Mapping and characterization of urban forest in Mexico City

Alejandra A. Lopez-Caloca; Franz Mora; Boris Escalante-Ramirez

doi:10.1117/12.514311

13 February 2004 Mapping and characterization of urban forest in Mexico City

Alejandra A. Lopez-Caloca, Franz Mora, Boris Escalante-Ramirez

Proceedings Volume 5239, Remote Sensing for Environmental Monitoring, GIS Applications, and Geology III; (2004) https://doi.org/10.1117/12.514311
Event: Remote Sensing, 2003, Barcelona, Spain

Abstract

Mapping and characterization of forest and vegetation are particularly challenging in urban areas. High resolution imagery is needed for mapping and characterization purposes, due to the areal extent of urban forests, parks and recreational areas. Fusion techniques of panchromatic (1m resolution) and multiband (4m resolution) IKONOS data were used for mapping and characterization of land covering characteristics of urban green areas, allowing the identification of parks, tree areas and fields with a minimal mapping unit of 160 m². Techniques, that integrate the fine details of the input data into the fused image, are used. Experimental results for different image fusion methods (Laplacian, Gradient pyramids, Principal Component Analysis and Wavelet transform) are also demonstrated in order to improve spatial resolution. Classification of urban areas, mapped with fused data, results in higher accuracies than when using a multiband approach with 4 m data alone. Furthermore, high spatial resolution data permitted to obtain new areal extents of green areas of the city, giving a better estimate of international indicators for a suitable green areas policy. Vegetation indexes derived from red and near infrared data IKONOS are used to evaluate vegetation conditions, which, along with their distribution, location and urban context, resulted in better indicators of green areas.

Citation Download Citation

Alejandra A. Lopez-Caloca, Franz Mora, and Boris Escalante-Ramirez "Mapping and characterization of urban forest in Mexico City", Proc. SPIE 5239, Remote Sensing for Environmental Monitoring, GIS Applications, and Geology III, (13 February 2004); https://doi.org/10.1117/12.514311

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