Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/1338
Title: The use of unmanned aircraft systems and highresolution satellite imagery to monitor tilapia fishcage aquaculture expansion in Lake Victoria, Kenya
Authors: Hamilton, S.
Gallo, S.
Krach, N.
Nyamweya, C.
Okechi, J.
Aura, C.
Ogari, Z.
Roberts, P.
Kaufman, L.
Keywords: Unmanned aircraft systems
Highresolution satellite imagery
Issue Date: 2020
Publisher: Rosenstiel School of Marine & Atmospheric Science of the University of Miami
Citation: Bulletin of Marine Science 96(1):71–93. 2020
Series/Report no.: Bulletin of Marine Science;96(1):71–93.
Abstract: Lake Victoria, the largest lake in the tropics, has a storied history that includes recent shifts in ecology due to a variety of point and nonpoint source anthropogenic impacts. Among the expanding industries contributing to environmental impacts (if not properly managed) is the recent and rapid expansion of cage aquaculture of Nile tilapia (Oreochromis niloticus). As part of an effort to assess the ecological consequences of this new industry, unmanned aerial systems (UAS), very high-resolution satellite imagery, and geographic information systems (GIS) were used to map the tilapia fish cages in the Kenya portion of Lake Victoria, Africa. Understanding the impacts of the growth of commercial finfish cage culture within Lake Victoria requires a systems view which, through the use of UAS and satellite technologies, can provide spatial context and change detection. This synthesis of UAS, very high-resolution satellite imagery, and GIS has allowed for accurate and rapid mapping of inshore tilapia fish cages with high positional accuracy. The significance of these observations lies in the speed and detection accuracy in the methodology, allowing for rapid visualization and assessment of cage culture in the Kenyan portion of Lake Victoria. As of 2012, there were very few floating aquaculture finfish cages in the Kenyan portion of Lake Victoria. Using UAS, satellite, and GIS technologies, in 2018 the same portion of the lake was found to contain 4357 fish cages covering 62,132 m2.
URI: http://hdl.handle.net/123456789/1338
Appears in Collections:Articles

Files in This Item:
File Description SizeFormat 
Unmanned drone_Stu-Aura et al. 2020.pdf3.2 MBAdobe PDFView/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.