Monitoring benthic habitats using Lyzenga model features from Landsat multi-temporal images in Google Earth Engine
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ORIGINAL ARTICLE
Monitoring benthic habitats using Lyzenga model features from Landsat multi‑temporal images in Google Earth Engine Ahmed Fuad Ahmed1 · Felix Nzive Mutua1 · Benson Kipkemboi Kenduiywo1,2 Received: 4 June 2020 / Accepted: 1 September 2020 © Springer Nature Switzerland AG 2020
Abstract Benthic habitats have conventionally been monitored through physical site visits by diving. This requires the use of expensive resources and time to achieve the desired results. This study adopts remotely sensed Landsat multi-temporal images to monitor benthic habitats within marine protected areas in Kenya. We adopt the Lyzenga approach to compute depth invariant index features on Google Earth Engine (GEE) API to aid benthic classification. Random Forest (RF) and Support Vector Machines (SVM) machine learning algorithms were used for the supervised classification of benthic habitats based on training classes selected under the guidance of an initial K-means unsupervised classification. RF had a higher overall accuracy of 83.48% compared to SVM at 52.69% as per 2015 reference data. We, therefore, used RF to map benthic habitats between 2003 and 2018. Findings indicate that there are high conversions between corals, seagrass and sand benthic classes. Since environmental and anthropogenic pressures act synergistically in causing changes, an in-depth research would be necessary to assess the vulnerability of benthic habitats to these factors. However, the use of multi-spectral imagery and powerful GEE cloud computing platform can aid monitoring and acquisition of marine data. Keywords Benthic · GEE · Landsat · Random Forest · Depth Invariant Index · Lyzenga
Introduction Benthic refers to anything associated with or occurring at the bottom of a body of water (NOAA 2018). In other words, benthic habitat is the underwater environment where benthos (animals and plants species that live on the surface or in the bottom) thrive and depend on. In most cases, corals, seagrass and mangroves are the main focus as the trinity of environments that sea life is dependent on. The shallow coral reef (depths 0–3 m), seagrass beds and mangroves are the main nursery biotopes for the juveniles of the many fish species (Nagelkerken et al. 2000). This is because of their structural complexity which provides a hiding place against predators (Bell and Westoby 1986). Coastal lagoons are as important despite their small size compared to the ocean, the * Ahmed Fuad Ahmed [email protected] 1
Department of Geomatic Engineering and Geospatial Information Systems, Jomo Kenyatta University of Agriculture and Technology, Nairobi, Kenya
Environmental Science and Policy, University of California, Davis, USA
2
lagoonal influence on the genetic diversity of marine populations (Pérez-Ruzafa et al. 2019). Coral polyps are primarily responsible for building reefs which are considered as the “rainforests of the sea” due to the diversity of life around them. Coral reefs only occupy 0.1% of the area of the ocean but they support 25% of all
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