Hierarchical classification of complex landscape with VHR pan-sharpened satellite data and OBIA techniques (Articolo in rivista)

Type

• Prodotto della ricerca (Classe)
• Articolo in rivista (Classe)

Label

• Hierarchical classification of complex landscape with VHR pan-sharpened satellite data and OBIA techniques (Articolo in rivista) (literal)

Anno

• 2014-01-01T00:00:00+01:00 (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi

• 10.5721/EuJRS20144715 (literal)

Alternative label

• Gianinetto, Marco; Rusmini, Marco; Candiani, Gabriele; Dalla Via, Giorgio; Frassy, Federico; Maianti, Pieralberto; Marchesi, Andrea; Nodari, Francesco Rota; Dini, Luigi (2014)
  Hierarchical classification of complex landscape with VHR pan-sharpened satellite data and OBIA techniques
  in European Journal of Remote Sensing
  (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori

• Gianinetto, Marco; Rusmini, Marco; Candiani, Gabriele; Dalla Via, Giorgio; Frassy, Federico; Maianti, Pieralberto; Marchesi, Andrea; Nodari, Francesco Rota; Dini, Luigi (literal)

Pagina inizio

• 229 (literal)

Pagina fine

• 250 (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume

• 47 (literal)

Rivista

• European Journal of Remote Sensing (Rivista)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#pagineTotali

• 22 (literal)

Note

• ISI Web of Science (WOS) (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni

• Polytechnic University of Milan; ERM Italia SpA; Italian Natl Res Council CNR; Space Geodesy Ctr G Colombo (literal)

Titolo

• Hierarchical classification of complex landscape with VHR pan-sharpened satellite data and OBIA techniques (literal)

Abstract

• Land-cover/land-use thematic maps are a major need in urban and country planning. This paper demonstrates the capabilities of Object Based Image Analysis in multi-scale thematic classification of a complex sub-urban landscape with simultaneous presence of agricultural, residential and industrial areas using pan-sharpened very high resolution satellite imagery. The classification process was carried out step by step through the creation of different hierarchical segmentation levels and exploiting spectral, geometric and relational features. The framework returned a detailed land-cover/land-use map with a Cohen's kappa coefficient of 0.84 and an overall accuracy of 85%. (literal)

Prodotto di

• Institute for electromagnetic sensing of the environment (IREA) (Istituto)

Autore CNR

• GABRIELE CANDIANI (Unità di personale interno)

Insieme di parole chiave

• Parole chiave di "Hierarchical classification of complex landscape with VHR pan-sharpened satellite data and OBIA techniques" (Insieme di parole chiave)

Incoming links:

Prodotto

• Institute for electromagnetic sensing of the environment (IREA) (Istituto)

Autore CNR di

• GABRIELE CANDIANI (Unità di personale interno)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#rivistaDi

• European Journal of Remote Sensing (Rivista)

Insieme di parole chiave di

• Parole chiave di "Hierarchical classification of complex landscape with VHR pan-sharpened satellite data and OBIA techniques" (Insieme di parole chiave)