Empirically Derived Suitability Maps to Downscale Aggregated Land Use Data

Understanding mechanisms that drive present land use patterns is essential in order to derive appropriate models of land use change. When static analyses of land use drivers are performed, they rarely explicitly deal with spatial autocorrelation. Most studies are undertaken on autocorrelation-free data samples. By doing this, a great deal of information that is present in the dataset is lost. This paper presents a spatially explicit, cross-sectional, logistic analysis of land use drivers in Belgium. It is shown that purely regressive logistic models can only identify trends or global relationships between socio-economic or physico-climatic drivers and the precise location of each land use type. However, when the goal of a study is to obtain the best model of land use distribution, a purely autoregressive (or neighbourhood-based) model is appropriate. Moreover, it is also concluded that a neighbourhood based only on the 8 surrounding cells leads to the best logistic regression models at this scale of observation. This statement is valid for each land use type studied – i.e. built-up, forests, cropland and grassland.

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