Cork oaks (Quercus suber L.) characterize many Mediterranean forest landscapes where they play important socio-economic and ecological functions for nature. This study, carried out in Mount Scrisi (Calabria Region, Italy) aims to map cork oak forests by using WorldView-3 (WV-3) high-resolution satellite image. For this aim, a supervised classification on WV-3’s images was implemented to assess the potential performance of this sensor either in detecting the presence of cork oak woodlands and in distinguishing them from other spectrally similar tree species. Particular attention was paid to the distinction of cork oaks from olive (Olea europaea L.) and chestnut trees (Castanea sativa, Mill.). By exploiting the panchromatic image with 31 cm resolution and multispectral image bands through pansharpening, the objective was achieved obtaining a high accuracy in classification (OA = 0.88). Results confirm the usefulness of WV-3 in the applications of remote sensing (RS) on forestry for mapping species distribution and monitoring vegetation and environmental health.

Preliminary Results in the Use of WorldView-3 for the Detection of Cork Oak (Quercus Suber L.): A Case in Calabria (Italy)

Modica Giuseppe
Ultimo
2022-01-01

Abstract

Cork oaks (Quercus suber L.) characterize many Mediterranean forest landscapes where they play important socio-economic and ecological functions for nature. This study, carried out in Mount Scrisi (Calabria Region, Italy) aims to map cork oak forests by using WorldView-3 (WV-3) high-resolution satellite image. For this aim, a supervised classification on WV-3’s images was implemented to assess the potential performance of this sensor either in detecting the presence of cork oak woodlands and in distinguishing them from other spectrally similar tree species. Particular attention was paid to the distinction of cork oaks from olive (Olea europaea L.) and chestnut trees (Castanea sativa, Mill.). By exploiting the panchromatic image with 31 cm resolution and multispectral image bands through pansharpening, the objective was achieved obtaining a high accuracy in classification (OA = 0.88). Results confirm the usefulness of WV-3 in the applications of remote sensing (RS) on forestry for mapping species distribution and monitoring vegetation and environmental health.
2022
978-3-031-06824-9
978-3-031-06825-6
File in questo prodotto:
Non ci sono file associati a questo prodotto.
Pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11570/3271529
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 1
  • ???jsp.display-item.citation.isi??? ND
social impact