TY - CHAP
T1 - Improving flood risk management in the city of Lisbon
T2 - Developing a detailed and updated map of imperviousness using satellite imagery
AU - Santos , Teresa
AU - Freire, Sérgio Manuel Carneiro
N1 - info:eu-repo/grantAgreement/FCT/5876/147304/PT#
UID/SOC/04647/2013
PY - 2013/1/1
Y1 - 2013/1/1
N2 - The spatial distribution and extent of pervious and impervious areas in the city are important variables for planning, mitigating, preparing and responding to potential urban flooding events. Remote sensing constitutes a valuable data source to derive land cover information required for flood risk assessment. The present paper describes the generation of a Land Cover Map for the city of Lisbon, Portugal. The data source is an IKONOS-2 pansharp image, from 2008, with a spatial resolution of 1 m, and a normalized Digital Surface Model (nDSM) from 2006. The methodology was based on the extraction of features of interest, namely: vegetation, soil and impervious surfaces. It is demonstrated that using a methodology based on Very-High Resolution (VHR) images, quick updating of detailed land cover information is possible and can be used to support decisions in a crisis situation where official maps are generally outdated.
AB - The spatial distribution and extent of pervious and impervious areas in the city are important variables for planning, mitigating, preparing and responding to potential urban flooding events. Remote sensing constitutes a valuable data source to derive land cover information required for flood risk assessment. The present paper describes the generation of a Land Cover Map for the city of Lisbon, Portugal. The data source is an IKONOS-2 pansharp image, from 2008, with a spatial resolution of 1 m, and a normalized Digital Surface Model (nDSM) from 2006. The methodology was based on the extraction of features of interest, namely: vegetation, soil and impervious surfaces. It is demonstrated that using a methodology based on Very-High Resolution (VHR) images, quick updating of detailed land cover information is possible and can be used to support decisions in a crisis situation where official maps are generally outdated.
KW - ArcGIS
KW - Asphalt
KW - IKONOS
KW - Landsat
KW - Permeability
UR - http://www.scopus.com/inward/record.url?scp=84958938479&partnerID=8YFLogxK
U2 - 10.1007/978-94-007-0726-9_16
DO - 10.1007/978-94-007-0726-9_16
M3 - Chapter
SN - 978-94-007-0725-2
SN - 978-94-017-8180-0
T3 - Lecture Notes in Computational Vision and Biomechanics
SP - 291
EP - 305
BT - Topics in Medical Image Processing and Computational Vision
A2 - R.S. Tavares, João Manuel
A2 - M. Natal Jorge, Renato
PB - Springer
CY - Dordrecht
ER -