Using the Fuzzy Majority Approach for GIS-based Multicriteria Group Decision-making

Computers & Geosciences, Volume 36, Issue 3, March 2010, pages 302-312

Soheil Boroushaki and Jacek Malczewski

“This paper is concerned with developing a framework for GIS-based multicriteria group decision-making using the fuzzy majority approach. The procedure for solving a spatial group decision-making problem involves two stages. First, each decision-maker solves the problem individually. Second, the individual solutions are aggregated to obtain a group solution. The first stage is operationalized by a linguistic quantifier-guided ordered weighted averaging (OWA) procedure to create individual decision-maker’s solution maps. Then the individual maps are combined using the fuzzy majority procedure to generate the group solution map which synthesizes the majority of the decision-makers’ preferences. The paper provides an illustrative example of the fuzzy majority method for a land suitability problem. It also demonstrates the implementation of the framework within the ArcGIS environment.”

Individual-based Modelling of Fish Population Dynamics in the River Downstream under Flow Regulation

Ecological Informatics, In Press, Corrected Proof, Available online 27 January 2010

Qiuwen Chen, Rui Han, Shen Qu, Zhongni Cheng

“Due to the operations of hydraulic structures, the flow regimes in downstream are dramatically altered, causing serious impacts on the aquatic ecosystem. To investigate the effects on the fish population dynamics, this study developed a model that integrated a two-dimensional water quality module with an individual-based fish module. Through field surveys and laboratory flume experiments, the preference curves of the studied fishes to the flow conditions were defined. Compared to the previous version of the model, the main improvements consist in the features of population grouping and escaping, space competition, and different adaptabilities to environment changes. The developed model was applied to a compound channel of the Lijiang River in the southwest China, where the flow has been largely modified by the upstream Qingshitan Reservoir. Two dominant species that are grass carp (Ctenopharyngodon idellus) and crucian carp (Carassius auratus) were modelled. The model was validated by the historical fish survey data and the field observations conducted during the study. The scenario analysis showed that, if only the flow aspect was concerned, the flow regulations had positive effects on the non-migrating fish grass carp, but had little impact on crucian carp. In particular, the present operation scheme from early April to end of May should be improved. The methodologies developed in the research can provide support to optimize reservoir operation schemes and improve river management.”

Environmental Risk Mapping of canine leishmaniasis in France

Parasites & Vectors, 2010, 3:31doi:10.1186/1756-3305-3-31

Lise Chamaille, Annelise Tran, Anne Meunier, Gilles Bourdoiseau, Paul Ready, and Jean-Pierre Dedet

Background: Canine leishmaniasis (CanL) is a zoonotic disease caused by Leishmania infantum, a Trypanosomatid protozoan transmitted by phlebotomine sandflies. Leishmaniasis is endemic in southern France, but the influences of environmental and climatic factors on its maintenance and emergence remain poorly understood. From a retrospective database, including all the studies reporting prevalence or incidence of CanL in France between 1965 and 2007, we performed a spatial analysis in order to i) map the reported cases in France, and ii) produce an environment-based map of the areas at risk for CanL. We performed a Principal Component Analysis (PCA) followed by a Hierarchical Ascendant Classification (HAC) to assess if the locations of CanL could be grouped according to environmental variables related to climate, forest cover, and human and dog densities. For each group, the potential distribution of CanL in France was mapped using a species niche modelling approach (Maxent model).

Results: Results revealed the existence of two spatial groups of CanL cases. The first group is located in the Cevennes region (southern Massif Central), at altitudes of 200-1000 m above sea level, characterized by relatively low winter temperatures (1.9degrees C average), 1042 mm average annual rainfall and much forest cover. The second group is located on the Mediterranean coastal plain, characterized by higher temperatures, lower rainfall and less forest cover. These two groups may correspond to the environments favoured by the two sandfly vectors in France, Phlebotomus ariasi and Phlebotomus perniciosus respectively. Our niche modelling of these two eco-epidemiological patterns was based on environmental variables and led to the first risk map for CanL in France.

Conclusion: Results show how an ecological approach can help to improve our understanding of the spatial distribution of CanL in France.”

Spatio-temporal Analysis and Modeling of Short-term Wind Power Forecast Errors

Wind Energy, Published Online 12 Apr 2010

Julija Tastu, Pierre Pinson, Ewelina Kotwa, Henrik Madsen, and Henrik Aa. Nielsen

“Forecasts of wind power production are increasingly being used in various management tasks. So far, such forecasts and related uncertainty information have usually been generated individually for a given site of interest (either a wind farm or a group of wind farms), without properly accounting for the spatio-temporal dependencies observed in the wind generation field. However, it is intuitively expected that, owing to the inertia of meteorological forecasting systems, a forecast error made at a given point in space and time will be related to forecast errors at other points in space in the following period. The existence of such underlying correlation patterns is demonstrated and analyzed in this paper, considering the case-study of western Denmark. The effects of prevailing wind speed and direction on autocorrelation and cross-correlation patterns are thoroughly described. For a flat terrain region of small size like western Denmark, significant correlation between the various zones is observed for time delays up to 5 h. Wind direction is shown to play a crucial role, while the effect of wind speed is more complex. Nonlinear models permitting capture of the interdependence structure of wind power forecast errors are proposed, and their ability to mimic this structure is discussed. The best performing model is shown to explain 54% of the variations of the forecast errors observed for the individual forecasts used today. Even though focus is on 1-h-ahead forecast errors and on western Denmark only, the methodology proposed may be similarly tested on the cases of further look-ahead times, larger areas, or more complex topographies. Such generalization may not be straightforward. While the results presented here comprise a first step only, the revealed error propagation principles may be seen as a basis for future related work.”

Geospatial Analysis of HIV-related Social Stigma: A Study of Tested Females across Mandals of Andhra Pradesh in India

International Journal of Health Geographics, 2010, 9:18

Rashmi Kandwal,Ellen-Wien Augustijn, Alfred Stein, Gianluca Miscione, Pradeep Garg, and Rahul Garg

Background: In Geographical Information Systems issues of scale are of an increasing interest in storing health data and using these in policy support. National and international policies on treating HIV (Human Immunodeficiency Virus) positive women in India are based on case counts at Voluntary Counseling and Testing Centers (VCTCs). In this study, carried out in the Indian state of Andhra Pradesh, these centers are located in subdistricts called mandals, serving for both registration and health facility policies. This study hypothesizes that people may move to a mandal different than their place of residence for being tested for reasons of stigma. Counts of a single mandal therefore may include cases from inside and outside a mandal. HIV counts were analyzed on the presence of outside cases and the most likely explanations for movement. Counts of women being tested on a practitioners’ referral (REFs) and those directly walking-in at testing centers (DWs) were compared and with counts of pregnant women.

Results: At the mandal level incidence among REFs is on the average higher than among DWs. For both groups incidence is higher in the South-Eastern coastal zones, being an area with a dense highway network and active port business. A pattern on the incidence maps was statistically confirmed by a cluster analysis. A spatial regression analysis to explain the differences in incidence among pregnant women and REFs shows a negative relation with the number of facilities and a positive relation with the number of roads in a mandal. Differences in incidence among pregnant women and DWs are explained by the same variables, and by a negative relation with the number of neighboring mandals. Based on the assumption that pregnant women are tested in their home mandal, this provides a clear indication that women move for testing as well as clues for explanations why.

Conclusions: The spatial analysis shows that women in India move towards a different mandal for getting tested on HIV. Given the scale of study and different types of movements involved, it is difficult to say where they move to and what the precise effect is on HIV registration. Better recording the addresses of tested women may help to relate HIV incidence to population present within a mandal. This in turn may lead to a better incidence count and therefore add to more reliable policy making, e.g. for locating or expanding health facilities.”

Topographic Impacts on Wheat Yields under Climate Change: Two Contrasted Case Studies in Europe

Theoretical & Applied Climatology, Volume 99, Numbers 1-2 / January, 2010

R. M. Ferrara , P. Trevisiol , M. Acutis , G. Rana , G. M. Richter, and N. Baggaley

“The topography of hilly landscapes modifies crop environment changing the fluxes of water and energy, increasing risk in these vulnerable agriculture systems, which could become more accentuated under climate change (drought, increased variability of rainfall). In order to quantify how wheat production in hilly terrain will be affected by future climate, a newly developed and calibrated micro-meteorological model for hilly terrain was linked to a crop growth simulation model to analyse impact scenarios for different European regions. Distributions of yield and growing length of rainfed winter wheat and durum wheat were generated as probabilistic indices from baseline and low (B2) and high (A2) emission climate scenarios provided from the Hadley Centre Regional Climate Model (HadRM3). We used site-specific terrain parameters for two sample catchments in Europe, ranging from humid temperate (southeast UK) to semi-arid Mediterranean (southern Italy). Results for baseline scenario show that UK winter wheat is mainly affected by annual differences in precipitation and yield distributions do not change with terrain, whilst in the southern Mediterranean climate yield variability is significantly related to a slope × elevation index. For future climate, our simulations confirm earlier predictions of yield increase in the UK, even under the high emission scenario. In the southern Mediterranean, yield reduction is significantly related to slope × elevation index increasing crop failure in drier elevated spots but not in wet years under baseline weather. In scenarios for the future, the likelihood of crop failure rises sharply to more than 60%, and even in wet years, yields are likely to decrease in elevated spots.”