THE RELATIONSHIP BETWEEN IMAGE STATISTICS, SENSOR GEOMETRY AND VEGETATION CANOPY GEOMETRY

M.J.Barnsley and S.A.W. Kay

Department of Geography, University College London,

26, Bedford Way, London WC 1H OAP,

England

RESULTS AND DISCUSSION

Changes in the variance of the spectral response recorded by an airborne multispectral scanner, as a function of sensor view angle, are examined for a number of different vegetation canopies. The variance of individual canopies is shown to decrease with increasing sensor view angle, due to an increase in the area of the sensor’s GRE, the consequent increased overlap of adjacent GREs, and the changing proportions of different canopy components viewed by the sensor. This will severely affect the accuracy of conventional multispectral classification algorithms, but may offer the potential to derive information on vegetation canopy biophysical parameters from multiple view angle imagery.

Keywords : Image variance, sensor view angle, vegetation canopy.

INTRODUCTION

In images obtained by sensors capable of off-nadir viewing, either by virtue of having a very wide field-of-view, or through the use of a pointable mirror system, variance in the detected spectral response of individual vegetation canopies is inversely related to sensor view angle [l]. This results from an increase in the area of the sensor’s ground resolution element (GRE) as a function of view angle, and the consequent increased over-sampling between adjacent GREs in both the along- and across-track directions. The relationship between image variance and sensor view angle is also dependent on the geometry and spatial variability of the vegetation canopy, in terms of the proportions of scene elements with different spectral reflectance characteristics (such as leaves, stems and soil) visible to the sensor at different view angles [l].

MULTIPLE VIEW-ANGLE DATA

In this investigation, data acquired by a Daedalus Airborne Thematic Mapper (ATM) scanner (AADS-1268) are used to illustrate the relationship between image variance and sensor view angle for a number different land cover types. The ATM has a 74’ field-of-view which allows sample areas on the ground to be sensed at a variety of different view angles from a series of closely-spaced, parallel flight lines [2].

A pronounced reduction in variance with increasing sensor view angle has been found for spatially non-homogeneous vegetation canopies, where the spatial variability of the canopy is approximately the same as or coarser than the GRE of the sensor at nadir. This is because the radiance associated with an off-nadir pixel is averaged over a larger area of the ground (the GRE) than its nadir-viewing counterpart. The increased overlap between GREs at oblique view angles also serves to increase the correlation between the values of adjacent pixels. Moreover, at oblique view angles the sensor “sees“ fewer of the predominantly shaded plant and soil elements towards the bottom of the canopy. This reduces the range of scene elements detected, and thus reduces the variation in detected radiance still further. By contrast, canopies with near-homogeneous ground cover exhibit little change in variance as a function of sensor view angle. This is because their spatial variability is much finer than the spatial resolution of the sensor at all view angles. Consequently, changes in the area and overlap of the sensor’s GRE have little effect on image variance.

CONCLUSIONS AND IMPLICATIONS

Changes in the variance of individual land cover types as a function of sensor view angle will severely affect the accuracy of conventional multispectral classification algorithms [3]. However, this effect offers the potential to discriminate between vegetation canopies with different geometric structures. It may also be possible to use view-angle dependent changes in image variance to estimate specific canopy biophysical properties.

REFERENCES

[ l ] Barnsley, M.J., and Kay, S.A.W., 1990, The relationship between sensor geometry, vegetation-canopy geometry, and image variance, Int. J . Remote Sensing, (in press). Barnsley, M.J., 1984a, Effects of off-nadir view angles on the detected spectral response of vegetation canopies. Int. J . Rem. Sens., 5,

Barnsley, M.J., 1985, Classification accuracy of land cover types as a function of sensor view angle. Proc. 11th Ann. Conf. of the Remote Sensing Society and CERMA, Vol. 2, Remote Sensing Society, Reading, 143-152.

[2]

715-728. [3]

1231