Abstract

Land degradation poses a persistent challenge to ecosystems and sustainable livelihoods in the Nigerian Guinea Savannah (NGS). While both human activity and climate variability have been implicated as degradation drivers, the lack of research fuels dispute over the causes and status of land degradation in the Savannah. Detailed evidence on the contributions of both rainfall and human activities can, however, help identify appropriate measures to address land degradation. MODIS vegetation "greenness" and TAMSAT rainfall data were employed to achieve the following objectives: (i) provide empirical insights on the pattern of savannah vegetation dynamics; (ii) control for rainfall effects in Savannah degradation; and (iii) characterize the extent, severity and geography of human-induced land degradation. The selected statistical techniques proved useful for highlighting the spatio-temporal dynamics of degradation in the NGS. Controlling for the effect of rainfall on vegetation greenness produces a Normalized Difference Vegetation Index (NDVI) residual that allows to us estimate the human impact on land degradation. Despite no indication of a worsening rainfall regime, inter-annual variation in vegetation greenness exhibits a consistently negative, declining trend. This continuous, negative, declining trend in the NDVI residual strongly suggests ongoing biomass loss in the NGS is the result of unsustainable human activity. Observed improvement is attributable to existing land management programmes (afforestation and the planting of drought tolerant species) initiated by states in the zone. In sum, approximately 38% of the NGS land area, including protected areas such as Kainji Lake National Park, are becoming more degraded, while 14% and 48% of the remaining area shows either improvement or no real change, respectively. These results serve as a baseline information resource for tracking future land use activities, land degradation and potential pathways for achieving more sustainable land management.

Keywords

Land degradation; MODIS; NDVI; RESTREND; Savannah; TAMSAT; Nigeria

Published in

Remote Sensing Applications: Society and Environment
2020, Volume: 19, article number: 100360
Publisher: ELSEVIER

SLU Authors

• Ellison, David

  • Department of Forest Resource Management, Swedish University of Agricultural Sciences
    
  • Ellison Consulting
  • University of Bern

UKÄ Subject classification

Forest Science
Remote Sensing


Publication identifier

DOI: https://doi.org/10.1016/j.rsase.2020.100360

Permanent link to this page (URI)

https://res.slu.se/id/publ/123169