Analysis of Trends in Vegetation Avhrr-Ndvi Data Across Sokoto State 1982 – 1986 Using Remote Sensing and GIS

  • SA Yelwa
  • AD Isah
Keywords: Vegetation, Changes, Remote Sensing and GIS


The current situation in vegetation productivity across Nigeria and indeed in Sokoto State is being affected by climatic change and other unfavourable environmental conditions. Time-series Remotely Sensed data within Geographic Information System (GIS) environment can be utilized to timely monitor the trajectory in vegetation productivity and dynamics in environmentally unstable areas across the state. In this study, dekadal Normalised Difference Vegetation Index (NDVI) data derived from the National Oceanic Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) Pathfinder (PAL) dataset was utilised in monitoring trends in vegetation NDVI productivity for 5-year growing seasons (July, August and September) within seven selected sites of irrigated and rainfed croplands across Sokoto State from 1982 to 1986. Ground truthing was conducted using Global positional System (GPS) and digital camera to establish typical status of the individual selected sites and evaluated with the IDRISI-ANDES GIS software. Profiles of the monitored sites were plotted using Excel Spreadsheet. Results have shown that shelter belts within the study area have high variability in vegetation NDVI productivity in all the growing season months compared to the irrigated and rain-fed cropland sites. Although studies have shown that NDVI from AVHRR has strong correlations with rainfall and net primary productivity particularly in the arid and semi arid areas, the month of July 1985, August 1985 and September 1984 had shown very low vegetation NDVI productivity in all the sites monitored compared to the productivity of the preceding months. This is likely to be connected to the Elnino Southern Oscillations (ENSO) warm phase (changes in sea surface temperature) which other studies have shown that it affected the world primary net production (NPP). Keywords: Vegetation, Changes, Remote Sensing and GIS

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print ISSN: 0794-5698