Mapping burned surfaces in sub-Saharan Africa based on multi-temporal neural classification (Articolo in rivista)

Type

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

Label

• Mapping burned surfaces in sub-Saharan Africa based on multi-temporal neural classification (Articolo in rivista) (literal)

Anno

• 2003-01-01T00:00:00+01:00 (literal)

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

• 10.1080/0143116031000103835 (literal)

Alternative label

• Brivio P. A., Maggi M., Binaghi E., Gallo I. (2003)
  Mapping burned surfaces in sub-Saharan Africa based on multi-temporal neural classification
  in International journal of remote sensing (Print); TAYLOR & FRANCIS LTD, London (Regno Unito)
  (literal)

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

• Brivio P. A., Maggi M., Binaghi E., Gallo I. (literal)

Pagina inizio

• 4003 (literal)

Pagina fine

• 4018 (literal)

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

• 24 (literal)

Rivista

• International journal of remote sensing (Rivista)

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

• 20 (literal)

Note

• ISI Web of Science (WOS) (literal)

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

• Brivio P. A., Maggi M.: CNR-IREA; Binaghi E., Gallo I.: Univ Insubria, Varese. (literal)

Titolo

• Mapping burned surfaces in sub-Saharan Africa based on multi-temporal neural classification (literal)

Abstract

• Biomass burning from vegetation fire is one of the major disturbances of natural terrestrial ecosystems and an increased understanding of its impact requires extensive documentation of the phenomenon at global scale. Satellite remote sensing has been demonstrated as the only tool able to cope with this global issue. Global daily coverage using the SPOT-VEGETATION instrument has been made for the year 2000 in the frame of the Global Burnt Area-2000 (GBA2000) initiative. This paper presents a new methodology for detecting burned areas from time series of coarse resolution satellite images. The proposed methodology is a supervised classification strategy based on hierarchical use of the Multi-Layer Perceptron neural network. The use of a neural network-based approach allows the exploitation of spatial and temporal dimensions within a unified scheme. The methodology has been applied to a series of daily SPOT-VEGETATION images covering the northern part of the African continent and daily burned area maps were produced for the dry season of the year 2000. Evaluation of the results has been done both in terms of the algorithm performance and of the final burned map accuracy using Landsat-7 Enhanced Thematic Mapper Plus (ETM+) data. (literal)

Editore

• TAYLOR & FRANCIS LTD (Editore)

Prodotto di

• Istituto per il rilevamento elettromagnetico dell'ambiente (IREA) (Istituto)
• Telerilevamento ottico e a microonde (TA.P06.007.005) (Modulo)

Autore CNR

• PIETRO ALESSANDRO BRIVIO (Unità di personale interno)

Insieme di parole chiave

• Keywords of "Mapping burned surfaces in sub-Saharan Africa based on multi-temporal neural classification" (Insieme di parole chiave)

Incoming links:

Autore CNR di

• PIETRO ALESSANDRO BRIVIO (Unità di personale interno)

Prodotto

• Istituto per il rilevamento elettromagnetico dell'ambiente (IREA) (Istituto)
• Telerilevamento ottico e a microonde (TA.P06.007.005) (Modulo)

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

• International journal of remote sensing (Rivista)

Editore di

• TAYLOR & FRANCIS LTD (Editore)

Insieme di parole chiave di

• Keywords of "Mapping burned surfaces in sub-Saharan Africa based on multi-temporal neural classification" (Insieme di parole chiave)