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)

Messina, Gaetano;Lumia, Giovanni;Pratico, Salvatore;Di Fazio, Salvatore;Modica, Giuseppe
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
9783031068249
9783031068256
eCognition Developer
Geographic Object-Based Image Analysis (GEOBIA)
Image classification
Segmentation
Support Vector Machine (SVM)
File in questo prodotto:
File Dimensione Formato  
2022 - Messina et al_Preliminary Results in the Use of WorldView-3_Cork_Oak_low.pdf

non disponibili

Tipologia: Versione Editoriale (PDF)
Licenza: Copyright dell'editore
Dimensione 335.72 kB
Formato Adobe PDF
335.72 kB Adobe PDF   Visualizza/Apri   Richiedi una copia

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/20.500.12318/144348
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 1
  • ???jsp.display-item.citation.isi??? ND
social impact