Paper
19 January 2001 Morphological segmentation/classification of vegetation cover types in remotely sensed images
Teresa Barata, Pedro Pina, Isabel Granado
Author Affiliations +
Abstract
A methodology based on mathematical morphology operators to classify vegetation cover types in remotely sensed images (ortho and satellite) is proposed in this paper. It consists on the automatic creation of the training sets by integrating the data extracted at higher spatial resolution with the corresponding data at higher spectral resolution, on the geometrical modelling of these sets to create a decision region for each class and on the automatic definition of the elementary units to be classified. The proposed approach is tested and illustrated with remotely sensed images from a region in centre Portugal.
© (2001) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Teresa Barata, Pedro Pina, and Isabel Granado "Morphological segmentation/classification of vegetation cover types in remotely sensed images", Proc. SPIE 4170, Image and Signal Processing for Remote Sensing VI, (19 January 2001); https://doi.org/10.1117/12.413887
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KEYWORDS
Image segmentation

Vegetation

Earth observing sensors

Satellites

Spatial resolution

Spectral resolution

Modeling

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