Lampiran 1. Scientific echosounder Simrad EY 60
Kabel Transducer
Transducer
GPT Laptop GPS
Lampiran 2. Alat pengambilan sampel sedimen
Lampiran 3. Kapal survei
Lampiran 4. Echoview 4,00 dan dongle
Lampiran 5. Alat pengukur parameter fisik sedimen
Shaker (ASTM E – 11. USA Standard)
Timbangan
Alat pengukur densitas sedimen
Alat pengukur porositas
Lampiran 6. Listing program Matlab_Rick Towler @ Untuk menampilkan echo envelope %readEKRaw_EY60.m %----------------------------------------------------------% % Rick Towler % National Oceanic and Atmospheric Administration % Alaska Fisheries Science Center % Midwater Assesment and Conservation Engineering Group %
[email protected] %----------------------------------------------------------% %readEKRaw_ChunkExample.m % % define paths to example raw and bot files rawFile = 'nama_file.raw'; botFile = 'nama_file.bot'; ping_awal = input('masukkan ping awal = '); ping_akhir = input('masukkan ping akhir = '); disp('Reading .raw file...'); % read in the first chunk of the file using PingRange to define chunk size. % Note that we specify the optional 3rd return argument "rstat" that will % contain the reader state when the function exits. % % also note that we do not read in angle data [header, firstRaw, rstat] = readEKRaw(rawFile, 'Frequencies', 120000, ... 'SampleRange',[1 800],'PingRange',[ping_awal ping_akhir],'Angles',false);
% extract calibration parameters from the first raw data structure calParms = readEKRaw_GetCalParms(header, firstRaw); disp('Reading .bot file...'); % read in the .bot file - by passing the optional 3rd argument we force % readEKBot to only return data for pings contained in the firstRaw structure. % again, we set the rstat return argument. [header, firstBot, rstat] = readEKBot(botFile, calParms, firstRaw, ... 'ReturnRange', true);
% convert power to Sv firstRaw = readEKRaw_Power2Sv(firstRaw, calParms); % plot up the two blocks of data disp('Plotting...');
% plot the first chunk echogram readEKRaw_SimpleEchogram(firstRaw.pings(1).Sv, firstRaw.pings(1).number, ... firstRaw.pings(1).range, 'Threshold', [-70,0], 'Title', ... ['Sv']); hold on % plot the bottom plot(firstRaw.pings(1).number, firstBot.pings.bottomdepth(1,:), 'c'); hold off % colorbar; colorbar('YTickLabel',{'-70 dB','-58 dB','-47 dB','-35 dB','-23 dB','-12 dB'}) xlabel ('Ping') ylabel ('Depth (m)') % plot echo envelope (digunakan setelah selesai menampilkan echogram) Sv1=firstRaw.pings.Sv; Sv1mean=mean(Sv1'); plot(Sv1mean); xlabel ('Time (ms)') ylabel ('Intensitas energi backscattering strength (dB)')
@ Untuk menampilkan grafik Sv dan SS (Purnawan, 2009) % readEKRaw_EY60.m %----------------------------------------------------------% % Rick Towler % National Oceanic and Atmospheric Administration % Alaska Fisheries Science Center % Midwater Assesment and Conservation Engineering Group %
[email protected] %----------------------------------------------------------% %readEKRaw_ChunkExample.m % % define paths to example raw and bot files rawFile = 'nama_file.raw'; botFile = 'nama_file.bot'; awal=input('masukkan ping awal = '); akhir=input('masukkan ping akhir = '); % membaca file .raw - hanya pada frekuensi 120 kHz disp('membaca .raw file...'); [header, rawData] = readEKRaw(rawFile, 'SampleRange', [1 500],... 'PingRange', [awal akhir]); calParms = readEKRaw_GetCalParms(header, rawData); %
membaca file .bot - data yang kembali sebagai range
disp('membaca .bot file...'); [header, botData] = readEKBot(botFile, calParms, rawData, ... 'ReturnRange', true); % konversi power ke Sv data = readEKRaw_Power2Sv(rawData, calParms); % konversi sudut electrical ke sudut physical data = readEKRaw_ConvertAngles(data, calParms); % mensortir kembali data yang digunakan % sehingga mempermudah dalam pengolahan data dasar perairan c=1546.35;%kecepatan suara tau=0.000128;%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);%ini untuk cari ss SS=10*log10(ss);%in untuk cari SS log 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 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+1,ll)=0; along1(kk,ll)=0; elseif y(kk,1)>(bd(1,ll)+0.5); Svbottom(kk,ll)=-1000; along1(kk,ll)=0; else svbottom(kk,ll)=Z(kk,ll); along1(kk,ll)=along(kk,ll); % mengambil data hanya pada dasar perairan hingga setengah meter, svbonly m=m+1; Svbottomonly(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=0.1; for ll=1:l; for i=1:m;
if y(i,1)<=hlyr; Svbonly(i,ll)=Svbottomonly(i,ll); along3(i,ll)=along2(i,ll); end; end; end Svbottommean=mean(mean(Svbonly)); [i l]=size(Svbonly); for ll=1:l;Zmax(ll)=-999; for ii=1:i; if Svbonly(ii,ll) > Zmax(ll) ; Zmax(ll) = Svbonly(ii,ll); alongmax(ll)=along3(ii,ll); end end end zmax=10.^(Zmax/10); % linier ratazmax=mean(zmax); ssmax=zmax*(c*tau/2); ssmean=mean(ssmax); SSmax=10*log10(ssmean) stdsv=std(zmax); rataZmax=10*log10(ratazmax) stdSv=10*log10(stdsv);
func
% membuat gambar echogram dan anglogram disp('Plotting...'); nFreqs = length(data.pings); for n=1:nFreqs % plot echogram readEKRaw_SimpleEchogram(SS,x,y, 'Threshold', [-50,0]);% disini ngerubahnya!!!!! % plot the bottom hold on plot(data.pings(n).number, botData.pings.bottomdepth(n,:), 'c'); hold off % plot anglogram readEKRaw_SimpleAnglogram(data.pings(n).alongship, ... data.pings(n).athwartship, data.pings(n).number, ... data.pings(n).range, 'Title', ... ['Angles ' num2str(calParms(n).frequency)]); % plot bottom hold on plot(data.pings(n).number, botData.pings.bottomdepth(n,:), 'c'); hold off end akhir=akhir-1; %mengembalikan nilai dari 'akhir' di atas %Zmax1=0; alongmax1=0;% untuk merubah kembali pingnya sp=akhir-l; %selisih ping yang dimasukkan dengan untuk looping for ll=awal:akhir; Zmax1(ll)=Zmax(ll-sp);
alongmax1(ll)=alongmax(ll-sp); end figure subplot(2,1,1); plot(Zmax1); axis([awal akhir -30 0]) xlabel('ping','fontsize',16); ylabel('Scattering volume (dB)','fontsize',16); legend('Sv max (dB)') subplot(2,1,2); plot(alongmax1); axis([awal akhir -10 10]) xlabel('ping','fontsize',16); ylabel('sudut (derajat)','fontsize',16); legend('sudut alongship (derajat)') figure plot (SS(:,1),y,'r') hold on plot (Z(:,1),y,'b') legend('SS','Sv') xlabel ('Intensitas acoustic backscattering strength (dB)') ylabel ('Depth (m)')
Lampiran 7. Foto tipe substrat dasar perairan di lokasi penelitian
Substrat Pasir
Substrat Pasir berlumpur
Lampiran 8. Tampilan echogram (Lanjutan)
Stasiun 1
Stasiun 2
Stasiun 5
Stasiun 6
Stasiun 8
Lampiran 9. Grafik pola Sv dan SS (Lanjutan)
Stasiun 1
Stasiun 2
Stasiun 5
Stasiun 6
Stasiun 8
Lampiran 10. Grafik intensitas energi acoustic backscattering dasar perairan (Lanjutan)
Stasiun 1
Stasiun 2
Stasiun 5
Stasiun 6
Stasiun 8
Lampiran 11. Cluster data sedimen Cluster Analysis of Observations: Pasir, Debu, Liat, Densitas, Porositas, Koef. Euclidean Distance, Average Linkage Amalgamation Steps Step Number of Similarity clusters level 1 8 80.61 2 7 78.51 3 6 76.92 4 5 76.67 5 4 68.68 6 3 62.72 7 2 48.20 8 1 35.31
Distance level 5.765 6.391 6.863 6.938 9.315 11.087 15.403 19.236
Clusters New Number of obs. joined cluster in new cluster 5 9 5 2 5 7 5 3 3 4 3 2 1 2 1 2 5 8 5 4 1 3 1 4 1 6 1 5 1 5 1 9
Final Partition Number of clusters:
1
Number of
Within cluster
observations 9
sum of squares 1107.010
Average distance Maximum
distance Cluster1
from centroid 10.461
from centroid 16.568
Cluo 'Pasir'-'BL';
Lampiran 12. Cluster data akustik Cluster Analysis of Observations: E1, E2, SS, EL Euclidean Distance, Average Linkage Amalgamation Steps Step Number of Similarity clusters level 1 8 90.23 2 7 88.81 3 6 87.12 4 5 76.16 5 4 73.48 6 3 73.37 7 2 52.58 8 1 21.17
Distance level 3.445 3.944 4.541 8.406 9.348 9.387 16.716 27.790
Clusters New Number of obs. joined cluster in new cluster 6 8 6 2 2 4 2 2 2 3 2 3 1 2 1 4 5 9 5 2 1 6 1 6 1 5 1 8 1 7 1 9
Final Partition Number of clusters:
1
Number of
Within cluster
observations 9
sum of squares 1233.479
Average distance Maximum
distance Cluster1
Cluo 'E1'-'EL';
from centroid 10.209
from centroid 24.067
Lampiran 13. Hasil olahan fraksi sedimen di Balai Penelitian Tanah, Laboratorium Fisika Tanah Bogor Nomor
Tekstur (%) Liat
Lumpur
Lumpur
Lumpur
Pasir
Pasir
Pasir
Pasir
Pasir
2 - 10 µm 3,27
10 - 20 µm 5,67
20 - 50 µm 12,98
50 - 100 µm 7,58
100 - 200 µm 11,27
200 - 500 µm 23,57
500 - 1000 µm 29,87
1000 - 2000 µm 4,89
Urut
Seri
Contoh
1
11 F
STA 1
0-2 µm 0,90
2
11 F
STA 2
0,82
4,31
6,83
15,67
4,57
13,61
20,15
31,26
2,78
3
11 F
STA 3
1,15
2,63
5,61
8,25
12,78
15,65
29,33
17,85
6,75
4
11 F
STA 4
0,89
2,39
6,62
11,74
4,56
7,88
53,57
7,84
4,51
5
11 F
STA 5
1,08
2,13
4,55
9,84
6,41
5,58
23,65
31,28
15,48
6
11 F
STA 6
1,28
3,67
6,88
15,31
14,64
19,84
21,38
12,36
4,64
7
11 F
STA 7
0,24
0,95
4,25
7,58
4,43
18,47
34,12
17,58
12,38
8
11 F
STA 8
0,73
1,25
2,13
5,63
20,34
16,94
31,26
18,45
3,27
9
11 F
STA 9
0,38
1,78
3,60
9,35
5,16
13,62
35,41
22,14
8,56
