Land Cover Mapping and Change Analysis in Tropical Humid-highlands: Case of Ndakaini Water Reservoir in Central Kenya
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Date
2020
Authors
Kagombe, Joram
Kiama, Stephen M.
Kungu, James B
Journal Title
Journal ISSN
Volume Title
Publisher
International Knowledge Sharing Platform
Abstract
We successfully used optical remote sensing approach to test the skills of post-classification change detection
technique as well as techniques of circumventing the challenges of cloud/cloud-shadow contamination and of
working in a data-scarce environment in tropical humid highlands. The aim was to generate an accurate estimate
of current land cover distribution map and analyze land-cover change around Ndakaini area in Kenya. Landsat
imageries (TM and ETM+
) acquired between 1985 and 2011 and corresponding to the study area was selected.
Employing bands 3 and 4 of respective Landsat images, thresholding techniques, Boolean and masking operations
were implemented in detecting cloud/cloud-shadows and subsequent removal and filling of gaps. In absence of
other historical ancillary data about land cover types, a total of 278 points across the study area were captured from
Google Earth and used to evaluate the accuracy of each of the generated land cover maps. From the results,
cloud/cloud-shadow gaps were reduced immensely (e.g. 90% for the 1985 image and 82% for the 2011 image).
With regard to quality of classification outputs, the respective land cover/land-use maps of 2000, 2005 and 2010
anniversaries had fairly high level of overall accuracy (64%, 79% and 68% respectively) and Kappa statistic (0.47,
0.69 and 0.53 respectively) while classification outputs of 1985 and 1995 yielded slightly lower overall accuracy
(60%) and Kappa statistic (0.42). Post-classification change involving three land cover classes, tea plantation,
forest/woodlot and annual crop fields denoted as others were successfully determined and conclusions based on
trend analysis drawn. The satisfactory results of this study imply the usefulness of post-classification change
detection method in generating information about land cover dynamics in tropical humid highlands especially
when coupled with robust techniques that adequately circumvent the cloud and cloud-shadow problem and scarcity
of ancillary data often common in these areas.
Description
A research article published in Journal of Natural Sciences Research
Keywords
Post-classification change detection, Thresholding and Boolean techniques, Landcover change, Tropical humid-highlands
Citation
Kagombe, J. K., Kiama, S., & Kungu, J. B. (2020). Land cover mapping and change analysis in tropical humid-highlands: Case of Ndakaini water reservoir in Central Kenya.