NDVI-based vegetation monitoring in Mau forest complex, Kenya

The normalized difference vegetation index (NDVI) measures vegetation health and density using plant reflectance characteristics recorded by satellite imagery. Dekadal NDVI data were obtained for January 1999‐December 2009 from 1-km resolution SPOT-VEGETATION sensor for closed woody vegetation type in four blocks of the Mau forest complex. Vegetation response to yearly seasonal variations was plotted and used to compare deviations by specific years. Subnormal vegetation conditions were recorded by the standardized vegetation index (SVI) and persistently low SVI values indicated a drought season or degraded vegetation. The general linear trend of the vegetation was plotted for the study period to identify trends towards degradation or vegetation recovery. Analysis of variance was used to compare forest blocks and shows spatial vegetation variations and also among years to identify vegetation variations with time. Rainfall data recorded for 2002‐2009 in east Mau were used to confirm rainfall-related vegetation variations block. Results show that NDVI patterns within an year follow cyclic trends with a strong dependence on rainfall seasons. The forest vegetation indicated negligible changes over the study period but effects of extended dry periods in 2000 and 2009 were evident. There were significant differences (P < 0.05) in NDVI between forest blocks. East Mau had significantly inferior vegetation that can be attributed to forest type, level of human degradation prior to the study and the lower rainfall. There were significant variations (P < 0.05) of NDVI among years but the forests showed a natural resilience to disturbance and can retain original vegetation vigour once stress is removed. The study proposes further monitoring of the forests including other vegetation types that are more vulnerable to climatic variations and anthropogenic effects.

[1]  Iucn Forest Conservation Programme,et al.  Kenya's indigenous forests : status, management, and conservation , 1995 .

[2]  H. Beentje,et al.  Kenya trees, shrubs, and lianas , 1994 .

[3]  L. Ji,et al.  Southeastern U.S. Vegetation Response to ENSO Events (1989–1999) , 2003 .

[4]  D. Burnside,et al.  The development of a system for monitoring trend in range condition in the arid shrublands of Western Australia. , 1987 .

[5]  C. Tucker,et al.  Analysis of Sahelian vegetation dynamics using NOAA-AVHRR NDVI data from 1981–2003 , 2005 .

[6]  D. Alder,et al.  Permanent sample plot techniques for mixed tropical forest , 1992 .

[7]  A. Belward,et al.  The Best Index Slope Extraction ( BISE): A method for reducing noise in NDVI time-series , 1992 .

[8]  C. Tucker,et al.  Increased plant growth in the northern high latitudes from 1981 to 1991 , 1997, Nature.

[9]  J. Leonard,et al.  The Vegetation of Africa , 1984 .

[10]  Sharon E. Nicholson,et al.  On the use of NDVI for estimating rainfall fields in the Kalahari of Botswana , 1997 .

[11]  C. Tucker,et al.  Coupled vegetation‐precipitation variability observed from satellite and climate records , 2003 .

[12]  Scott N. Miller,et al.  Assessing land cover change in Kenya's Mau Forest region using remotely sensed data , 2008 .

[13]  J. Raini.  Impact of land use changes on water resources and biodiversity of Lake Nakuru catchment basin, Kenya. , 2009 .

[14]  T. Carlson,et al.  On the relation between NDVI, fractional vegetation cover, and leaf area index , 1997 .

[15]  C. Tucker,et al.  A comparative study of NOAA–AVHRR derived drought indices using change vector analysis , 2006 .

[16]  Joseph Hitimana,et al.  Forest structure characteristics in disturbed and undisturbed sites of Mt. Elgon Moist Lower Montane Forest, western Kenya , 2004 .

[17]  Compton J. Tucker,et al.  From El Niño to La Niña: Vegetation Response Patterns over East and Southern Africa during the 1997-2000 Period. , 2002 .

[18]  T. M. Lillesand,et al.  Remote Sensing and Image Interpretation , 1980 .

[19]  A. Kibe,et al.  The effects of East African low level jet on food security in horn of Africa: A case study of coastal region of Kenya , 2009 .

[20]  G. Poveda,et al.  Seasonally in ENSO‐related precipitation, river discharges, soil moisture, and vegetation index in Colombia , 2001 .