MONITORING OF GEOSPATIAL DIFFUSION OF AGRICULTURAL TECHNOLOGIES Theoretical background and How do we want to address the topic 

A quick literature review Diffusion of innovations or technologies has become a widely investigated research area in sociology, economics, political science and communication In the field of agriculture, two primary research objectives : (1) To understand the mechanisms that motivate the innovation and diffusion processes (ex-ante assessment) (2) To assess the direct and indirect impacts of innovation’s or technologies’ diffusion on agriculture performance (ex-post assessment) 

(1) To understand the mechanisms that motivate the innovation and diffusion processes (ex-ante assessment) • Rogers (1953) : the « founding father” of Agricultural Innovaton Diffusion Research. An individual- centered approach that lead to a individual-blame bias • Agricultural Innovaton Systems (AIS) : a more comprehensive, systemic and pluralistc approach to innovaton and its diffusion  Understanding how innovation’s or technologies’ adoption spreads over space and time is of good help in this process, to better understand the different factors that may impact this diffusion 

(2) To assess the direct and indirect impacts of innovations’ or technologies’ diffusion on agriculture performance (ex-post impact assessment) - Assessment of the direct impacts of adopton on the incomes of poor farming households, on productvity, etc. - Assessment of the indirect impacts on food prices, economic growth, powerty reducton, food security, and so on (Janvry et al, 2011)  a lot a methodological issues 

What about geography and geospatial science? • Hägerstrand's early and famous work (1953) on innovation diffusion studies the geographical spread of new technologies focusing on the dialectical relationship between space and time. • (Blackman, 1974; Mahajan and Peterson, 1978; Sharif and Ramanathan, 1981) among others have used mathematical (logistic functional form) models to study diffusion processes but have not intended to map this diffusion. Most of these models have a binomial form (adopt or not), and result in a typical S-shaped diffusion curve. • Revisiting Hägestrand and using an agent-based approach, Daudé (2004) proposed the modeling and the simulation of the diffusion of an agricultural innovation. • Audouin (2014) assessed the speeds and patterns of cashew orchards’ spatial diffusion in Burkina Faso and constrasted theses results with innovation system structure and functions. helps better understanding the AIS and relies on point 1).