Sustainability and change in the institutionalized commute in Belgium: exploring regional differences

This paper examines regional differences in commute-energy performance in Belgium, and explores their relationships with spatial characteristics such as the distribution of population and housing, the metropolitan influence of the Brussels agglomeration, and the compactness of cities and towns. We also investigate contradictions between Belgian state-wide commute policy and regional differences in average commuting distance and mode choice. Against a background of long-term federal measures that traditionally encourage long-distance commuting in Belgium, we find striking discrepancies between the structure and the development of commuting patterns in the three administrative regions of Flanders, Wallonia and Brussels. Residents of Brussels show the most sustainable commuting patterns, due to the metropolitan spatial structure. Residents of Wallonia represent the least sustainable commute. Given the rather weak regional economy of Wallonia compared with Flanders, commuters must frequently seek employment far from their residence. Population changes and consequent developments in the housing market seem to exacerbate this competitive disadvantage, since most growth occurs in relatively remote rural areas that are nevertheless within reach of the main employment centres

Urban Sprawl and Travel Energy Consumption: the Case of the Walloon Region of Belgium

peer reviewedIn the actual context of growing interests in environmental issues, reducing energy consumption in the transport sector, which represents 27% of final energy in the Walloon region of Belgium, appears as an important policy target. Although it is often argued that more compact urban forms would significantly reduce transport energy consumption, urban sprawl is a concern in a large part of the regional territory. Moreover, assessment tools dedicated to transport energy consumption are lacking. In this context, the paper first presents a quantitative method developed to assess the transport system in the Walloon region of Belgium. Statistical data available at the neighbourhood scale and characteristics of cars and public vehicles are used to predict transport needs and assess energy consumption as far as home-to-work and home-to-school travels are concerned. Three index are presented and mapped (the energy performance index, the modal share and the mean distance travelled) to investigate the interdependences between spatial planning, urban sprawl and travel energy consumption in the Walloon region of Belgium. Three complementary scales are used: the “municipality” scale allows to highlight the general structure of the territory whereas the “former municipality” and the “census block” scales (the smallest geographical unit in which data are available in Belgium) highlight more detailed phenomenon. The evolution of the performance index between 1991 and 2001 and the difference in energy performance between home-to-work and home-to-school travels are also presented. Our main findings are presented and highlight that urban planning acts upon travel energy consumption. We show particularly that main cities present low energy consumption. However, a local scale approach is useful to highlight the existence of secondary suburban and rural cores presenting low transport energy consumption. In this respect, distance from home to destination is paramount while the mode of transport used has a lower impact.Suburban Areas Favoring Energy efficiency (SAFE

Relative impacts of climate and landuse changes on future flood damage along River Meuse in Wallonia

Climate change is expected to increase flood hazard across most of Europe, both in terms of peak discharge intensity and frequency. Consequently, managing flood risk will remain an issue of primary importance for decades to come. Flood risk depends on territories’ flood hazard and vulnerability. Beside climate change, land use evolution is thus a key influencing factor on flood risk. The aim of this research is to quantify the relative influence of climate and land use changes on flood damage evolution during the 21st century. The study focuses on River Meuse in Wallonia for a 100-year flood. A scenario-based approach was used to model land use evolution. Nine urbanization scenarios for 2100 were developed: three of them assume a “current tend” land use evolution, characterized by urban sprawl, while six others assume a sustainable spatial planning, leading to an increase in density of residential areas as well as an increase in urban functions diversity. A study commissioned by the EU has estimated a 30 % increase in the 100-year discharge for River Meuse by the year 2100. Inundation modeling was conducted for the present day 100-year flood (HQ100) and for a discharge HQ100 + 30%, using the model Wolf 2D and a 5m grid resolution Digital Elevation Model (Ernst et al. 2009). Based on five different damage curves related to land use categories, the relative damage was deduced from the computed inundation maps. Finally, specific prices were associated to each land use category and allowed assessing absolute damages, which were subsequently aggregated to obtain a damage value for each of the 19 municipalities crossed by River Meuse. Results show that flood damage is estimated to increase by 540 to 630 % between 2009 and 2100, reaching 2.1 to 2.4 billion Euros in 2100. These increases mainly involve municipalities downstream of a point where the floodplain width becomes significantly larger. The city of Liège, which is protected against a 100-year flood in the present situation, would undergo about 450 million Euros damage for a 100-year flood in the 2100, i.e. in-between 21% and 25 % of the whole damage increase. The influence of climate is three to eight times higher than the effect of land use change according to the land use evolution scenarios considered. Nevertheless, these two factors have a comparable influence on seven municipalities. Consequently, although a careful spatial planning would not considerably reduce the overall flood damage at the level of theWalloon part of the Meuse Valley, more sustainable spatial planning could efficiently reduce future flood damage at the level of several most critical municipalities. Reference Ernst, J, Dewals, B, Detrembleur, S, Archambeau, P, Erpicum, S, & Pirotton, M. (2010). Micro-scale flood risk analysis based on detailed 2D hydraulic modelling and high resolution geographic data. Natural Hazards, 55(2), 181-209

Making space for experiential knowledge in climate change adaptation? Insights from municipal planning officers in Bohol, Philippines

Climate change is a global phenomenon that has multiple local effects on people and places. Yet, climate change knowledge often travels uncomfortably across scales and needs constant re-interpretation as it is applied in different spatial contexts. This requires the examination of how scientific and local knowledge about climate change travel across social systems and shape local meanings and adaptive actions on climate change. Using an interpretive social science analysis of environmental change, this study investigates development planning as a key boundary object for handling both kinds of knowledge and explores experiential knowledge of climate change held by planning officers from the coastal landscape of the island province of Bohol, Philippines. Drawing upon face-to-face interviews, mental maps, and planning documents review, main results first characterise three experiential ways of knowing about climate change across spaces of lived experiences and spaces of maps and plans. Then, we show how planners engage with climate change adaptation by combining national, techno-scientific and local, on-the-ground ways of knowing, offering a venue in which experiential knowledge on climate change is used for building planning significance and making more grounded accounts of adaptation moving forward in planning policy and practice

Spatial Optimization Methods for Malaria Risk Mapping in Sub-Saharan African Cities Using Demographic and Health Surveys

Vector-borne diseases, such as malaria, are affected by the rapid urban growth and climate change in sub-Saharan Africa (SSA). In this context, intra-urban malaria risk maps act as a key decision-making tool for targeting malaria control interventions, especially in resource-limited settings. The Demographic and Health Surveys (DHS) provide a consistent malaria data source for mapping malaria risk at the national scale, but their use is limited at the intra-urban scale because survey cluster coordinates are randomly displaced for ethical reasons. In this research, we focus on predicting intra-urban malaria risk in SSA cities-Dakar, Dar es Salaam, Kampala and Ouagadougou-and investigate the use of spatial optimization methods to overcome the effect of DHS spatial displacement. We modeled malaria risk using a random forest regressor and remotely sensed covariates depicting the urban climate, the land cover and the land use, and we tested several spatial optimization approaches. The use of spatial optimization mitigated the effects of DHS spatial displacement on predictive performance. However, this comes at a higher computational cost, and the percentage of variance explained in our models remained low (around 30%-40%), which suggests that these methods cannot entirely overcome the limited quality of epidemiological data. Building on our results, we highlight potential adaptations to the DHS sampling strategy that would make them more reliable for predicting malaria risk at the intra-urban scale

Modelling and mapping the intra-urban spatial distribution of Plasmodium falciparum parasite rate using very-high-resolution satellite derived indicators

BACKGROUND: The rapid and often uncontrolled rural-urban migration in Sub-Saharan Africa is transforming urban landscapes expected to provide shelter for more than 50% of Africa's population by 2030. Consequently, the burden of malaria is increasingly affecting the urban population, while socio-economic inequalities within the urban settings are intensified. Few studies, relying mostly on moderate to high resolution datasets and standard predictive variables such as building and vegetation density, have tackled the topic of modeling intra-urban malaria at the city extent. In this research, we investigate the contribution of very-high-resolution satellite-derived land-use, land-cover and population information for modeling the spatial distribution of urban malaria prevalence across large spatial extents. As case studies, we apply our methods to two Sub-Saharan African cities, Kampala and Dar es Salaam. METHODS: Openly accessible land-cover, land-use, population and OpenStreetMap data were employed to spatially model Plasmodium falciparum parasite rate standardized to the age group 2-10 years (PfPR2-10) in the two cities through the use of a Random Forest (RF) regressor. The RF models integrated physical and socio-economic information to predict PfPR2-10 across the urban landscape. Intra-urban population distribution maps were used to adjust the estimates according to the underlying population. RESULTS: The results suggest that the spatial distribution of PfPR2-10 in both cities is diverse and highly variable across the urban fabric. Dense informal settlements exhibit a positive relationship with PfPR2-10 and hotspots of malaria prevalence were found near suitable vector breeding sites such as wetlands, marshes and riparian vegetation. In both cities, there is a clear separation of higher risk in informal settlements and lower risk in the more affluent neighborhoods. Additionally, areas associated with urban agriculture exhibit higher malaria prevalence values. CONCLUSIONS: The outcome of this research highlights that populations living in informal settlements show higher malaria prevalence compared to those in planned residential neighborhoods. This is due to (i) increased human exposure to vectors, (ii) increased vector density and (iii) a reduced capacity to cope with malaria burden. Since informal settlements are rapidly expanding every year and often house large parts of the urban population, this emphasizes the need for systematic and consistent malaria surveys in such areas. Finally, this study demonstrates the importance of remote sensing as an epidemiological tool for mapping urban malaria variations at large spatial extents, and for promoting evidence-based policy making and control efforts.SCOPUS: ar.jinfo:eu-repo/semantics/publishe

QR-CODE PROJECT : Towards better traceability of field sampling data

Ensuring traceability of field experimental data or laboratory sampling data to conduct reproducible research is a challenge at the present time. Between the time when geolocalized specimens (biotic or abiotic) are taken, and the time the resulting data ends up in analysis published with a study, many manual operations take place and may generate errors. The French LTSER have joined forces at the national level to propose a solution as generic as possible to this problem of monitoring of the samples and the data associated with them. Compared to existing solutions (such as Laboratory Information Management Systems), we target a robust labeling solution adapted to outdoor working conditions, with the management of stocks and movements of samples. We designed and realized a prototype tested from end to end, using an open source software, cheap Zebra printers (mobile or not) and raspberries as devices. This solution provides sufficient flexibility for the wide variety of existing protocols. In strength is the record of all contextual data associated with the samples, which constitute important parameters of the subsequent analyses. At last, not only traceability is guaranteed, but also a gain of time and a rationalization of the storage of samples that will induce a return on investment