Ghent University Academic Bibliography

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Your filters: cql: author="Kempeneers, Pieter" or (type any "bookEditor issueEditor" and editor="Kempeneers, Pieter")

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- Conference Paper
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Tree species mapping by combining hyperspectral with LiDAR data

Pieter Kempeneers, Frieke Vancoillie (UGent) , Wenzhi Liao (UGent) , Flore Devriendt (UGent) and Kris Vandekerkhove

(2014) Geoscience and Remote Sensing, IEEE International symposium, Proceedings.
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Kan hyperspectrale remote sensing gebruikt worden voor vitaliteitsbepaling van individuele bomen? : een verkennend onderzoek

Marie-Leen Verdonck, Frieke Vancoillie (UGent) , Kris Vandekerkhove, Pieter Kempeneers and Robert De Wulf (UGent)

(2014) BOSREVUE (MELLE). p.12-15
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- Conference Paper
- C3
Tree species mapping within unmanaged closed forest reserves in Flanders (Belgium) using hyperspectral and LiDAR imagery to support forest management

Flore Devriendt (UGent) , Frieke Vancoillie (UGent) , Robert De Wulf, Kris Vandekerkhove, Pieter Kempeneers and Felix Morsdorf

(2013) 8th EARSeL SIG imaging spectroscopy workshop : abstracts.
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- Conference Paper
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Combining LiDAR and hyperspectral remote sensing data to improve information extraction for forestry

Pieter Kempeneers, Flore Devriendt (UGent) , Frieke Vancoillie (UGent) , Kris Vandekerkhove and Felix Morsdorf

(2012) LiDAR Applications for Assessing Forest Ecosystems, 12th International conference, Abstracts.
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Classification of unmanaged forest reserves in Flanders (Belgium) at the tree crown level using airborne hyperspectral and LiDAR data

Flore Devriendt (UGent) , Frieke Vancoillie (UGent) , Robert De Wulf (UGent) , Luc Bertels, Pieter Kempeneers and Kris Vandekerckhove

(2012) Proceedings of the 4th GEOBIA. p.141-145

Academic Bibliography

Tree species mapping by combining hyperspectral with LiDAR data

Kan hyperspectrale remote sensing gebruikt worden voor vitaliteitsbepaling van individuele bomen? : een verkennend onderzoek

Tree species mapping within unmanaged closed forest reserves in Flanders (Belgium) using hyperspectral and LiDAR imagery to support forest management

Combining LiDAR and hyperspectral remote sensing data to improve information extraction for forestry

Classification of unmanaged forest reserves in Flanders (Belgium) at the tree crown level using airborne hyperspectral and LiDAR data

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