Urban land use land cover mapping in tropical savannah using Landsat-8 derived normalized difference vegetation index (NDVI) threshold
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Date
2022-02
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Publisher
University of Cape Town, South Africa.
Abstract
Generation of land use/land cover map at different spatial scales using satellite remote sensing
data has been in practice as far back as early 1970s. Since then, research focus has been on the
development of classification steps and improving the quality of the resulting maps. In recent times,
the demand for detailed high accuracy land-use and land-cover (LULC) data has been on the increase
due to the growing complexity of earth processes, while, at the same time, processing step is becoming
more complex. This paper explores Landsat 8 derived normalized difference vegetation index (NDVI)
threshold for the purpose of simplifying land cover classification process. NDVI images of January,
May and December, 2018, representing dry, wet and harmattan seasons were generated. Thereafter,
NDVI values corresponding to the location of a set of training data representing the target urban
land covers (water, built-up area, soil, grassland and shrub) were extracted. Using the statistics of
the extracted values, NDVI threshold for the respective land cover type were determined for the
classification process. Finally, the classification accuracy was evaluated using the unbiased matrix
coefficient technique which produced overall accuracy of 71.3%, 46.4% and 75.6% at 95%
confidence limit for the months of January, May and December of the year review respectively. The
result has shown that NDVI threshold is a simple and practical alternative to obtain LULC map at a
reasonable time with a few data.
Description
Keywords
land use
Citation
Mohammed O. Idrees, Dahir M. Omar, Ayo Babalola, Hussein A. Ahmadu, Abdulganiyu Yusuf, and Falilat O. lawal (2022). Urban land use land cover mapping in tropical savannah using Landsat 8 derived Normalized Difference Vegetation Index (NDVI) threshold. South African Journal of Geoinformatics, Vol. 11, No. 1., pp. 100 – 112