Kontakt
Wie einkaufen
Versand
Kaufberater
Integrating Openstreetmap Data
in Object Based Land-Cover and Land-Use Classification for Disaster Recovery
Englisch
91 b
Bis zu 30 Tage Rückgaberecht
Kunden kauften auch
/
Broschur
11.29
€
/
Broschur
16.09
€
Land cover and land use (LCLU) change is a very important indicator that can assist in the monitoring and assessment of both physical and functional recovery. Its fundamental approach rests on change assessment comparing the situation before, the immediate post-disaster situation and later the recovery stage through image classification. Remote sensing (RS) imagery provides spatial, spectral and contextual information that can assist in the LCLU classification. However, this works well with the classification of land cover (LC) but not for land use (LU) as it fails to capture information on the building use and function which are highly significant in LU classification. OpenStreetMap (OSM) data have been an emerging data source for providing base map information (roads, buildings, etc) on the ground. Most of the studies conducted using OSM data have been mainly concentrated on OSM data quality issues, but the potential of OSM data in disaster recovery assessment has been less explored. Therefore, the main objective of this study was to investigate the potential of using RS imagery and OSM data in LCLU classification for improving the understanding of post-disaster recovery.
Informationen zum Buch
Englisch
Verschenken Sie dieses Buch noch heute
Es ist ganz einfach
1 Legen Sie das Buch in Ihren Warenkorb und wählen Sie den Versand als Geschenk 2 Wir schicken Ihnen umgehend einen Gutschein 3 Das Buch wird an die Adresse des beschenkten Empfängers geliefertDas könnte Sie auch interessieren
/
Broschur
37.69
€
