A localized contour tree method for deriving geometric and topological properties of complex surface depressions based on high-resolution topographical data

Wu, Qiusheng; Liu, Hongxing; Wang, Shujie; Yu, Bailang; Beck, Richard; Hinkel, Kenneth M.

doi:10.1080/13658816.2015.1038719

Cited by 67 publications

(91 citation statements)

References 37 publications

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“…Previous studies [23,53,58] showed that such contour clusters could be further represented by graph-based localized contour trees. Detailed information about the conceptual framework of the localized contour tree method can be found in [23,53].…”

Section: Graph-based Localized Contour Tree Constructionmentioning

confidence: 99%

“…In this study, we aim to address the drawbacks identified above by employing the graph-based localized contour tree method [53] and bipartite graph-matching theory to reconstruct 3D building models directly from building contours. The proposed method is capable of capturing the topological structure of buildings by using the graph theory-based localized contour tree method, and then reconstructs different parts of buildings from the contours separated by the contour tree.…”

Section: Introductionmentioning

confidence: 99%

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A Graph-Based Approach for 3D Building Model Reconstruction from Airborne LiDAR Point Clouds

et al. 2017

Remote Sensing

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3D building model reconstruction is of great importance for environmental and urban applications. Airborne light detection and ranging (LiDAR) is a very useful data source for acquiring detailed geometric and topological information of building objects. In this study, we employed a graph-based method based on hierarchical structure analysis of building contours derived from LiDAR data to reconstruct urban building models. The proposed approach first uses a graph theory-based localized contour tree method to represent the topological structure of buildings, then separates the buildings into different parts by analyzing their topological relationships, and finally reconstructs the building model by integrating all the individual models established through the bipartite graph matching process. Our approach provides a more complete topological and geometrical description of building contours than existing approaches. We evaluated the proposed method by applying it to the Lujiazui region in Shanghai, China, a complex and large urban scene with various types of buildings. The results revealed that complex buildings could be reconstructed successfully with a mean modeling error of 0.32 m. Our proposed method offers a promising solution for 3D building model reconstruction from airborne LiDAR point clouds.

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Section: Graph-based Localized Contour Tree Constructionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Graph-Based Approach for 3D Building Model Reconstruction from Airborne LiDAR Point Clouds

et al. 2017

Remote Sensing

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“…To identify and delineate the nested hierarchical structure of potential wetland depressions, we utilized the localized contour tree method proposed by Wu et al (2015). The concept of the contour tree was initially proposed to extract key topographic features (e.g., peaks, pits, ravines, and ridges) from contour maps (Kweon and Kanade, 1994).…”

Section: Extraction Of Hierarchical Wetland Depressionsmentioning

confidence: 99%

“…The contour tree is a tree-shaped data structure that can represent the nesting of contour lines on a continuous topographic surface. Wu et al (2015) improved and implemented the contour tree algorithm, making it a locally adaptive version. In other words, the localized contour tree algorithm builds a series of trees rather than a single global contour tree for the entire area.…”

Section: Extraction Of Hierarchical Wetland Depressionsmentioning

confidence: 99%

Delineating wetland catchments and modeling hydrologic connectivity using lidar data and aerial imagery

Lane

2017

Hydrol. Earth Syst. Sci.

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Abstract. In traditional watershed delineation and topographic modeling, surface depressions are generally treated as spurious features and simply removed from a digital elevation model (DEM) to enforce flow continuity of water across the topographic surface to the watershed outlets. In reality, however, many depressions in the DEM are actual wetland landscape features with seasonal to permanent inundation patterning characterized by nested hierarchical structures and dynamic filling-spilling-merging surface-water hydrological processes. Differentiating and appropriately processing such ecohydrologically meaningful features remains a major technical terrain-processing challenge, particularly as highresolution spatial data are increasingly used to support modeling and geographic analysis needs. The objectives of this study were to delineate hierarchical wetland catchments and model their hydrologic connectivity using high-resolution lidar data and aerial imagery. The graph-theory-based contour tree method was used to delineate the hierarchical wetland catchments and characterize their geometric and topological properties. Potential hydrologic connectivity between wetlands and streams were simulated using the least-cost-path algorithm. The resulting flow network delineated potential flow paths connecting wetland depressions to each other or to the river network on scales finer than those available through the National Hydrography Dataset. The results demonstrated that our proposed framework is promising for improving overland flow simulation and hydrologic connectivity analysis.

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“…The nested hierarchical structure of wetland depressions and catchments was identified and quantified using the localized contour tree method (Wu et al 2015). The surface water connectivity between wetlands and streams was characterized using the least-cost path algorithm.…”

Section: Introductionmentioning

confidence: 99%

GIS and Remote Sensing Applications in Wetland Mapping and Monitoring

2017

Preprint

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Wetlands are recognized as one of the world's most valuable natural resources. With the increasing world population, human demands on wetland resources for agricultural expansion and urban development continue to increase. In addition, global climate change has pronounced impacts on wetland ecosystems through alterations in hydrological regimes. To better manage and conserve wetland resources, we need to know the distribution and extent of wetlands and monitor their dynamic changes. Wetland maps and inventories can provide crucial information for wetland conservation, restoration, and management. Geographic Information System (GIS) and remote sensing technologies have proven to be useful for mapping and monitoring wetland resources. Recent advances in geospatial technologies have greatly increased the availability of remotely sensed imagery with better and finer spatial, temporal, and spectral resolution. This chapter presents an introduction to the uses of GIS and remote sensing technologies for wetland mapping and monitoring. A case study is presented to demonstrate the use of high-resolution light detection and ranging (LiDAR) data and aerial photographs for mapping prairie potholes and surface hydrologic flow pathways.

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A localized contour tree method for deriving geometric and topological properties of complex surface depressions based on high-resolution topographical data

Cited by 67 publications

References 37 publications

A Graph-Based Approach for 3D Building Model Reconstruction from Airborne LiDAR Point Clouds

A Graph-Based Approach for 3D Building Model Reconstruction from Airborne LiDAR Point Clouds

Delineating wetland catchments and modeling hydrologic connectivity using lidar data and aerial imagery

GIS and Remote Sensing Applications in Wetland Mapping and Monitoring

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