System wizualizacji łąk podwodnych i profili wgłębnych w kontekście geograficznym na podstawie akustycznych danych pomiarowych
Zleceniodawca:Instytut Oceanologii PAN, Sopot, Pracownia Akustyki Morza Koordynator: dr Z. Łubniewski, mgr A. Partyka Wstępna specyfikacja zadania projektowego: Opracowanie systemu do mapowania akustycznych danych pomiarowych (na temat roślinności podwodnej oraz dna morskiego) w kontekście geograficznym, z możliwością mozaikowania danych z sąsiednich obszarów i łączenia danych akustycznych z kartograficznymi oraz tworzenia gotowych map w formie widoków 2D i 3D
MAIN MOTIVATION:
to study the possibility of underwater meadow detection, biomass estimation species identification
in the Puck Bay (southern Baltic Sea) using hydroacoustic techniques
underwater meadows
HYDROACOUSTIC TECHNIQUES
echosounder
scattered sound
information on target
data collection
data processing
to detect and track the bottom
to detect and to characterize the vegetation
acoustical data:
1. Biosonics dual beam echosounder frequency: 208 kHz,
2. EdgeTech Side Scan Sonar DF-1000 frequency 100 and 500 kHz
precise position data :
DGPS TRIMBLE SE4000 frequency: 1 kHz,
horizontal accuracy: 0.3 – 1 m
biological data:
diver observation and sampling
underwater video recording
APPROACH
DATA ACQUISITION
PROCESSING THE POSITION – REFERENCED HYDROACOUSTICAL DATA
Site conditions
studied area - 500 m x 500 m size, northern part of the outer Puck Bay
bottom conditions - sand bottom
bathymetry - a very slight variability, mean depth about 2 m
patchy vegetation spatial distribution
dominant species – Zostera Marina, Zanichellia sp. and Potamogeton sp.
APPROACH
DIFFICULTIESCOMPLICATED BACKSCATTERING MECHANISM:
3.
“acoustically hard” sessile organisms
brown filamentous algae (Pilayella sp.) (eutrophication)
1.
2.
BUBBLES
UNDERWATER MEADOW DETECTION
THE DETECTION TECHNIQUE WAS DEVELOPED
SPECIES IDENTIFICATION
THE DATA WERE COLLECTED AND SOME PROCESSING
ALGORYTHMS WERE DEVELOPED
BIOMASS ESTIMATION
THE DATA WERE COLLECTED
RESULTS(down looking echosounder)
2. „Parametric” method
UNDERWATER MEADOWS DETECTION. METHODS
1. „Bottom tracking” method
3. Neural Net-based recognition method
RESULTS(down looking echosounder)
„BOTTOM TRACKING” METHOD
sandy bed
p
echosounder
pulsez1
vegetation
echosounder
z2
z1
t
sandy bottom
t2=2z2/c
t1=2z1/c
p
t
„BOTTOM TRACKING” METHOD
(i) detection (underwater meadows occurrence)
(ii) plant height measurement
(iii) mapping
possibilities
UNDERWATER MEADOWS DETECTION . METHODS
1. „Bottom tracking” method
3. Neural Net-based recognition method
2. „Parametric” method
“PARAMETRIC” METHOD,
first step - definition of important parameters
0.5
1
1.5
2
2.5-95 -90 -85 -80 -75 -70 -65 -60 -55
Depth [m]
Sv [dB]
0.5
1
1.5
2
2.5-95 -90 -85 -80 -75 -70 -65 -60 -55
Depth [m]
Sv [dB]
sandy bottom
vegetation