|
|
|
|
LEADER |
02317 am a22002413u 4500 |
001 |
131218 |
042 |
|
|
|a dc
|
100 |
1 |
0 |
|a Ovienmhada, Ufuoma
|e author
|
100 |
1 |
0 |
|a Massachusetts Institute of Technology. Media Laboratory
|e contributor
|
100 |
1 |
0 |
|a Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
|e contributor
|
700 |
1 |
0 |
|a Fatoyinbo, T
|e author
|
700 |
1 |
0 |
|a Lagomasino, D
|e author
|
700 |
1 |
0 |
|a Mouftaou, F
|e author
|
700 |
1 |
0 |
|a Ashcroft, E
|e author
|
700 |
1 |
0 |
|a Lombardo, Seamus
|q (Seamus Joseph Holt)
|e author
|
700 |
1 |
0 |
|a Wood, Danielle
|e author
|
245 |
0 |
0 |
|a Using earth observation data to inform community management of invasive plants and traditional fishing practices on Lake Nokoué in Benin
|
260 |
|
|
|b International Astronautical Federation,
|c 2021-08-31T13:38:41Z.
|
856 |
|
|
|z Get fulltext
|u https://hdl.handle.net/1721.1/131218
|
520 |
|
|
|a 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.
|
546 |
|
|
|a en
|
655 |
7 |
|
|a Article
|
773 |
|
|
|t Proceedings of the International Astronautical Congress
|