While error propagation in GIS is a topic that has received a lot of attention, it has not been researched with 3D GIS data. We extend error propagation to 3D city models using a Monte Carlo simulation on a use case of annual solar irradiation estimation of building rooftops for assessing the efficiency of installing solar panels. Besides investigating the extension of the theory of error propagation in GIS from 2D to 3D, this paper presents the following contributions. We 1 introduce varying XY/Z accuracy levels of the geometry to reflect actual acquisition outcomes; 2 run experiments on multiple accuracy classes 121 in total; 3 implement an uncertainty engine for simulating acquisition positional errors to procedurally modelled synthetic buildings; 4 perform the uncertainty propagation analysis on multiple levels of detail LODs; and 5 implement Solar3Dcity – a CityGML-compliant software for estimating the solar irradiation of roofs, which we use in our experiments. The results show that in the case of the city of Delft in the Netherlands, a 0.3/0.6 m positional uncertainty yields an error of 68 kWh/m2/year 10% in solar irradiation estimation. Furthermore, the results indicate that the planar and vertical uncertainties have a different influence on the estimations, and that the results are comparable between LODs. In the experiments we use procedural models, implying that analyses are carried out in a controlled environment where results can be validated. Our uncertainty propagation method and the framework are applicable to other 3D GIS operations and/or use cases. We released Solar3Dcity as open-source software to support related research efforts in the future.

Propagation of positional error in 3D GIS: estimation of the solar irradiation of building roofs

This study examines the effects of line simplification on the positional accuracy of linear features. The goal is to quantify the relation between the level of simplification and the degree of positional error, so that users can choose appropriate levels of simplification that will yield results meeting specific accuracy criteria. The study focuses on the Douglas-Peucker line simplification algorithm and examines both natural and anthropogenic features (streams and roads) derived from United States Geological Survey Digital Line Graphs. Results show that error can be modelled at an aggregate level using cumulative frequency curves and their confidence limits. This makes it possible to identify the level of simplification that eliminates the largest number of vertices while still attaining a specific positional accuracy standard. A simple implementation strategy is described in which an optimal level of simplification is identified and simplification is applied selectively for different lines. The study sh...

Quantifying positional error induced by line simplification

This research aims to improve the urban excavation safety by creating an uncertainty-aware, geospatial augmented reality (AR) to visualize and monitor the proximity between invisible utilities and digging implements. Excavation is the single largest cause of utility strikes. Utility strikes could be prevented if the excavator operator were able to “see” buried utilities and excavator movement, and judge the proximity between them in real time. Geospatial augmented reality (AR) is an enabling technology for such knowledge-based excavation. It synergizes the geospatial utility locations and the excavator movement into a real-time, three-dimensional (3D) spatial context accessible to excavator operators. The key to its success is the quality of the utility location data. This paper describes a dynamic approach to incorporate positional uncertainties of buried utilities into an uncertainty-aware, geospatial-AR system for real time visualization and proximity analysis. Uncertainties are modeled as probability bands (e.g. spatial bands with certain probabilities of enclosing the “true” location of utilities). Positional uncertainties are derived in real time by referring to its determinant, data lineage, the genesis and processes used to collect and interpret data. A computational framework, and a generic data model and its XML-format implementation are developed and tested. A method is developed to analyze the proximity in the context of positional uncertainties of both the utilities and the excavator movement. This newly created approach is expected to contribute to the safety in urban excavation via the integration of Geoinformatics and construction informatics into an uncertainty-aware, geospatial-AR, with real time visualization and analytical capabilities.

/pdf/uncertainty-aware-visualization-and-proximity-monitoring-in-3jqyaymobr.pdf

Uncertainty-aware visualization and proximity monitoring in urban excavation: a geospatial augmented reality approach

This paper describes an application of fuzzy set theory to perform temporal interpolation in a raster GIS database. Specific fuzzy membership functions have been derived to simulate spatial changes between consecutive snapshots registered in the database. The proposed approach is tested on a very dynamic rural-urban environment of Montreal Metropolitan area in Quebec, Canada, covering the period from 1956 to 1986 with a temporal resolution of ten years. A user friendly software package named FUZZY_TEMP was developed and integrated in the GRASS4.1 environment in order to perform the implementation of the developed concepts.

A fuzzy set approach for modelling time in GIS

Over the past twenty years a set of methods for home-range estimation and analysis of animal observation data have been developed. Whereas comparisons among the estimation methods and different estimation software are available, only the adahabitat analysis toolbox for R is under a free and open source software license and includes established and new home range estimation approaches, such as Kernel Density Estimation, Brownian Bridges and Local Convex Hulls. However, R and adehabitat are rather catering the needs of the scientific user and not the wildlife manager with respect to its general look & feel, and further, provide only a limited set of functions for the analysis of home ranges with environmental geodata, e.g. land-cover and elevation data. This article presents a free and open-source home range analysis toolbox that (i) focuses on the evaluation of GPS collar data, (ii) aims to be fairly straight forward to use by the wildlife manager, and (iii) integrates with a desktop GIS to allow data analysis beyond the creation of home ranges. Since the developed software is distributed under a free and open source license also research can benefit since implemented algorithms can be directly tested and improved.

OpenJUMP HoRAE - A free GIS and toolbox for home range analysis

Positional accuracy in spatial databases

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Positional accuracy in spatial databases