Hedgerow segmentation on VHR optical satellite images for habitat monitoring

M. Arias; J. Inglada; R. Lucas; P. Blonda

doi:10.1109/IGARSS.2013.6723533

Hedgerow segmentation on VHR optical satellite images for habitat monitoring

M. Arias, J. Inglada, R. Lucas, P. Blonda

Department of Geography and Earth Sciences

Research output: Contribution to journal › Article › peer-review

4 Citations (Scopus)

Abstract

This paper presents a method for hedgerow extraction from very high resolution optical images using image segmentation. The method is based on a connected component region growing approach followed by an object based image analysis filtering allowing to introduce high level knowledge about the characteristics of the desired hedgerows. The proposed approach is used as a part of the EODHaM image processing system developed in the framework of the BIO SOS FP7 project.

Original language	English
Pages (from-to)	3301-3304
Journal	IEEE International Geoscience and Remote Sensing Symposium Proceedings
DOIs	https://doi.org/10.1109/IGARSS.2013.6723533
Publication status	Published - 27 Jan 2014

Keywords

biodiversity monitoring
segmentation
connected component
mean-shift
hedgerows

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title = "Hedgerow segmentation on VHR optical satellite images for habitat monitoring",

abstract = "This paper presents a method for hedgerow extraction from very high resolution optical images using image segmentation. The method is based on a connected component region growing approach followed by an object based image analysis filtering allowing to introduce high level knowledge about the characteristics of the desired hedgerows. The proposed approach is used as a part of the EODHaM image processing system developed in the framework of the BIO SOS FP7 project.",

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author = "M. Arias and J. Inglada and R. Lucas and P. Blonda",

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AU - Lucas, R.

AU - Blonda, P.

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AB - This paper presents a method for hedgerow extraction from very high resolution optical images using image segmentation. The method is based on a connected component region growing approach followed by an object based image analysis filtering allowing to introduce high level knowledge about the characteristics of the desired hedgerows. The proposed approach is used as a part of the EODHaM image processing system developed in the framework of the BIO SOS FP7 project.

KW - biodiversity monitoring

KW - segmentation

KW - connected component

KW - mean-shift

KW - hedgerows

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JO - IEEE International Geoscience and Remote Sensing Symposium Proceedings

JF - IEEE International Geoscience and Remote Sensing Symposium Proceedings

ER -

Hedgerow segmentation on VHR optical satellite images for habitat monitoring

Abstract

Keywords

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