Mapping vegetation productivity dynamics and degradation trends over East Africa using a decade of medium Resolution MODIS time-series data

This paper aims to characterize spatial and temporal vegetation productivity trends that could be related to land degradation in East Africa. A decade of AQUA/TERRA-Moderate Resolution Imaging Spectroradiometer (MODIS) satellite observations on vegetation chlorophyll activity, or Normalized Differential Vegetation Index (NDVI) data, and 25-km rainfall data from the TRMM passive radar instrument were used for the same observation period of 2000-2011. Linear trends in land cover based Rain Use Efficiencies (RUE) corrected NDVI and cumulative differences of RUE between consecutive years from 2000 to 2011 (that is amplitudes) were derived and investigated for their robustness. The trend maps were overlaid and classified to map “hot spot” areas of productivity productivity decline. We found vegetation productivity decline areas mostly along the edges of protected areas in Kenya and in the agro-ecological systems in eastern Uganda, whilst the most severely degraded areas were found in southern Ethiopia and eastern Uganda. These severely degraded areas seem to be already under high land use intensities.

[1]  Simon M. Mugatha,et al.  The linkages between land use change, land degradation and biodiversity across East Africa. , 2009 .

[2]  Tobias Landmann,et al.  MODIS-based change vector analysis for assessing wetland dynamics in Southern Africa , 2013 .

[3]  F. van den Bergh,et al.  Limits to detectability of land degradation by trend analysis of vegetation index data , 2012 .

[4]  David Dent,et al.  Recent Land Degradation and Improvement in China , 2009, Ambio.

[5]  N. F. M U S T A,et al.  Comparison of phenology trends by land cover class : a case study in the Great Basin , USA , 2007 .

[6]  John F. Mustard,et al.  Comparison of phenology trends by land cover class: a case study in the Great Basin, USA , 2007 .

[7]  Mannava V. K. Sivakumar,et al.  Climate and Land Degradation , 2007 .

[8]  Benjamin W. Heumann,et al.  AVHRR Derived Phenological Change in the Sahel and Soudan, Africa, 1982 - 2005 , 2007 .

[9]  R. Fensholt,et al.  Evaluation of Earth Observation based global long term vegetation trends — Comparing GIMMS and MODIS global NDVI time series , 2012 .

[10]  Kelly K. Caylor,et al.  Determinants of woody cover in African savannas , 2005, Nature.

[11]  Eric F. Lambin,et al.  Land-cover changes in sub-saharan Africa (1982–1991): Application of a change index based on remotely sensed surface temperature and vegetation indices at a continental scale , 1997 .

[12]  P. Eilers,et al.  Evaluating the effectiveness of smoothing algorithms in the absence of ground reference measurements , 2011 .

[13]  Jonas Ardö,et al.  Exploring the potential of MODIS EVI for modeling gross primary production across African ecosystems , 2011 .

[14]  G. Henebry,et al.  Land surface phenology, climatic variation, and institutional change: Analyzing agricultural land cover change in Kazakhstan , 2004 .

[15]  D. Fuller,et al.  Trends in NDVI time series and their relation to rangeland and crop production in Senegal, 1987-1993 , 1998 .

[16]  Quang Bao Le,et al.  Multi-pronged assessment of land degradation in West Africa to assess the importance of atmospheric fertilization in masking the processes involved , 2012 .

[17]  M. Schaepman,et al.  Proxy global assessment of land degradation , 2008 .

[18]  R. Fensholt,et al.  Evaluation of earth observation based long term vegetation trends - Intercomparing NDVI time series trend analysis consistency of Sahel from AVHRR GIMMS, Terra MODIS and SPOT VGT data , 2009 .