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Construction of an orthophoto-draped 3D model and classification of intertidal habitats using UAV imagery in the Galapagos Archipelago
De Cock, A.; Vandeputte, R.; Bruneel, S.; De Cock, L.; Liu, X.; Bermúdez, R.; Vanhaeren, N.; De Wit, B.; Ochoa, D.; De Maeyer, P.; Gautama, S.; Goethals, P. (2023). Construction of an orthophoto-draped 3D model and classification of intertidal habitats using UAV imagery in the Galapagos Archipelago. Drones 7(7): 416. https://dx.doi.org/10.3390/drones7070416
In: Drones. MDPI: Basel. e-ISSN 2504-446X, more
Peer reviewed article  

Available in  Authors 

Keyword
    Marine/Coastal
Author keywords
    Uncrewed Aerial Vehicle imagery; categorization; intertidal areas; island system; Ecuador; orthophoto; habitat map

Authors  Top 
  • Liu, X., more
  • Bermúdez, R.
  • Vanhaeren, N., more
  • De Wit, B., more
  • Ochoa, D.
  • De Maeyer, P., more
  • Gautama, S., more
  • Goethals, P., more

Abstract
    Worldwide, an increasing number of marine islands suffer from various pressures on the environment, driven by climate change and increasing land demands. The Galapagos Archipelago is one of the most iconic group of islands, yet population growth and tourism have resulted in a rising need for efficient environmental monitoring of its fragile ecosystems, such as the intertidal zone which harbors diverse and unique fauna. The purpose of this study was to investigate the image classification opportunities for these intertidal habitats using Uncrewed Aerial Vehicle (UAV) imagery. The data for this research were collected in Puerto Ayora on Santa Cruz in August 2017, the most urbanized island of the Galapagos. An orthophoto, a digital elevation model (DEM), and an orthophoto-draped 3D model of the intertidal zone were obtained using image registration software. Based on the orthophoto, an initial classification of the intertidal zone was performed using the spectral angle mapper algorithm. A habitat map with four classes (water, sand, rock, and vegetation) was created with an overall classification accuracy of 77%, indicating the suitability of UAV high resolution aerial imagery for the classification of intertidal habitats. The developed method could be applied to map and monitor other coastal regions and islands systems.

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