Full text: Proceedings, XXth congress (Part 4)

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of this particular study area. A sensor is needed that is able to 
detect land cover changes, in particular deforestation, with 
lower spatial resolution than the AIRSAR sensor, but with more 
bands and more polarizations than the ERS-1 sensor. Especially 
bands with larger wavelengths are needed to improve the 
accuracy of the classification of secondary vegetation. 
Another possibility can be using high spatial resolution data to 
derive information (e.g. the location of recently cut areas) and 
to correct misclassification. Therefore, it is recommended to 
include the AIRSAR data in the ERS-1 monitoring system 
proposed by Bijker (1997) in regular intervals either at the 
initial stage and/or at a later stage. It can be expected that the 
location of those classes, which could not be detected properly 
in the ERS-1 images, such as secondary forest and recently cut 
areas, becomes known and so the accuracy of later ERS-1 
classifications will be improved by including this knowledge. 
Nevertheless, field observations should still be included, 
specifically in areas showing non-conformity between high and 
lower spatial resolution data. 
REFERENCES 
Bian, L. in Quattrochi, D.A. and Goodchild, M.F., 1997. Scale 
in remote sensing and GIS. Lewis Publishers, chapter 1, pp.13— 
26. 
Bijker, W., 1997. Radar for rain forest — A monitoring system 
for land cover change in the Colombian Amazon. PhD thesis, 
ITC, Enschede, The Netherlands. 
Cross, A.M., Settle, J.J. and Drake, N.A., Paivinen, R.T.M., 
1991. Subpixel measurement of tropical forest cover using 
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Gupta, R.K., Prasad, T.S. Krishnarao, P.V. and Bala 
Manikavelu, P.M., 2000. Problems in upscaling of high 
resolution remote sensing data to coarse spatial resolution over 
land surface. Advances in Space Research, 26(7), pp.1111- 
1121. 
Hoekman, D.H. and Quiriones, M.J., 2000. Land cover type and 
biomass classification using airsar data for evaluation of 
monitoring scenarios in the Colombian amazon. IEEE 
Transactions on Geoscience and Remote Sensing, 38(2), 
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Jarvis, P.G., 1995. Scaling processes and problems. Plant, Cell 
and Environment 18, pp.1079—1089. 
Malingreau, J.P., Tucker, C.J. and Laporte, N.. 1989. AVHRR 
for monitoring global tropical deforestation. International 
Journal Remote Sensing, 10 (4and5), pp.855-867. 
Mayaux, P. and Lambin, E.F., 1995. Estimation of tropical 
forest area from coarse spatial resolution data: a two-step 
correction function for proportional errors due to spatial 
aggregation. Remote Sensing of Environment, 53, pp.1-15. 
Quifiones, M.J. 1995. Assessment of airsar airborne, 
polarimetric data for forested land recognition and tropical 
forest structure and physiognomic composition analysis. 
Master’sthesis, ITC, Enschede, The Netherlands. 
Rahman, A.F., Gamon, J.A., Sims, D.A. and Schmidts, M., 
2003. Optimum pixel size for hyperspectral studies of 
961 
ecosystem function in southern california chaparral and 
grassland. Remote Sensing of Environment, 84, pp.192—207. 
Skole, D. and Tucker, C.J., 1993. Tropical deforestation and 
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Woodcock, C.E. and Strahler, A.H., 1987. The factor of scale in 
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332. 
ACKNOWLEDGEMENTS 
The authors would like to thank Marcela Quifiones and Dirk 
Hoekman for providing their AIRSAR data and classification. 
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B4. Istanbul 2004 
 
	        
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