Foot-and-mouth disease in Tanzania from 2001 to 2006.

Foot-and-mouth disease (FMD) is endemic in Tanzania, with outbreaks occurring almost each year in different parts of the country. There is now a strong political desire to control animal diseases as part of national poverty alleviation strategies. However, FMD control requires improving the current knowledge on the disease dynamics and factors related to FMD occurrence so control measures can be implemented more efficiently. The objectives of this study were to describe the FMD dynamics in Tanzania from 2001 to 2006 and investigate the spatiotemporal patterns of transmission. Extraction maps, the space-time K-function and space-time permutation models based on scan statistics were calculated for each year to evaluate the spatial distribution, the spatiotemporal interaction and the spatiotemporal clustering of FMD-affected villages. From 2001 to 2006, 878 FMD outbreaks were reported in 605 different villages of 5815 populated places included in the database. The spatial distribution of FMD outbreaks was concentrated along the Tanzania-Kenya, Tanzania-Zambia borders, and the Kagera basin bordering Uganda, Rwanda and Tanzania. The spatiotemporal interaction among FMD-affected villages was statistically significant (P≤0.01) and 12 local spatiotemporal clusters were detected; however, the extent and intensity varied across the study period. Dividing the country in zones according to their epidemiological status will allow improving the control of FMD and delimiting potential FMD-free areas

Russian Real Estate Purchases in Finland, 1990-2016

Foreign real estate ownership has been a frequent topic in the Finnish public discourse in the 2010s. Real estate purchases by Russian citizens have received lots of negative attention. In this thesis, the spatial distribution of real estate bought by Russians was studied. Purchases between January 1990 and August 2016 were mapped and analyzed using Getis-Ord Gi* hot spot analysis. The home addresses of the buyers were also geocoded to find out where the majority of buyers live, and geodetic distances to their properties were calculated. Buildings on these properties were analyzed to examine motives for the purchases

Exploring the Spatial Relative Risk of COVID-19 in Berlin-Neukölln

Identifying areas with high and low infection rates can provide important etiological clues. Usually, areas with high and low infection rates are identified by aggregating epidemiological data into geographical units, such as administrative areas. This assumes that the distribution of population numbers, infection rates, and resulting risks is constant across space. This assumption is, however, often false and is commonly known as the modifiable area unit problem. This article develops a spatial relative risk surface by using kernel density estimation to identify statistically significant areas of high risk by comparing the spatial distribution of address-level COVID-19 cases and the underlying population at risk in Berlin-Neukölln. Our findings show that there are varying areas of statistically significant high and low risk that straddle administrative boundaries. The findings of this exploratory analysis further highlight topics such as, e.g., Why were mostly affluent areas affected during the first wave? What lessons can be learned from areas with low infection rates? How important are built structures as drivers of COVID-19? How large is the effect of the socio-economic situation on COVID-19 infections? We conclude that it is of great importance to provide access to and analyse fine-resolution data to be able to understand the spread of the disease and address tailored health measures in urban settings.Deutsche ForschungsgemeinschaftPeer Reviewe

The role, opportunities and challenges of 3D and geo-ICT in archaeology

Archaeology joins in the trend of three-dimensional (3D) data and geospatial information technology (geo-ICT). Currently, the spatial archaeological data acquired is 3D and mostly used to create realistic visualizations. Geographical information systems (GIS) are used for decades in archaeology. However, the integration of geo-ICT with 3D data still poses some problems. Therefore, this paper clarifies the current role of 3D, and the opportunities and challenges for 3D and geo-ICT in the domain of archaeology. The paper is concluded with a proposal to integrate both trends and tackle the outlined challenges. To provide a clear illustration of the current practices and the advantages and difficulties of 3D and geo-ICT in the specific case of archaeology, a limited case study is presented of two structures in the Altay Mountains

Knowledge discovery from trajectories

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial TechnologiesAs a newly proliferating study area, knowledge discovery from trajectories has attracted more and more researchers from different background. However, there is, until now, no theoretical framework for researchers gaining a systematic view of the researches going on. The complexity of spatial and temporal information along with their combination is producing numerous spatio-temporal patterns. In addition, it is very probable that a pattern may have different definition and mining methodology for researchers from different background, such as Geographic Information Science, Data Mining, Database, and Computational Geometry. How to systematically define these patterns, so that the whole community can make better use of previous research? This paper is trying to tackle with this challenge by three steps. First, the input trajectory data is classified; second, taxonomy of spatio-temporal patterns is developed from data mining point of view; lastly, the spatio-temporal patterns appeared on the previous publications are discussed and put into the theoretical framework. In this way, researchers can easily find needed methodology to mining specific pattern in this framework; also the algorithms needing to be developed can be identified for further research. Under the guidance of this framework, an application to a real data set from Starkey Project is performed. Two questions are answers by applying data mining algorithms. First is where the elks would like to stay in the whole range, and the second is whether there are corridors among these regions of interest