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Open AccessArticle

Detecting Vegetation Change in Response to Confining Elephants in Forests Using MODIS Time-Series and BFAST

1
School of Science and Engineering, Manchester Metropolitan University, Chester Street, Manchester M1 5GD, UK
2
Chester Zoo, Cedar House, Caughall Road, Upton by Chester, Chester CH2 1LH, UK
3
Kenya Wildlife Service, P.O. Box 40241-00100, Nairobi 00100, Kenya
*
Author to whom correspondence should be addressed.
Remote Sens. 2018, 10(7), 1075; https://doi.org/10.3390/rs10071075
Received: 4 June 2018 / Revised: 3 July 2018 / Accepted: 4 July 2018 / Published: 6 July 2018
(This article belongs to the Special Issue GIS and Remote Sensing advances in Land Change Science)
Afromontane forests are biodiversity hotspots and provide essential ecosystem services. However, they are under pressure as a result of an expanding human population and the impact of climate change. In many instances electric fencing has become a necessary management strategy to protect forest integrity and reduce human-wildlife conflict. The impact of confining hitherto migratory elephant populations within forests remains unknown, and monitoring largely inaccessible areas is challenging. We explore the application of remote sensing to monitor the impact of confinement, employing the Breaks For Additive Season and Trend (BFAST) time-series decomposition method over a 15-year period on Moderate Resolution Imaging Spectroradiometer (MODIS) Enhanced Vegetation Index (EVI) (MOD13Q1) datasets for two Kenyan forests. Results indicated that BFAST was able to identify disturbances from anthropogenic, fire and elephant damage. Sequential monitoring enabled the detection of gradual changes in the forest canopy, with degradation and regeneration being observed in both sites. Annual rates of forest loss in both areas were significantly lower than reported in other studies on Afromontane forests, suggesting that installing fences has reduced land-use conversion from human-related disturbances. Negative changes in EVI were predominantly gradual degradation rather than large-scale, abrupt clearings of the forest. Results presented here demonstrate that BFAST can be used to monitor biotic and abiotic drivers of change in Afromontane forests. View Full-Text
Keywords: time series analysis; BFAST; montane forests; change detection; degradation; MODIS; fencing; elephant time series analysis; BFAST; montane forests; change detection; degradation; MODIS; fencing; elephant
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MDPI and ACS Style

Morrison, J.; Higginbottom, T.P.; Symeonakis, E.; Jones, M.J.; Omengo, F.; Walker, S.L.; Cain, B. Detecting Vegetation Change in Response to Confining Elephants in Forests Using MODIS Time-Series and BFAST. Remote Sens. 2018, 10, 1075.

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