Requirements for Uview

To create the requirements for Uview, four available tools were reviewed and considered, along with the findings of the survey in Chapter 3. Evaluation of these four tools was based on availability, ease of installation, usability and if it met the needs highlighted in the first survey. These needs can be classified as:

 usability by colour blind individuals;

 availability of a download for further analysis;

 techniques used;

 data requirements for a visualization of uncertainty to be created;

 type of visualization created measured against the choice of the sample in Chapter 3. The four tools evaluated are R-VIS, UncertWeb, Aguila and UVIS.

R-VIS was specifically developed by Howard & MacEachren (1996) for uncertainty visualization. UncertWeb was a project funded by the European Commission (EC) to create a web client for uncertainty visualization (Gerharz et al. 2012). Aguila is the visualization tool of PCRaster which has been used for uncertainty visualization, particularly by Senaratne et al. (2012). PCRaster is a raster dataset modelling tool that has its basis in the Department of Geography and Environmental Studies, Faculty of Geosciences at Utrecht University; it is open source and available in both Windows and Linux environments (Karssenberg et al. 2010; Pebesma, De Jong & Bierkens 2007). Lastly there is the web based tool Uvis, developed by Alberti (2013) during the course of his research for his master’s thesis.

4.1.1 R-VIS

R-VIS, developed by Howard & MacEachren (1996), is one of the oldest visualization tools available. It was developed in 1995 for a specific use case, as a method to evaluate the uncertainty of a nitrogen level dataset. It used kriging as its method for developing the visualization. It has been cited by 126 researchers, most recently by Sacha et al. (2016) and McKenzie et al. (2015), thus it can be seen as an effective and still relevant tool. The techniques used are well documented in the paper by Howard & MacEachren (1996); they are still mentioned by MacEachren in recent research (MacEachren et al. 2005). It is, however, not available for download and general use, therefore can only be evaluated based on the information from literature by Howard & MacEachren (1996) and MacEachren (2005). Furthermore, no native support for visualization for colour blind people is supported. Thus, it remains a powerful tool to start off with but, due to unavailability, it is mainly theoretical and not a practical tool that can be used by GIS professionals.

4.1.2 UncertWeb

UncertWeb was part of an EC funded project (Gerharz et al. 2012). It has a solid literature basis and a few proposed methods (UncertWeb s.a.). Being a product of an academic conglomerate project on uncertainty, it had a lot of potential to develop into a largely accepted tool, especially in academia. The project had a set amount of time to achieve its goals. In 2013, the year of the project’s planned completion, the project stalled, with a website and the literature still available, but no further indication of progress or any usable tool. A framework developed by the UncertWeb team and described in Bastin el al. (2013) was however published.

4.1.3 Aguila (PCRaster)

Aguila is the primary visualization tool for the PCRaster suite (Karssenberg et al. 2010). PCRaster has been used by Senaratne et al. (2012) for the Aguila tool for uncertainty visualization, but also has many other modelling capabilities; it serves as one of the Faculty of Geosciences at Utrecht University’s raster data processing tools, which they continue to improve. It can read many formats of input data and thus can be used with other modelling and GIS software packages (Karssenberg et al. 2010). Aguila can visualize temporal and spatial data, with the added ability of visualizing uncertainty within the data. Thus, it can be used for data analysis and for data exploration (Pebesma, De Jong & Bierkens 2007).

Aguila is a comprehensive tool with advanced statistical analysis and data provided in graphs, with probability, time and cumulative probability options for its visualization (Pebesma, De Jong & Bierkens 2007). While Aguila may be the most comprehensive tool for visualization of uncertainty, it has a few major flaws. Firstly, the installation of PCRaster, as well as Aguila, is no easy task; it requires advanced knowledge and access to administrator rights to install all the dependencies of the software in the Windows environment. Further, the learning curve to use the tool is very steep. The advanced nature of the statistical analysis, as well as an interface that is not very intuitive, may be partly why Aguila is not considered a very popular solution outside of its development institution. It has been mentioned in research about uncertainty and therefore should be evaluated and investigated here (Kinkeldy 2014; Alberti 2013; Senaratne et al. 2012; Gerharz, Pebesma & Hecking 2010). If PCRaster is already part of the GIS user’s workflow, Aguila can easily be implemented. However, if the user is new to PCRaster or the stand alone Aguila package, the difficulty of installing Aguila, as well as time lost in development of the skills needed to operate it, may not justify the use of it for uncertainty visualization.

4.1.4 UVIS

Alberti’s (2013) work on UVIS was also part of a Master’s research project. UVIS has a good academic basis and uses Type A (statistical analysis of observations) probabilistic methods for visualization. It is also a web based tool. However, whilst the tool is incredibly intuitive and user friendly: 1) the visualization scored only moderately in the Chapter 3 survey of this study; 2) Alberti had to be contacted personally to gain access to the tool; 3) the tool was only available as a product demonstration with pre-set data; and 4) no colour blind setting is available natively. It was therefore not possible to use UVIS with one’s own data.

4.1.5 Requirements for Uview

The aim is for Uview to be an easy to install tool, especially when compared to Aguila. Uview was therefore developed as a QGIS plugin, because: a) QGIS is an open source GIS package based on the cross-platform library Qt, ensuring that it runs on operating systems such as Linux and Mac OS X as well as Windows; and b) QGIS offers a plugin mechanism which enables individual developers to extend functionality of the main program in a modular way (Shekhar & Xiong 2007). A QGIS user can thus simply install Uview from the QGIS repository with a few clicks (independent of the platform) and easily incorporate it into

their workflow, as suggested by Kinkeldey & Schiewe (2014). To evaluate how Uview would compare, it was evaluated against the four tools evaluated above.

Table 4.1 gives an overview of where Uview is positioned compared to the four software packages evaluated in this study. Only Aguila is freely available, with the others (R-VIS, UVIS and UncertWeb) not having any available implementation to test and incorporate into one’s workflow. As Uview will be uploaded to the QGIS repository and be freely accessible for download, it is listed as freely available in this comparison (Table 4.1). Meanwhile, UncertWeb and UVIS were both designed as web applications (WebApps), so theoretically both should have easy access to their functionality as no installation is needed.

Table 4.1 Comparing software

Uview UncertWeb R-VIS Aguila UVIS

Freely available

X X

WebApp X X

Easy to install X N/A N/A X

Easy to use X N/A N/A X

Provides Statistics X X X X X Colour blind support X Advanced statistical analysis X X X

From a perspective of ease of use, only UVIS (albeit at a limited testing opportunity) was the most intuitive. Aguila had the steepest learning curve, whereas the skill level required for Uview is no higher than that of the most basic QGIS plugin. All tools rely on statistical analysis to provide a visualization. Further advanced statistics are provided by UncertWeb (according to its literature), R-VIS and Aguila.

Uview provides: 1) the expected statistics for accuracy assessment of a created continuous raster dataset, such as MAE, RMSE and standard deviation; and 2) an easy to understand extrinsic visualization, which does not modify the input dataset and aids in the geographic communication of uncertainty. Thus Uview can easily be incorporated into the workflow of a producer of spatial data, as it provides an accuracy assessment, as well as a visualization, that can be used to communicate the spatiality of uncertainty in the dataset. It can also be utilised by users of spatial data to test datasets quality before data is used, if reference data is available. In contrast to Aguila, no expert knowledge is needed to use Uview, as it only requires basic inputs from the user.