DETERMINATION OF FOREST AND NON-FOREST IN SERAM ISLAND MALUKU PROVINCE USING MULTI-YEAR LANDSAT DATA
Abstract
Seram Island is one of the islands in Maluku Province. Forest in Seram Island still exists because there is Manusela National Park, but they should be monitored. The forest and non-forest information is usually obtained through the classification process from single remote sensing data, but in certain places in Indonesia it is difficult enough to get  single Landsat data with cloud free, so annual mosaic was used. The aim of this research was to analyze the stratification zone, their indices and thresholds to get spatial information of annual forest area in Seram Island using multi-year Landsat Data. The method consists of four stages: 1) analyzing the base probability result for determination of stratification zone 2) determining the annual forest probability by applying indices from stage-I, 3) determining the spatial information of forest and non-forest annual phase-I by searching the lowest boundary of forest probability, and 4) determining the spatial information of forest and non-forest annual phase-II using the method of permutation of three data and multi-year forest rules. The results of this study indicated that Seram Island could be coumpond into one stratification zone with three indices. The index equations were B2+B3-2B for index-1, B3+B4 for index-2, and -B3+B4 for index-3.  The threshold of index 1, 2, and 3 ranged between -60 and 0, 61 and 104, and 45 and 105, respectively. The lowest boundary of forest probability in Seram Island since 2006 to 2012 have a range between 46% and 60%. The last result was the annual forest spatial information phase II where the missing data on the forest spatial information phase I decreased. The information is very important to analyze forest area change, especially in Seram Island.Â
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Campbell NA and Atchley WR, (1981), The Geometry of Canonical Variate Analysis, Syst. Zool, vol. 30, no. 3, 268–280, 1981.
Danoedoro P, (2012), Introduction of Digital Remote Sensing. (in Indonesia), Yogyakarta: Andi.
FAO, (2014), http://wrm.org.uy/oldsite/forests/ Definition_of_Forest.pdf [accessed on September 2014].
Fisher RA, (1971), The Design of Experiments, New York: Hafner Publishing Company, 24-29.
Furby S and Walles J, (2011), Guidelines for Annual Forest Extent and Change Mapping Version 2.2. Australia: CSIRO Mathematics, Informatics and Statistics, 2011.
Furby SL, Caccetta PA, and Wallace JF, (2010), Salinity Monitoring in Western Australia using Remotely Sensed and Other Spatial data, J Environ. Quality, vol. 39, 16-25.
Furby SL, Caccetta PA, Wallace JF, Wu X, O’Connell J, Collings S, Traylen A, and Deveraux D, (2008), Recent Developments in Landsat-Based Continental Scale Land Cover Change Monitoring in Australia, the international archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol. XXXVII, part B7, 1491-1496.
Gilbert N, (2009), Forest Definition Comes Under Fire, Nature International Weekly Journal Science, 2009.
IAFCP, (2014), https://issuu.com/iafcp/docs/ fact_sheet_ incas [accessed on March 2014].
Kartika T, Carolita I, and Vidyan S, (2014), Determination of Base Forest Probability for Multi Temporal Classification of Forest and Non-Forest in Seram Island, (in Indonesia) in Proceeding Sinas Inderaja, 142-151.
Kartika T, Hawariyyah S, Harini S, (2013), Segmentation and Structure Classifications used Object Base Digital Technique to Classify Forest and Bon-Forest–Case Study in Block E of PPLG in Kapuas Regency Center Kalimantan, (In Indonesia) in Proceeding PIT MAPIN XIX, 173-184.
Kim DH, Sexton JO, Noojipady P, Huang C, Anand A, Channan S, Feng M, and Townshend JR, (2014), Global, Landsat Based Forest Cover Change from 1990 to 2000, Remote Sens. Environ., vol. 155, pp. 178–193.
Kustiyo, Roswintiarti O, Tjahjaningsih A, Dewanti R, Furby S, Wallace J, (2015), Annual Forest Monitoring as part of the Indonesia’s National Carbon Accounting System, the international archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XL-7/W3, 2015, 36th International Symposium on Remote Sensing of Environment, Berlin, Germany, 11–15 May 2015.
LAPAN, (2014), The Remote Sensing Monitoring Program of Indonesia’s National Carbon Accounting System: Methodology and Products, Version 1. LAPAN-IAFCP, Jakarta, 2014.
Margono BA, Potapov PV, Turubanova S, Stolle F, and Hansen MC, (2014), Primary Forest Cover Loss in Indonesia over 2000–2012, Nat. Clim. Chang., vol. 4, no. June, 1–6.
Symeonakis E, Caccetta P, Koukoulas S, Furby S, and Karathanasis N, (2012), Multi-Temporal Land-Cover Classification and Change Analysis with Conditional Probability Networks: the Case of Lesvos Island (Greece), Int. J. Remote Sens., vol. 33, no. 13, 4075–4093.Tofallis C., (1999), Model Building with Multiple Variables, J. R. Stat. Soc. Ser. D Stat., vol. 48, no. 3, 371–378.
State Secretariat, (1999), Act of the Republic of Indonesia No. 41 of 1999 on Forestry (in Indonesia).
Wardoyo, (2009), The Development of National Carbon Accounting in the Foresty Sector, (in Indonesia) in Proc. Seminar National of the National Association of Agricultural Indonesia, 1–6.
Wikipedia, (2014), https://en.wikipedia.org/ wiki/Manusela_National_Park [accessed on August 2014].
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