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 derivation of a simplified reflectance model for the estimation of LAI. J. G. P. W. Clevers

Document type:: Multivolume work

Structure type:: Chapter

Symposium on Remote Sensing for Resources Development and Environmental Management / Enschede / August 1986 215 The derivation of a simplified reflectance model for the estimation of LAI J.G.P.W.Clevers Dept, of Landsurveying and Remote Sensing, Wageningen Agricultural University, Netherlands ABSTRACT: Information about crop reflectance obtained from the literature suggests that reflectance factors in the near-infrared are most suitable for estimating leaf area index (LAI). A problem arises if a multitemporal analysis is required. Soil moisture content is not constant during the season and differences in soil moisture content greatly influence soil reflectance. A correction for soil background has to be made when ascertaining the relationship between reflectance and crop(characteristics. Since in the literature no satisfactory solution for correcting for soil background was found, an appropriate simplified reflectance model for estimating LAI is presented. First of all, an apparent soil cover is defined. Then, a corrected infrared reflectance is calculated by subtracting the contribution of the soil from the mea sured reflectance. The assumption that there is a constant ratio between the reflectances of bare soil in different spectral bands, independent 6f soil moisture content, enables the corrected infrared reflectance to be calculated without knowing soil reflectances. Subsequently, this corrected infrared reflectance is used for estimating LAI according to the inverse of a special case of the Mitscherlich function. Simulations with the SAIL model confirmed the potential of this simplified (semi-empirical) reflectance model for estimating LAI. 1 INTRODUCTION Remote sensing techniques enable information about agricultural crops to be obtained quantitatively, instantaneously and, above all, non-destructively. During the past decades knowledge about remote sensing techniques and their application to fields such as agriculture has improved considerably. Bunnik (1978) demonstrated the possibilities of applying remote sensing in agriculture, particularly with regard to its relation with crop characteristics such as soil cover, leaf area index (LAI) and dry matter weight. LAI is regarded as a very important plant characteristic because photosynthesis takes place in the green plant parts. One of the main results of the work done by Bunnik (1978) was the identification of five wave lengths based on optimum information about variation in relevant crop characteristics. These wavelengths were: one in the green at 550 nm, one in the red at 670 nm, one in the near-infrared at 870 nm and (to a less extent) two in the middle-infrared - one at 1650 nm and the other at 2200 nm. In the literature there is a certain consensus that bands in the green, red and near-infrared regions are optimal if infor mation about vegetation is to be obtained (e.g. Kondratyev & Pokrovsky, 1979). From the literature it is evident that, in the visible region, vegetation absorbs much radiation (for photosynthesis) and shows a relatively low reflectance. This is especially true in the red region, because of the large absorption of this radiation by the chlorophyll in the leaves. In the near-infrared region the opposite occurs. The spec tral reflectance in this region is high. In the visible and near-infrared region the reflectance and transmittance of a green leaf are approximately equal (e.g. Goudriaan, 1977; Youkhana, 1983). The low transmittance of a green leaf in the visible region implies that in this region only the reflectance of the upper layer of leaves determines the measured reflectance of that canopy. In the near- infrared region the transmittance of a green leaf is in the order of 50%, and there is hardly any infrared absorptance by a green leaf. In this situation leaves or canopy layers underneath the upper layer contri bute significantly to the total measured reflectance. This contribution decreases with increasing depth in the canopy (and is negligible from 6-8 layers onwards). This multiple reflectance indicates that the infrared reflectance may be a suitable estimator of LAI. Soil reflectance has an important influence on the relationship between reflectance and LAI. At low soil cover, soil reflectance contributes strongly to the measured reflectance in the different spectral bands. For a given soil type, soil moisture will be the main factor determining soil reflectance. An increasing moisture content of the soil causes the reflectance to decrease, but the relative effect of soil moisture on the reflectance at distinct wavelengths is similar (Bowers & Hanks, 1965). Janse & Bunnik (1974) noticed that reflectance decreases with increasing soil moisture content, but this decrease is almost indepen dent of wavelengths between 400 nm and 1000 nm for a sandy soil. This means that the ratio of the reflec tance in two spectral bands in this interval is nearly independent of soil moisture content. Results obtained by Condit (1970) and Stoner et al. (1980) confirm that the ratio of the reflectance in two spectral bands is independent of the soil moisture content. The starting point of the study of this paper were calibrated reflectance factors in the green, red and near-infrared. These may be obtained, for instance, by means of multispectral aerial photography. The radiometric calibration and atmospheric correction of such measurements are described by Clevers (1986a, 1986b). The main aim was to investigate some index or model, derived from reflectance factors, for estima ting LAI in a multitemporal analysis. In order to enable such a multitemporal analysis a correction for soil background should be made. The ideal model for practical applications is one that is simple and requires the least number of input variables. For instance, if the agronomist has to ascertain a leaf angle distribution (necessary for some existing models), he will probably prefer to collect the conventional field data as he has always done.

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