Dari hasil penelitian, maka dapat disimpulkan bahwa:
1) Berdasarkan hasil nilai akustik volume backscattering strength (SV) maupun surface backscattering strength (SS) yang diperoleh, dapat menggambarkan klasifikasi kategori lifeform terumbu karang.
2) Hasil ekstrak raw data terlihat bahwa nilai volume backscattering strength (SV) untuk kedelapan jenis lifeform terumbu karang terlihat sangat tinggi dengan nilai berkisar antara -10dB sampai -20dB .
3) Hasil pengolahan dengan matlab juga terlihat bahwa nilai mean surface backscattering strength (SS) untuk kedelapan jenis lifeform terumbu karang berkisar antara -27,5dB sampai -32,5dB.
5.2 Saran.
Untuk penelitian selanjutnya hingga mendapatkan bentuk – bentuk lifeform terumbu karang yang lebih banyak, perlu dilakukan dengan frekuensi pengambilan transek yang lebih banyak.
36
DAFTAR PUSTAKA
Anderson JT, Gregory RS, Collins WT. 2002. Acoustic Classification of Marine Habitat in Coastal Newfoundland. ICES J Mar Sci 59:156-167.
Andréfouët S. 2004 Keynote Address: The Diversity and Extent of Planet Earth’s Modern Coral Reefs as View from Space. International Coral Reef Symposium.
Biosonics. 2004. User Guide Visual : Analyzer 4. Seattle: Biosonic Inc.
Birkeland C. (ed). 1997. Life and Death of Coral Reefs. New York: Chapman and Hall. 536p.
Burczynski J. 2004. Bottom Classification. Seattle: BioSonics Inc.
Burk L, Selig E. and Spalding M. 2002. Reef at Risk in Southeast Asia. World Resources Institut. 72 pp.
Collier, J.S and Brown CJ. 2005. Correlation of Sidescan Backscatter with Grain
Size Distribution of Surficial Seabed Sediments. Marine Geology 214:
431–449.
De Moustier and Matsumoto H. 1993. Seafloor Acoustic Remote Sensing with
Multibeam Echosounders and Bathymetric SideScan Sonar Systems. Mar
Geophys Res 15: 27–42.
Deswanti SR. 2009. Evaluasi Metode Akustik untuk Pendeteksian Padang lamun. [tesis]. Bogor: Program Pascasarjana, Institut Pertanian Bogor.
English S, Wilkinson CR, Baker V. 1997. Survey Manual for Tropical Marine Resources. Townsville: Australian Institute of Marine Science.
Fronseca L, Mayer L. 2007. Remote Estimation of Surficial Seafloor Properties Through the Application Angular Range Analysis to Multibeam Sonar Data. Mar Geophys Res 28: 119-126.
Green EP, Mumby PJ, Edwards ED, Clark CD. 2000. Remote Sensing Handbook for Tropical Coastal Management. UNESCO Publishing.
Hamilton LJ. 2001. Acoustic Seabed Classification Systems. DSTO-TN-0401 Aeronautical and Maritime Reseach Laboratory.DSTO-Department of Defense. Australia.
Hill J, Wilkinson C. 2004. Methods for Ecological Monitoring of Coral Reefs. Townsville: Australian Institute of Marine Science.
37
Huvenne VAI, Blondel P, Henriet JP. 2002. Textural Analysis of SideScan Sonar
Imagery from Two Mound Provinces in the Porcupine Seabight. Marine
Geology 189: 323–341.
ICRAN (The International Coral Reef Action Network). 2006. The International Coral Reef Action Network available at http://www.incran.org/Accesced in Nov 7th 2006.
Joyce KE, Phinn SR, Roelfsema C, Neil DT, Dennison WC. 2004. Combining Landsat ETM and Reef Check for Mapping Coral Reefs: An Example from the Southern Great Barrier Reef, Australia. Coral Reefs 23: 21-25. Krastel S et al. 2006. Mapping of Seabed Morphology and shallow Sediment
Structure of Mauritania Continental Margin, Northwest Africa: Some Implications for Geohazard Potensial. Norwegian. Journal of Geology 86:163-176
Louchard EC, Reid PR, Stephens CF, Davis CO, Leathers RA, Downes VT. 2003 Optical Remote Sensing of Benthic Habitats and Bathymetry in Coastal Environments at Lee Stocking Island, Bahamas: A comparative spectral Classification Approach. Limnol Oceanogr 48: 511– 521.
Manuputty AEW. 1986. Karang Lunak, Salah Satu Penyususun Terumbu Karang Oseana Vol XI (4):131-14.P3O LIPI. Jakarta
Manik HM, Furusawa M, Amakasu K. 2006. Measurement of sea Bottom Surface Backscattering Strength by Quantitative Echo Sounder. J Fisheries Science 72: 503-512.
Mazel CH, Strand MP, Lesser MP, Crosby B, Coles and Nevis. 2003. High- Resolution Determination of Coral Reef Bottom Cover from Multispectral Fluorescence Laser Line Scan Imagery. Limnol Oceanogr 48:522-534.
Mc Mullen KY, Poppe LJ, Denny JF, Haupt TA, Crocker JM. 2007. Sidescan Sonar Imagert and Surficial Geologic Interpertation of the Sea Floor in Central Rhode Island Sound. USGS. Report Series 2007-1366.
Mitchell NC, Hughes CJE. 1994. Classification of Seafloor Geology using Multibeam Sonar Data from the Scotia Shelf. Marine Geology 121: 143-160.
Moustier CD. 1986. Beyond Bathymetry: Mapping Acoustic Backscattering from the Deep Seafloor with Sea Beam. J acoust Soc Am 79: 316-331.
Mumby PJ, Green E, Edwards AJ and Clark CD. 1997. Coral Reef Habitat Mapping : How Much Detail Can remote Sensing Provide? Mar Biol 130:193-202.
38
Nasby-Lucas NM, Merle SG, Embley BW, Tissot, BN, Hixon MA. and Wright D.J. 2002. Integration of Submersible Transect Data and High-Resolution Sonar Imagery for a Habitat-Based Groundfish Assessment of Heceta Bank, Oregon". Fishery Bulletin 100: 739-751.
Nontji A. 2002. Laut Nusantara. Jakarta: Penerbit Djambatan.
Orlowski. 2007. Acoustic Seabed Classification Applied to Baltic benthic habitat Studies: a New Approach. Oceanologia 49:229-243.
Ostrand WD, Tracey AG, Shay H and Martin DR. 2005. Journal Habitat Selection Models For Pasific Sand Lance (Ammodytes Hexapterus) In Prince William Sound, Alaska. Washington D.C. [25 Agustus 2007].
Purnawan S. 2009. Analisis Model Jackson Pada Sedimen Berpasir Menggunakan Metode Hidroakustik di Gugusan Pulau Pari, Kepulauan Seribu [tesis]. Bogor: Program Pascasarjana, Institut Pertanian Bogor.
Richardson MD dan Bringgs KB. 1993. On the Use of Acoustic Impedance Values to Determine Sediment properties. Proceeding of Institut of Acoustics.Vol 15.
Roff JC, Taylor ME, Laughren J. 2003. Geophysical Approaches to the Classification, Delineation and Monitoring of Marine Habitats and Their Communities. Aquatic Conservation: Marine and Freshwater Ecosystem 13: 77-90.
Simmonds EJ, Mac Lennan DN. 2005. Fisheries Acoustics: Theory and Practice. Oxford:.Blackwell Science Ltd. 437 pp.
Simrad. 1993. Simrad EK 500 Scientific Echo sounder Operator Manual. Simrad Sub sea Horten: Norway. 204p.
Situmorang B. 2004 .Valuasi Ekonomi Terumbu Karang Kepulauan Seribu. [tesis]. Bogor: Program Pasca Sarjana, Institut Pertanian Bogor.
Siwabessy PJW. 2001. An Investigation of Relation between Seabed Type and Benthyc and bentho-pelagic Biota Using Acoustic Technique. [thesis]. Australia: School of Applied Science, the Curtin Universitas of Technology.
Spelding MD, Ravilious C, Green EP. 2001. World Atlas of Coral Reef. Berkeley: University of California Press.
Stenlicht DD, Moustier CD. 2003. Time-Dependent Seafloor Acoustic Backscatter (10 -100kHz). J Acoust Soc Am. 114:2709 – 2725.
Supriharyono. 2000. Pengelolaan Ekosistim Terumbu Karang. Jakarta: Penerbit Djambatan.
39
Tegowski J, Gorska N, Klusek Z. 2003. Statistical Analysis of Acoustic Echoes from Underwater Meadows in the Eutrophic Puch Bay (Soulthern Baltic Sea). Aquatic Living Resources 16: 215-221
Tegowski J. 2005. Acoustic Classification of the Bottom Sediment in the Southern Baltic Sea, Quatern. Int 130:153 -161.
Urick R.J. 1983. Principles of Underwater Sound. New York: Mc-Graw-Hill Publishing.
Van Woesik R. 2002. Coral Communities and Reef Growth in the Southern Great Barrier Reef. Florida: Coral Reef Report.
Veron JE. 2002. Coral of the World. Australian: Institute of Marine Science. Waite AD. 2002. Sonar for Practising Engineers 3 rd ed. USA: John Wiley &
Sons Ltd.
Walker BK, Riegl B, Dodge RE. 2008. Mapping Coral Reef Habitats in Southeast Florida Using a Combined Technique Approach. J Coast Res 24:1138-1150.
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Lampiran 1 Dokumentasi survei, peralatan instrumentasi akustik yang digunakan dalam penelitian.
Contoh tampilan echogram pada saat Komputer dan stabilizer tranduser perekaman
Kapal yang digunakan untuk penelitian GPS digunakan untuk pencatatan Posisi
Jenis tranduser split beam yang digunakan untuk sounding data akustik
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Lampiran 2 Jenis lifeform terumbu karang yang ditemukan pada lokasi penelitian. Titik Bentuk
lifeform
Kode Kedalaman Photo/dokumentasi family
1 Foliose (CF) 2,5 meter Faviidae
2 Masive (CM) 2 meter Faviidae
3 Branching (CB) 2,5 meter Acropidae
4 Acropora
Tabular (ACT) 2 meter Poritidae
5 Sponge (SP) 2,5 meter Agaricidae
6 Acropora
Digitale (ACD) 2,5 meter Acropidae
7 Mushroom (CMR) 2,5 meter Fungiidae
8
Acropora Branching
(ATB) 2 meter
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Lampiran 3 Uraian Listening program Rick Towler (Purnawan 2009)
%readEKRaw_EY60.m % Richard Towler
% NOAA Alaska Fisheries Science Center
% Midwater Assesment and Conservation Engineering Group % rick.towler@noaa.gov
% dimodifikasi oleh Jafry Manuhutu, c552070011 % Mahasiswa
site='lifeform\';
file = input ( 'file yang akan diolah? ( site - site 8)','s'); rawFile = strcat ( '../jefri-1//D20090714-T120017.raw');
botFile =strcat ( '../jefri-1//D20090714-T120017.bot'); awal = input ('masukkan nilai ping awal');
akhir = input ('masukkan nilai ping akhir');
%memberikan +1 ping, agar data yang diproses adalah = jumlah akhir akhir=akhir+1;
% read in raw file - only reading 120 khz disp('Reading .raw file...');
[header, rawData] = readEYRaw(rawFile, 'SampleRange',[1 600],'PingRange',[1 1800]);
calParms = readEYRaw_GetCalParms(header,rawData); % read in the .bot file - return data as range disp('Reading .bot file...');
[header, botData] = readEYBot(botFile, calParms, rawData, ...
'ReturnRange', true); % convert power to Sv
data = readEYRaw_Power2Sv(rawData,calParms); % convert electrical to physical angles
data = readEYRaw_ConvertAngles(data, calParms); % mensortir kembali data yang digunakan
%sehingga mempermudah dalam pengolahan data dasar perairan
c=1.543;% kecepatan suara
tau=0.1280000;%panjang gelombang
x=data.pings.number; y=data.pings.range; Z=data.pings.Sv;%z =Sv logaritma z=10.^(Z/10); ss=z*(c*tau/2); SS=10*log10(ss);
along =data.pings.alongship;%sudut alongship
athw=data.pings.athwartship;%sudut athwartship
Svbottom=Z; along1=along;
bd=botData.pings.bottomdepth; [k l]=size(Z);
%data tbd pada 1 ping terakhir memberikan nilai yang tidak akurat % sehingga perlu dihilangkan
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l=l-1;
for ll=1:l;
m=0;
for kk=1:k;
%mengambil data dasar perairan, dari permukaan hingga 1/2
meter
% data yang lainnya diberikan pada kedalaman lain adalah
nol if y(kk,1)<(bd(1,ll)+0.05); Svbottom (kk,ll)=-1000;%svbottom (kk+l,ll)=0; alongl (kk,ll)=0; elseif y(kk,1)>(bd(1,ll)+0.5); Svbottom(kk,ll)=-1000; alongl(kk,ll)=0; else svbottom(kk,ll)=Z(kk,ll); along (kk,ll)=along (kk,ll);
% mengambil data hanya pada dasar perairan hingga setengah meter, svbonly
m=m+1;
Svbottomly(m,ll)=Z(kk,ll); along2(m,ll)=along(kk,ll);
end;end;end;
%agar jumlah data tiap kolom sama
%ditentukan ketebalan lapisan yang digunakan,hlyr hlyr=0.3; for ll=1:l; for i=1:m; if y(i,1)<=hlyr; Svbonly(i,ll)=Svbottomly (i,ll); along3(i,ll)=along2(i,ll);
end;end;end
Svbottommean=mean(mean(Svbonly)); Svbperping=mean(Svbonly) [i l]=size(Svbonly); for ll=1:ll;Zmax(ll)=-999; for ii=1:i; if Svbonly(ii,11) >Zmax(ll); Zmax(ll)=Svbonly(ii,ll); alongmax(ll)=along3(ii,ll); end end end zmax=10.^(Zmax/10); ratazmax=mean(zmax); ssmax=zmax*(c*tau/2); SSmax=10*log10(ss); stdsv=std(zmax); rataZmax=10*log10(ratazmax) stdSv=10*log10(stdsv);
%membuat gambar echogram dan anglogram disp('plotting...'); nFreqs=length(data.pings); for n=1:nFreqs %plote chogram readEKRaw_SimpleEchogram(Z,x,y,'Threshold',[-60,0])%colormap('jet'); %colorbar;
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colorbar('YTickLabel',{'-120','-80','-60','-40','-20','0'}) %plot the bottom
hold on
plot(data.pings(n).number,botData.pings.bottomdepth(n,:),'c'); hold off
end
akhir=akhir-1;%mengembalikan nilai dari 'akhir'diatas
%Zmax1=0; alongmax1=0;%untuk merubah kembali pingnya
sp=akhir-1;%selisih ping yang dimasukkan dengan untuk looping
for ll=awal:akhir; Zmax1(ll)=Zmax(ll); end %plot(Svmax) %plot(Svmax(:,1)) figure plot(Zmax1); axis([awal akhir -50 0]); xlabel('pings','fontsize',8); ylabel('Sv Maksimum(db)','fontsize',8); legend('Sv max (dB)')
%merubah nilai Sv maksimum menjadi SS maksimum zmax1=10.^(Zmax1/10); ssmakping=zmax1*(c*tau/2); SSmakping=10*log10(ssmakping) %plot(SSmax) %plot(SSmax(:,1)) figure plot(SSmakping); axis([awal akhir -65 0]); xlabel('pings','fontsize',8); ylabel('SS Maksimum(db)','fontsize',8); legend('SS max (dB)')
%plot(rata2 sv bottom tiap ping) figure
plot(Svbperping);
axis([awal akhir -60 0]); xlabel('pings','fontsize',8);
ylabel('Sv rata-rata(db)','fontsize',8); legend('Sv rata2 per ping (dB)')
%merubah nilai Sv rata2 menjadi SS rata2 svrata1=10.^(Svbperping/10); ssrataping=svrata1*(c*tau/2); SSrataping=10*log10(ssrataping) %plot(SS rata2) %plot(SSrata(:,1)) figure plot(SSrataping); axis([awal akhir -40 0]);
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xlabel('pings','fontsize',8);
ylabel('SS rata2(db)','fontsize',8); legend('SS rata-rata per ping (dB)') %axis([awal akhir -10 10])
%xlabel('pings','fontsize',16);
%ylabel('sudut (derajat)','fontsize',16); %legend('Sudut alongship (derajat)') bottom1=data.pings.Sv(100:200,:); bottom2=data.pings.Sv(200:300,:); mean1=mean(bottom1'); minE1=min(mean1) maxE1=max(mean1) mE1=mean(mean1) svbottom2=z; bd2=bd*2; [k l]=size(z); for ll=1:l; for kk=1:k; if y(kk,1)<bd2(1,ll); svbottom2(kk,ll)=0; elseif y(kk,1)>(bd2(1,ll)+100); svbottom2(kk,ll)=0; else svbottom2(kk,ll)=z(kk,ll); svbottomonly2(kk,ll)=z(kk,ll); end;end;end;
mean2=mean(bottom2'); minE2=min(mean2) maxE2=max(mean2) mE2=mean(mean2) %subplot(SS(:,1),y,'r') %hold on %plot (z(:,1),y,'b') %legend ('SS','SV')
