Viewing Angle Effect on the Remote Sensing Monitoring of Wheat and Rice Crops

Transcription

1 Viewing Angle Effect on the Remote Sensing Monitoring of Wheat and Rice Crops Hafizur Rahman, D. A. Quadir, A.Z.M. Zahedul Islam and Sukumar Dutta Bangladesh Space Research and Remote Sensing Organization (SPARRSO), Agargaon, Shere Bangla Nagar, Dhaka-1207, Bangladesh Abstract Bidirectional reflectance characteristics of a wheat and a rice canopy were studied using radiometric measurements over the two canopies with an Exotech Radiometer Model 100AX. For both rice and wheat, the measurements exhibited significant variations in reflectance amplitude for varying viewing zenith angles and their values decreased from backward to forward scattering direction. Reflectance obtained its maximum value in the backscatter direction for the viewing angle that corresponds approximately to the solar zenith angle at the time of measurements. Canopy background condition (irrigated or non-irrigated) was an important determining factor of canopy reflectance particularly in the near-infrared region of the solar spectrum. Furthermore, bidirectional response characteristics of a vegetation canopy were influenced by the amount of vegetation cover. Introduction The grave concern generated by food deficit due to ever increasing human population has resulted in various scientific programmes the world over. Land areas are fixed and maximum production should be ensured within these limited areas through proper planning and management to meet the increasing food demand. Agriculturists are very much active regarding this issue. The use of fertilizer and irrigation can transform single cropped lands to double or triple cropped lands. Constant monitoring of crop condition is a prerequisite for improving overall crop production. Satellite remote sensing offers an efficient means of monitoring crop condition over large areas with an adequate spatial and temporal resolution. The data acquired by different satellite sensors presently in orbit offer valuable information concerning the condition and evolution of earth s surface. Particularly, the emergence of multidirectional viewing capacity airborne sensor like the Advanced Solid- State Array Spectroradiometer (ASAS) (Irons et al. 1991): space borne sensors like the Polarization and Directionality of the Earth's Surface Reflectance (POLDER) Vermote et al. 1992); or the Multiangle Imaging Spectro Radiometer (MISR) (Diner et al. 1989) opens a new era of research in quest of tools for the extraction of relevant information on earth s surface condition using remote sensing. Due to non-lambertian nature of the plant and soil surfaces, the reflectance measurements over a surface vary with the geometry of both illumination and observation (Colwell, 1974; Shibyama and Wiegand, 1985; Rahman, 1996a; Rahman, 1996b) and hence the name is bidirectional reflectance. Such variations in surface reflectance complicate 74 the interpretation processes particularly when dealing with multitemporal data acquired under different viewing or illumination geometries or data acquired by different sensors having same spectral bands but different viewing and illumination geometries (Rahman, 1996a). Bidirectional property has been successfully employed for the retrieval of vegetation parameters through inversion of a vegetation canopy reflectance model (Pinty and Verstraete, 1991a; Pinty and Verstraete, 1991b; Pinty et al ) or for the simultaneous retrieval of the parameters characterizing the coupled surface-atmosphere system through inversion of a coupled surface-atmosphere reflectance model against bidirectional reflectance data (Rahman et al., 1993a; Rahman et al., 1993b). For a clear and cloud free atmosphere, the variations in spectral reflectance measurements over a vegetation canopy are principally related to the optical and architectural properties of the canopy in addition to the illumination and viewing geometries (Ranson and Biehl, 1985; Pinty et al., 1990). The remotely sensed bidirectional reflectance data contain valuable information regarding vegetation condition, type and its growth (Rahman, 1996b). However, the interpretation of these data requires a thorough understanding of the bidirectional response characteristics of the vegetation canopy in relation to their morphological and optical properties with a consideration of illumination and viewing geometries. The aim of this work was to study the dynamic behavior of bidirectional response characteristics of agricultural crop canopies that influences the extraction of information on their growth and condition using multidirectional remote sensing data. In this paper, two important seasonal crops, Geocarto International, Vol. 14, No. 1, March 1999 Published by Geocarto International Centre, G.P.O. Box 4122, Hong Kong.

2 rice (Oryza Sativa L.) cultivar and wheat (Triticum aestivum L.) cultivar have been considered. The wheat was planted on the 8 December, 1994 and was non-irrigated. Whereas, the rice was planted on the 20 January, 1995 and was fully irrigated (flooded) at the time of measurements. Experimental Details Wheat and Rice Canopy Characteristics The wheat (Triticum aestivum L.) cultivar canopy is characterized by a vegetation cover of about 35 to 40% and is mixed with some grass impurities. The approximate height of the canopy was 39 to 51 cm. A dominant vertical structure of leaf is noticed with an average leaf angle of 45 to 62. An average of 260 to 320 stems per square meter was counted. There was an average of 6 open leaves on each stem, five of which were fully expanded. The dimensions of typical leaves were measured. The relatively dry soil background was visible from above the canopy and the soil moisture was found to be 17% through laboratory analysis. On the other hand, the rice (Oryza Sativa L.) cultivar canopy was near fully covered (90 to 95%) and was at its fully grown stage at the time of radiometric measurements (just before flowering starts). However, the water background due to irrigation was slightly visible from the top. The vegetation height was about 47 to 55 cm on average with a leaf inclination angle of about l0 to 25. Measurements of Bidirectional Reflectance A four channel radiometer Exotech, Model 100 AX was used for bidirectional reflectance measurements over a wheat and rice canopy. The channels are positioned at µm, µm, µm and µm which correspond to bands 1, 2, 3 and 4 respectively of LANDSAT TM. Measurements were carried out from directions ranging from 60 in the backward direction to 60 in the forward direction by 10 steps in the principal plane from a height of about 130 cm above ground level. So, for a given solar angle, a total of about 14 measurements were made for different viewing angle conditions. The radiometer was mounted on a tall frame. Measurements were performed on the 15th January, 1995 on wheat and on the 13th April, 1995 on rice. The solar zenith angles were approximately 46 and 44 during measurements over wheat and rice canopy, respectively. In both cases, the sky was almost cloud free with a medium range visibility. The surface was illuminated directly by the sun and there was no significant wind during measurements. The wheat was at its early stage of growth while the rice was in its full growth stage. Data Preprocessing Due to atmospheric perturbations, in situ measurements were affected during the traverse of solar radiation from the sun-surface-sensor trajectory depending on the illumination, observation geometry and atmospheric condition. As the measurements have been performed at near surface, the atmospheric contribution is negligibly small in the surfacesensor trajectory due to very small optical path. The measured surface reflectance ρ m (θ1,θ2,φ) can be expressed as a function of actual surface reflectance ρ s (θ1,θ2,φ) as follows (Rahman et al. 1993b): ρ m,φ) = ρ s,φ)+[ρ,φ) - ρ s,φ)]f d ) (1) Where, θ1, θ2 are the solar and viewing zenith angles respectively, φ is the relative azimuth between the solar and viewing plane. - The term ρ(θ1,θ2,φ) is the angular average of the bidirectional reflectance weighted by the diffuse irradiance and it can be estimated by the following equation: - ρ aρs,φ) +b (2) For a given atmospheric condition, a and b are two spectral band dependent constants (Tanré et al ). In equation 1 atmospheric function f d ) is the ratio of the transmittance of the atmosphere on the incoming and outgoing direction for the direct and diffuse solar radiation and is given by, t ) f d ) = (3) T ) T ) and t ) are the diffuse and total (direct and diffuse) transmittance of the atmosphere due to combined aerosol and molecular scattering for the incoming solar direction. The first term in equation 1 is the contribution of direct component of radiation and the second term represents the diffuse component of radiation. The second term tends to modify the directional variability of surface reflectance depending on the atmospheric condition. All radiometric measurements have been preprocessed by using equations 1 through 3 and the different atmospheric functions are provided by the simple atmospheric function of SMAC (Simplified Method for Atmospheric Correction) (Rahman and Dedieu 1994). SMAC is a computationally fast and reasonably accurate technique for the atmospheric correction of satellite measurements in the solar spectrum and is based on a unique set of equations with different coefficients which depend on the spectral band of the sensor. Semi-empirical formulations are used to describe the different interactions (absorption scattering etc.) of solar radiation with atmospheric constituents during its traversion through the atmosphere. An average aerosol loading of 0.2 is considered for the atmospheric correction and data have been corrected both for Rayleigh and aerosol scattering. Results and Discussions Figures 1 and 2 show respectively for wheat and rice, the plot of bidirectional reflectance as a function of viewing angle in the principal plane for bands 1, 2, 3 and 4 of 75

3 Figure 1 Bidirectional reflectance in bands 1, 2, 3 and 4 of Landsat TM as a function of viewing angle in the principal plane for a wheat canopy. The solar zenith angle corresponds to 46º Figure 2 Same as in figure 1, except for a rice canopy. The solar zenith angle corresponds to 44º Landsat TM. The solar zenith angle during measurements corresponds approximately to 46 and 44 in case of wheat and rice canopy respectively. The reflectance values are relatively small in bands 1, 2 and 3 in comparison to band 4 for both wheat and rice canopies. The wheat canopy shows relatively higher reflectance values than that for rice canopy in bands 1, 2 and 3 because of relatively low vegetation density and some soil surface (having relatively high surface reflectance) was visible from the top of the canopy. Rice canopy has a higher vegetation amount than that of wheat canopy which results in high photosynthetic absorption in the visible (bands 1, 2 and 3). Consequently, reflectance is lower for the rice canopy as compared to the wheat canopy. In both canopies, reflectances are slightly higher in band 2, than in bands 1 and 3 and reflectance is minimum in band 3. In both band 1 and band 3, strong absorption of incident solar radiation by chlorophyll occurs. As a result, reflectance is relatively small and typically about and in band 1 for wheat and rice, respectively, for nadir observation. In band 2 reduced levels of chlorophyll absorption occur and the reflectances are about and for wheat and rice canopies, respectively, for the same viewing angle and in band 3, the reflectances are about and for the above mentioned crops respectively. Finally in band 4, minimal absorption occurs and the leaf scattering mechanisms result in high levels of spectral reflectance, about and for wheat and rice canopies respectively. However, in band 4, reflectance is relatively small for rice canopy particularly around the nadir. This water background which caused increased absorption of radiation in this band and thereby, reduces reflectance (for a near nadir observation the water background was more visible). However, in the visible, (bands 1, 2 and 3) water and vegetation responses do not differ greatly. As a result, measurements in the visible region over the rice canopy did not exhibit any significant anomaly despite the presence of turbid water background under the canopy. It is evident from these data that reflectance varies significantly with viewing angles for both rice and wheat canopies. The variations are maximum in the backward scattering direction. Reflectance is relatively high in the backward scatter direction and decreases towards forward scatter direction. The minimum reflectances are obtained at about 40 and 20 in the forward scatter direction for wheat and rice canopies respectively. The reflectances vary from to in band 1, from to in band 2, from to in band 3 and from to in band 4 for the wheat canopy. Whereas, in case of rice canopy the variations are from to in band 1, from to in band 2, from to in band 3 and from to in band 4. The standard deviations of surface reflectance values over the viewing angles (a total of 13 different viewing angles for a given solar angle) in the four bands for wheat are larger than that for rice. The values of the standard deviations are about (about 44.8% of average reflectance values over the angle considered), (about 41.7% of the average reflectance), (about 50.8% of the average reflectance) and (about 35.2% of the average reflectance) for wheat canopy and about (about 37.6% of the average reflectance), (37.4% of the average reflectance), (32.2% of the average reflectance) and (28.8% of the average reflectance) 76

4 for rice canopy in bands 1, 2, 3 and 4 respectively. In case of wheat the directional variations are relatively higher than that for rice. This is due to the fact that for wheat crop the soil had a vegetation cover of about 40% and the remaining 60% was bare soil. Changing viewing angles change the proportion of soil and vegetation exposed to that particular direction and thereby, it results in more variation in directional response due to different spectral response of soil and vegetation. In contrast, for rice the surface was nearly fully covered by vegetation which gave a more homogeneous structure of the surface. Consequently, the change in viewing angles results in relatively less variation in directional response in this case. The observed variability in reflectance is due to the combined effect of viewing shaded sides (caused by mutual shadowing of canopy elements which depends on the structural properties, e.g., leaf area, leaf height, orientation etc.) of the plant in the forward scatter direction and of viewing a high proportion of lower canopy components, which reflect less than the upper canopy components and in addition, soil exposure in the viewing direction has an important role in determining the reflectance. The role of solar and viewing angles as well as leaf orientation angle is very important in determining the directional response of a given vegetation canopy. The solar zenith angle jointly with the leaf orientation angle determine the effective intercepting area that will be used for radiation incidence. For a normal incidence of radiation (normal to the leaf plane), maximum radiation will be intercepted by the leaf, whereas, away from the normal will decrease the amount of intercepted radiation. At the same time, for a normal incidence (normal to the surface) maximum radiation will interact with the background soil while away from the normal the interaction with soil decreases and the interaction with vegetation increases. For an incomplete canopy, viewing angle determines the amount of soil that is exposed to solar radiation in that direction. As the viewing angle moves from nadir, less soil and more vegetation will be seen. When a sensor is looking close to the direction of Sun, it senses less shadowed portion of the surface, which results in a relatively high reflectance in the backward scatter direction as is seen in cases of both the rice or wheat canopies. Away from the Sun direction (towards backward scatter direction), the sensor looks at more shaded portion resulting in decreased reflectance value. An important point to note is that, minimum forward scattering reflectance is observed near in case of rice and about in case of wheat. These angles correspond approximately to the leaf orientation angles for rice and wheat respectively. Above these angles reflectance increases slightly in both cases probably due to the increased contribution of specular component of reflectance. A sharp rise in reflectance observed at about in the backward direction corresponds to the solar zenith angle at that time. Increases in reflectance amplitudes for wheat canopy are about 121.7%, 68.7%, 157.8% and 56.4% in bands 1, 2, 3 and 4 respectively compared with nadir values. In case of rice canopy the corresponding increments are about 130.0%, 131.7%, 85.7% and 103.7% compared with nadir values. The sharp rises in reflectances are due to the hot spot i.e., a condition when a surface is observed from the same direction it is illuminated; and in that case the mutual shadowing of the leaf elements is minimum and, as a result, reflectance is high. The width and intensity of the hot spot is closely related to the structural properties of the crop canopy. On either side of the hot spot region i. e., towards forward scatter direction and for higher viewing angles in the backward scatter direction reflectance decreases for both rice and wheat canopies. Conclusions The bidirectional response characteristics of wheat and rice crops have been studied. The study shows that remote sensing measurements are largely influenced by the geometric condition of observation and illumination. Reflectance is maximal in the backscatter direction for a viewing angle closely corresponding to the solar zenith angle (hot spot effect). This angular variation in reflectance is very significant and can not be ignored. This bidirectional effect can be minimized by taking measurements away from the hot spot region. However, as the variations are due to the optical and structural properties of the plants, effective use of this directional variation can provide valuable information regarding the vegetation. Acknowledgments This paper is a contribution to the Biological Growth Rhythm Study Program of Bangladesh Space Research and Remote Sensing Organization (SPARRSO) and is financed by SPARRSO. References Colwell, J.E., 1974, Grass canopy bidirectional spectral reflectance. Proceedings of the 9th International Symposium on Remote Sensing of Environment, Ann Arbor, MI, Vol.II, pp Diner, D.J., Bruegge, C.J., Martonchik, J.V., Ackerman. T.P., Davies, R., Gerstl, S.A.W., Gordon, H.R. Sellers, P.J., Clark, J., Daniels. J.A., Danielson, E.D., Duval, V.G., Klaasen, K.P., Lilienthal, G.W., Nakamoto, D.I., Pagano, R.J. and Reilly T.H., 1989, MISR: A Multiangle Imaging Spectroradiometer for Geophysical and Climatological I.E.E.E. Transactions on Geoscience and Remote Sensing, 27, Irons. J.R., Ranson, K.J., Williams, D.L., Irish, R.I. and Huegel, F.G., 1991, An off-nadir-pointing imaging spectroradiometer for terrestrial ecosystem studies. I.E.E.E. Transactions on Geoscience Remote Sensing, GE-29, Pinty, B. and M.M. Verstraete, 1991a, Bidirectional Reflectance and Surface Albedo: Physical Modeling and Inversion. Proceedings of the 5th International Colloquium on Spectral Signatures of Objects in Remote Sensing, Courchevel, France, January 1991, ESA SP-319 (Noordwijk, The Netherlands: ESA Publications Division, European Space Research and Technology Center),

5 Pinty, B. and M.M. Verstraete, 1991b, Extracting information on surface properties from bidirectional reflectance measurements. Journal of Geophysical Research, 96, No. D2, Pinty, B., Verstraete, M.,M. and R., E., Dickinson, 1990, A physical model of the bidirectional reflectance of vegetation canopies 2. Inversion and validation. Journal of Geophysical Research, 95, No. D8, 11,767-11,775. Rahman H., Pinty, B. and M.M. Verstraete. 1993a. Coupled surfaceatmosphere reflectance (CSAR) model 1. Model description and inversion on synthetic data. Journal of Geophysical Research, Vol. 98, No. D11, pp 20,779-20,789. Rahman, H., Pinty, B. and M.M. Verstraete, 1993b. Coupled surfaceatmosphere reflectance (CSAR) model 2. Semiempirical surface model usable with NOAA Advanced Very High Resolution Radiometer Data. Journal of Geophysical Research. 98, 20, Rahman, H. and G. Dedieu, 1994, SMAC: A simplified method for the atmospheric correction of satellite measurements in the solar spectrum. International Journal of Remote Sensing, 15, Rahman, H., 1996a, Effect of Surface Anisotropy on Remote Sensing of Soil Surface using NOAA AVHRR Data. Asian-Pacific Remote Sensing and GIS Journal, 9, No.1, Rahman, H., 1996b, Atmospheric Optical Depth and Water Vapour Effects on the Angular Characteristics of Surface Reflectance in NOAA AVHRR. International Journal of Remote Sensing, 17, Ranson, K.J. and L.L. Biehl, 1985, Variation in spectral response of soybeans with respect to illumination, view and canopy geometry. International Journal of Remote Sensing, 6, No. 12, Shibayama and Wiegand, 1985, View azimuth and zenith, and solar angle effects on wheat canopy reflectance. Remote Sensing of Environment, 18, Tanré. D., M. Herman and P. Y. Deschamps, 1983, Influence of the atmosphere on space measurements of directional properties. Applied Optics, 22, Vermote. E., Santer, R., Deschamps, P.Y., and M., Herman, 1992, In- Flight Calibration of Large Field of View Sensors at Short Wavelengths Using Rayleigh Scattering. International Journal of Remote Sensing. 13,

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