Spatiotemporal land use modelling to assess land availability for energy crops - illustrated for Mozambique

Floor Van der Hilst*, Judith A. Verstegen, Derek Karssenberg, André P.C. Faaij

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

23 Citations (Scopus)


A method and tool have been developed to assess future developments in land availability for bioenergy crops in a spatially explicit way, while taking into account both the developments in other land use functions, such as land for food, livestock and material production, and the uncertainties in the key determinant factors of land use change (LUC). This spatiotemporal LUC model is demonstrated with a case study on the developments in the land availability for bioenergy crops in Mozambique in the timeframe 2005-2030. The developments in the main drivers for agricultural land use, demand for food, animal products and materials were assessed, based on the projected developments in population, diet, GDP and self-sufficiency ratio. Two scenarios were developed: a business-as-usual (BAU) scenario and a progressive scenario. Land allocation was based on land use class-specific sets of suitability factors. The LUC dynamics were mapped on a 1 km2 grid level for each individual year up to 2030. In the BAU scenario, 7.7 Mha and in the progressive scenario 16.4 Mha could become available for bioenergy crop production in 2030. Based on the Monte Carlo analysis, a 95% confidence interval of the amount of land available and the spatially explicit probability of available land was found. The bottom-up approach, the number of dynamic land uses, the diverse portfolio of LUC drivers and suitability factors, and the possibility to model uncertainty mean that this model is a step forward in modelling land availability for bioenergy potentials.

Original languageEnglish
Pages (from-to)859-874
Number of pages16
JournalGCB Bioenergy
Issue number6
Publication statusPublished - Nov 2012
Externally publishedYes


  • Bioenergy potentials
  • GIS
  • Land use change
  • Model
  • Mozambique
  • Spatiotemporal uncertainty modelling


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