Generation and Dissemination of a National Virtual 3D City and Landscape Model for the Netherlands

Elberink, Sander Oude; Stoter, J.E.; Ledoux, Hugo; Commandeur, T.J.F.

doi:10.14358/pers.79.2.147

Cited by 26 publications

(17 citation statements)

References 8 publications

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“…Airborne light detection and ranging (LiDAR) point clouds and derivatives covering large areas are becoming increasingly available, either as commercial or open datasets, and offer great potential for high-resolution mapping at regional and national scales (e.g., Elberink et al 2013). Aside from obvious benefits associated with high-accuracy digital elevation models (DEMs), these data are valuable in supporting a range of forest map-501 ping objectives (Nelson et al 1984;Nelson 2013).…”

Section: Introductionmentioning

confidence: 99%

Multisensor and Multispectral LiDAR Characterization and Classification of a Forest Environment

Hopkinson

Chasmer

Gynan³

et al. 2016

Canadian Journal of Remote Sensing

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Abstract. Airborne LiDAR is increasingly used in forest carbon, ecosystem, and resource monitoring. For practical design and manufacture reasons, the 1064 nm near-infrared (NIR) wavelength has been the most commonly adopted, and most literature in this field represents sampling characteristics in this wavelength. However, due to eye-safety and application-specific needs, other common wavelengths are 1550 nm and 532 nm. All provide canopy structure reconstructions that can be integrated or compared through space and time but the consistency or complementarity of 3D airborne LiDAR data sampled at multiple wavelengths is poorly understood. Here, we report on multispectral LiDAR missions carried out in 2013 and 2015 over a managed forest research site. The 1st used 3 independent sensors, and the 2nd used a single sensor carrying 3 lasers. The experiment revealed differences in proportions of returns at ground level, vertical foliage distributions, and gap probability across wavelengths. Canopy attenuation was greatest at 532 nm, presumably due to leaf tissue absorption. Relative to 1064 nm, foliage was undersampled at midheight percentiles at 1550 nm and 532 nm. Multisensor data demonstrated differences in foliage characterization due to combined influences of wavelength and acquisition configuration. Single-sensor multispectral data were more stable but demonstrated clear wavelength-dependent variation that could be exploited in intensity-based land cover classification without the aid of 3D derivatives. This work sets the stage for improvements in land surface classification and vertical foliage partitioning through the integration of active spectral and structural laser return information.

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Section: Introductionmentioning

confidence: 99%

Multisensor and Multispectral LiDAR Characterization and Classification of a Forest Environment

Hopkinson

Chasmer

Gynan³

et al. 2016

Canadian Journal of Remote Sensing

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“…We have encountered several instances of enhanced LOD1 block models with differentiated roof tops (Emem and Batuk, 2004;Commandeur, 2012;Oude Elberink et al, 2013;Döllner et al, 2006;Ellul and Altenbuchner, 2013;He et al, 2013;Häfele, 2011;Sanborn, 2014) that include multiple flat surfaces instead of a single surface for the top, to differentiate terraced houses, large roof constructions, etc. Related to extrusion, sizeable parts of buildings (e.g.…”

Section: Lod0 and Lod1 Familiesmentioning

confidence: 99%

An improved LOD specification for 3D building models

Biljecki

Ledoux

Stoter

2016

Computers, Environment and Urban Systems

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331

176

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The level of detail (LOD) concept of the OGC standard CityGML 2.0 is intended to differentiate multi-scale representations of semantic 3D city models. The concept is in practice principally used to indicate the geometric detail of a model, primarily of buildings. Despite the popularity and the general acceptance of this categorisation, we argue in this paper that from a geometric point of view the five LODs are insufficient and that their specification is ambiguous.We solve these shortcomings with a better definition of LODs and their refinement. Hereby we present a refined set of 16 LODs focused on the grade of the exterior geometry of buildings, which provide a stricter specification and allow less modelling freedom. This series is a result of an exhaustive research into currently available 3D city models, production workflows, and capabilities of acquisition techniques. Our specification also includes two hybrid models that reflect common acquisition practices. The new LODs are in line with the LODs of CityGML 2.0, and are intended to supplement, rather than replace the geometric part of the current specification. While in our paper we focus on the geometric aspect of the models, our specification is compatible with different levels of semantic granularity. Furthermore, the improved LODs can be considered format-agnostic.Among other benefits, the refined specification could be useful for companies for a better definition of their product portfolios, and for researchers to specify data requirements when presenting use cases of 3D city models. We support our refined LODs with experiments, proving their uniqueness by showing that each yields a different result in a 3D spatial operation.Keywords: Level of detail; 3D city modelling; 3D GIS; 3D building models; CityGML; Scale Highlights• CityGML LODs are an industry standard for conveying the grade of 3D city models.• The 5 LODs are not defined precisely, and they are not sufficient for this purpose.• We present a refined series of 16 LODs that overcomes these issues.

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“…The automatic 3D city modeling is intensively investigated in the last decades and summarized in (Haala and Kada, 2010). Oude Elberink (Elberink et al, 2013) creates a national-wide general 3D city model by using topographic maps and point clouds, e.g. Top10NL and AHN2 respectively.…”

Section: Study Area and Datamentioning

confidence: 99%

“…Normally, forest only includes low vegetations without the trees as they are very difficult to model and can be various in different seasons. More details of model reconstruction can be found in (Elberink et al, 2013). A LoD2 3D model with buildings,terrain and road classes and the corresponding aerial image for partial city area of Amersfoort are shown in …”

Section: Study Area and Datamentioning

confidence: 99%

Shadowdetection From VHR Aerial Images in Urban Area by Using 3d City Models and a Decision Fusion Approach

Zhou

Gorte

2017

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:In VHR(very high resolution) aerial images, shadows indicating height information are valuable for validating or detecting changes on an existing 3D city model. In the paper, we propose a novel and full automatic approach for shadow detection from VHR images. Instead of automatic thresholding, the supervised machine learning approach is expected with better performance on shadow detection, but it requires to obtain training samples manually. The shadow image reconstructed from an existing 3D city model can provide free training samples with large variety. However, as the 3D model is often not accuracy, incomplete and outdated, a small portion of training samples are mislabeled. The erosion morphology is provided to remove boundary pixels which have high mislabeling possibility from the reconstructed image. Moreover, the quadratic discriminant analysis (QDA) which is resistant to the mislabeling is chosen. Further, two feature domains, RGB and ratio of the hue over the intensity, are analyzed to have complementary effects on better detecting different objects. Finally, a decision fusion approach is proposed to combine the results wisely from preliminary classifications from two feature domains. The fuzzy membership is a confidence measurement and determines the way of making decision, in the meanwhile the memberships are weighted by an entropy measurements to indicate their certainties. The experimental results on two cities in the Netherlands demonstrate that the proposed approach outperforms the two separate classifiers and two stacked-vector fusion approaches.

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Generation and Dissemination of a National Virtual 3D City and Landscape Model for the Netherlands

Abstract: This paper describes the generation and dissemination of a national three-dimensional (3D)

Cited by 26 publications

References 8 publications

Multisensor and Multispectral LiDAR Characterization and Classification of a Forest Environment

Multisensor and Multispectral LiDAR Characterization and Classification of a Forest Environment

An improved LOD specification for 3D building models

Shadowdetection From VHR Aerial Images in Urban Area by Using 3d City Models and a Decision Fusion Approach

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