rubio, E. Valor and F. Sospedra Department of Thermodynamics, Faculty of Physics, University of Valencia, C/ Dr. Moliner 50, Burjassot, Spain Received??-(Revised??)-Accepted?? Abstract. Emissivity measurements were made during the ReSeDA experiment. Emissivities are necessary for obtaining surface temperatures from remote sensing data in the thermal infrared, and they enter the radiative balance in the atmosphere-surface system. The objective of this study was to assess the spatial variation of surface emissivity in the area, with special regard to the spectral variation of emissivity in the 8-14 µm band. Field broadband (8-14 µm) measurements were performed for the main crops of the Alpilles experimental site (wheat, corn, sunflower and alfalfa). The box method was used for the field campaigns. This methodology is suitable for in situ emissivity measurements and permits covering the major crops and surface types, which gives us a good picture of the emissivity variability in the area In addition, laboratory spectral measurements were made to assess the spectral variation of emissivity. These measurements could only be made for soil samples, however, the spectral variation of green vegetation is known to be small. The field and laboratory measurements, together with estimates of plant dimensions and cover, were used in an emissivity model to derive effective spectral emissivities for various surface types and crops. In addition, we have shown that broadband (8-14 µm) integrated emissivities are a good approximation to equivalent hemispheric emissivities for the estimation of the longwave radiative balance. 1 Introduction Emissivity measurements made during the ReSeDA experiment are presented in this paper. Various fields of the main crops of the area were selected, including wheat, corn, sunflower and alfalfa. The interest of surface emissivities is twofold. First, field measurements are necessary in order to separate temperature and emissivity in thermal infrared data measured by remote sensors. The underdetermined nature Correspondence to: César Coll emissivity measurements or emissivity models, which are in turn derived from emissivity measurements. Second, surface emissivities, together with temperatures are key variables to determine the energy and water balances in the surface-atmosphere system. In both cases, the assessment of surface emissivity must take into account the spatial scale considered (what leads to the definition of effective emissivities) and the appropriate spectral resolution (which depend on the application and the remote instrument). The objective of this study was to assess the spatial variation of surface emissivity in the ReSeDA experimental area, with special regard to the spectral variation of emissivity in the 8-14 µm band. To this end several types of measurements were performed: (i) field broadband (8-14 µm) measurements for the typical surfaces of the study area, and (ii) laboratory spectral measurements for soil samples collected from selected fields. The laboratory measurements included narrow-band ( 1 µm) emissivities and spectral emissivities. The measurements, together with estimates of plant dimensions (height, width and separation) were used in the model of Valor and Caselles (1996) to derive effective emissivities for different spectral intervals. Band-integrated emissivities measurements were made by means of the box method, which is briefly described in the next section. The purpose of the measurements is to provide input emissivities and validation reference for the temperature-emissivity extraction algorithm applied to multispectral thermal data acquired by the Digital Airborne Imaging Spectrometer (DAIS) over the ReSeDA area (see Coll et al., 2000). Finally, we have also analysed the utility of band-integrated (8-14 µm) emissivities measured in the field for the estimation of the longwave flux. 2 The box method Field measurements were performed using the box method. The box is bottomless and has a base of cm 2 and a height of 80 cm. The sides of the box are made of polished

2 aluminium with reflectivity close to unity. Two interchangeable lids are used as top of the box: the cold lid made of the same polished aluminium and the hot lid made of anodised, rough aluminium painted in Parson s black, with reflectivity close to zero. The hot lid was provided with an electrically powered heating system with a thermostat, which permits achieving stable, high temperatures ( 55 ºC). The external sides and lids of the box were covered with a thermal insulator to assure a better temperature stability of the box-sample system. The box is placed over the sample and a series of radiometric measurements are made through small holes in the top lids. Two versions can be used with the box method depending on weather conditions. The two-lid version requires four radiometric measurements with the box for an emissivity determination: (i) Cold lid at top with sample at bottom. (ii) Hot lid at top with sample at bottom. (iii) Hot lid at top with cold lid at bottom. And (iv) cold lid at top and bottom (a second cold lid is required here). This method is more independent on the weather conditions, nevertheless calm wind is always preferred. A key factor in the measuring process is that the sample temperature must remain constant when successively measured with the cold and the hot lid. The one-lid version also requires four radiometric measurements but only the first and the last ones are made using the box in the same way as for the two-lid version. The second one is a direct measurement of the radiance emitted by the sample, without box. The third one is a measurement of the downwelling atmospheric radiance. The one-lid method is more suitable in the case of totally clear or totally cloudy sky in order to a better estimation of the downwelling sky radiance, and windless conditions to ensure thermal stability of the sample. In both versions, the fourth measurement is necessary to correct for the non-ideality of the box. For more details and rationale of the box method in its two versions see Rubio et al. (1997). 3 Emissivity measurements Field emissivity measurements were carried out using a hand-held Everest radiometer (8-14 µm) and the box method. This methodology is suitable for in situ emissivity measurements and permits covering the major crops and surface types. Laboratory spectral measurements could only be made for soil samples, however, the spectral variation of green vegetation is known to be small. Field and laboratory measurements, together with estimates of plant dimensions, were used in an emissivity model to derive effective spectral emissivities for various surface types and crops 3.1 Field measurements The experimental part of the ReSeDA project included two field campaigns in April and July, The major crops and surface types of the area were measured, which gives us a good picture of the emissivity variability in the area. Field measurements were carried out for alfalfa and wheat crops in April and for sunflower and corn in July. Emissivity measurements are shown in Table 1 for different crops and fields. For each sample, 30 emissivity measurements were taken and then averaged. Mean values and standard deviations, ± σ(), are given. For alfalfa and wheat crops in April, measurements were taken for plants in their natural plantation conditions (i. e., over the soil background). Therefore measurements can be regarded as effective emissivities in these cases. Results indicate that for crops with nearly full cover, effective emissivity is around For the soil and stubble composite remaining in the wheat fields in July, effective emissivity drops to 0.96 approximately. Due to the size of sunflower and corn plants in July, soils and vegetation were measured separately. Plants were cut from the plots and measured immediately and the corresponding soils were measured apart. Data for sunflower and corn fields in Table 1 refer to emissivities of pure components (bare soil or plant). In these cases we also measured the height (H), width (L) and separation (S) of plant rows. As seen from the measurements, emissivity of green vegetation is around in average. 101 (wheat) plant + soil soil + stubble ± ± (wheat) plant + soil soil + stubble ± ± (wheat) bare soil ± (corn) plant bare soil (wet) ± ± (corn) plant bare soil ± ± (sunflower) plant bare soil ± ± wild vegetation ± (sunflower) bare soil ± (sunflower) bare soil ± (alfalfa) plant + soil ± Table 1. Emissivity at nadir for the 8-14 µm waveband measured in the ReSeDA test site. Mean values of emissivity and standard deviations, ± σ(), are given. 3.2 Laboratory measurements We collected soil samples from selected fields in order to obtain spectral measurements of emissivity. A four-band CIMEL radiometer (CE 312) was used in the laboratory with the box method. The CE 312 radiometer has a wide channel (channel 1, 8-14 µm) and three narrow channels (channel 2, µm; channel 3, µm; and channel 4, µm). Thus, channel 1 is comparable to the Everest radiometer used in the field campaign. The other three narrow channels ( 1 µm) permit an assessment

3 CE 312-ch. 4 CE 312-ch. 3 CE 312-ch. 2 CE 312-ch. 1 EVEREST-Field Sample µm µm µm 8-14 µm 8-14 µm ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±0.013 Table 2. Laboratory emissivity measurements in the CE 312 channels for soil samples from the indicated fields. The last column compares the field measurements obtained with the Everest radiometer. of the spectral emissivity variations in the 8-14 µm window. Table 2 show the emissivities measured for the collected soil samples in the four CE 312 channels. The last column of Table 2 shows the field measurements with the Everest radiometer for comparison. Laboratory measurements are more accurate due to stable ambient conditions, which are not usually met on the field. Nevertheless, the agreement between laboratory and field measurements was satisfactory. On the other hand, the narrow band measurements of Table 2 indicate a moderate spectral contrast ( 0.015, with maximum emissivities in channel 2 and minimum emissivities in channel 4). The results also show a high homogeneity along the ReSeDA test site in terms of soil emissivity. Additionally, S. Hook (personal communication) made spectral measurements at the Jet Propulsion Laboratory for the same soils of Table 2. Again, spectra indicated a high homogeneity in soil emissivity. As an example, Fig. 1 shows the spectra measured for field 102 compared with the laboratory CE 312 measurements. Comparison of spectral measurements with broadband emissivities of Table 2 shows satisfactory agreement for the soils considered. emissivity wavelength (µm) Figure 1. Soil emissivity spectra for field 102 (continuous line), and comparison with laboratory measurements for CE-312 channels 2-4 (thick error bars, the horizontal bar representing the bandwidth). 4 Modelling effective emissivity When ground-measured emissivities are used for analysing thermal infrared remote sensing measurements (for calibration and/or validation purposes), it is necessary to adapt the emissivities to the spatial and spectral resolution of the image data. An example is the Digital Airborne Imaging Spectrometer (DAIS), with six channels in the 8-14 µm waveband region, which was used for temperature and emissivity inversion in ReSeDA (Coll et al., 2000). DAIS was flown at an altitude of 3000 m (ground resolution of 6 m) over the test area on July, 8, At the spatial scale of DAIS, most surfaces of the study area were composite; that is, they comprised exposed bare soil and green vegetation or stubble with variable cover. In addition, the ground measurements were to be adapted to the spectral ranges spanned by the six DAIS channels. Therefore an effective emissivity was required to describe such surfaces. Effective emissivities in the DAIS channels were determined for several heterogeneous fields using the field measurements and the model of Valor and Caselles (1996). This model assesses the land surface emissivity for heterogeneous and rough surfaces from the emissivity values of their basic components, i.e. soil and vegetation. The effective emissivity is given by = v P v + g (1-P v) + (1- g ) (1-P v ) v F + (1- v ) ( g G + v F') P s (1) where v and g are the vegetation and soil emissivities measured at ground in the DAIS channels, P v is the vegetation cover estimate for the mixed surface, P s is the side of vegetation proportion viewed by the sensor in offnadir observation, and F, G, and F are coefficients that consider the energy transferences by reflection between the different elements of the system, thus taking into account the cavity effect. These coefficients depend on the surface geometry, and consequently an estimation of the length (L), height (H) and separation (S) of the plants in the field is needed. It is also necessary a geometric model of the surface to determine the vegetation cover from the surface geometry and the observation conditions of the instrument. In the model of Valor and Caselles (1996) the vegetation is represented by boxes of dimensions L and H, made up by Lambertian surfaces, regularly distributed on the soil at a S distance from each other. This simple model can give the effective emissivity estimate with reasonably accuracy (Colton, 1996). To apply the model, the vegetation and soil emissivities for the DAIS channels, and the estimation of P v and P s are needed as inputs. First, emissivity of green vegetation is high and shows little spectral variation (Salisbury and D Aria, 1992), so that the 8-14 µm measurements performed in the field are useful in this case. Thus green vegetation emissivity was set to in all channels, and for all fields. Secondly, soil emissivity was taken from the

4 spectral measurements made for the soil samples. The spectra were convolved with the DAIS channels filter functions in order to obtain the adequate band-integrated emissivity values. Finally, the vegetation cover estimates and energy transfer coefficients were calculated from the geometric model proposed by Valor and Caselles (1996), considering average estimates of H, L, and S for each field, and using zenith viewing angles between 10º and 30º, since the observation conditions of DAIS ranged within these two values for the fields selected. Several examples of calculated effective emissivities are shown in Fig. 2, for different vegetation covers. The emissivity of bare soil (field 120) is also plotted for comparison. Emissivities are plotted against the centre wavelength of the DAIS channels. For moderate to large covers, cavity effects produce high effective emissivities with practically no spectral contrast. In July, this was the case for alfalfa (field 203), corn (126 and 500) and some sunflower fields (201 and 304). Sunflower field 121 showed lesser vegetation cover (around 20 %), its emissivity spectrum being also plotted in Fig. 2. Off-nadir observations tend to increase the influence of vegetation, the fraction of exposed bare soil being reduced. Also notice that the soil emissivity used here was relatively high and with small spectral contrast. These reasons make the effective emissivity spectra to be high and flat even for fields with small green vegetation cover. emissivity wavelength (µm) full cover 40% cover 20% cover bare soil soil+stubble Figure 2.- Effective emissivity for the DAIS thermal channels as calculated with the model of Valor and Caselles (1996) for the indicated surface types. Field 120 was a mixture of soil and wheat stubble, with approximate proportions of 2/3 and 1/3 respectively. For the stubble emissivity needed to estimate the effective emissivity, spectral measurements of senescent vegetation from Salisbury and D Aria (1992) were convolved with DAIS bands filter functions. The calculated effective emissivity is shown in Fig. 2. A significant decrease at large wavelengths (around 11 µm) is observed due mainly to the stubble spectrum. In this case the cavity effect is not observed since the mixture of soil and stubble is a relatively flat surface. Following this procedure, the effective emissivity for different fields imaged by DAIS were assessed. These fields served for calibration and validation of DAIS thermal data (see Coll et al., 2000 for details). 5 Use of 8-14 µm emissivities for longwave flux determination The effective radiation, F 0, represents the longwave radiation balance at surface level, that is, the difference between the downward atmospheric radiation which is absorbed by the surface and the radiation emitted from the surface. It is given by F 0 = e [F sky - σt 4 ] (2) where F sky is the downward irradiance of the atmosphere, σ is the Stefan-Boltzmann constant, T is the surface temperature, and e is the equivalent hemispheric emissivity. This emissivity is the result of the integration of the directional spectral emissivity to all directions of the upper hemisphere, and then the integration to the whole electromagnetic spectrum. In this last integration the weighting function depends on F sky and Planck functions at temperature T. This definition of emissivity is coherent with the relationship of the flux balance given by Eq. (2) (Rubio, 1998). Surface emissivity is usually determined from measurements. The problem addressed here is the optimisation of emissivity measurements for use in Eq. (2). Laboratory spectral measurements usually refer to plant elements (e.g., leaves) and soil samples, so that they do not represent the effective emissivity of complex natural surfaces. In order to have good emissivity estimates for a given experimental area, it is more convenient to perform in situ measurements, which are usually done with broadband instruments band and thus band-averaged emissivities are obtained. We have not considered angular emissivity effects in non-lambertian surfaces (e.g. rough heterogeneous systems), which would require a physical model of the surface to account for the angular distribution of the emitted radiance. We have limited ourselves to Lambertian surfaces (where directional and hemispheric emissivities are equal). Thus the problem is to determine the optimal wavelength range for which e could be estimated. The most significant contribution to F 0 comes from the 3 to 25 µm spectral region. This region reduces to the 3-14 µm interval region when surface temperature, T, and air temperature near the surface, T air, are similar. Rubio (1998) showed that, in average, an error of 10 % in the emissivity value beyond 14 µm results in an error of 1.4±1.0 Wm -2 in F 0 and of 0.013±0.007 in e (i.e. 1.4±0.8 % in both magnitudes). Because the available emissivity spectra of natural surfaces usually covers the 2-14 µm spectral region (Salisbury and D Aria, 1992), the calculation of e was limited to this interval. We have checked to approximate the equivalent emissivity e by the hemispherical emissivity, h i, where i is a spectral region within 3-14 µm. Three different intervals have been considered: 3-14 µm, 8-

5 14 µm and µm, resulting in the emissivities h(3-14), h(8-14) and h( ). The interval 3-14 µm corresponds to the spectral range covered by most spectral emissivity databases. The other two intervals correspond to typical bands of portable field radiometers as used in the preceding sections. Calculations of F 0, e, and h i were performed for a total of 2295 surface-atmosphere systems obtained as the combination of the following input data: (i) 27 spectra of atmospheric radiance for tropical, mid-latitude summer and mid-latitude winter conditions; (ii) 17 spectra of directional emissivity; and (iii) 5 surface temperatures defined as differences of 5, 0, 5,10 and 15 K with respect to T air (so, T varies between 270 and 320 K). Then, we have evaluated the systematic deviations in F 0, d(f 0 ), that implies using h(3-14), h(8-14) and h( ) instead of e in Eq. (2). A detail of d(f 0 ) can be seen in Fig. 3. Table 3 contains the average and maximum values of d(f 0 ). These results reveal that the integrated emissivity h(8-14) can be used to replace e in F 0, being more appropriate than h(3-14) or h ( ). The usefulness of h(8-14) is reinforced in situations which are more problematic, i.e. for samples with low emissivities (samples of Fig. 3) d(f 0) (%) 6 3 Serie1 h (8-14) Serie7 h (3-14) Serie3 h ( ) µm of general categories of vegetation, soil and rocks can be used (Rubio et at., 1997). d(f 0) h(3-14) h(8-14) h( ) Average (Wm -2 ) 0.6± ±0.5 1±2 Maximum (Wm -2 ) Maximum (%) Table 3. Average and maximum values of the errors in F 0. The first row contains the average and deviation of these errors for the three values h(3-14), h(8-14) and h( ) analysed. 6 Conclusions Emissivity measurements were performed for the ReSeDA test site in the intensive field campaigns of April and July, 1997 and in the laboratory. Field measurements were made in the 8-14 µm waveband for the most representative surfaces of the area, including different crops and bare soils. Laboratory measurements were made for soil samples with the CE 312 radiometer. Spectral measurements were also performed for the soils. Band-averaged emissivities (both field and laboratory) were in concordance with the spectral measurements for each sample. Spectral and narrow-band emissivities are necessary to calibrate and validate air- or space-borne thermal infrared data. Finally, our results reveal that broad-band (8-14 µm) integrated emissivity is a good approximation to the equivalent emissivity for the estimation of the longwave radiative balance, F 0. Acknowledgements. The present work has been financed by the Spanish CICyT (contract AMB CE) and the European Union through the ReSeDA project (contract ENV4-CT PL952071). We wish to thank Dr. S. Hook (Jet Propulsion laboratory) for the spectral emissivity measurements Sample number Figure 3. Percentage of error in F 0 due to approximate the equivalent emissivity e by the hemispheric emissivity h i in the 3-14, 8-14 and µm spectral regions. These results are consistent with the fact that the maximum of F 0 is found in the 8-14 µm spectral region. Therefore an integrated value of the emissivity in this region fits better to e than the emissivity in a wider region such as h(3-14). Notice that these F 0 deviations correspond to the cases in which the surface emissivity is measured or known with precision. When no information on the sample emissivity is available, representative emissivities in 8-14 References Coll, C., Caselles V., Rubio E., Valor E., Sospedra F. and Baret F., Estimating temperature and emissivities from the DAIS instrument, EGS 25 th General Assembly, Nice, France, April 24-28, Colton, A. L., Effective thermal parameters for a heterogeneous land surface. Remote Sens. Environ., 57: , Rubio, E., Hacia la optimización de la emisividad y la temperatura en teledetección, Doctoral Thesis, University of Valencia, Rubio, E., Caselles, V. and Badenas, C., Emisivity measurements of several soils and vegetation types in the 8-14 µm wave band: Analysis of two field methods. Remote Sens. Environ., 59, , Salisbury, J. W. and D Aria, D. M., Emissivity of terrestrial materials in the 8-14 µm atmospheric window. Remote Sens. Environ., 42: , Valor, E., and Caselles, V., Mapping land surface emissivity from NDVI: Application to European, African and South American areas. Remote Sens. Environ., 57: , 1996.