Abstract:
Soil Organic Carbon (SOC) is the basis of soil fertility by releasing nutrients for plants
growth, promotes the structure, biological and physical health of the soil and is a buffer
against harmful substances. This study focuses to assess the effects of land use and land
cover changes on SOC using satellite imagery (from 1995 to 2018 with 5 years epoch),
Digital Elevation Model and soil data. Landsat 5, 7 and 8 has been used in this study. From
Landsat imagery four indices were extracted to aid in SOC estimation. They included;
vegetation indices; Normalized Differential Vegetation Index (NDVI), soil indices; Bare
Soil Index (BSI) and spectral color indices Coloration Index (CI) and Hue Index (HI).
Supervised classification was carried out to derive the land cover types in the region.
Relationships and trends between the indices and LULCC were derived. HI and NDVI had
a positive correlation coefficient with SOC. NDVI had a high positive correlation with R
of 0.92. SOC is corelated with SOC by the equation y = 0.039x + 0.15. on the other side
the other two indices (BSI and CI) had a strong negative correlation with SOC. BSI is
strongly negatively correlated with SOC with R
2
of a value 0.98. BSI is corelated with SOC
by the equation y = -0.04x + 10.10. The main dominant classes of land cover in this region
were found to be forest, bare land, thickets and bushland and the agricultural land. The
study showed that forest had the highest SOC content with a mean of 14.65 followed by
agricultural land with a mean value of 10.54. Bare land had the lowest value of SOC
recording a mean of 6.87. The results showed a reduction in SOC in the forest land cover.
Different land cover conversion had diverse effects on SOC. Conversion from forest to
built-ups for the purpose of settlements depletes SOC stocks by almost 72%. Conversion
to agriculture land for the purposes of agriculture depletes the SOC by almost 30%. Best
agricultural practices should therefore be adopted. This information is crucial in
agricultural institutions and also the county government of Meru since it can be used to
lead on to the farming practices that need to be practiced and also in the County government
to know areas of concern for the purposes of laws implementation.