Paper
23 October 2012 Analysis of regional vegetation changes with medium and high resolution imagery
Author Affiliations +
Abstract
The singular characteristics of the Canarian archipelago (Spain) and, in particular, of the Gran Canaria island have allowed the development of a unique biological richness. Almost half of its territory is protected to preserve the natural environment and, in consequence, the monitoring of vegetated regions plays an important role for regional administrations which aim to develop the corresponding policies for the conservation of such ecosystems. The Normalized Difference Vegetation Index (NDVI) is a common index applied for vegetation studies. It is important to emphasize that NDVI is sensor-dependent, and changes are affected by soil background, irradiance, solar position, atmospheric attenuation, season, hydric situation and climate of the area. So, a fixed threshold cannot be set, even for the same sensor or season, to properly segment vegetated areas. In this context, a robust methodology has been applied to ensure a reliable estimation of changes using the same sensor in multiple dates or different sensors. To that respect, a supervised procedure is presented consisting on the selection of different regions within each image to precisely map each cover with its associated NDVI values and, in consequence, obtain for each individual image the optimal threshold to properly segment vegetation without the need to perform the complex preprocessing required to estimate the ground reflectivity. On the other hand, fires are an important aspect of an ecosystem and their study, a fundamental task to perform a complete assessment of the environmental and economic damage. In our work we have also analyzed in detail the fire occurring during 2007 and precisely assessed the results.
© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
J. Marcello, F. Eugenio, and A. Medina "Analysis of regional vegetation changes with medium and high resolution imagery", Proc. SPIE 8531, Remote Sensing for Agriculture, Ecosystems, and Hydrology XIV, 85311R (23 October 2012); https://doi.org/10.1117/12.974385
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KEYWORDS
Vegetation

Sensors

Earth observing sensors

Image segmentation

Composites

Landsat

Image resolution

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