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:: The application of a vegetation index in correcting the infrared reflectance for soil background. J. G. P. W. Clevers

Document type:: Multivolume work

Structure type:: Chapter

222 A red band, for instance, will be denoted by the subscript r and equation (1) is then written as: r = r r v,r B + r . (1-B) s, r ' ' (2) For estimation of LAI the corrected infrared reflec tance was used. It was defined as: r! = r. - r . . (1-B) ir ir s,ir ' ' (3) r : ir = corrected infrared reflectance r. = total measured infrared reflectance ir r . = infrared reflectance of the soil. s,ir The infrared reflectance corrected for soil back ground, as derived by Clevers (1986a), is given by: r! = r. ir ir C 0 . (r .r - r .r ) 2 g v,r r v,g (4) v,g with C, = r and C„ = r 1 i s,g^ 1 s,r ~2 s,ir" s,r J r r^ = total measured green reflectance = total measured red reflectance r = green reflectance of the vegetation rJ'J = red reflectance of the vegetation r ' = green reflectance of the soil r s, 9 = red reflectance of the soil. s,r Finally the LAI is estimated by using this cor rected infrared reflectance: LAI = -1/a . In(1 r ; / r . ) ir' Oo,ir' (5) Parameters a and r ffl . have to be estimated empir ically from a training set, but they have a phys- ical nature (Clevers, 1986a). Equation (5) is the inverse of a special case of the Mitscherlich func tion. The main assumption was that C* and C 2 are con stants, meaning that the ratio of the reflectance in two spectral bands (in the region of the electro magnetic spectrum considered) is independent of the soil moisture content. The validity of this assump tion for many soil types is confirmed by results ob tained by e.g. Condit (1970) and Stoner et al. (1980) For many soil types, the reflectance in the differ ent spectral bands does not differ very much (e.g. Condit, 1970); often there is only a slight increase in reflectance with increasing wavelength. 2.2 The vegetation index In order to apply equation (3) for ascertaining the corrected infrared reflectance, the apparent soil cover (B) has to be known. The apparent soil cover can be estimated by applying, for instance, equa tion (2). Combination of equations (2) and (3) gives: r - r V, r s, ir r - r s,r v,r (6) However, the reflectance of bare soil in the red and infrared and the reflectance of vegetation in the red should be known. An approximation may be given in the following way. If the reflectance of bare soil in the red (r ) is large compared with the reflectance of thl'green vegetation (r ), this latter reflec tance, which is very small, could be omitted from the denominator. If the soil type under considera tion has a similar reflectance in the red and infra red spectral bands, equation (6) may be approximated by equation (7): r : = r. (7) In the situation of bare soil the term r should be omitted in order to get the same result as in equation (6) (under the assumption r = r . ). In the situation of high soil cover fhe term'r r is very small compared with r. -r , so it may b'e omitted. A crude approximation for estimating the corrected infrared reflectance will result in the equation: (8) For application of this equation in estimating LAI, the difference between the infrared and red reflec tance (which is the vegetation index in this paper) must be ascertained and then equation (5) must be used. The combination of equations (5) and (8) is called the semi-empirical reflectance model. In this regard r ffi . in equation (5) will be the asymp totic value of'¥he difference between infrared and red reflectance at very high LAI. If in equation (4) the measured reflectances in the green and red spectral bands are assumed to be equal (r = r ), then this equation is equivalent to equat?on (&) under the assumption C* = C 2 = 1. This assumption agrees with the specific situation that the reflectances of bare soil in the green, red and infrared are equal. This drastic approach will be tested in the next section with a data set cal culated by means of Verhoef's SAIL model, and pro vided by him. Furthermore it will be verified with real field data. COMPARING THE MODEL WITH THE SAIL MODEL In this section the accuracy of the vegetation index presented in section 2.2 for ascertaining the cor rected infrared reflectance will be compared to the corrected infrared reflectance obtained if soil re flectances are known, by means of calculations with the SAIL model (Verhoef, 1984). The following vari ables for the SAIL model have been used: - two soil types: dry soil (green reflectance = 20.0 %, red reflec tance = 22.0 %, infrared reflectance = 24.2 %); wet soil (green reflectance = 10.0 %, red reflec tance = 11.0 %, infrared reflectance = 12.1 %); - spherical leaf angle distribution. - direct sunlight only (solar zenith angle: 45°). - direction of observation vertically downwards. - equality of reflectance and transmittance of a single leaf: green reflectance = 8 %, red reflec tance = 4 % and infrared reflectance = 45 %. Model calculations were carried out with the fol lowing LAI values: 0 (0.1) 1.0 (0.2) 2.0 (0.5) 5.0 (1.0) 8.0. The green, red and infrared reflectance factors were calculated according to the SAIL model for each of the above situations. In estimating LAI the infrared reflectance was corrected for soil background and subsequently this corrected infrared reflectance was used for estima ting LAI. If soil reflectance is known, equation (6) may be applied in order to ascertain the corrected infrared reflectance. This method will be called method 0 (indicating that it cannot be applied with out knowing soil reflectances explicitly). In prac tice, however, soil reflectances often are not known. In order to ascertain the corrected infrared reflec tance for the situation that soil reflectances are not known, the validity of equation (8) will be test ed. This method, called method 2, in addition to me thod 0 and method 1 given by Clevers (1986a), ascer tains the corrected infrared reflectance by taking the difference between measured infrared and red re flectance - a drastic simplification compared with method 1 (given by equation 4). Results for all three methods are given in figure 1. All three meth ods gave essentially the same results. As expected, Figure 1 ences ir Spherica xx: ca — : si (Rw is figure 4.5). the estj 2 as cor due to t given tc by methe not mucl methods. A mor vegetal SAIL me also f (1986c) vestigi yses ii crop Vi disturl red re: presenl angle c for thi SAIL me

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