Using earth observation data to inform community management of invasive plants and traditional fishing practices on Lake Nokoué in Benin
Name
IAC Paper - Ufuoma Ovienmhada.pdf
Description
Accepted version
Size
3.56 MB
Format
Adobe PDF
Checksum (MD5)
39b416c1e523ca4b871b21df0ca68166
Author(s)
Ovienmhada, Ufuoma
Fatoyinbo, T
Lagomasino, D
Mouftaou, F
Ashcroft, E
Lombardo, Seamus(Seamus Joseph Holt)
Wood, Danielle
Date Issued
January 2020
Journal
Proceedings of the International Astronautical Congress
Publisher
International Astronautical Federation
Citation
Ovienmhada, Ufuoma et al. "Using earth observation data to inform community management of invasive plants and traditional fishing practices on Lake Nokoué in Benin." Proceedings of the International Astronautical Congress (January 2020): 58835. © 2020 The Authors
Version
Author's final manuscript
Abstract
The research explores an Earth Observation (EO) application with the enterprise Green Keeper Africa (GKA) based in Cotonou, Benin, that addresses the management of an invasive plant species that threatens economic activities such as fishing, transportation and irrigation. GKA pays local community members to harvest the water hyacinth and transform it into a product that absorbs oil-based waste. The EO application is an online observatory and decision support tool that utilizes satellite, aerial and ground data to map the location of the water hyacinth and a fish farming practice known as “acadja” over time, providing valuable information for government, private and public users. The acadja analysis is relevant due to the adverse effects on water quality that the practice results in. This paper is a follow up on the work presented in the 2019 contribution to IAC session B1.5 by the authors. New research in this paper includes (i) improved and validated remote sensing algorithms for monitoring water hyacinth extent, (ii) trend analysis and forecasting of water hyacinth growth with other environmental data sets, (iii) improved and validated remote sensing algorithms for identifying and quantifying acadja and (iv) analysis of water quality parameters describing the coastal ecosystem.
MIT Department
Massachusetts Institute of Technology. Media Laboratory
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
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Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
http://iafastro.directory/iac/paper/id/58835/summary/
