This paper describes how spatial statistical techniques may be used to analyse weed occurrence in tropical fields. Quadrat counts of weed numbers are available over a series of years, as well as data on explanatory variables, and the aim is to smooth the data and assess spatial and temporal trends. We review a range of models for correlated count data. As an illustration, we consider data on striga infestation of a 60 × 24 m2 millet field in Niger collected from 1985 until 1991, modelled by independent Poisson counts and a prior auto regression term enforcing spatial coherence. The smoothed fields show the presence of a seed bank, the estimated model parameters indicate a decay in the striga numbers over time, as well as a clear correlation with the amount of rainfall in 15 consecutive days following the sowing date. Such results could contribute to precision agriculture as a guide to more cost-effective striga control strategies.
|Number of pages||6|
|Journal||International Journal of Applied Earth Observation and Geoinformation|
|Publication status||Published - 2001|
- Quadrat counts
- Spatial statistics