Judul: Deteksi Perubahan Tutupan Hutan dan Lahan Menggunakan Citra ALOS PALSAR Multiwaktu Resolusi 50 Meter di Provinsi Jambi Bagian Timur
Abstrak: Degradation and deforestation in Indonesia is a complex issue that needs to be addressed comprehensively and wisely. Within the period of 2000 - 2012, the national level rate of deforestation is estimated at about 832.126,9 ha / year, while in Jambi Province is approximately 76.522,7 ha/year. Now, the national level deforestation is generally estimated using medium-resolution satellite, such as Landsat, SPOT, ASTER, IRS etc with post-classification comparison approach. For Indonesia, which is located in the tropical region, the use of optical imagery is often constrained due to the high proportion of cloud cover and/or haze during the wet season, and smoke coverage during dry season. The availability of radar imagery such as ALOS PALSAR, JERS-1, Radarsat and ERS-1 that capable to record the earth in all weather conditions as well as capable to penetrate clouds and smoke/haze provide a new prospective in detecting forest and land cover changes. The availability of ALOS PALSAR imageries since 2006/2007 had been provided a good opportunity either for complementing or substituting the optical imagery, especially in the areas of high atmospheric disturbances. Based on the above, this research is aimed to evaluate the ability of 50-meters resolution of ALOS PALSAR imagery for detecting forest and land cover, as well as their changes in eastern part of Jambi Province between 2007 and 2009. The study site includes five regencies in Eastern Part of Jambi Province, namely Tanjung Jabung Barat, Tanjung Jabung Timur, Muaro Jambi, Jambi and Batanghari. Meanwhile, image processing and data analysis was carried out in the Physical Laboratory of Remote Sensing and Geographycal Information System, Laboratory of Forest Resource Inventory Faculty of Forestry IPB. The images used in this reasearch are ALOS PALSAR with HH, HV and synthetic band HH / HV bands recorded on 8 June to 30 November 2007 and from 13 June to 15 October 2009. The softwares used in this research are the Arcview GIS 3.2, ArcGIS 9.3, and Erdas Image 9.1. The classification method used consisted of qualitative and quantitative approaches. In qualitative approach, the classification was performed by visual interpretation on the basis of diagnostic elements of interpretation while in the quantitative approach, classification was done using the supervised classification. The research results show that the Kappa Accuracy of qualitative classification of ALOS PALSAR for 2007 and 2009 are 80% and 82% respectively, while the quantitative approach provides Kappa accuracy of 56% for 2007 and 59% for 2009. The study also found that the largest changes in land cover occured from barren land to plantation forest having area of about 16.866,4 ha. Within 2 years (2007 – 2009) period, the deforestation area is approximately 10.264,3 ha or approximately 5132.15 ha per year, where the largest deforestation occured from forest plantation to oil palm covering area of about 6.928,4 ha or 68% or about 34% per year. Besides, the largest degradation, i.e, from forest plantation to 5 barren land is about 10.195,7 ha or 87% ((or about 34% per year.) By considering the spatial patterns of forest and land cover change between 2007 and 2009, the deforestation and land degradation
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Judul: Klasifikasi dan Detektsi Perubahan Tutupan Hutan dan Lahan Menggunakan Citra ALOS PALSAR Resolusi 50 Meter di Wilayah Barat Provinsi Jambi.
Abstrak: Currently, knowledge on conditions of forest and land cover as well as its dynamics changes, particularly in the form of deforestation and forest or land degradation in the region is highly important, especially to support sustainable forest management. Detection of forest and land condition could be performed either using terrestrial, remote sensing or a combination between remote sensing and terrestrial approach. In Indonesia, since the 1990s, the mapping and monitoring forest and land cover condition is generally performed using optical satellite remote sensing approach. However, in the tropics, the use of optical images often have serious obstacle due to the presence of clouds and haze in the rainy seasonand the presence of smog and smoke during the dry season. However, since the presence ofradar images, a newperspective is coming, which may give complementary and/or substitution information over optical image. Satellite ALOS (Advanced Land Observation Sattelite) with sensor PALSAR (Phased Array L-band Synthetic Aperture Radar) is a radar image that had been launched in 2006 by the Government of Japan. They have four polarizations, namely HH, HV, VH, and VV. However, the image released to the public is commonly consisted of only HH and HV polarization. The study objective are (1) to identify forest and land cover and (2) to detect patterns of change in forest and land cover in the Western Part of Jambi Province using 50-meter ALOS PALSAR. The results of this research are expected to be used for supporting the preparation of MRV or REDD++ as well as for basic information in regional spatial planning. The method used in this study includes (1) image classification using qualitative classification approach (visual) on the composite image ALOS PALSAR (HH-HV-HH/HV) of 2007 and 2009, (2) image classification using quantitative classification (digital analysis) with the supervised method and (3) post-classification comparison by comparing 2007 and 2009 classified imageries. For ground checking and accuracy analysis, the location of ground observations were determined using systematic sampling with random start with the distance range from 100 meters to 500 meters from the edge of the road. The study results show that there are 13 classes of forest and land cover that can be identified through visual classification of 50-meter ALOS PALSAR composite image, namely water body, dry land forest, swamp forest, dry land farming, mixed farms/crop, rubber plantations, oil palm plantations, bush, shrub swamps, marshes, settlements and bare area. The qualitative classification approach provides Kappa accuracy of 82,38% for 2007 and 83,48% for 2009. With quantitative classification approach, slightly lower accuracy and separability were identified, where the average of inter-class separability value of Transformed Divergence for the image of 2007 and 2009 are 1641.7 and 1611.78. The Kappa accuracy with quantitative approach for 2007 is 53,3% and for 2009 is 58.8%. Based on the pattern distribution analysis of forest and landcover changes occurred between 2007 and 2009, it was found that the pattern of forest and land cover changes within the study site is clustered particularly in Tebo and Sarolangun Regencies. Deforestation of 14,583.5 hectaresis mostly occurred in Tebo Regency, while forest and land degradation of 399.8
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Judul: Akupuntur pada Kasus Konstipasi Kucing Persia.
Abstrak: Seekor kucing betina ras persia bernama Lucy telah mengalami konstipasi yang berulang kali sehingga terjadi kronis. Terapi akupuntur digunakan sebagai pengobatan alternatif dalam studi kasus ini dengan tujuan meningkatkan motilitas gastrointestinal. Studi kasus ini bertujuan untuk mengetahui efek akupuntur pada kasus konstipasi di kucing Lucy. Terapi akupuntur dilakukan dengan menggunakan dry neddle pada titik BL-21, BL-25, CV-4, CV-6, CV-12, GV-1, ST-25, dan ST-36. Terapi dilaksanakan selama 15 menit setiap terapi dan dilakukan seminggu 3 kali sampai terjadi perkembangan persembuhan. Berdasarkan hasil pemeriksaan fisik dan pemeriksaan penunjang radiografi, terdapat penumpukan feses yang banyak dari kolon hingga rektum. Kucing dapat defekasi dengan lancar setelah terapi ke-3 dan kondisi kucing yang awalnya buruk semakin membaik.
Keyword: akupuntur, dry needle akupuntur, konstipasi, motilitas gastrointestinal