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PEMANFAATAN PENGINDERAAN JAUH UNTUK ESTIMASI STOK KARBON DI AREA REKLAMASI PT. ANTAM UBPE PONGKOR, KABUPATEN BOGOR Andini Tribuana Tunggadewi; Lailan Syaufina; Nining Puspaningsih
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

Abstract

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
ESTIMASI HILANGNYA CADANGAN KARBON DARI PERUBAHAN PENGGUNAAN LAHAN DI KABUPATEN BOGOR Gatot Setiawan; Lailan Syaufina; Nining Puspaningsih
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
PREDIKSI PERUBAHAN TUTUPAN LAHAN DENGAN MODEL MARKOV CHAIN DAN ANN-MARKOV DI DAS KRUENG ACEH (Land cover change prediction using Markov Chain and ANN-Markov Model in Krueng Aceh Watershed) Yudi Armanda Syahputra; Muhammad Buce Saleh; Nining Puspaningsih
Jurnal Penelitian Pengelolaan Daerah Aliran Sungai (Journal of Watershed Management Research) Vol 5, No 2 (2021): Jurnal Penelitian Pengelolaan Daerah Aliran Sungai (Journal of Watershed Managem
Publisher : Center for Implementation of Standards for Environmental and Forestry Instruments Solo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20886/jppdas.2021.5.2.185-206

Abstract

ABSTRACT Prediction of land cover change will be a consideration in determining the development strategy in the future. There are many methods for predicting  land cover change. It depends on data availability, model algorithms and output needed. The objective of this reasearch was to predict land cover change from 2007 to 2020 in the Krueng Aceh watershed. The method used remote sensing and GIS.  The Markov Chain (MC) and Artificial Neural Network-Markov (ANN-M) models were used to understand the spatio-temporal dynamics of land cover. The accuracy of the classified imagery was obtained from on-screen digitation using  medium resolution landsat-8 OLI image in 2020 with Kappa Accuracy around 84%. Both prediction algorithms used year 2007 (T1) and year 2017 (T2) land cover data to calculated the probability of land cover change prediction in year 2020 (T3). The Kappa Accuracy of both models shows a strong correlation between the simulated land cover maps and the results of visual interpretation (ANN=87.81% and MC=88.69%), this proves high accuracy of both models. Key words: model; ANN-Markov; landcover change prediction; Markov Chain ABSTRAKPrediksi perubahan tutupan lahan yang baik akan menjadi pertimbangan dalam menentukan strategi pembangunan di masa depan. Terdapat banyak metode dalam melakukan prediksi perubahan tutupan lahan yang tergantung pada kebutuhan data, algoritma pemodelan yang dilakukan dan output apa saja yang diperlukan. Penelitian ini dilakukan untuk mengkaji model prediksi perubahan tutupan lahan dari tahun 2007 hingga 2020 di DAS Krueng Aceh. Pendekatan yang dilakukan menggunakan penginderaan jauh dan SIG. Model Markov Chain (MC) dan Artificial Neural Network-Markov (ANN-MC) digunakan untuk memahami dinamika spatio-temporal tutupan lahan. Akurasi dari citra penginderaan jauh yang diklasifikasikan diperoleh dari hasil interpretasi visual pada citra resolusi sedang Landsat OLI tahun 2020 dengan nilai Kappa Accuracy sebesar 84%. Kedua model prediksi menggunakan data tutupan lahan tahun 2007 (T1) dan 2017 (T2) untuk membuat probabilitas perubahan yang digunakan dalam memprediksi tutupan lahan pada tahun 2020 (T3). Validasi kedua algoritma menunjukkan korelasi yang kuat dengan peta tutupan lahan 2020, hal tersebut membuktikan kehandalan model kedua simulasi (ANN=87,81% dan MC=88,69%).Kata kunci: model; ANN-Markov; prediksi tutupan lahan; Rantai Markov
OPTIMASI USULAN PERUBAHAN KAWASAN HUTAN DALAM RENCANA TATA RUANG WILAYAH PROVINSI (RTRWP) DI PROVINSI KALIMANTAN TIMUR Donny Satria; Omo Rusdiana; Nining Puspaningsih
Journal of Environmental Engineering and Waste Management Vol 2, No 1 (2017)
Publisher : President University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (625.685 KB) | DOI: 10.33021/jenv.v2i1.167

Abstract

In 2009 the province of East Kalimantan submitted the proposed changes of forest area of ± 2.535.858 ha, however the recommended changes only  ± 464.895 ha (18.33% of the proposal), according to the figure can be seen that there were significant gaps (differences) among the proposed changes with recommendations for forest areas changes that need to be optimized in any proposed changes of forest area by calculating the capacity of the environment in accordance to the Minister of Environment Regulation Number 17 of 2009 as well as spatial analysis. The purpose of this research was to determine land  requirements, the effectiveness of land-use and forest areas that still have the potential for the proposed changes. Referring to the data processing, it was discovered that East Kalimantan Province in 2015 experienced the surplus of  land availability of  ± 1.374.046 ha and  it was discovered that there are still non-productive land area of  ± 2.774.571 ha. The results of  the spatial data analysis suggests that changes of forest area can still be done in 8 districts/cities with a total area of ±132.578,57 ha.
POLA SEBARAN SPASIAL BIOMASSA DI AREAL REVEGETASI BEKAS TAMBANG NIKEL Witno Witno; Nining Puspaningsih; Budi Kuncahyo
Jurnal Penelitian Kehutanan BONITA Vol 1, No 2 (2019): Desember 2019
Publisher : Universitas Andi Djemma Palopo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55285/bonita.v1i2.308

Abstract

The aim of this study was to identify the spatial pattern of biomass distribution in the revegetation of the post-mining area in PTVI. The nearest neighbour analysis method by comparing the distance of an individual was used to determine the spatial biomass distribution pattern in the post nickel mining revegetation area of PTVI. The nearest neighbour analysis was used to explain the distribution pattern of locations using a calculation that considers the distance, number of locations and acreage. This analysis produced a final result in the form of an index ranging from 0 until more than 1. It can be explained as NNI 1, clustered spatial pattern, NNI = 1, random spatial pattern and NNI 1 dispersed spatial pattern. This research was found that there are clustered (K1, K2, K3) and dispersed patterns (K4) of biomass spatial distribution patterns in PTVI’s post nickel mining revegetation area.Keywords: post-mining, revegetation, biomass, spatial distribution pattern
Ground Water Level as an Indicator of Fire in Tanjung Jabung Timur, Jambi Province Atfi Indriany Putri; Lailan Syaufina; Nining Puspaningsih
Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan (Journal of Natural Resources and Environmental Management) Vol 12 No 4 (2022): Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan (JPSL)
Publisher : Pusat Penelitian Lingkungan Hidup, IPB (PPLH-IPB) dan Program Studi Pengelolaan Sumberdaya Alam dan Lingkungan, IPB (PS. PSL, SPs. IPB)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/jpsl.12.4.749-756

Abstract

Kebakaran hutan dan lahan setiap tahunnya menjadi salah satu isu lingkungan yang menjadi perbincangan masyarakat, baik tingkat lokal, nasional, hingga internasional. Faktor yang mempengaruhi kebakaran di lahan gambut antara lain: tinggi muka air, hotspot, dan curah hujan. Badan Restorasi Gambut dan Mangrove beberapa tahun ini telah membuat alat dalam bentuk sensor Sistem Pemantauan Air Lahan Gambut (SIPALAGA) dengan tujuan pengukuran tinggi muka air. Tujuan dari penelitian ini ialah untuk (1) menganalisis hubungan tinggi muka air dengan hotspot sebagai indikator terjadinya kebakaran hutan dan lahan, serta (2) menganalisis tinggi muka air dengan curah hujan. Kabupaten Tanjung Jabung Timur memiliki distribusi hotspot periode Januari 2019 – Desember 2021 senilai 916 titik panas (hotspot). Hasil uji korelasi hubungan hotspot dengan tinggi muka air memperoleh nilai korelasi sedang dengan nilai -0.408 dan P-Value 0.001, hal tersebut menunjukkan bahwa hotspot dengan tinggi muka air mempunyai hubungan negatif, yang artinya tinggi nilai hotspot akan diikuti bersama-sama dengan turunnya nilai tinggi muka air. Adapun untuk korelasi tinggi muka air dengan curah hujan mendapatkan nilai korelasi tinggi dengan nilai 0.705 dengan nilai P-Value sebesar 0.001 dan memiliki notasi positif, yang artinya tingginya jumlah curah hujan akan diikuti Bersama tingginya nilai tinggi muka air.
Developing a Spatial Mathematical Model for Assessing the Rate of Natural Forest Changes Dahlan Dahlan; I Nengah Surati Jaya; Muhammad Buce Saleh; Nining Puspaningsih; Muzailin Affan
Aceh International Journal of Science and Technology Vol 12, No 1 (2023): April 2023
Publisher : Graduate Program of Syiah Kuala University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13170/aijst.12.1.31703

Abstract

Establishing a spatial mathematical model that uses diverse data types such as ratio data, interval data, and ordinal and nominal data is a challenge. This paper describes how the mathematical model of the rate of natural forest cover change was developed by considering the causes and/or driving forces that come from the society's biophysical and/or socioeconomic aspects. The main objective of this research is to establish a spatial mathematical model using the environmental and socioeconomic variables that play a significant role in determining the rate of natural forest cover change. From a number of variables considered in the analysis, coupled with any other reason, the rate of natural forest cover change (y), in units of ha per year), this study found that there are 10 potential variables, namely the proximity of the road (x4), the proximity of the river (x5), the proximity of the settlement (x6), proximity from the regency capital (x8), the proximity of the capital city of the district (x9), proximity of the edge of the forest in 2015 (x11), the proximity of the plantation area in 2009 (x12), the proximity of the plantation in 2015 (x13), slope class (x16), and elevation class (x17). The standardization process successfully transformed the non-ratio data type into a ratio data type. Using the standardized data, the study obtained spatially mathematical models that are reliable in estimating the rate of forest cover change, namely y = 0.017 + 0.00040x9 with SR of 17.3% and R2 is 88.0%. The study concludes that the most significant factor affecting the natural forest cover change in the study site is the proximity of the district's capital city (x9). Therefore, a spatial mathematical model can facilitate the government in monitoring forest cover.
Estimation Model of Site Quality of Teak (Tectona grandis) Using Very High-Resolution Imagery from Unmanned Aerial Vehicle in KPH Nganjuk Kusnadi; I Nengah Surati Jaya; Nining Puspaningsih; Makin Basuki; Lukman Hakim
Jurnal Penelitian Kehutanan Wallacea Vol. 5 No. 2 (2016)
Publisher : Foresty Faculty of Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (925.323 KB) | DOI: 10.18330/jwallacea.2016.vol5iss2pp185-194

Abstract

Site quality is one of the main information needed in forest stand management. Site quality classes need to be evaluated every certain period because the quality of forest stands may change as a result of management applied. This study describes the use of very high-resolution imagery derived from unmanned aerial vehicle (UAV) for estimating the site quality of teak (Tectona grandis). The UAV imagery used was taken from 400 m above datum (the average land surface elevation) with ground spatial resolution of 15 cm. Site quality estimation models was built using discriminant analysis. The study found that the best accuracy from discriminant function using multiple variables canopy density (C) and average of crown diameter (Dc ̅̅̅) is 60.9%.
Dynamics of Change in Mangrove Forest Cover as a Protected Area Using Satellite Image on Peleng Island, Central Sulawesi Mohammad Malik; Kuncahyo, Budi; Puspaningsih, Nining
Journal of Tropical Silviculture Vol. 14 No. 03 (2023): Jurnal Silvikutur Tropika
Publisher : Departemen Silvikultur, Fakultas Kehutanan dan Lingkungan, Institut Pertanian Bogor (IPB)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/j-siltrop.14.03.183-190

Abstract

Mangrove forest is an important ecosystem supporting the life activities of coastal communities because it has various functions so it is very vulnerable to various disturbances. This problem is an important factor in the decline in the ability of mangroves to maintain the stability of the coastal ecosystem. Therefore, it is necessary to monitor and evaluate the dynamics of mangrove cover change in a spatio-temporal manner using remote sensing methods. Landsat imagery with a spatial resolution of 30 m was chosen as a data source to analyze the dynamics of mangrove forest cover. The purpose of the study was to measure, map and estimate the area of mangrove cover in 2019 and build a guided classification of mangrove cover changes in 2029 to estimate changes in mangrove forest cover, vegetation analysis to calculate diversity values and the Markov chain method using software. Stella. The results showed that the value of mangrove vegetation diversity in the belta strata was higher than the tree strata. Based on the significance value according to the criteria of ecosystem stability, it shows that the mangrove vegetation on Peleng Island is in the medium category and quite stable. Mangrove forests have continued to decline by 10.21% from 1999 to 2019, and in 2029 it is predicted that the area will continue to decline if this condition is left without any government policies that regulate it. Keywords: Dynamics, diversity, Landsat, mangroves, Peleng Island
Carbon Stock Estimation on Oil Palm Plantations and Oil Palm-Based Agroforestry in Gunung Mas Regency Rosaprana, Wanella; Kuncahyo, Budi; Puspaningsih, Nining
Media Konservasi Vol. 28 No. 3 (2023): Media Konservasi Vol 28 No 3 December 2023
Publisher : Department of Forest Resources Conservation and Ecotourism - IPB University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/medkon.28.3.253-261

Abstract

Central Kalimantan has one of the highest rates of deforestation and palm oil production in Indonesia. These changes have ecological impacts such as loss of animals, loss of water absorption functions, and increased carbon emissions. Agroforestry is a synergistic planting system between agricultural crops and forest stands to maintain the ecological balance. Sengons are legume plants that can be utilized in agroforestry systems. This study aimed to calculate the amount of belowground and aboveground carbon stocks on palm oil plantations and agroforestry lands consisting of palm oil and sengon trees in Manuhing and Rungan Barat districts. Belowground carbon consist of soil carbon, which is affected by the soil depth, bulk density, and soil C-organic value. Aboveground carbon consists of the sum of litter carbon, undergrowth carbon, and top stand vegetation carbon. Belowground carbon was measured using both disturbed and undisturbed methods. Litter and undergrowth carbon were measured using a destructive method, then top stand vegetation was measured by the allometric equations using breast height diameter. The comparison from all carbon pool shows that the palm oil plantations (2106,520 tons/ha) was higher than agroforestry lands (1834,734 tons/ha). This difference is strongly influenced by the potential of the different in belowground carbon stock for each land-use type. The highest potential carbon stock from this study was owned by belowground carbon stock. In the Manuhing district, belowground carbon stock was led by agroforestry lands (1786,907 tons/ha), whereas in the Rungan Barat district was led by palm oil plantations (1756,291 tons/ha).