Tree mapping using airborne, terrestrial and mobile laser scanning – A case study in a heterogeneous urban forest

Holopainen, Markus; Kankare, Ville; Vastaranta, Mikko; Liang, Xinlian; Lin, Yi; Vaaja, Matti; Yu, Xiaowei; Hyyppä, Juha; Hyyppä, Hannu; Kaartinen, Harri; Kukko, Antero; Tanhuanpää, Topi; Alho, Petteri

doi:10.1016/j.ufug.2013.06.002

Cited by 116 publications

(91 citation statements)

References 30 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Principally, it should be feasible to use the proposed algorithm together with point cloud data obtained with other sensors, such as mobile laser scanners [42,43] or close range photogrammetry [44][45][46][47][48], as long as a comparable point-cloud density is achieved. For point clouds with a lower density, e.g., obtained from airborne laser scanning (ALS), other approaches are required [49][50][51][52][53].…”

Section: Sensormentioning

confidence: 99%

Automatic Assessment of Crown Projection Area on Single Trees and Stand-Level, Based on Three-Dimensional Point Clouds Derived from Terrestrial Laser-Scanning

Ritter

Nothdurft

2018

Forests

View full text Add to dashboard Cite

Abstract:Crown projection area (CPA) is a critical parameter in assessing inter-tree competition and estimating biomass volume. A multi-layer seeded region growing-based approach to the fully automated assessment of CPA based on 3D-point-clouds derived from terrestrial laser scanning (TLS) is presented. Independently repeated manual CPA-measurements in a subset of the stand serve as the reference and enable quantification of the inter-observer bias. Allometric models are used to predict CPA for the whole stand and are compared to the TLS-based estimates on the single tree-and stand-level. It is shown that for single trees, the deviation between CPA measurements derived from TLS data and manual measurements is on par with the deviations between manual measurements by different observers. The inter-observer bias propagates into the allometric models, resulting in a high uncertainty of the derived estimates at tree-level. Comparing the allometric models to the TLS measurements at stand-level reveals the high influence of crown morphology, which only can be taken into account by the TLS measurements and not by the allometric models.

show abstract

Section: Sensormentioning

confidence: 99%

Automatic Assessment of Crown Projection Area on Single Trees and Stand-Level, Based on Three-Dimensional Point Clouds Derived from Terrestrial Laser-Scanning

Ritter

Nothdurft

2018

Forests

View full text Add to dashboard Cite

show abstract

“…IfSAR mapping is a process of generating 3D maps from airborne IfSAR system, see for example [33]. The experience to date is that the coarser the IFSAR spatial resolution is, the more difficult it will be to produce the terrain elevation data [34].…”

Section: Terrain Data Collection and Processing For Flood Modellingmentioning

confidence: 99%

Modeling Flood Disasters: Issues Concerning Data for 2D Numerical Models

2017

View full text Add to dashboard Cite

Abstract. Flood disasters are one of the worst natural disasters and they occur almost daily. Correspondingly, city managers are nowadays increasingly investing in data collection and modelling activities. Typically, flows in pipes and channels have been modelled using a onedimensional (1D) approach. Also, if the flood flows on the ground are confined to streets and curbs, the use of 1D/1D modelling approach (a.k.a. as dual drainage concept) may be a feasible way forward. However, if the flows are two-dimensional with complex interactions taking place through surface/sub-surface links, then the required approach would be the socalled 1D/2D modelling approach. The ever-increasing power of computers is now allowing a 3D fluid dynamics analysis of overflow and manhole structures, and in time these may be coupled with 1D models that may be used in situations where flow characteristics require with higher dimensionality. With the use of 2D models, the importance of terrain data has become a growing issue. The current paper discusses some of the key modelling approaches and makes particular reference to the terrain data processing and collection which can either improve or deteriorate their predictive capability.

show abstract

“…Such applications include 3D map reconstruction for intelligent vehicle navigation and control [1][2][3][4], 3D city modeling [5][6][7], city visualizations [8], road asset inventories [9], railway modeling [10], vegetation detection and urban forest inventories [11][12][13]. As the primary provider of static environment information for the intelligent vehicles, maps constructed through MMSs have even been considered as "virtual sensors" [14] that would enable long-distance autonomous navigation [15].…”

Section: Introductionmentioning

confidence: 99%

Towards High-Definition 3D Urban Mapping: Road Feature-Based Registration of Mobile Mapping Systems and Aerial Imagery

Javanmardi

et al. 2017

Remote Sensing

View full text Add to dashboard Cite

Abstract:Various applications have utilized a mobile mapping system (MMS) as the main 3D urban remote sensing platform. However, the accuracy and precision of the three-dimensional data acquired by an MMS is highly dependent on the performance of the vehicle's self-localization, which is generally performed by high-end global navigation satellite system (GNSS)/inertial measurement unit (IMU) integration. However, GNSS/IMU positioning quality degrades significantly in dense urban areas with high-rise buildings, which block and reflect the satellite signals. Traditional landmark updating methods, which improve MMS accuracy by measuring ground control points (GCPs) and manually identifying those points in the data, are both labor-intensive and time-consuming. In this paper, we propose a novel and comprehensive framework for automatically georeferencing MMS data by capitalizing on road features extracted from high-resolution aerial surveillance data. The proposed framework has three key steps: (1) extracting road features from the MMS and aerial data; (2) obtaining Gaussian mixture models from the extracted aerial road features; and (3) performing registration of the MMS data to the aerial map using a dynamic sliding window and the normal distribution transform (NDT). The accuracy of the proposed framework is verified using field data, demonstrating that it is a reliable solution for high-precision urban mapping.

show abstract

Tree mapping using airborne, terrestrial and mobile laser scanning – A case study in a heterogeneous urban forest

Cited by 116 publications

References 30 publications

Automatic Assessment of Crown Projection Area on Single Trees and Stand-Level, Based on Three-Dimensional Point Clouds Derived from Terrestrial Laser-Scanning

Automatic Assessment of Crown Projection Area on Single Trees and Stand-Level, Based on Three-Dimensional Point Clouds Derived from Terrestrial Laser-Scanning

Modeling Flood Disasters: Issues Concerning Data for 2D Numerical Models

Towards High-Definition 3D Urban Mapping: Road Feature-Based Registration of Mobile Mapping Systems and Aerial Imagery

Contact Info

Product

Resources

About