Estimation of forest carbon stock in southwestern Nigeria using moderate resolution imaging spectroradiometer enhanced vegetation index (MODIS EVI)time series.

Cudjoe-Gimba, Joseph (2016)

xix, 130p

Thesis

The study estimated vegetation biomass using moderate resolution spectroradiometer enhanced vegetation index (MODIS EVI) product. It also accessed the changes in the forest areas, identified hot and cold spot areas and investigated the correlation between EVI and the forest types. This was with a view to providing information on the efficacy and reliability of the use of MODIS EVI to monitor report and verify reducing emission from deforestation and degradation (REDD) project. The study took place in the tropical rainforest of the Southwestern Nigeria. Both satellite images and forest inventory data were used for the study. An average of sixteen days at 500 m resolution data, labelled as MODIS/Terra Vegetation Indices 16-Day L3 Global 500 m SIN Grid V005 spanning from 2010 to 2014 in raw format (HDF format), was downloaded. MODIS EVI data was extracted from the MODIS VI product (MOD13A1). Layer stacking was performed on the geo-reference EVI images, which measured the “greenness” signal as a proxy for the amount of vegetation at a location and afterwards masked for the study area. The scene covering the study area was subjected to the supervised classification procedure in order to determine the various vegetation types for carrying out cell statistics to determine the EVI signal which was used to estimate the vegetation biomass. A trend analysis and image differencing was carried out on the EVI time series to determine the changes in forest areas and used to detect hot (negative hot spot) and cold spots (positive hot spot) area. Pearson correlation analysis was also used to determine the correlation between the forest types and EVI. The results of the cell statistics showed that the broadleaf (deciduous and evergreen) forest had the highest green biomass (4256.44 and 4239.15) compared to other landuse/landcover (LULC) types while barren/sparsely vegetated surface had the lowest value (207.72). The trend analysis showed that there was a general decline in vegetation greenness for most of the landuse/landcover (LULC) types during the study period, with 2012 having the lowest greenness. Idanre and Ogbesse Forest reserves were showed more of positive hot spot areas, while Oluwa and Oni Forest Reserves had more of negative hot spot areas. The correlation between EVI and the different forest types indicated that there was a strong relationship meaning the EVI image was able to distinguish between the different types. The strongest relationship occurred between the woody savanna and the savanna EVI values (0.984) which was significant at the 0.01 level. However, mixed forest, open and close shrubland showed very high coefficient of variation indicating that the MODIS EVI was not efficient in detecting vegetation signal from these areas. The study concluded that using MODIS EVI in monitoring, reporting and verification (MRV) of the REDD project was efficient and reliable.

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