TY - GEN
T1 - Assessing validation methods for building identification and extraction
AU - Wentz, Elizabeth
AU - Zhao, Qunshan
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/6/9
Y1 - 2015/6/9
N2 - As data sources and algorithm choices become increasingly more available for automatically extracting and reconstructing 3D buildings, methods are needed to assess the accuracy of the classification process. Our research goal is to compare validation data sources and methods to assess objectivity, sensitivity, and reliability of current validation approaches. Our results show that when relying on object-oriented methods for building classification and extraction, methods other than pixel assessment are needed.
AB - As data sources and algorithm choices become increasingly more available for automatically extracting and reconstructing 3D buildings, methods are needed to assess the accuracy of the classification process. Our research goal is to compare validation data sources and methods to assess objectivity, sensitivity, and reliability of current validation approaches. Our results show that when relying on object-oriented methods for building classification and extraction, methods other than pixel assessment are needed.
UR - http://www.scopus.com/inward/record.url?scp=84938826384&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84938826384&partnerID=8YFLogxK
U2 - 10.1109/JURSE.2015.7120453
DO - 10.1109/JURSE.2015.7120453
M3 - Conference contribution
AN - SCOPUS:84938826384
T3 - 2015 Joint Urban Remote Sensing Event, JURSE 2015
BT - 2015 Joint Urban Remote Sensing Event, JURSE 2015
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2015 Joint Urban Remote Sensing Event, JURSE 2015
Y2 - 30 March 2015 through 1 April 2015
ER -