Historic Low Wall Detection via Topographic Parameter Images Derived from Fine-Resolution DEM
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 la...
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doaj-0dd69ea6a515406a9c1fa4470f46c95f2020-11-24T23:56:43ZengMDPI AGISPRS International Journal of Geo-Information2220-99642017-11-0161134610.3390/ijgi6110346ijgi6110346Historic Low Wall Detection via Topographic Parameter Images Derived from Fine-Resolution DEMHone-Jay Chu0Min-Lang Huang1Yu-Ching Tain2Mon-Shieh Yang3Bernhard Höfle4Department of Geomatics, National Cheng Kung University, Tainan 701, TaiwanDepartment of Geomatics, National Cheng Kung University, Tainan 701, TaiwanDepartment of Geomatics, National Cheng Kung University, Tainan 701, TaiwanInstitute of Geography, Heidelberg University, Heidelberg 69117, GermanyInstitute of Geography, Heidelberg University, Heidelberg 69117, GermanyCoral 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.https://www.mdpi.com/2220-9964/6/11/346LiDAR-based DEMtopographic parameterswall detectionfeature identification |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Hone-Jay Chu Min-Lang Huang Yu-Ching Tain Mon-Shieh Yang Bernhard Höfle |
spellingShingle |
Hone-Jay Chu Min-Lang Huang Yu-Ching Tain Mon-Shieh Yang Bernhard Höfle Historic Low Wall Detection via Topographic Parameter Images Derived from Fine-Resolution DEM ISPRS International Journal of Geo-Information LiDAR-based DEM topographic parameters wall detection feature identification |
author_facet |
Hone-Jay Chu Min-Lang Huang Yu-Ching Tain Mon-Shieh Yang Bernhard Höfle |
author_sort |
Hone-Jay Chu |
title |
Historic Low Wall Detection via Topographic Parameter Images Derived from Fine-Resolution DEM |
title_short |
Historic Low Wall Detection via Topographic Parameter Images Derived from Fine-Resolution DEM |
title_full |
Historic Low Wall Detection via Topographic Parameter Images Derived from Fine-Resolution DEM |
title_fullStr |
Historic Low Wall Detection via Topographic Parameter Images Derived from Fine-Resolution DEM |
title_full_unstemmed |
Historic Low Wall Detection via Topographic Parameter Images Derived from Fine-Resolution DEM |
title_sort |
historic low wall detection via topographic parameter images derived from fine-resolution dem |
publisher |
MDPI AG |
series |
ISPRS International Journal of Geo-Information |
issn |
2220-9964 |
publishDate |
2017-11-01 |
description |
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. |
topic |
LiDAR-based DEM topographic parameters wall detection feature identification |
url |
https://www.mdpi.com/2220-9964/6/11/346 |
work_keys_str_mv |
AT honejaychu historiclowwalldetectionviatopographicparameterimagesderivedfromfineresolutiondem AT minlanghuang historiclowwalldetectionviatopographicparameterimagesderivedfromfineresolutiondem AT yuchingtain historiclowwalldetectionviatopographicparameterimagesderivedfromfineresolutiondem AT monshiehyang historiclowwalldetectionviatopographicparameterimagesderivedfromfineresolutiondem AT bernhardhofle historiclowwalldetectionviatopographicparameterimagesderivedfromfineresolutiondem |
_version_ |
1725456954856308736 |