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THE CHARACTERISTICS OF VEGETATION, SOIL AND CARBON RESERVES IN MINE AREA OF MOUNT PONGKOR, BOGOR, WEST JAVA KARAKTERISTIK VEGETASI DAN CADANGAN KARBON PADA LAHAN TAMBANG DI GUNUNG PONGKOR, BOGOR, JAWA BARAT Kartini, Entin; Syaufina, Lailan; Mansur, Irdika
Jurnal Silvikultur Tropika Vol. 7 No. 2 (2016): Jurnal Silvikultur Tropika
Publisher : Departemen Silvikultur, Fakultas Kehutanan, Institut Pertanian Bogor (IPB)

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Abstract

This research was conducted in the undisturbed land, underground mining area and illegal mine (PETI) land of Mount Pongkor. This research is aimed to analyze the difference of structure and composition of vegetation, and to predict carbon reserves above soil surface in undisturbed land, underground and PETI, so then adaptive type of vegetation can be identified. This study was conducted by using simple random sampling method with 40 plots. Estimation of carbon stocks using non- destructive method according ISO 7742 2011. The results show that structure and composition between underground is same as undisturbed land with complete stratification which consists of bushes, seedling, pole, trees, liana and epifit, while PETI land has no complete stratification. In PETI land, it?s only found one type of vegetation on pole level that is Vernonea arborea while trees is not found. The species Syzygium lineatum, Lithocarpus sp, Maesopsis eminii, Altingia excelsa, and Ziziphus mauritiana are the species with highest Important Value Index (IVI) in undisturbed land. The Species M eminii, Lithocarpus sp, Altingia excelsa, Vernonea arborea, and Castanopsis argentea are the highest in underground area, so that they are the most dominant species in that location. Species Diversity Index (H?) in undisturbed land is between 1.28-2.62 (medium), while in underground are is between 1.93-2.88 (medium), and in PETI land is between 0-2.45 (very low to medium). Index of Species Richness (R) in undisturbed land and underground on every level of vegetatation is between 1.74-5.9, while in PETI land is lower than 3.5 (very low). Similarity Index (E) in research sites on every level of vegetation is between 0.58-0.98 (relatively uniform), except in PETI land for pole level and trees, the value of E is zero. The potency of carbon stock in undisturbed land was about 288.94 tons C/ha and 192.74 ton C/ha for underground area, whereas was about 0.06 tons C/ha was found in PETI location.Key words: llegal mining, underground mining, suspected carbon stocks, vegetation
ESTIMASI HILANGNYA CADANGAN KARBON DARI PERUBAHAN PENGGUNAAN LAHAN DI KABUPATEN BOGOR Setiawan, Gatot; Syaufina, Lailan; Puspaningsih, Nining
Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan (Journal of Natural Resources and Environmental Management) Vol 5, No 2 (2015): Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan (JPSL)
Publisher : Graduate School Bogor Agricultural University (SPs IPB)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/jpsl.5.2.141

Abstract

One of the primary sectors that contributes to green house gas emissions is land use changes. Bogor Regency is one of the districts close to the capital city and industrial areas so that the intensity of land use changes are very dynamic. This study aims to determine the dynamics of land use changes and CO2-eq emissions from land use change in 2000 to 2014 in Bogor. In the period 2000-2014 the most land undergone many changes occur in mixed garden, cropland, open land and shrub that converted turned into settlement with a total amounted to 11.12% of the total area, while the CO2-eq emissions in 2005-2009 increased approximately six times the emissions from 2000-2005 in the amount of 681 006.94 tons of CO2-eq per year.Keywords: green house gas emission, land use change, CO2-eq emissions
Spatial Model of Land and Forest Fire Risk Index, Case Study in Central Kalimantan Province Samsuri, Samsuri; Surati Jaya, I Nengah; Syaufina, Lailan
FORESTA Vol 1, No 1 (2012): MARET
Publisher : FORESTA

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Abstract

This article describes spatial models of land and forest fire risk in Central Kalimantan. The models were established base on human factor and biophysical factor approaches. The main objective of this research is to map out forest fire risk index in Central Kalimantan as well as to identify the major factor that significantly affect the forest fire risk itself. The study use CMA method to develop spatial model of land and forest fire risk. The mathematical model obtained from this study is: y = -0,00004x2 + 0,021x – 0,356 having R2 about 54 %. The significant factors that affect the forest fire risk are land allocation, land cover, land system and soil type. Model validation shows that the model can predict the risk fire index providing 66,76 % of accuracy.Key words: Central Kalimantan, forest fire risk, CMA, spatial model
THE EFFECTS OF CLIMATIC VARIATIONS ON PEAT SWAMP FOREST CONDITION AND PEAT COMBUSTIBILITY Syaufina, Lailan; Nuruddin, Ahmad Ainuddin; Basharuddin, Jamaluddin; See, Lai Food; Yusof, Mohid Rashid Mohd
Jurnal Manajemen Hutan Tropika Vol. 10 No. 1 (2004)
Publisher : Institut Pertanian Bogor (IPB University)

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Abstract

Studi tentang pengaruh variasi iklim terhadap kondisi hutan rawa gambut dan kemampuan terbakar gambut ini dilaksanakan di Hutan Simpan Sungai karang, Tanjong Karang, Selangor, Malaysia. Tujuan dari studi ini adalah untuk menentukan: 1) Variasi iklim di daerah penelitian , 2) Pengaruh variasi iklim terhadap kondisi hutan rawa gambut; 3) Kemampuan terbakar gambut dan faktor-faktor yang mempengaruhinya; dan 4) Pengaruh kebakaran hutan terhadap kondisi hutan rawa gambut. Studi ini dilakukan di kompartemen 127 selama dua periode, yaitu: Oktober 1999 sampai Januari 2000 dan Mei 2000 sampai Oktober 2000, sementara, studi tentang pengaruh kebakaran dilakukan di kompartemen 132 dari Oktober 1999 sampai dengan Januari 2000. Studi ini mengklasifikasikan musim kemarau dan musim penghujan sebagai periode dengan curah hujan bulanan berturut-turut kurang dari atau sama dengan 125 mm dan lebih besar dari 125 mm. Daerah penelitian memiliki dua periode kering, yaitu: Januari, Februari, dan Maret sebagai periode pertama dan Mei sampai Agustus sebagai periode kedua. Secara statistik, musim berpengaruh pada kadar air, bulk density, potassium, magnesium, sodium dan tinggi muka air. Dengan menggunakan prediksi curah hujan mingguan, kadar air kritis dari lahan gambut terhadap kebakaran adalah 355 %.Keywords:  climatic variations, peat swamp forest, forest fire, peat combustibility
KEANEKARAGAMAN ARTHROPODA TANAH DI HUTAN PENDIDIKAN GUNUNG WALAT (DIVERSITY OF SOIL ARTHROPODS IN GUNUNG WALAT EDUCATION FOREST) Syaufina, Lailan; Haneda, Noor Farikhah; Buliyansih, Asri
Media Konservasi Vol 12 No 2 (2007): Media Konservasi
Publisher : Deparement of Forest Resources Conservation and Ecotourism - Bogor Agricultural University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (249.579 KB) | DOI: 10.29244/medkon.12.2.%p

Abstract

Astudy was conducted to investigate the difference in abundance, richness, diversity and evenness of soil arthropods in Gunung Walat Education Forest, Sukabumi, West Java. Sampling was done in two difference habitats, e.g. burn and unburn habitat. A total of 1280 individuals from 40 families and 16 orders were collected by soil and litter extracting (Berlesse funnel). The biodiversity indices indicated that unburn habitat had a higher indices than that of burn habitat.Keywords: Diversity, Berlesse funnel, Forest Health Monitoring, unburn, soil arthropods
DETEKSI AREA BEKAS KEBAKARAN HUTAN DAN LAHAN MENGGUNAKAN DATA CITRA RESOLUSI MENENGAH MODIS DENGAN PENDEKATAN INDEKS KEBAKARAN Hanifah, Mirzha; Syaufina, Lailan; Prasasti, Indah
Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan (Journal of Natural Resources and Environmental Management) Vol 6, No 1 (2016): Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan (JPSL)
Publisher : Graduate School Bogor Agricultural University (SPs IPB)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/jpsl.6.1.77

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This research examined the use of fire index algorithms to detect and recognize the burnt area in West Kalimantan by applying the pre-fire and post-fire image comparison technique.  The main data used were derived from remotely sensed data MODIS acquired from Januari to April 2014.  The examined algorithms utilized the near-infrared (NIR) and short-infrared (SWIR) wavelength spectrums.  in the case of forest and land fires, occured the value of NIR decreases as the amount of chlorophyll decrease, while the pixel values and the inceasing value of SWIR will increase due to the rising temperature.  The research objective was to the capability of the algorithms in detecting burnt forest and land areas in several selected areas in West Kalimantan, using few indices generated from MODIS data.  The examined indices were NDFI (Normalized Difference Fire Index) and MNDFI (Modified Normalized Difference Fire Index), which utilize the reflectance values of band 2 (NIR) and band 7 (SWIR) from MODIS.  The study results show that both the NDFI and MNDFI were applicable in detecting burnt area having good performance with the Normalize Distance (D) values larger than 1.  Based on D-Value and accuracy assessment, MNDFI algorithm gave better index than the NDFI in detecting both forest and land areas.
ESTIMATION OF CARBON STOCK LOSS FROM LAND USE CHANGES IN BOGOR REGENCY PENDUGAAN HILANGNYA CADANGAN KARBON DARI PERUBAHAN PENGGUNAAN LAHAN DI KABUPATEN BOGOR Setiawana, Gatot; Syaufina, Lailan; Puspaningsih, Nining
Jurnal Silvikultur Tropika Vol. 7 No. 2 (2016): Jurnal Silvikultur Tropika
Publisher : Departemen Silvikultur, Fakultas Kehutanan, Institut Pertanian Bogor (IPB)

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Abstract

One of the primary sectors that contribute on national greenhouse gas emissions are land use changes. Land use change contributes approximately 50% of national emissions. In the context of climate change, land use change can contribute as the source and sink of carbon. Bogor Regency is one of the districts close to the capital city of Indonesia and industrial areas so that the intensity of land use changes are very dynamic. The aim of this study was to determine the dynamics of land use change and CO2-eq emissions from year 2000 to 2014 in Bogor Regency. Approach to estimate carbon stock change in this study was conducted with stock difference method, the method of calculation of carbon which assesses the carbon deposits at two time points. Most of land use change occurred in mixed garden, wetland, open land, and shrubs that converted into settlement that amounted to 33 283 ha or approximately 11.12% of the Bogor Regency, while the rate of total annual emissions of the greatest historical, namely in the period 2005-2009 amounted to 681 006.94 tones of CO2-eq / year. Increase of emissions occurred in the conversion into other land uses that have a lower carbon stock.Key words: land use change, greenhouse gas emissions, carbon stock
PEMANFAATAN PENGINDERAAN JAUH UNTUK ESTIMASI STOK KARBON DI AREA REKLAMASI PT. ANTAM UBPE PONGKOR, KABUPATEN BOGOR Tunggadewi, Andini Tribuana; Syaufina, Lailan; Puspaningsih, Nining
Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan (Journal of Natural Resources and Environmental Management) Vol 4, No 1 (2014): Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan (JPSL)
Publisher : Graduate School Bogor Agricultural University (SPs IPB)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/jpsl.4.1.49

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Mining is an environment-altering activity especially on land by reducing landcover and stored carbon. PT ANTAM, a prominent mining company in an industrial scale, is doing reclamation in order to restore the ability of the land to its optimum function. Reclamation in the relation with global warming, is an efforts to mitigate climate change by increasing the ability of land to absorb carbon (revegetation). Therefore land cover monitoring at reclamation area becomes an important thing to do, one way to do it is by using remote sensing. Not only for land cover, remote sensing also can be used to estimate carbon stocks. Based on visual interpretation of google earth image data in 2007, there were five classes of secondary forest at reclamation area of PT ANTAM UBPE Pongkor : class A (tight forest) covering 8,65 ha; class B (medium forest) covering 0,88 ha; class C (sparse forest) covering 1,57 ha; and class D (shrubs) covering 0,92 ha. Meanwhile, the calculation of carbon stocks based on three sampling locations that representing secondary forest classes A, B, and C, resulting estimated average carbon stock in the whole reclamation area of PT ANTAM UBPE Pongkor is 113,79 tons/ha. Keywords: mining, reclamation, google earth image data, carbon stock
RATIO OF HOTSPOT SOURCE AS AN INDICATOR OF FOREST AND PEAT FIRE AND ITS CORRELATION WITH RAINFALL IN SEPAHAT VILLAGE, BENGKALIS DISTRICT, RIAU Syaufina, Lailan; Siwi, Rinenggo; Nurhayati, Ati Dwi
Jurnal Silvikultur Tropika Vol. 5 No. 2 (2014): Jurnal Silvikultur Tropika
Publisher : Departemen Silvikultur, Fakultas Kehutanan, Institut Pertanian Bogor (IPB)

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Abstract

Riau is one of the areas in Indonesia which annually contributes to the regional haze problem, not only in Indonesia but also to neighboring countries, one of which comes from Sepahat village, Bukit Batu subdistrict, Bengkalis district, Province of Riau in 2009-2010 contributed the big haze until neighboring countries. Information about data hotspot may be one source of early detection information of forest fires and land. If the data hotspots combined with rainfall data, it will discover the model calculations of spatial correlation between the amounts of rainfall with the amountsof hotspot detection in Sepahat village. This study is aimed to compare hotspot of the NOAA-18 satellite with hotspot data of the TERRA-AQUA satellite and examine the correlation between rainfall and hotspot in 2008-2010. This study uses hotspot secondary data by NOAA satellite from the Ministry of Forestry of Indonesia, hotspot secondary data byAQUA TERRA satellite from Center for Applied Biodiversity (CABS), and rainfall data from the Department of Agriculture and Animal Husbandry of Bengkalis. The result of this study indicates that the number of hotspot detection captured by TERRA-AQUA satellite is higher than that of the NOAA satellite. Average hotspot detection from NOAA satellite in 2008-2010 was 11 hotspots, while average hotspot detection from TERRAAQUA satellite in 2008-2010 was 119 hotspots. While average rainfall in Bukit Batu sub-district, in 2008-2010 was 1617.8 mm/year. The result of the correlation between the amount of rainfall and hotspot detection from NOAA satellite is 0.893, while the result of the correlation between the amount of rainfall and hotspot detection from TERRA-AQUA satellite is 0.5888. Best Equation Model of rainfall with hotspot detection in Sepahat village, Bangkalis is y = 146.5 - 17.49x + 8.52x2 - 0.5444x3 whereby y is the number of hotspots of NOAA satellite and x is rainfall.
Detection and Prediction of Peatland Cover Changes Using Support Vector Machine and Markov Chain Model Khaira, Ulfa; Sitanggang, Imas Sukaesih; Syaufina, Lailan
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 14, No 1: March 2016
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v14i1.2400

Abstract

Detection and prediction of peatland cover changes needs to be done in the rapid rate of deforestation in Indonesia. This work applied Support Vector Machine (SVM) and Markov Chain Model on multitemporal satellite data. The study area is located in the Rokan Hilir district, Riau Province. SVM classification technique used to extract information from satellite data for the years 2000, 2004, 2006, 2009 and 2013. The Markov Chain Model was used to predict future peatland cover. The SVM classification result showed that the Kappa accuracy of peatland cover classification is more than 0.92. The non vegetation areas increased to 307% and the sparse vegetation areas increased to 22% between 2000 and 2013, while dense vegetation areas decreased to 61%. Prediction of future land cover by the Markov Chain Model showed that the use of multitemporal satellite data with 3 years interval provides accurate result for predicting peatland cover changes.