Object-based benthic habitat mapping in the Florida Keys from hyperspectral imagery

2013 ◽  
Vol 134 ◽  
pp. 88-97 ◽  
Author(s):  
Caiyun Zhang ◽  
Donna Selch ◽  
Zhixiao Xie ◽  
Charles Roberts ◽  
Hannah Cooper ◽  
...  
2017 ◽  
Vol 2 (1) ◽  
pp. 1 ◽  
Author(s):  
Muhammad Hafizt ◽  
Marindah Yulia Iswari ◽  
Bayu Prayudha

<strong>Assessment of Landsat-8 Classification Method for Benthic Habitat Mapping in Padaido Islands, Papua.</strong> Indonesia is the biggest archipelagic country in the world with an area of coral reefs of 39,583 km.This area has to be managed effectively and efficiently utilizing satellite remote sensing technique capable of mapping of benthic habitat coverage, such as coral reefs, seagrasses, macroalgae, and bare substrates. The technique is supported by the availability of Landsat-8 OLI satellite images that have been recording the regions of Indonesia continuously every 16 days. This research was carried out in June 2015 in parts of Padaido Islands, Papua. This area was selected due to high coral reef damages. This study utilized Landsat-8 OLI to compare two classification methods, namely pixel based and object based methods using ‘maximum 2 likelihood’ (ML) and ‘example based feature extraction’ classifications, respectively, after water column correction (Lyzenga method).  The results showed that both methods produced benthic habitat maps with 7 class covers. The pixel-based classification resulted in a better overall accuracy (47.57%) in the mapping of benthic habitats than object-based classification approach (36.17%). Thus, the ML classification is applicable for benthic habitat mapping in Padaido Islands. However, the consistency of this method must be analyzed in many diffrent locations of Indonesian waters.


2015 ◽  
Vol 24 ◽  
pp. 222-227 ◽  
Author(s):  
Nurhalis Wahidin ◽  
Vincentius P. Siregar ◽  
Bisman Nababan ◽  
Indra Jaya ◽  
Sam Wouthuyzen

2018 ◽  
Vol 10 (12) ◽  
pp. 1983 ◽  
Author(s):  
Lukasz Janowski ◽  
Karolina Trzcinska ◽  
Jaroslaw Tegowski ◽  
Aleksandra Kruss ◽  
Maria Rucinska-Zjadacz ◽  
...  

Recently, the rapid development of the seabed mapping industry has allowed researchers to collect hydroacoustic data in shallow, nearshore environments. Progress in marine habitat mapping has also helped to distinguish the seafloor areas of varied acoustic properties. As a result of these new developments, we have collected a multi-frequency, multibeam echosounder dataset from the valuable nearshore environment of the southern Baltic Sea using two frequencies: 150 kHz and 400 kHz. Despite its small size, the Rowy area is characterized by diverse habitat conditions and the presence of red algae, unique on the Polish coast of the Baltic Sea. This study focused on the utilization of multibeam bathymetry and multi-frequency backscatter data to create reliable maps of the seafloor. Our approach consisted of the extraction of 70 secondary features of bathymetric and backscatter data, including statistic and textural attributes of different scales. Based on ground-truth samples, we have identified six habitat classes and selected the most relevant features of the bathymetric and backscatter data. Additionally, five types of image processing pixel-based and object-based classifiers were tested. We also evaluated the performance of algorithms using an accuracy assessment based on the validation subset of the ground-truth samples. Our best results reached 93% overall accuracy and a kappa coefficient of 0.90, confirming that nearshore seabed habitats can be accurately distinguished based on multi-frequency, multibeam echosounder measurements. Our predictive habitat mapping of shallow euphotic zones creates a new scientific perspective and provides relevant data for the management of natural resources. Object-based approaches previously used in various environments and areas suggest that methodology presented in this study may be scalable.


2016 ◽  
Vol 76 ◽  
pp. 200-208 ◽  
Author(s):  
Christopher E. Parrish ◽  
Jennifer A. Dijkstra ◽  
Jarlath P.M. O'Neil-Dunne ◽  
Lindsay McKenna ◽  
Shachak Pe'eri

2021 ◽  
Vol 3 ◽  
pp. 100015
Author(s):  
Benjamin Misiuk ◽  
Myriam Lacharité ◽  
Craig J. Brown

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