Crisis intervention after the Tsunami in Phuket and Khao Lak

After the Tsunami disaster in Southeast Asia, India, Sri Lanka, and Africa, the German government set up a crisis task force that implemented crisis-intervention teams covering Thailand (Phuket and Khao Lak), Sri Lanka, and Sumatra. Two crisis teams were sent to Phuket; the first one on 28 December 2004, and the second one on 3 January 2005, each for an average of 1 week. This intervention was primarily for the benefit of German citizens and their expatriates and relatives caught up in a major catastrophe as well as the German helpers. This article describes the organizational structures of the German crisis intervention, protective factors for the helpers, psychiatric syndromes--often acute traumata, the problems of the identification process for relatives, and crisis intervention itself. Consequences for further crisis intervention after natural disasters are discussed.     

On The Application of Fuzzy Clustering for Crime Hot Spot Detection

   One of the fundamental challenges in crime mapping and analysis is pattern recognition. Efforts and methods to detect crime hot-spots, or geographic areas of elevated criminal activity, are wide ranging. For aggregate data, such as total crime events in a census tract(s), measures of spatial autocorrelation have proven useful. For disaggregate data (i.e. individual crime events), kernel density smoothing and non-hierarchical cluster analysis (e.g. k-means), are widely used. Non-hierarchical techniques are particularly effective in delineating geographic space into areas of higher or lower crime concentrations, because each observation is assigned to one and only one cluster. The resulting set of partitions provides clear-cut spatial boundaries that can be used for hot-spot evaluation and interpretation. However, the strength of non-hierarchical methods can also be viewed as a weakness. Although the hard-clustering of observations into a set of discrete clusters is helpful, there are many cases where ambiguity exists in the data. In such cases, a more generalized approach for hot-spot detection would be helpful. The purpose of this paper is to explore the use of a generalized partitioning method known as fuzzy clustering for hot-spot detection. Functional and visual comparisons of fuzzy clustering and two hard-clustering approaches (medoid and k-means), across a range of cluster values are analyzed. The empirical results suggest that a fuzzy clustering approach is better equipped to handle intermediate cases and spatial outliers.

Small-scale irrigation in sub-Saharan Africa: Sparse lessons,big problems,any solutions?

This paper identifies from studies made of specific schemes the major social and administrative problems confronting the improvement and extension of small-scale irrigation in Africa. The first section reviews the studies and notes the conclusions to be drawn from each separate one. Underlying these separate conclusions six general problems are identified and in the second section of the article each of these six is elaborated and discussed: the relation between the direct producer'S benefit and wider social benefits: problems of control, commitment to hierarchy, the working of production units, and how to learn from farmers in respect of water use; and finally the general problem of how to plan for the further change that follows after irrigation is introduced.