Toward automatic estimation of urban green volume using airborne LiDAR data and high resolution Remote Sensing images

Huang, Yan; Yu, Bailang; Zhou, Jianhua; Hu, Chunling; Tan, Wei; Hu, Zhiming; Wu, Jianping

doi:10.1007/s11707-012-0339-6

Cited by 77 publications

(50 citation statements)

References 28 publications

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“…Due to differences in viewing geometry and information content, the algorithms and methods designed for ALS data cannot be directly translated for MLS data. In addition, many methods proposed to extract individual trees from ALS data are based on either the original point clouds data directly (e.g., [38][39][40]) or the interpolated Digital Surface Model (or Canopy Height Model) in raster format (e.g., [18,23,24,41]). In contrast, methods for processing MLS data have to directly deal with laser scanning point cloud in order to preserve and extract the faç ade structures under the rooftop or tree canopy.…”

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confidence: 99%

A Voxel-Based Method for Automated Identification and Morphological Parameters Estimation of Individual Street Trees from Mobile Laser Scanning Data

et al. 2013

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Abstract:As an important component of urban vegetation, street trees play an important role in maintenance of environmental quality, aesthetic beauty of urban landscape, and social service for inhabitants. Acquiring accurate and up-to-date inventory information for street trees is required for urban horticultural planning, and municipal urban forest management. This paper presents a new Voxel-based Marked Neighborhood Searching (VMNS) method for efficiently identifying street trees and deriving their morphological parameters from Mobile Laser Scanning (MLS) point cloud data. The VMNS method consists of six technical components: voxelization, calculating values of voxels, searching and marking neighborhoods, extracting potential trees, deriving morphological parameters, and eliminating pole-like objects other than trees. The method is validated and evaluated through two case studies. The evaluation results show that the completeness and correctness of our method for street tree detection are over 98%. The derived morphological parameters, including tree height, crown diameter, diameter at breast height (DBH), and crown base height (CBH), are in a good agreement with the field OPEN ACCESS Remote Sens. 2013, 5 585 measurements. Our method provides an effective tool for extracting various morphological parameters for individual street trees from MLS point cloud data.

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A Voxel-Based Method for Automated Identification and Morphological Parameters Estimation of Individual Street Trees from Mobile Laser Scanning Data

et al. 2013

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“…Isolated trees could be detected with high accuracy, which is likely the main reason for the good overall detection result, and thus indicates the algorithm is suitable for urban applications. Although the validation results in the backyard Krausnickpark has been positive, non-dominant trees in dense stocks and located near rooftops are likely to be overlooked by the local maxima algorithm in several locations of the study transect [12]. These are probably the main reasons for the high underestimations of the reference trees in park groves and backyards and the overall underestimation of 17 trees (93 detected trees − (64 assigned trees + 12 false trees) = 17 trees).…”

Section: Discussionmentioning

confidence: 93%

“…Very high resolution multispectral images such as QuickBird enable a detailed separation of vegetation and non-vegetation, even in dense urban areas, and provide an important information source for further combined analysis with airborne LiDAR [10,[12][13][14]. Using airborne LiDAR data, tree carbon assessments have been successfully completed for an entire tree stock [15], and for single trees by using neighbored pixel information [16].…”

Section: Introductionmentioning

confidence: 99%

“…Some of these approaches have been transferred to urban areas and have been frequently augmented by using additional data sets such as terrestrial laser scanning (TLS) to improve the derivation of dendrometric parameters. The effectiveness of the chosen approach was found to vary depending on the local tree stock conditions, the spatial data resolution, and the algorithms used [12,[29][30][31].…”

Section: Introductionmentioning

confidence: 99%

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Using Airborne LiDAR and QuickBird Data for Modelling Urban Tree Carbon Storage and Its Distribution—A Case Study of Berlin

et al. 2014

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While CO2 emissions of cities are widely discussed, carbon storage in urban vegetation has been rarely empirically analyzed. Remotely sensed data offer considerable benefits for addressing this lack of information. The aim of this paper is to develop and apply an approach that combines airborne LiDAR and QuickBird to assess the carbon stored in urban trees of Berlin, Germany, and to identify differences between urban structure types. For a transect in the city, dendrometric parameters were first derived to estimate individual tree stem diameter and carbon storage with allometric equations. Field survey data were used for validation. Then, the individual tree carbon storage was aggregated at the level of urban structure types and the distribution of carbon storage was analysed. Finally, the results were extrapolated to the entire urban area. High accuracies of the detected tree locations were reached with 65.30% for all trees and 80.1% for dominant trees. The total carbon storage of the study area was 20,964.40 t (σ = 15,550.11 t). Its carbon density equaled 13.70 t/ha. A general center-to-periphery increase in carbon storage was identified along the transect. Our approach methods can be used by scientists and decision-makers to gain an empirical basis for the comparison of carbon storage capacities

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“…It is computed as the difference between the digital surface model (DSM) and the digital elevation model (DEM). In our study, the DSM was generated from the airborne LiDAR point clouds by using the linear triangulated irregular network (TIN) interpolation method [23][24][25][26]. The DEM was then interpolated from the ground points which was classified using a progressive morphological filter [55].…”

Section: Building Contours Generationmentioning

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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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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Toward automatic estimation of urban green volume using airborne LiDAR data and high resolution Remote Sensing images

Cited by 77 publications

References 28 publications

A Voxel-Based Method for Automated Identification and Morphological Parameters Estimation of Individual Street Trees from Mobile Laser Scanning Data

A Voxel-Based Method for Automated Identification and Morphological Parameters Estimation of Individual Street Trees from Mobile Laser Scanning Data

Using Airborne LiDAR and QuickBird Data for Modelling Urban Tree Carbon Storage and Its Distribution—A Case Study of Berlin

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

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