Urban land use land cover mapping in tropical savannah using Landsat-8 derived normalized difference vegetation index (NDVI) threshold

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dc.contributor.authorMohammed, Oludare Idrees
dc.contributor.authorDahir, Muazu Omar
dc.contributor.authorAyo, Babalola
dc.contributor.authorHussein, Adomu Ahmadu
dc.contributor.authorAbdulganiyu, Yusuf
dc.contributor.authorFalilat, O. Lawal
dc.date.accessioned2022-12-14T12:36:00Z
dc.date.available2022-12-14T12:36:00Z
dc.date.issued2022-02
dc.description.abstractGeneration 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.en_US
dc.identifier.citationMohammed 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 – 112en_US
dc.identifier.issn2225-8531
dc.identifier.urihttps://uilspace.unilorin.edu.ng/handle/20.500.12484/8029
dc.publisherUniversity of Cape Town, South Africa.en_US
dc.relation.ispartofseriesVolume 11;No. 1
dc.subjectland useen_US
dc.titleUrban land use land cover mapping in tropical savannah using Landsat-8 derived normalized difference vegetation index (NDVI) thresholden_US
dc.typeArticleen_US

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