Sharing Geoprocessing Workflows with Business Process Model and Notation (BPMN)

Graphical geoprocessing workflows are often built visually on interactive canvases of GIS software. Such workflows cannot be shared among different software, due to structural and semantical differences. This study experiments with a workflow created for ILWIS software and transforms it into a BPMN process model, exploiting XML serialisations of the two workflows. Ultimately, it aims at contributing to interoperability of geoprocessing workflows, through an extended approach serving as a frame around workflow conversion

Using ILWIS Software for teaching Core Operations in Earth Observation

Computational methods in GIS and Earth Observation are an important part of the curricula in Geo - informatics. Apart from the theoretical foundations students need to get acquainted with the practical application of these methods in software. However, many GI software packages are not designed for the purpose of educating principles of GIS and Earth Observation and therefor do not provide the right tools and interfaces for students and novice users to comprehend the coreconcepts. In this paper we describe our effort to build a GI software that does support students in learning through visual workflows and linked views of different representations of raster images such as maps, tables and graphs

Evaluating the MSG satellite Multi-Sensor Precipitation Estimate for extreme rainfall monitoring over northern Tunisia

Knowledge and evaluation of extreme precipitation is important for water resources and flood risk management, soil and land degradation, and other environmental issues. Due to the high potential threat to local infrastructure, such as buildings, roads and power supplies, heavy precipitation can have an important social and economic impact on society. At present, satellite derived precipitation estimates are becoming more readily available. This paper aims to investigate the potential use of the Meteosat Second Generation (MSG) Multi-Sensor Precipitation Estimate (MPE) for extreme rainfall assessment in Tunisia. The MSGMPE data combine microwave rain rate estimations with SEVIRI thermal infrared channel data, using an EUMETSAT production chain in near real time mode. The MPE data can therefore be used in a now-casting mode, and are potentially useful for extreme weather early warning and monitoring. Daily precipitation observed across an in situ gauge network in the north of Tunisia were used during the period 2007–2009 for validation of the MPE extreme event data. As a first test of the MSGMPE product's performance, very light to moderate rainfall classes, occurring between January and October 2007, were evaluated. Extreme rainfall events were then selected, using a threshold criterion for large rainfall depth (>50 mm/day) occurring at least at one ground station. Spatial interpolation methods were applied to generate rainfall maps for the drier summer season (from May to October) and the wet winter season (from November to April). Interpolated gauge rainfall maps were then compared to MSGMPE data available from the EUMETSAT UMARF archive or from the GEONETCast direct dissemination system. The summation of the MPE data at 5 and/or 15 min time intervals over a 24 h period, provided a basis for comparison. The MSGMPE product was not very effective in the detection of very light and light rain events. Better results were obtained for the slightly more moderate and moderate rain event classes in terms of percentage of detected events, correlation coefficient, and ratio bias. The results for extreme events were mixed, with high pixel correlations of R=0.75 achieved for some events, while for other events the correlation between satellite and ground observation was rather weak. MPE data for northern Tunisia seem more reliable during the summer season and for larger event scales. The MSGMPE data have demonstrated to be very informative for early warning purposes, but need to be combined with other near real time data or information to give reliable and quantitative estimates of extreme rainfall

Development of an open-source toolbox for the analysis and visualization of remotely sensed time series

The GEONETCast data-dissemination system delivers free multi-source raw satellite images and processed products to users worldwide; from these data, users can construct long time series to study dynamic phenomena. To explore these dynamics, using an animation with few controls is common practice. But animations easily produce information overload leading to change blindness, a problem that can be addressed in various ways. We present a combination of analytical and visual functionalities to better support visual exploration of animated time series. Analytical pre-processing functions include slicing and tracking of objects of interest. Results of the slicing and the tracking are input to the visualization environment, which is further enriched by tools to make various time, attribute, and area selections and by options to visually enhance selections relative to their surroundings, visualize the path of moving objects, and multiple layers. The resulting toolbox is dedicated to visual exploration and analysis of dynamic phenomena in time series. A case study demonstrates, with a use scenario, how it works. Early exposure of some visualization functions to users has already led to improvements, but more extensive testing will follow after further enrichment of the toolbox. Directions of future research are described

Site selection for waste disposal through spatial multiple criteria decision analysis

This article deals with the application of spatial multiple criteria evaluation (SMCE) concepts and methods to support identification and selection of proper sites for waste disposal. The process makes use of a recently developed SMCE module, integrated into ITC's existing geographic information system called ILWIS. This module supports application of SMCE in planning and decision making processes through several compensatory and non- compensatory approaches, allowing inclusion of the spatial and thematic priority of decision makers. To demonstrate the process, a landfill site selection problem around the town of Chinchina, in Colombia, is used as an example. Based on different objectives, a spatial data set consisting of several map layers, e.g., land use, geological, landslide distribution, etc., is made available and used for modeling the site selection process