GIS Colloquium – Talks (Summer Term 2017)
Asher Yair Grinberger
Mon, April 3, 2.15 pm (Ort: INF 348, Raum 015)
Correctly identifying the contextual units that influence geographic phenomena is a fundamental issue within spatial analysis. As ‘true casually relevant’ activity-related geographic contexts vary at the level of the individual by time, space, and activity, they are prone to errors of misspecification, which affect the validity of results. The uncertainty related to this issue is reduced today when widely available high-resolution mobility data is used to reconstruct individual activity spaces. Yet, as activity is mediated by spatial cognition, knowledge, and preferences, delineating these spaces using only objective spatio-temporal constructs may hamper the effort, i.e. considering spaces based only on physical accessibility and not on their behavioral relevance may constrain the extent to which uncertainty may be reduced. To establish this argument, this presentation would rely on three studies: a field experiment studying changes in activity patterns within a tourist attraction when visitors are exposed to different spatial information and geographical layouts; a model predicting visit probabilities within a road network via the integration of non-Euclidean time-space constructs into models of Probabilistic Time Geography; a procedure formalizing topologies of time-space consumption behaviors represented by movement trajectories as well as delimiting the activity spaces related to them. The first study stresses the need to consider the cognitive-behavioral element when delineating geographical contexts, while the latter two studies constitute the means for this end.
Mon, April 24, 2.15 pm (Ort: INF 348, Raum 015)
The first part of the talk will present the 3D geoinformation research group at the Delft University of Technology and cover current developments in 3D GIS in the Netherlands, such as standardisation of 3D geoinformation and applications. The second part will focus on the PhD research of the presenter. The research comprised several topics around the level of detail (LOD) in 3D city models. For example, it developed a method to benchmark the influence and value of different LODs in different spatial analyses, and the influence of the propagation of positional error. The method is supported by procedurally generated (synthetic) 3D data that may be automatically degraded thus simulating acquisition errors.
From Clouds to Crops: a journey through various data assimilation showcases in environmental science
Dr. Oliver Sus
Tue, May 2, 10.15 am (Ort: INF 348, Raum 015)
Data assimilation, or more generally phrased machine learning, has been gaining popularity in academia and industry in recent years. Today, affordable computing power and the immense availability of accessible data are fueling a data science boom. With the start of the EU's Copernicus programme, highly resolved satellite data will further push this development in the geosciences. Such recently emerging sources of spatial data provide new challenges and opportunities in geographic information technology. In this talk, I will summarize my own research activities in applied data science or assimilation throughout the last 10 years. To quantify the carbon balance of croplands, I have assimilated carbon flux and remotely sensed NDVI data (MODIS) into an ecosystem model. I trained the same model for an improved simulation of plant hydraulics and drought resistance through corroboration with transpiration data, and investigated statistical relationships between variables of forest inventory data. I finally applied an artificial neural network and a variational data assimilation algorithm within a cloud model to retrieve climatologies of cloud parameters from space (AVHRR, MODIS). These attempts are a mixture of success stories and failures, and both of which shall be given attention in this presentation. I will conclude with a brief outlook on the potential of the Copernicus programme to spark research activities and business ideas around the globe.