Tom Veldkamp

Evaluation of the variation in semantic contents of class sets on modelling dynamics of land-use changes

Understanding the scale of interaction and the scale of different environmental and social processes is of paramount importance to define and explain the interaction of human–environment systems. There are three dimensions of scale: space, time and the organisational hierarchy as constructed by the observer. The latter is synonymous with the variation in semantic contents of data expressed as differences in categorisation. This dimension of scale has received little attention. In this article the relationship between the semantic contents of data and modelling dynamics is explored using two land-cover data sets for Romania, one based on the Land-Cover Classification System and the other as used in the EURURALIS study. Three levels of semantic contents of the LCCS data and the single semantic level present in the EURURALIS data are used to establish empirical relations between the land-cover class and its explaining factors. The analysis results show that the variations in semantic contents of data within one data set and between two data sets lead to different sets of spatial determinants for land cover. We did not recognise patterns when establishing the organisational hierarchy. Future policy and decision-making depend to a great extent on which organisational hierarchy is present in the data set used to formulate a policy or to make an informed decision. This would mean that if the same results would be found in other data sets using different models not only multi-scale but also multi-semantic analysis are needed in order to make meaningful predictions of spatially explicit land change.

Modelling potential landscape sediment delivery due to projected soybean expansion: A scenario study of the Balsas sub-basin, Cerrado, Maranhão state, Brazil

In Brazil, agriculture expansion is taking place primarily in the Cerrado ecosystems. With the aim of supporting policy development and protecting the natural environment at relevant hotspots, a scenario study was conducted that concerned not only land-use change, but also the resulting effects on erosion and deposition. This coupled approach helped to evaluate potential landscape impacts of the land-use scenarios. In the study area, the Balsas sub-basin in Maranhão State, a model chain was used to model plausible future soybean expansion locations (CLUE-S model) and resulting sediment mobilization patterns (LAPSUS model) for a business-as-usual scenario. In the scenario, more erosion occurred in areas where the conversion of natural vegetation into soybean cultivation is likely to take place, but the generated sediments tended to accumulate mainly within the conversion areas, thus limiting the offsite effects of the increased erosion. These results indicated that when agricultural expansion is kept away from rivers, Cerrado conversion will have only a limited impact on the sediment loads of local rivers. Where land-use changes are most concentrated are coincident with areas where more new sediments are generated (higher erosion) and where more sediments are re-deposited.

Spatio-temporal dynamics of schistosomiasis in Rwanda between 2001 and 2012: Impact of the national neglected tropical disease control programme

Schistosomiasis is recognised as a major public health problem in Rwanda. We aimed to identify the spatio-temporal dynamics of its distribution at a fine-scale spatial resolution and to explore the impact of control programme interventions. Incidence data of Schistosoma mansoni infection at 367 health facilities were obtained for the period 2001-2012. Disease cluster analyses were conducted using spatial scan statistics and geographic information systems. The impact of control interventions was assessed for three distinct sub-periods. Findings demonstrated persisting, emerging and re-emerging clusters of schistosomiasis infection across space and time. The control programme initially caused an abrupt increase in incidence rates during its implementation phase. However, this was followed by declining and disappearing clusters when the programme was fully in place. The findings presented should contribute to a better understanding of the dynamics of schistosomiasis distribution to be used when implementing future control activities, including prevention and elimination efforts.