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Cohen, R., Kaion, J., Okello, J. A., Bosire, J. O., Kairo, J. G., Huxham, M., & Mencuccini, M. (2013). Propagating Uncertainty to Estimates of Above-Ground Biomass for Kenyan Mangroves.

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Article

Assessment of Mangrove Spatial -Temporal Dynamics and Biomass by Remotely Sensed Data, Case Study Kilifi County: Kenya

1Department of Geomatic Engineering and Geospatial Information Systems, Jomo Kenyatta University of Science and Technology, Nairobi, Kenya


Journal of Geosciences and Geomatics. 2017, Vol. 5 No. 1, 24-36
DOI: 10.12691/jgg-5-1-3
Copyright © 2017 Science and Education Publishing

Cite this paper:
Anam Safi Ibrahim, Thomas.G. Ngigi. Assessment of Mangrove Spatial -Temporal Dynamics and Biomass by Remotely Sensed Data, Case Study Kilifi County: Kenya. Journal of Geosciences and Geomatics. 2017; 5(1):24-36. doi: 10.12691/jgg-5-1-3.

Correspondence to: Thomas.G.  Ngigi, Department of Geomatic Engineering and Geospatial Information Systems, Jomo Kenyatta University of Science and Technology, Nairobi, Kenya. Email: safy.ibrah@gmail.com,safiaanab@yahoo.com

Abstract

This research uses multi-temporal medium resolution satellite images and ground truthing to analyze the patterns and dynamics of Kenyan coastal mangrove forest cover changes spanning over 30 years from 1990-2015. The major aims of this study were to first analyze and assess mangrove forest cover and change over the period 1990 to 2015 together with the specific drivers. Replacement of cloudy pixels with the best available non-cloud pixels from a secondary image was followed by maximum likelihood classification from which change detection analysis was carried out. Literature reviews and interviews were then used to correlate these land use changes with their potential drivers. Metrics were extracted from the image and correlated with the ground observed biomass values to model the linear relationship between the selected variable and biomass. Independent component transformation 3 was found to show the strongest correlation with biomass with a coefficient of determination value of about 0.7. Based on the post classification change detection, during the epoch 1990-2000, mangrove area decreased by about 7.03%, forestland decreased by about 21.11%, cropland also decreased by about 0.39%. Grassland, however, increased by about 3.54% while settlement increased by a significant 74 percentage points.

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