TY - GEN
T1 - Forest Extraction on Semimountainous Rural Area with a Combination of Full Polarimetric SAR Image and LiDAR Data
AU - Miura, Yumi
AU - Yonezawa, Chinatsu
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/7
Y1 - 2019/7
N2 - We investigate the capability of forest extraction method combining full polarimetric L-band SAR imagery with LiDAR data. The analyzed data are an ALOS2-PALSAR2 image and airborne LiDAR data observed over Osaki city in Japan. In this study, three different types of extraction methods based on an object-oriented classification are compared using a SPOT6 image, the volume scattering component of the PALSAR2 image, and the integrated classification of a volume scattering component of PALSAR2 image and LiDAR data. The accuracy of each method is assessed using the confusion matrix. The results show that method by the integration of volume scattering component image and LiDAR data has a potential to extract forest with high accuracy compared to other two methods.
AB - We investigate the capability of forest extraction method combining full polarimetric L-band SAR imagery with LiDAR data. The analyzed data are an ALOS2-PALSAR2 image and airborne LiDAR data observed over Osaki city in Japan. In this study, three different types of extraction methods based on an object-oriented classification are compared using a SPOT6 image, the volume scattering component of the PALSAR2 image, and the integrated classification of a volume scattering component of PALSAR2 image and LiDAR data. The accuracy of each method is assessed using the confusion matrix. The results show that method by the integration of volume scattering component image and LiDAR data has a potential to extract forest with high accuracy compared to other two methods.
KW - forestry
KW - light detection and ranging (LiDAR)
KW - radar scattering
KW - synthetic aperture radar (SAR)
UR - http://www.scopus.com/inward/record.url?scp=85077713548&partnerID=8YFLogxK
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U2 - 10.1109/IGARSS.2019.8899331
DO - 10.1109/IGARSS.2019.8899331
M3 - Conference contribution
AN - SCOPUS:85077713548
T3 - International Geoscience and Remote Sensing Symposium (IGARSS)
SP - 6736
EP - 6739
BT - 2019 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2019 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 39th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2019
Y2 - 28 July 2019 through 2 August 2019
ER -