
Aims and Scope
Spatial data appear in most scientific disciplines and are gathered in ever increasing quantities due to advances in communication, sensing, and computational power. Spatial statistics is concerned with statistical analysis of three types of spatial data: observations measured at a fixed set of sites, random point patterns, and random geometrical objects. The first type of data is analysed by means of random field models, while point process models are appropriate for the second type. The last type of data is handled by methods of stochastic geometry. Spatial statisticians are challenged with the need for increasingly complicated mathematical models which a) account for nonstationary variation b) describe complex interactions at different scales, and c) include attributes associated to the points or pixels. For data sets of moderate size, spatial statisticians typically apply a direct statistical modelling of the data, but for huge data sets this is not feasible with existing spatial models due to excessive computing time and a lack of efficient procedures. Harmonic analysis is a branch of mathematical analysis that studies representations of signals as superpositions of elementary signals. A signal such as an image has countless possible representations and the goal is to find a cost effective representation. Cost effective means reducing storage requirements while keeping only 'relevant features' of the data. Such representations are also referred to as sparse representations. A sparse representation enables compression of the signal (e.g. music stored in the mp3format) and can also be used to extract hidden structures of particular interest. Harmonic analysts are challenged with the need for new and more cost effective representation methods, which a) are adapted to capture specific structures such as edges and b) capture complex interaction on different scales, thus allowing sophisticated statistical modelling. The aim of this workshop is to explore the interface between spatial statistics and harmonic analysis with the purpose of developing new methods and algorithms for sparse representation and statistical analysis of spatial data. Topics include (but are not restricted to)
Posters:
Every particant is encouraged to present a poster in the poster sessions taking place each day of the workshop. Excursion:
The excursion on Wednesday June 3 is slightly adventurous: a canoe trip on the gently flowing Lindenborg Å. The trip will take us through beautiful landscape and we will visit the most productive fresh water springs in Northern Europe (Blå Høl and Lille Blåkilde). List of participants in excursion. Registration: Participation is by invitation only. We will cover accomodation and food for all participants. A limited amount of travel funding is available on a first come first serve basis.
Please register for the conference before April 1, 2015, by email to Amra Ibrisevic (amra@math.aau.dk). Please mention in the mail whether you will bring a poster and whether you wish to take part in the excursion. Local Organizing Committee: Morten Nielsen, Rasmus Waagepetersen and Amra Ibrisevic. 

Department of Mathematical Sciences  Aalborg University  Last modified 