Javascript is not activated in your browser. This website needs javascript activated to work properly.
You are here

Using panel survey and remote sensing data to explain yield gaps for maize in sub-Saharan Africa

  • Göran Djurfeldt
  • Ola Hall
  • Magnus Jirström
  • Maria Archila
  • Björn Holmquist
  • Sultana Nasrin
Publishing year: 2018
Language: English
Pages: 344-357
Publication/Series: Journal of Land Use Science
Volume: 13
Issue: 3
Document type: Journal article
Publisher: Taylor & Francis

Abstract english

The aim of this paper is to combine remote sensing data with geo-coded household survey data in order to measure the impact of different socio-economic and biophysical factors on maize yields. We use multilevel linear regression to model village mean maize yield per year as a function of NDVI, commercialization, pluriactivity and distance to market. We draw on seven years of panel data on African smallholders, drawn from three rounds of data collection over a twelve-year period and 56 villages in six countries combined with a time-series analysis of NDVI data from the MODIS sensor. We show that, although there is much noise in yield forecasts as made with our methodology, socio-economic drivers substantially impact on yields, more, it seems, than do biophysical drivers. To reach more powerful explanations researchers need to incorporate socio-economic parameters in their models.


  • Human Geography
  • smallholders
  • sub-Saharan Africa
  • yield gaps
  • panel data
  • transdisciplinary explanation


  • ISSN: 1747-423X
E-mail: maria_francisca [dot] archila_bustos [at] keg [dot] lu [dot] se


Department of Human Geography


Doctoral student

Centre for Economic Demography


The Department of Human Geography
and the Human Ecology Division

Address: Sölvegatan 10,
223 62 Lund
Phone: 046-222 17 59

Faculty of Social Sciences