Generating, Storing, Updating and Disseminating a Countrywide 3d Model

Abstract

Abstract. As in many countries, in The Netherlands governmental organisations are acquiring 3D city models to support their public tasks. However, this is still being done within individual organisation, resulting in differences in 3D city models within one country and sometimes covering the same area: i.e. differences in data structure, height references used, update cycle, data quality, use of the 3D data etc. In addition, often only large governmental organisations can afford investing in 3D city models (and the required knowledge) and not small organisations, like small municipalities. To address this problem, the Dutch Kadaster is collaborating with the 3D Geoinformation research group at TU Delft to generate and disseminate a 3D city model covering the whole of the Netherlands and to do this in a sustainable manner, i.e. with an implementation that ensures periodical updates and that aligns with the 3D city models of other governmental organisations, such as large cities. This article describes the workflow that has been developed and implemented.

Modeling Buildings in CityGML LOD1: Building Parts, Terrain Intersection Curve, and Address Features

“…In addition, the model is extended with building models in LOD0 and LOD1. Prominent results of producing and visualizing country-wide official datasets are shown in the Netherlands [13,14], Sweden [15], and Finland [16], as well as other countries.…”

“…However, this proposal for LOD received high attention from researchers and practitioners. The Dutch Kadaster and the 3D Geoinformation research group at TU Delft produced a 3D city model in LOD1.3 that covered the whole of the Netherlands [13]. This dataset is available officially [18].…”

Open government geospatial data on buildings for planning sustainable and resilient cities

“…Finally, universities leverage their expertise to integrate data, multiplying their instances. For example, in the Netherlands, a research group has conflated multiple government datasets, and released the processed and enriched dataset as open data [27]. Further, being research-driven users of data, they are spearheading new use cases, possibly leading to influencing future data releases and enhancing data requirements.…”

“…Similar initiatives at the regional or global level, for example the ISO standard 19115:2013 "Geographic Information -Metadata" may help improve the current data situation. Leveraging local partners, such as universities or other research organisations, which have demonstrated their interest and expertise [27], is a promising pathway that could be followed by more governments.…”

“…Microsoft's dataset of building footprints in the United States (https: //www.microsoft.com/en-us/maps/building-footprints). Research institutions, universities, and international organisations [21] have also generated highly valuable datasets [15,27], for example, through large-scale remote sens-ing analysis [28].…”