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

Författare:
  • Göran Djurfeldt
  • Ola Hall
  • Magnus Jirström
  • Maria Archila
  • Björn Holmquist
  • Sultana Nasrin
Publiceringsår: 2018
Språk: Engelska
Sidor: 344-357
Publikation/Tidskrift/Serie: Journal of Land Use Science
Volym: 13
Nummer: 3
Dokumenttyp: Artikel i tidskrift
Förlag: 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.

Keywords

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

Other

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

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