Investigation of Sentinel 1 derived land subsidence using wavelet tools and triple exponential smoothing algorithm in Lagos, Nigeria
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Date
2021
Authors
Ikuemonisan, F.E
Ozebo, V.C
Olatinsu, O.B
Journal Title
Journal ISSN
Volume Title
Publisher
Springer
Abstract
Lagos has a history of long-term groundwater abstraction that is often compounded by the rising indiscriminate siting of pri vate borehole and water well. This has resulted in various forms of environmental degradation, including land subsidence.
Prediction of the temporal evolution of land subsidence is central to successful land subsidence management. In this study, a
triple exponential smoothing algorithm was applied to predict the future trend of land subsidence in Lagos. Land subsidence
time series was computed with SBAS-InSAR technique with Sentinel-1 acquisitions from 2015 to 2019. Besides, Matlab
wavelet tool was implemented to investigate the periodicity within land displacement signal components and to understand
the relationship between the observed land subsidence, and groundwater level change and that of soil moisture. Results show
that land subsidence in the LOS direction varied approximately between − 94 and 15 mm/year. According to the wavelet based analysis result, land subsidence in Lagos is partly infuenced by both groundwater-level fuctuations and soil moisture
variability. Evaluation of the proposed model indicates good accuracy, with the highest residual of approximately 8%. We
then used the model to predict land subsidence between the years 2020 and 2023. The result showed that by the end of 2023
the maximum subsidence would reach 958 mm, which is approximately a 23% increase
Description
Scholarly articles
Keywords
Wavelet analysis , Landsubsidence , Temporal evolution , Prediction , Research Subject Categories::SOCIAL SCIENCES
Citation
Femi Ikuemonisan,,Vitalis Chidi Ozebo, Olawale Babatunde Olatinsu (2021). Investigation of Sentinel 1 derived land subsidence using wavelet tools and triple exponential smoothing algorithm in Lagos, Nigeria. Environmental Earth Sciences 80:722