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Sensors 2008, 8(6), 3880-3902;

Comparing Different Approaches for Mapping Urban Vegetation Cover from Landsat ETM+ Data: A Case Study on Brussels

Vrije Universiteit Brussel, Department of Geography, Cartography and GIS Research Unit, Pleinlaan 2, B-1050 Brussels, Belgium
Author to whom correspondence should be addressed.
Received: 2 April 2008 / Revised: 28 May 2008 / Accepted: 30 May 2008 / Published: 10 June 2008
(This article belongs to the Special Issue Sensors for Urban Environmental Monitoring)
Full-Text   |   PDF [537 KB, uploaded 21 June 2014]


Urban growth and its related environmental problems call for sustainable urban management policies to safeguard the quality of urban environments. Vegetation plays an important part in this as it provides ecological, social, health and economic benefits to a city’s inhabitants. Remotely sensed data are of great value to monitor urban green and despite the clear advantages of contemporary high resolution images, the benefits of medium resolution data should not be discarded. The objective of this research was to estimate fractional vegetation cover from a Landsat ETM+ image with sub-pixel classification, and to compare accuracies obtained with multiple stepwise regression analysis, linear spectral unmixing and multi-layer perceptrons (MLP) at the level of meaningful urban spatial entities. Despite the small, but nevertheless statistically significant differences at pixel level between the alternative approaches, the spatial pattern of vegetation cover and estimation errors is clearly distinctive at neighbourhood level. At this spatially aggregated level, a simple regression model appears to attain sufficient accuracy. For mapping at a spatially more detailed level, the MLP seems to be the most appropriate choice. Brightness normalisation only appeared to affect the linear models, especially the linear spectral unmixing. View Full-Text
Keywords: urban vegetation cover; spectral mixture analysis; multi-layer perceptrons urban vegetation cover; spectral mixture analysis; multi-layer perceptrons
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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Van de Voorde, T.; Vlaeminck, J.; Canters, F. Comparing Different Approaches for Mapping Urban Vegetation Cover from Landsat ETM+ Data: A Case Study on Brussels. Sensors 2008, 8, 3880-3902.

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