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Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/10579

Title: Classification of time series NDVI for the assessment of land cover change in Ghana using NOAA/AVHRR data
Authors: Nyamekye, C.
Osei Jnr., E. M.
Oseitutu, A.
Keywords: Principal Component Analysis (PCA)
NDVI
Land cover
Multi-year analysis
Issue Date: Apr-2014
Publisher: Journal of Geomatics
Citation: Journal of Geomatics, Vol 8 No. 1 April 2014
Abstract: Land cover information is a key environmental information for many scientific, resource management and policy purposes as well as for a range of human activities. Land cover information is currently scarce for Ghana, which is undergoing rapid and wide-range changes in vegetation due to climate change, the practice of slash-and-burn or shifting cultivation. Although remote sensing technology has been used for mapping in Ghana for some time now, there have been little attempts to use either unsupervised or supervised classification methods for NOAA/AVHRR images for the whole of Ghana. Therefore a qualitative approach to the use of low resolution NDVI data to produce land cover maps of Ghana and also to evaluate the relative change in land cover from 1982 to 2002 is of essence. The study was carried out by applying principal component analysis and classification of average NDVI values. It showed that the dominant land cover change process was conversion of natural vegetation to savannah and shrub thicket, which occurred at an annual rate of 4% and 6.5% respectively. Most of the land cover change process occurred in the first period (1982-1992).The overall annual rate of change in land cover (1982-1992) was highest for agriculture (3.5%) and lowest for water (1.03%). The results suggest that, yearly phonological behavior as revealed by NDVI data can be used to map general patterns in the spatial distribution of Ghana’s main vegetation formation.
Description: An article published by Journal of Geomatics, Vol 8 No. 1 April 2014
URI: http://hdl.handle.net/123456789/10579
Appears in Collections:College of Engineering

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