Abstract
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.
Highlights
Historic landscape prospecting via remote sensing and computing technologies has considerably advanced in recent years
Many dense point clouds are obtained by using light detection and ranging (LiDAR) scanners
Many dense point clouds are obtained by current airborne LiDAR scanners to derive rasterized digital terrain and surface models
Summary
Historic landscape prospecting via remote sensing and computing technologies has considerably advanced in recent years. The high-resolution DEM offers common information for extracting vital topographic data, which are important in studying various landform processes and landscape patterns. Topographic parameters, such as slope and curvature, based on the high-resolution LiDAR DEM demonstrate obvious correspondence with the expected form of features that people recognize, such as a peak with a mountain, channel with a valley, and ridge and pass [14,15,16,17]. The different characteristics of parameters can provide partial information on morphometric landforms and historic features to allow accurate identification Multiple topographic parameters, such as slope, curvature, and openness, provide the feasibility of distinguishing historic low walls. This detection with multiple parameter approaches was used to improve the overall accuracy of classifying historic anthropogenic features
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