Remote sensing for resources development and environmental management: Remote sensing for resources development and environmental management

Damen, M. C. J.

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Multivolume work

Persistent identifier:: 856342815

Title:: Remote sensing for resources development and environmental management

Sub title:: proceedings of the 7th international Symposium, Enschede, 25 - 29 August 1986

Year of publication:: 1986

Place of publication:: Rotterdam; Boston

Publisher of the original:: A. A. Balkema

Identifier (digital):: 856342815

Language:: English

Additional Notes:: Volume 1-3 erschienen von 1986-1988

Editor:: Damen, M. C. J.

Document type:: Multivolume work

Volume

Persistent identifier:: 856343064

Title:: Remote sensing for resources development and environmental management

Sub title:: proceedings of the 7th international Symposium, Enschede, 25 - 29 August 1986

Scope:: XV, 547 Seiten

Year of publication:: 1986

Place of publication:: Rotterdam; Boston

Publisher of the original:: A. A. Balkema

Identifier (digital):: 856343064

Illustration:: Illustrationen, Diagramme

Signature of the source:: ZS 312(26,7,1)

Language:: English

Usage licence:: Attribution 4.0 International (CC BY 4.0)

Editor:: Damen, M. C. J.

Publisher of the digital copy:: Technische Informationsbibliothek Hannover

Place of publication of the digital copy:: Hannover

Year of publication of the original:: 2016

Document type:: Volume

Collection:: Earth sciences

Chapter

Title:: 3 Spectral signatures of objects. Chairman: G. Guyot, Liaison: N. J. J. Bunnik

Document type:: Multivolume work

Structure type:: Chapter

Chapter

Title:: Relation between spectral reflectance and vegetation index. S. M. Singh

Document type:: Multivolume work

Structure type:: Chapter

2 ATMOSPHERIC CORRECTION SCHEME The satellite-sensor recorded radiance, L(A) in mW/(cm 2 sr pm) is calculated from (Hughes and Henderson-Sellers, 1982) L(*) = 0.01 COS e g K e (A) [G DN + I]/ir (2) where 6 is the solar zenith angle, K is the correction factor for Sun-Earth distance variation, DN is the digital count, G is the percentage spectral albedo per count, I is the percentage intercept alb edo (Lauritson et al., 1979) and e(A) is given by e(A) = / E(X l ) cf>( A 1 )d A 1 (3) 0 where ^ is a dummy integration variable, E(A) is the solar irradiance on the top of atmosphere for mean Sun-Earth distance per unit projected area (Thekaekara et al., 1969) and <t>(A) is the sensor response function which is normalized to unity, i.e. / $(A)dA = 1 (4) so that estimated using an expression given by Singh et al. (1985). To calculate surface reflectances from the AVHRR data an iterative method was adopted which is summarized below. To start with p was set equal to zero. An average continental type aerosol was assumed (Janza, 1975) and path radiances were estimated from equation (7). Clearly path radiances estimated in this manner would be underestimated, the diffuse surface radiance, L S (A), calculated from equations (2), (6) and (7) would be overestimated. When this value of L S (A) is substituted in equation (8) then the resulting diffuse reflectance would be larger than the actual value. In the next step of iteration this value of reflectance is used in equation (7) and the above procedure is repeated. Using reasoning parallel to the above it is apparent that the reflectivity obtained from the second iteration step would be smaller than the actual value. This procedure is continued until a desired convergence is reached, i.e. until the absolute ’difference in reflectivities from nth and (n+l)th iteration steps is found to be smaller or equal to a prefixed threshold value. The threshold is determined from equation (8) with radi ance which is equivalent to half a digital number. This iterative procedure has been tested using ten AVHRR scenes and for most cases only three or four iterations were required and there was only one case for which about seven iterations were required for the desired convergence. The atmospherically corrected NDVI was then evaluated from Î (A) = <KA)/ / ^(A 1 )dA 1 (5) where the values of <f>(A) can be estimated from Lauritson et al. (1979). On the other hand the satellite-sensor recorded radiance may be expressed as L(A) = L pR (A) + L pa (A) + L g (A)t(A,0) (6) where L r (A) is the Rayleigh path radiance, L & (A) is the aerosol path radiance, L (A) is the diffuse surface radiance, t(A,0) is the diffuse transmittance from surface being viewed to the sensor and 0 is the zenith angle of a ray from surface being viewed to the sensor. In writing equation (6), separability of the Rayleigh and aerosol atmospheres has been assumed (Gordon, 1978). Within the single scattering approximation an expression for path radiance may be written as L (A) = E(A)KT (A,0,0 ) t (A) x px v ' oz v s' x v [P x ( ¥-) + P(M S )P X ( *+)] (7) where T is the two way transmittance through the ozone layer, t is the optical thickness, P is the phase function, is the scattering angle, p is the surface reflectivity and x = R for Rayleigh scattering processes and x = a for aerosol scattering processes. Further details can be found in Singh and Cracknell (1986). For a Lambertian surface the diffuse reflectance is defined by P (A) = ttL (A)/E (A) (8) s 8 where E (A) is the global solar irradiance on the surface? Note that the global solar irradiance is not known without experimentation and it changes with solar elevation, wavelength and optical thickness. In this work global solar irradiance was NDVI , PQ2) - cOi) p(A2) + p ( A ]_ ) (9) If the atmospheric correction algorithm were perfect then it would suffice to define vegetation index (VI) as VI = p(A2)/ p(A^). The reason for retaining the form of equation (9) similar to the form of equation (1) is to further compensate for residual atmospheric contributions and to compensate (partially) for changing solar zenith angle, varying global irradiance and topographic effects. Topographic effects on remotely sensed data are difficult to correct for. From the work of Duggin et al. (1982) and Singh and Cracknell (1985, 1986) it seems that there are at least three factors which contribute to the satellite data as view angle changes: (a) the larger the view angle the larger is the atmospheric path length and hence the larger will be atmospheric contribution; (b) natural sur faces are non-Lambertian whereas remotely sensed radiances are assumed to be from Lambertian surfaces and (c) solar irradiation on the surface as seen by a remote sensor along a scan line is not necessarily uniform and this is because of shadows cast by vertical relief (natural as well as man made). An approximate atmospheric correction scheme which has been outlined above and which has been applied to a number of images by Singh and Cracknell (1985, 1986) indicates that a significant amount of view angle dependence of atmospheric effects caused by (a) above can be removed. However, it is not yet possible to correct remotely sensed data due to causes (b) and (c) above. 3 DATA USED The AVHRR/2 data from N0AA-7 satellite which have been used in this preliminary investigation were collected at 14:37 GMT on 20 August, 1984 at the Dundee University satellite-data receiving station. The selected area is the United Kingdom from about 50 to 55 degrees latitude. The western part including Ireland were cloudy. Only those pixels were selected for which raw NDVI values were positive. This constraint eliminates water pixels, and to some

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