XXII ISPRS Congress 2012: Technical Commission VIII

Bibliographic data

Multivolume work

Persistent identifier:: 1663813779

Title:: XXII ISPRS Congress 2012

Sub title:: Melbourne, Australia, 25 August-1 September 2012

Year of publication:: 2013

Place of publication:: Red Hook, NY

Identifier (digital):: 1663813779

Write comment:: Konferenzschrift; Kongress-Thema: Imaging a sustainable future

Reihe:: ISPRS archives

Language:: English

Additional Notes:: Kongress-Thema: Imaging a sustainable future

Publisher of the original:: Curran Associates, Inc.

Document type:: Multivolume work

Collection:: Earth sciences

Volume

Persistent identifier:: 1663822514

Title:: Technical Commission VIII

Scope:: 590 Seiten

Year of publication:: 2014

Place of publication:: Red Hook, NY

Identifier (digital):: 1663822514

Write comment:: Konferenzschrift; Erscheinungsdatum des Originals ist ermittelt.; Literaturangaben

Reihe:: ISPRS archives (volume 39, B8 (2012))

Signature of the source:: ZS 312(39,B8)

Language:: English

Additional Notes:: Erscheinungsdatum des Originals ist ermittelt.; Literaturangaben

Publisher of the original:: Curran Associates, Inc.

Usage licence:: Attribution 4.0 International (CC BY 4.0)

Editor:: Shortis, M.; Shimoda, H.; Cho, K.

Publisher of the digital copy:: Technische Informationsbibliothek Hannover

Place of publication of the digital copy:: Hannover

Year of publication of the original:: 2019

Document type:: Volume

Collection:: Earth sciences

Chapter

Title:: [VIII/9: Oceans]

Document type:: Multivolume work

Structure type:: Chapter

ch should be done on te snow mapping E h Observing System earch was funded by evelopment Plan of 122004), the special )2092411) and State f China (Grant No. nating clear sky from asis document. cloud detection and ical research letters, r's guide. University t. al., 1992. Remote r properties from the C JEEE Transactions |-27. . Radiative processes Scientific Publishing sensing for snow nces Journal, 41(4), ng over the Tibetan Second International Global Changes, Society for Optical EXTRACTION OF BENTHIC COVER INFORMATION FROM VIDEO TOWS AND PHOTOGRAPHS USING OBJECT-BASED IMAGE ANALYSIS M. T. L. Estomata* *, A. C. Blanco 5, K. Nadaoka *, E. C. M. Tomoling * * Environmental Systems Applications of Geomatics Engineering Research Laboratory, Dept. of Geodetic Eng’g, College of Eng'g, University of the Philippines, Diliman, Quezon City, Philippines — *trixia.estomata@gmail.com, edcarla.tomoling@yahoo.com.ph ® Geodetic Engineering Faculty, College of Eng’g, University of the Philippines, Diliman, QC, Phils. — ayeh75@yahoo.com ° Tokyo Institute of Technology, Ookayama, Meguro, Tokyo — nadaoka@mei.titech.ac jp Commission VIII, WG VIII/9 KEY WORDS: Marine, Oceans, Mapping, Bathymetry, Recognition, Object, Camera, Photography ABSTRACT: Mapping benthic cover in deep waters comprises a very small proportion of studies in the field of research. Majority of benthic cover mapping makes use of satellite images and usually, classification is carried out only for shallow waters. To map the seafloor in optically deep waters, underwater videos and photos are needed. Some researchers have applied this method on underwater photos, but made use of different classification methods such as: Neural Networks, and rapid classification via down sampling. In this study, accurate bathymetric data obtained using a multi-beam echo sounder (MBES) was attempted to be used as complementary data with the underwater photographs. Due to the absence of a motion reference unit (MRU), which applies correction to the data gathered by the MBES, accuracy of the said depth data was compromised. Nevertheless, even with the absence of accurate bathymetric data, object-based image analysis (OBIA), which used rule sets based on information such as shape, size, area, relative distance, and spectral information, was still applied. Compared to pixel-based classifications, OBIA was able to classify more specific benthic cover types other than coral and sand, such as rubble and fish. Through the use of rule sets on area, less than or equal to 700 pixels for fish and between 700 to 10,000 pixels for rubble, as well as standard deviation values to distinguish texture, fish and rubble were identified. OBIA produced benthic cover maps that had higher overall accuracy, 93.78+0.85%, as compared to pixel-based methods that had an average accuracy of only 87.30+6.11% (p-value = 0.0001, a = 0.05). 1. INTRODUCTION 1.1 Background of the study Monitoring of coral reefs is the gathering of data and information on ecosystems or on those who use these resources (Hill & Wilkinson, 2004). The general process of monitoring is identifying the population of benthic components in a reef such as rock, rubble, algae and sand, dead or living coral (Kenchington & Hudson, 1984 as cited in Marcos, et al., 2008). Determining the benthic population is greatly dependent on the scale required for assessment (Marcos, et al., 2008). For areas of reef that need a resolution of not less than 25m? the typically-used monitoring methods are multi-spectral satellite imagery and aerial remote sensing (Mumby, et al, 2004). However, such methods require ground-truthing and acquiring such remotely-sensed images would require monetary costs. Also, reef monitoring in many countries cover a small and unrepresentative proportion, such that available data are insufficient for a quantitative assessment [18]. General visual monitoring methods are able to get information from broad to fine scale with the advantage of using inexpensive equipment, but these methods take a lot of time (Hill & Wilkinson, 2004). An alternative for monitoring is the use of digital equipment, which can greatly shorten the time in the field and reduce field expenses, since less time is required underwater as compared to visual methods (Hill & Wilkinson, 2004). The major drawback of using digital equipment is that data processing, such as digitizing, is very time consuming and equipment used are expensive (Hill & Wilkinson, 2004). Also, accurately and automatically mapping live benthic cover has remained extremely difficult to produce from multi-spectral images such as satellite images and aerial photographs, thus alternative methods of producing these maps still need to be investigated (Bour, et al., 1996 as stated in [18]) such as the use object- based image analysis (OBIA). This method initially groups pixels into objects (also called segmentation) based on certain similarities (spectral information or external variable — such as height) (Addink & Coillie, 2010). Rules are then developed in order to automatically classify the image objects produced after segmentation. With the use of OBIA, the tedious task of digitizing and manually classifying benthic cover in the acquired videos and photographs may be eliminated. 1.2 Objectives and significance Objectives. This research aims to develop an improved method of extracting benthic cover through OBIA with the use of underwater videos and photographs with corresponding bathymetric data. Applying the same theory used in a previous research (Levick & Rogers, 2006) to this study, the height component from the bathymetric data will aid in producing a benthic cover map with better accuracy as compared to pixel- based classification methods. The specific objectives of this research are as follows: e To investigate ways of georeferencing and mosaicking snapshots of the underwater videos, as well as means of rectifying the underwater video snapshots to the bathymetric data, given some constraints on data availability and quality; e To develop the OBIA rule sets for accurately and automatically classifying benthic cover; To evaluate the performance of OBIA against commonly used pixel-based image classification algorithms. Significance. Through this automated classification. system, fast and frequent data acquisition of benthic cover such as living and non-living is possible to support reef studies that

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