Saran The backscatter characteristic of ALOS PALSAR imagery within eucalyptus grandis forest plantation stand

1. Perlu dilakukan penelitian yang sama dengan citra ALOS PALSAR yang memiliki slope corrected data dan memperbaiki atau mereduksi noise. 2. Perlu dilakukan kajian backscatter pada hutan tanaman Eucalyptus grandis di daerah dataran rendah untuk melihat polarisasi HH atau HVdengan karakteristik tempat tumbuh yang berbeda. DAFTAR PUSTAKA Awaya,T Takahashi., Y Kiyono, H. Saito, M. Shimada, INS Jaya, MB Saleh and Limin SH. 2009.Landcover Monitoring and Biomass Estimation Using PALSAR Data in Palangkaraya, Indonesia, dalam; Workshop on Exploring The Use of ALOS PAlSAR for Forets Resource Management; Development of Forest Degradation Index and Carbon Emission Estimation Method Using PALSAR Data In Indonesia . 3 November 2009. DiGiacomo PM, L. Washburn, B Holt, Burton HJ. 2004. Coastal pollution hazards in southern California observed by SAR imagery: storm water plumes, wastewater plumes, and natural hydro carbon seeps. Marine Pollution Bulletin 49:1013–1024. 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Jansen, 2000.Remote Sensing of TheEnviroment An Earth Resource Perspetif. Univerity of South Carolina. Prentice Hall Upper, New Jersey. [JAXA] Japan Aerospace Exploration Agency. 2007. ALOS User Handbook.http:www.eorc.jaxa.jpALOSendocalos_userhb_en.p df [15 Februari 2011 JICA and IPB. 2010. Penafsiran Visual Citra ALOS PALSAR ;Pengenalan Penutupan Lahan Hutan di Indonesia.Versi 2. Jaenicke J, Englhart S, Siegert F. 2011. Monitoring the effect of restoration measures in Indonesian peatlands by radar satellite imagery. Journal of Environmental Management 92:630-638. Kaukab M. 2008. Rancang Bangun Simulasi Radar. Modul Pengajaran Fakultas Teknik Univesitas Indonesia 2008. Latifah S. 2004. Pertumbuhan Dan Hasil Tegakan Eucalyptus Grandi di Hutan Tanaman Industri “Jurnal Fakultas Pertanian Universitas Sumatera Utara”. Lillesand, MT. and Kiefer RW. 1997. Remote Sensing and Image Interpretation Dulbahri. PenerjemahSuharyadi, penyutingYogyakarta :GadjahMada University Press Mattjik, A.A. dan M Sumertajaya. 2000. Perancangan Percobaan: Aplikasi SAS dan Minitab. Jilid 1 IPB Press. Bogor Onrizal, Cecep Kusmana, M Mansor, Rudi Hartoni. 2009. Estimating aboveground Biomassa and Carbon Stock of planted Eucaluptus Grandis in Toba Plateau North Sumatera. Purbaya BSdanAshari. 2005. AnalisisStatistikdengan Microsoft Exeldan SPSS.Yogyakarta :Edisi I PenerbitAndi Yogyakarta. Purwadhi FSH. 2001.Interpertasi Citra Digital. Jakarta :PT Gramedia Widiasarana Indonesia Jakarta. Saleh M B. 2010. Modul Pelatihan Penggunaan Citra Alos Palsar Dalam Pemetaan Penutupan Lahan Hutan, Bogor: Kerjasama Japan International Cooperation Agency JICA dan Fakultas Kehutanan Institut Pertanian Bogor . Februari 2010. Soesilo, I 1992. Teknolgi Pencinteraan RADAR untuk Kesejahteraan dan Keamanan, Disampaikan pada persentase Teknis Aplikasi Imaging Radar Untuk Militer di Markas TNI AU, Jakarta 21 November 1992. Santoso S. 2010. Statistik Multivariat, Konsep dan Aplikasi SPSS. Jakarta :Penerbit PT Elex Media Komputindo. Shimada M,O Isoguchi.TK Isono. 2009. PALSAR Kalibration Faktor Update. httpsauig.eoc jaxa.JPauigsendokan20090109en_- 3.html [Desember 2009] -------- Shimada and Watanabe. 2007.New Eyes in the Sky: Cloud-Free Tropical Forest Monitoring for REDD with the Japanese Advanced Land Observing Satellite ALOS. Konvensi Kerangka Kerja PBB tentang Perubahan Iklim UNFCCC Konferensi Para Pihak COP, 3-14 Desember 2007. Urso GD, Minacapilli M. 2006. A semi-empirical approach for surface soil water content estimation from radar data without a-priori information on surface roughness. Journal of Hydrology 321: 297– 310. Wisnu W, Imam AR, 2000 Penafsiran Luas Bidang Dasar pada Tegakan Jati dengan menggunakan parameter tinggi, diameter tajuk, tinggi jumlah pohon melalu foto udara Buletin Kehutanan No. 34. 2000. LAMPIRAN Lampiran 2 Nilai backsscatter resolusi 50 M CLUSTER Band_HH Band_HV Class 1 -6.39500113 -14.90044835 Class 2 -6.679975725 -15.60495232 Class 3 -6.061315042 -13.81542133 Class 4 -5.729104737 -14.15332191 Class 5 -5.815181674 -15.53412859 Class 6 -4.897344465 -13.23595678 Class 7 -5.271090743 -13.85432976 Class 8 -4.959551171 -12.57368401 Class 9 -7.238958061 -15.30005157 Class 10 -5.664277544 -13.94486748 Class 11 -5.939062737 -13.34181462 Class 12 -5.294984041 -14.6229331 Class 13 -5.967564205 -14.38111243 Class 14 -6.144453591 -15.33033806 Class 15 -7.555883521 -15.52902061 Class 16 -5.505306227 -14.43669059 Class 17 -4.73304014 -14.37072933 Class 18 -4.763189169 -14.77723186 Class 19 -5.968687242 -16.36081322 Class 20 -6.429759434 -14.32430372 Class 21 -5.38197072 -15.73107227 Class 22 -6.393758348 -14.95294046 Class 23 -5.130999157 -14.23650176 Class 24 -5.15189077 -13.23009117 Class 25 -4.91114311 -15.03134665 Class 26 -5.240361705 -14.00889445 Class 27 -5.904501046 -14.82427683 Class 28 -5.732031604 -13.74210934 Class 29 -4.638439972 -14.65994524 Class 30 -5.705480245 -13.08172218 Class 31 -7.164632191 -17.11978395 Class 32 -4.862873754 -14.601893 Class 33 -5.392530592 -14.48108231 Class 34 -6.021848019 -13.59601703 Class 35 -5.486089843 -13.41053544 Class 36 -4.835080187 -15.20817136 Class 37 -5.865595845 -14.23239807 Class 38 -5.165451215 -15.10627567 Class 39 -5.503537548 -14.94415547 Lampiran 2 lanjutan nilai backscatter resolusi 50 m CLUSTER Band_HH Band_HV Class 40 -5.148363745 -15.07332442 Class 41 -5.554362333 -14.72991049 Class 42 -4.887188316 -13.95848737 Class 43 -5.500167193 -13.05684175 Class 44 -5.794482133 -14.03664966 Class 45 -5.61549003 -13.97798394 Class 46 -6.40613153 -14.36666804 Class 47 -5.858795309 -15.83805368 Class 48 -6.133084194 -14.24188954 Class 49 -5.475320502 -12.62321391 Class 50 -6.437031528 -14.54474301 Class 51 -6.614661552 -14.61996599 Class 52 -5.49944197 -14.15846513 Class 53 -6.43901309 -14.89348034 Class 54 -5.850224201 -14.29248075 Class 55 -4.789113496 -14.62284983 Class 56 -6.176600216 -14.82768596 Class 57 -6.636504523 -14.02091645 Class 58 -6.592915257 -14.29114089 Class 59 -7.291847834 -15.10108803 Class 60 -7.625209491 -15.15222283 Lampiran 3 Nilai backsscater resolusi 6, 25 M CLUSTER Band_HH Band_HV Class 1 -7.219056916 -11.80774902 Class 2 -7.048156265 -11.95561331 Class 3 -7.004309284 -11.36511355 Class 4 -6.733000994 -11.54174635 Class 5 -6.226317577 -11.19902002 Class 6 -6.744034151 -13.49274365 Class 7 -6.187547611 -12.57877171 Class 8 -5.986528239 -12.79594704 Class 9 -8.016284563 -12.96605059 Class 10 -6.694322158 -11.44344955 Class 11 -6.196613898 -10.80086382 Class 12 -7.185171116 -12.03095117 Class 13 -5.747803773 -11.02336856 Class 14 -7.444238159 -12.60769144 Class 15 -7.569359443 -12.14857019 Class 16 -6.02177116 -11.00655362 Class 17 -6.720739066 -11.16330342 Class 18 -6.059304712 -12.47735396 Class 19 -5.989360423 -12.81842417 Class 20 -7.112717058 -12.28219192 Class 21 -6.464666609 -13.82436292 Class 22 -7.170806102 -12.06914649 Class 23 -5.765082393 -11.12510248 Class 24 -5.369392507 -10.39552709 Class 25 -5.924788499 -12.67304734 Class 26 -5.814486306 -11.1513715 Class 27 -6.8421392 -12.06347021 Class 28 -7.031723429 -11.89045314 Class 29 -5.98227436 -10.9990616 Class 30 -6.300711416 -10.63857473 Class 31 -6.137783376 -11.93451968 Class 32 -6.710788993 -12.08605766 Class 33 -6.684307518 -11.62825909 Class 34 -6.380386216 -10.9492558 Class 35 -6.313957999 -11.45882727 Class 36 -6.3038814 -12.01677791 Class 37 -7.03450843 -12.10148059 Class 38 -6.59447569 -13.40297133 Class 39 -6.622363173 -12.2783801 Lampiran 3 lanjutan nilai backscatter resolusi 6,25 m CLUSTER Band_HH Band_HV Class 40 -6.246333295 -12.00090747 Class 42 -7.05695493 -12.09087473 Class 43 -6.856064299 -11.22581247 Class 44 -6.698725855 -11.85155276 Class 45 -6.640457088 -11.08374912 Class 46 -7.126765665 -11.6531449 Class 47 -6.745533604 -12.55222192 Class 48 -6.643757305 -11.51820989 Class 49 -5.474806538 -10.09460712 Class 50 -6.644399239 -11.93201526 Class 51 -6.797153048 -11.43281191 Class 52 -6.705015886 -11.88337585 Class 53 -7.248735703 -12.22395594 Class 54 -7.038761169 -12.19431796 Class 55 -5.867386098 -12.15997669 Class 56 -6.93495611 -12.11824245 Class 57 -6.534971445 -11.66896984 Class 58 -6.935195457 -11.52908992 Class 59 -8.152072143 -12.56235026 Class 60 -7.009321204 -11.93943293 Lampiran 4 Analisis diskriminan Citra ALOS PALSAR resolusi 6.25 m Discriminant Notes Output Created 11-Aug-2011 08:21:41 Comments Input Data C:\Data_AYUB\Palsar_6.25\Back_komposit \analisis_5klas_6.25m_final.spv.sav Active Dataset DataSet1 Filter none Weight none Split File none N of Rows in Working Data File 60 Missing Value Handling Definition of Missing User-defined missing values are treated as missing in the analysis phase. Cases Used In the analysis phase, cases with no user- or system-missing values for any predictor variable are used. Cases with user-, system- missing, or out-of-range values for the grouping variable are always excluded. Resources Processor Time 0:00:01.297 Elapsed Time 0:00:01.313 Analysis Case Processing Summary Unweighted Cases N Percent Valid 60 100.0 Excluded Missing or out-of-range group codes .0 At least one missing discriminating variable .0 Both missing or out-of- range group codes and at least one missing discriminating variable .0 Total .0 Total 60 100.0 Group Statistics GRIDCODE Valid N listwise Mean Std. Deviation Unweighted Weighted 2 Diameter .148333 .1069268 12 12.000 LAI .642500 .2180544 12 12.000 Tinggi Pohon 9.681667 5.3939273 12 12.000 Volume Pohon 7.110833 6.5238032 12 12.000 Jumlah Pohon 69.416667 3.5280263 12 12.000 Diameter Tajuk 2.810833 .3160684 12 12.000 Luas Tajuk 627.818333 126.1676328 12 12.000 Kerapatan Pohon 1535.333333 77.9047593 12 12.000 LBDS 6.338833 2.0027173 12 12.000 Biomassa 69.671750 47.9837083 12 12.000 4 Diameter .060000 .0000000 2 2.000 LAI .725000 .0070711 2 2.000 Tinggi Pohon 2.735000 .3747666 2 2.000 Volume Pohon .505000 .2050610 2 2.000 Jumlah Pohon 75.000000 .0000000 2 2.000 Diameter Tajuk 2.100000 .1414214 2 2.000 Lampiran 4 lanjutan analisis diskriminan Luas Tajuk 342.635000 51.9087088 2 2.000 Kerapatan Pohon 1659.000000 .0000000 2 2.000 LBDS 3.948500 .4306280 2 2.000 Biomassa 15.576000 4.4830570 2 2.000 5 Diameter .111087 .0367713 46 46.000 LAI .679348 .1955323 46 46.000 Tinggi Pohon 9.403043 5.5993436 46 46.000 Volume Pohon 7.005217 6.7522272 46 46.000 Jumlah Pohon 67.956522 3.3925181 46 46.000 Diameter Tajuk 2.703261 .3676112 46 46.000 Luas Tajuk 582.468913 147.6644649 46 46.000 Kerapatan Pohon 1503.760870 75.6019355 46 46.000 LBDS 6.071783 2.1645837 46 46.000 Biomassa 69.074174 52.6657638 46 46.000 Total DBH__M_ .116833 .0591606 60 60.000 Diameter .673500 .1958019 60 60.000 LAI 9.236500 5.5528914 60 60.000 Tinggi Pohon 6.809667 6.6411825 60 60.000 Volume Pohon 68.483333 3.5960980 60 60.000 Jumlah Pohon 2.704667 .3697616 60 60.000 Diameter Tajuk 583.544333 148.3617486 60 60.000 Luas Tajuk 1515.250000 79.8521144 60 60.000 Kerapatan Pohon 6.054417 2.1193358 60 60.000 LBDS 67.410417 51.3751451 60 60.000 Lampiran 4 lanjutan analisis diskriminan Tests of Equality of Group Means Wilks Lambda F df1 df2 Sig. Diameter .904 3.037 2 57 .056 LAI .992 .234 2 57 .792 Tinggi Pohon .952 1.452 2 57 .243 Volume Pohon .968 .931 2 57 .400 Jumlah Pohon .858 4.707 2 57 .013 Diameter Tajuk .893 3.430 2 57 .039 Luas Tajuk .892 3.434 2 57 .039 Kerapatan Pohon .861 4.596 2 57 .014 LBDS .963 1.101 2 57 .340 Biomassa .964 1.056 2 57 .355 Boxs Test of Equality of Covariance Matrices Log Determinants GRIDCODE Rank Log Determinant 2 2 12.158 4 . a . b 5 2 12.296 Pooled within-groups 2 12.248 The ranks and natural logarithms of determinants printed are those of the group covariance matrices. a. Rank 2 b. Too few cases to be non-singular Test Results a Boxs M .812 F Approx. .252 df1 3 df2 5608.025 Sig. .860 Tests null hypothesis of equal population covariance matrices. Lampiran 4 lanjutan analisis diskriminan Stepwise Statistics Variables EnteredRemoved

a,b,c,d

Step Wilks Lambda Entered Statistic df1 df2 df3 1 Jumlah Pohon .858 1 2 57.000 2 Luas Tajuk .713 2 2 57.000 At each step, the variable that minimizes the overall Wilks Lambda is entered. a. Maximum number of steps is 20. b. Minimum partial F to enter is 3.84. c. Maximum partial F to remove is 2.71. d. F level, tolerance, or VIN insufficient for further computation. Variables EnteredRemoved

a,b,c,d