TY - JOUR
T1 - Historic Low Wall Detection via Topographic Parameter Images Derived from Fine-Resolution DEM
AU - Chu, Hone Jay
AU - Huang, Min Lang
AU - Tain, Yu Ching
AU - Yang, Mon Shieh
AU - Fle, Bernhard H.
N1 - Funding Information:
Acknowledgments: Thanks for enhancing the quality of the paper from the editors and anonymous reviewers. This research was funded by the Headquarters of the University Advancement at the National Cheng Kung University, which is sponsored by the Ministry of Education, Taiwan.
Funding Information:
Thanks for enhancing the quality of the paper from the editors and anonymous reviewers. This research was funded by the Headquarters of the University Advancement at the National Cheng Kung University, which is sponsored by the Ministry of Education, Taiwan.
Publisher Copyright:
2017 by the authors.
PY - 2017/11
Y1 - 2017/11
N2 - Coral walls protect vegetation gardens from strong winds that sweep across Xiji Island, Taiwan Strait for half the year. Topographic parameters based on light detection and ranging (LiDAR)-based high-resolution digital elevation model (DEM) provide obvious correspondence with the expected form of landscape features. The information on slope, curvature, and openness can help identify the location of landscape features. This study applied the automatic landscape line detection to extract historic vegetable garden wall lines from a LiDAR-derived DEM. The three rapid processes used in this study included the derivation of topographic parameters, line extraction, and aggregation. The rules were extracted from a decision tree to check the line detection from multiple topographic parameters. Results show that wall line detection with multiple topographic parameter images is an alternative means of obtaining essential historic wall feature information. Multiple topographic parameters are highly related to low wall feature identification. Furthermore, the accuracy of wall feature detection is 74% compared with manual interpretation. Thus, this study provides rapid wall detection systems with multiple topographic parameters for further historic landscape management.
AB - Coral walls protect vegetation gardens from strong winds that sweep across Xiji Island, Taiwan Strait for half the year. Topographic parameters based on light detection and ranging (LiDAR)-based high-resolution digital elevation model (DEM) provide obvious correspondence with the expected form of landscape features. The information on slope, curvature, and openness can help identify the location of landscape features. This study applied the automatic landscape line detection to extract historic vegetable garden wall lines from a LiDAR-derived DEM. The three rapid processes used in this study included the derivation of topographic parameters, line extraction, and aggregation. The rules were extracted from a decision tree to check the line detection from multiple topographic parameters. Results show that wall line detection with multiple topographic parameter images is an alternative means of obtaining essential historic wall feature information. Multiple topographic parameters are highly related to low wall feature identification. Furthermore, the accuracy of wall feature detection is 74% compared with manual interpretation. Thus, this study provides rapid wall detection systems with multiple topographic parameters for further historic landscape management.
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U2 - 10.3390/ijgi6110346
DO - 10.3390/ijgi6110346
M3 - Article
AN - SCOPUS:85044574451
SN - 2220-9964
VL - 6
JO - ISPRS International Journal of Geo-Information
JF - ISPRS International Journal of Geo-Information
IS - 11
M1 - 347
ER -