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All Journal MANAJEMEN HUTAN TROPIKA Journal of Tropical Forest Management Jurnal Ilmu Pertanian Indonesia Jurnal Silvikultur Tropika (JST) Indonesian Journal of Geography Jurnal Penelitian Hutan Tanaman Jurnal Penelitian Pengelolaan Daerah Aliran Sungai JURNAL METEOROLOGI DAN GEOFISIKA Indonesian Journal of Electrical Engineering and Computer Science

Muhammad Buce Saleh

Departemen Manajemen Hutan, Fakultas Kehutanan, Kampus IPB Darmaga Bogor 16680

Author-ID : 369156

Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Decision Sciences, Operations Research & Management Earth & Planetary Sciences Energy Environmental Science Physics Social Sciences

Published : 21 Documents Claim Missing Document

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Canopy Cover Estimation in Lowland Forest in South Sumatera, Using LiDAR and Landsat 8 OLI imagery Muhammad Buce Saleh; Rosima Wati Dewi; Lilik Budi Prasetyo; Nitya Ade Santi
Jurnal Manajemen Hutan Tropika Vol. 27 No. 1 (2021)
Publisher : Institut Pertanian Bogor (IPB University)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.7226/jtfm.27.1.50

Canopy cover is one of the most important variables in ecology, hydrology, and forest management, and useful as a basis for defining forests. LiDAR is an active remote sensing method that provides the height information of an object in three-dimensional space. The method allows for the mapping of terrain, canopy height and cover. Its only setback is that it has to be integrated with Landsat to cover a large area. The main objective of this study is to generate the canopy cover estimation model using Landsat 8 OLI and LiDAR. Landsat 8 OLI vegetation indices and LiDAR-derived canopy cover estimation, through First Return Canopy Index (FRCI) method, were used to obtain a regression model. The performance of this model was then assessed using correlation, aggregate deviation, and raster display. Lastly, the best canopy cover estimation was obtained using equation, FRCI = 2.22 + 5.63Ln(NDVI), with R2 at 0.663, standard deviation at 0.161, correlation between actual and predicted value at 0.663, aggregate deviation at -0.182 and error at 56.10%.

Interpretasi Visual dan Digital untuk Klasifikasi Tutupan Lahan di Kabupaten Kuningan, Jawa Barat Dede Kosasih; Muhammad Buce Saleh; Lilik Budi Prasetyo
Jurnal Ilmu Pertanian Indonesia Vol. 24 No. 2 (2019): Jurnal Ilmu Pertanian Indonesia
Publisher : Institut Pertanian Bogor

Land cover information are needed to support decision making process on natural resource management. Remote sensing has been provideingr a huge distribution of geographical land cover information on various spatial scales. Landsat 8 OLI can be used on various applications and researches, including on land cover classification. Parameters used on land cover identification can be extracted from Landsat 8 OLI (Operational Land Imager). The research tried to explore land cover classification in Kuningan District by using two different classification methods, visual and digital maximum likelihood using Landsat 8 OLI acquired on August 5th2014. The main objectives of the research were to develop land cover map and assess the result accuracy on both different methods used. Confusion matrix using Overall accuracy and Kappa value was used as a reference on defining the accuracy. As a result, visual interpretation identified 10 land cover classes with Overall accuracy of 94.02% and Kappa value of 0.93. While digital maximum likelihood identified 10 land cover classes with Overall accuracy of 93.17% and Kappa value of 0.92.

APLIKASI CITRA ALOS PALSAR UNTUK PENDUGAAN SIMPANAN KARBON DI HUTAN TANAMAN AKASIA Muhammad Abdul Qirom; Muhammad Buce Saleh; Budi Kuncahyo
Jurnal Penelitian Hutan Tanaman Vol 9, No 3 (2012): JURNAL PENELITIAN HUTAN TANAMAN
Publisher : Pusat Penelitian dan Pengembangan Hutan

Pendugaan persediaan karbon secara langsung mempunyai keterbatasan terkait dengan kecepatan memperoleh hasil, cakupan luasan yang terbatas dan biaya yang mahal. Penginderaan jarak jauh dapat dimanfaatkan untuk menduga persediaan karbon dengan akurasi yang cukup memadai. Tujuan penelitian ini yakni: 1) mendapatkan potensi simpanan karbon jenis A. mangium, 2) mendapatkan model penduga simpanan karbon berdasarkan citra Radar (nilai backscatter citra Alos Palsar), 3) mendapatkan peta sebaran potensi simpanan karbon jenis A. mangium di PT. Inhutani II, Kalimantan Selatan. Metode yang digunakan dengan melakukan inventarisasi persediaan karbon secara langsung yakni pembuatan plot pengukuran sebanyak 69 plot dengan luas masing-masing plot seluas 0,1 Ha tersebar pada beberapa umur. Hasil inventarisasi tersebut digunakan untuk membentuk hubungan dengan nilai polarisasi dari citra Alos Palsar. Hasil penelitian menunjukkan potensi simpanan karbon permukaan sebesar 32,03 - 46,10 ton/ha dengan rata-rata 39,06 ton/ha. Potensi simpanan karbon total per Ha berkisar antara 35,48 -51,01 ton/ha dengan rata-rata 43,24 ton/ha. Model alometrik terbaik hubungan antara simpanan karbon dan nilai polarisasi HH dan HV dari citra Alos Palsar adalah Simpanan karbon = 292 + 2,00 HH2 + 27,1 HV dengan koefisien determinasi sebesar 40,9%. Potensi sebaran simpanan karbon total terbesar berdasarkan aplikasi citra Alos Palsar yakni berkisar antara 40 - 80 ton/Ha. Penggunaan Alos Palsar untuk menduga simpanan karbon menghasilkan dugaan yang cukup akurat sehingga teknologi ini dapat digunakan untuk mengukur atau monitoring persediaan karbon pada tegakan hutan tanaman.

PENENTUAN JENIS TUMBUHAN LOKAL DALAM UPAYA MITIGASI LONGSOR DAN TEKNIK BUDIDAYANYA PADA AREAL RAWAN LONGSOR DI KPH LAWU DS: Studi Kasus di RPH Cepoko Determination of Local Plants Species in Mitigation Effort at Areas Prone and Cultivation Techniques .... Fibo Adhitya; Omo Rusdiana; Muhammad Buce Saleh
Jurnal Silvikultur Tropika Vol. 8 No. 1 (2017): Jurnal Silvikultur 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.8.1.9-19

Natural disasters that occur in most areas of Indonesia would certainly give rise to a wide range of impacts on the physical, social, and economic life of the society. One of these natural disasters is landslides. KPH Lawu Ds is a owned company Perhutani, which produces pine resin. KPH area Lawu Ds are generally located in areas that have a steep slope has an area prone to landslides are quite extensive. Therefore, in carrying out forest cultivation of plants which are generally homogenous need additional types of vegetation can reduce the level of vulnerability to landslides. Landslides can also be regarded as a form of land use that have little or no attention to soil conservation techniques, but in this study only look from the vegetation in developing soil conservation techniques in homogeneous plantation forests in the forest management unit areas KPH Lawu Ds. Therefore, the purpose of this study was to obtain the right local plant species as the plant are prioritized and appropriate to prevent the occurrence of landslides and obtain the shape and pattern of cultivation. Data analysis using descriptive analysis of qualitative and models that fit the preferences of local preferences of plants grown on land prone to landslides in RPH Cepoko by using the method of AHP (Analytical Hierarchy Process). Alternatives are obtained based on the plants prioritized is clove, coffee, chocolate, calliandra, Leucaena leucocephala, durian, Swietenia macrophylla, Aleuriteus Moluccana, Paraserianthes falcataria, Pangium edule, Anacardium occidentale , and Sterculia foetida and cultivation techniques of forest vegetation on the sides of the plant adjusted based onsolum soil, slope and vegetation cover of pine with dense composition, middle and rare on research plots in the area of KPH Lawu Ds and planting distance is determined by the density of the canopy.Key words: mitigation, native plant species, preference, cultivation techniques.

TIPE KOMUNITAS HUTAN LAHAN KERING DI HUTAN LINDUNG SENTAJO, KABUPATEN KUANTAN SINGINGI, RIAU Community Types of Dryland Forest Within The Sentajo Protected Forest, Kuantan Singingi Regency, Riau Province Pebriandi .; Omo Rusdiana; Muhammad Buce Saleh
Jurnal Silvikultur Tropika Vol. 8 No. 2 (2017): Jurnal Silvikultur 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.8.2.103-109

Sentajo Protected Forest located in Kuantan Singingi Regency, Riau Province. There is no information about vegetation diversity in this location. Therefore this study was conducted. This study aimed to determine the diversity of vegetation, structure, and composition of each community in Sentajo Protected Forest. The study was conducted in April-September 2016. A sampling design was determined using systematic sampling with random start. The sampling intensity used was 5%. The parameters measured in this study were the importance value index, similarity index between communities, species diversity index, evenness index, dominance index, regeneration, as well as horizontal and vertical structures. Based on the type of soil, elevation, and slope, 6 communities were grouped from the dense coverage area (forested). The results showed that the Sentajo Protected Forest had 424 flora consisted of 254 species, and 102 families. Sentajo Protected Forest had similarity index between 18 - 64%, species diversity index of 2.62 - 4.15, evenness index of 0.59 - 0.86, dominance index of 0.02 - 0.08. The larger the diameter of the tree, the smaller the number of individuals. The stratification of the canopy had 5 layers of canopy. Sentajo Protected Forest regeneration was relatively good as the number of seedlings> saplings> mature trees.Key words: community, composition and structure, diversity, Sentajo Protected Forest.

Ecosystem Services Dynamics in Bogor Regency Sri Lestari Munajati; Hariadi Kartodihardjo; Muhammad Buce Saleh; Nurwadjedi Nurwadjedi
Indonesian Journal of Geography Vol 53, No 2 (2021): Indonesian Journal of Geography
Publisher : Faculty of Geography, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijg.64493

The decline in the quality of ecosystem services in Bogor Regency is indicated by the existence of various natural disasters in recent years. Prudent development must be carried out to minimize the impact of a decrease in the ecosystem services index. The purpose of this research is to map ecosystem services for food supply, water supply, water and flood management, and tourism aspects within 2000-2017. The data used were land cover and land facet maps at a scale of 1:25,000 obtained from BIG, accompanied by a reinterpretation process. The data sources were Indonesia's topographic maps (RBI), Citra SPOT 7, DEMNAS, and field surveys. The ecosystem services index (ESI) is calculated based on an analysis of changes in land use and land facets. The value of ESI was weighted using analytic hierarchy process approaches to each of the variables assessed by experts. The results showed that the largest changes in land use occurred in residential and forest areas. The residential area increased by 1.96%, while the forest area decreased by 1.8% in 17 years. Bogor Regency is dominated by forest and rice fields which are spread over four main landforms, namely volcanic, structural, fluvial, and karst. The most significant increase of 5.65% was found in the clean water provisioning function, while the most significant decrease of 38.47% was found in the tourism and ecotourism sector. Accumulatively, the increase in ESI was 23%, while the decrease was 20.64%. Mitigation efforts that can be done are to maintain the availability of green open space by implementing strong regulations.

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 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

ASSESSMENT OF ATMOSPHERIC CORRECTION METHODS FOR OPTIMIZING HAZY SATELLITE IMAGERIES Umara Firman Rizidansyah; Muhammad Buce Saleh; Antonius Bambang Wijanarto
Jurnal Meteorologi dan Geofisika Vol 15, No 3 (2014)
Publisher : Pusat Penelitian dan Pengembangan BMKG

Tujuan penelitian ini untuk menguji kesesuaian tiga jenis metode koreksi haze terhadap kejelasan obyek permukaan di wilayah tutupan vegetasi dan non vegetasi, berkenaan menghilangkan haze di wilayah citra satelit optis yang memiliki karakteristik tertentu dan diduga proses pembentukan partikel hazenya berbeda. Sehingga daerah penelitian dibagi menjadi wilayah rural yang diasumsikan sebagai daerah vegetasi dan urban sebagai non vegetasi. Pedesaan terpilih kecamatan Balaraja dan Perkotaan terpilih kecamatan Penjaringan. Tiap lokasi menggunakan Avnir-2 dan Landsat 7. Untuk mendapatkan hasil pengurangan kabut di kedua lokasi tersebut digunakan metode Dark Object Substraction (DOS), Virtual Cloud Point (VCP) dan histogram Match (HM) dengan persamaan nilai optimasi kabut HOT = DNbluesin(∂)-DNredcos(∂). hasil penelitian ini sebagai berikut: dalam hal AVNIR-Rural, VCP memiliki hasil yang baik di Band-1 sedangkan HM memiliki hasil yang baik pada band-2, 3 dan 4 sehingga dalam kasus AVNIR-Rural dapat diterapkan HM. Dalam hal AVNIR-Urban, DOS memiliki hasil yang baik pada band-1, 2 dan 3. Sementara HM memiliki hasil yang baik pada band 4, sehingga dalam kasus AVNIR-Urban dapat diterapkan DOS. Dalam kasus Landsat-Rural, DOS memiliki hasil yang baik pada band-1, 2 dan 6, Sementara VCP memiliki hasil yang baik pada band 4 dan 5. Sehingga dalam kasus Landsat-Rural dapat diterapkan DOS. Dalam hal Landsat-Urban, DOS memiliki hasil yang baik pada band-1, 2 dan 6 sedangkan VCP memiliki hasil yang baik pada band-3, 4, dan 5. Sehingga dalam hal Landsat-Urban dapat diterapkan VCP. Semakin baik citra hasil koreksi semakin kecil nilai optimasi kabut, nilai rata–rata terkecil adalah 106,547 dengan VCP di Landsat-Rural. The purpose of this research is to examine the suitability of three types of haze correction methods toward the distinctness of surface objects in land cover. Considering the formation of haze, therefore, the main research is divided into both region namely rural assumed as vegetation and urban assumed as non-vegetation area. Region of interest for rural selected Balaraja and urban selected Penjaringan. Haze imagery reduction utilized techniques such as Dark Object Subtraction, Virtual Cloud Point and Histogram Match. By applying an equation of Haze Optimized Transformation HOT = DNbluesin(∂)-DNredcos(∂), the main result of this research includes: in the case of AVNIR-Rural, VCP has good results on Band 1 while the HM has good results on band 2, 3 and 4, therefore in the case of Avnir-Rural can be applied to HM. in the case of AVNIR-Urban, DOS has good result on band 1, 2 and 3 meanwhile HM has good results on band 4, therefore in the case of AVNIR-Urban can be applied to DOS. In the case of Landsat-Rural, DOS has a good result on band 1, 2 and 6 meanwhile VCP has good results on band 4 and 5 and the smallest average value of HOT is 106.547 by VCP, therefore in the case of Lansat-Rural can be applied to DOS and VCP. In the case of Landsat-Urban, DOS has a good result on band 1, 2 and 6 meanwhile VCP has good results on band 3, 4 and 5, therefore in the case of Landsat-Urban can be applied to VCP.

Information Required for Estimating The Indicator of Forest Reclamation Success in Ex Coal-Mining Area Hasriani Muis; I Nengah Surati Jaya; Muhammad Buce Saleh; Kukuh Murtilakono
Indonesian Journal of Electrical Engineering and Computer Science Vol 3, No 1: July 2016
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v3.i1.pp182-193

This paper describes how the information of the key indicators for assessing the degree of forest reclamation success in ex coal-mining area was identified. Those indicators were analyzed using the descriptive statistic as well as the discriminant analysis on the basis of biophysical data representing age class of vegetation after reclamation. The main objective of the study was to find out the predominant key indicator that determines the success of forest reclamation in ex coal-mining areas. This study found that the variance of basal area, green biomass and increment was relatively high between young plantation and old plantation. The study confirmed that the variation of the success of reclamation was strongly influenced by site quality. . The study concluded that the best indicators to be used for assessing the success of forest reclamation was the increment providing accuracy more than 79.6% either for indicator five or three classes.

Algorithm for assessing forest stand productivity index using leaf area index Faid Abdul Manan; Muhammad Buce Saleh; I Nengah Surati Jaya; Uus Saepul Mukarom
Indonesian Journal of Electrical Engineering and Computer Science Vol 16, No 3: December 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v16.i3.pp1311-1319

This paper describes a development of an algorithm for assessing stand productivity by considering the stand variables. Forest stand productivity is one of the crucial information that required to establish the business plan for unit management at the beginning of forest planning activity. The main study objective is to find out the most significant and accurate variable combination to be used for assessing the forest stand productivity, as well as to develop productivity estimation model based on leaf area index. The study found the best stand variable combination in assessing stand productivity were density of poles (X2), volume of commercial tree having diameter at breast height (dbh) 20-40 cm (X16), basal area of commercial tree of dbh >40 cm (X20) with Kappa Accuracy of 90.56% for classifying into 5 stand productivity classes. It was recognized that the examined algorithm provides excellent accuracy of 100% when the stand productivity was classified into only 3 classes. The best model for assessing the stand productivity index with leaf area index is y = 0.6214x - 0.9928 with R2= 0.71, where y is productivity index and x is leaf area index.

Co-Authors Afandi Ahmad Ahyar Gunawan Antonius Bambang Wijanarto Ari Ardelina Tatang Tiryana Muhdin, Ari Ardelina Tatang Tiryana Beni Iskandar Budi Kuncahyo Budi Kuncahyo Dede Kosasih Dewayany Sutrisno Dwi Noventasari Eva Achmad Faid Abdul Manan Fibo Adhitya Hanifah Ikhsani Hariadi Kartodihardjo Hasriani Muis I Gusti Bagus Wiksuana I Nengah Surati Jaya I Nengah Surati Jaya I Nengah Surati Jaya Irlan Kukuh Murtilakono Lilik Budi Prasetyo Liu Qian Muhammad Abdul Qirom Nanin Anggraini Nining Puspaningsih Nitya Ade Santi Nitya Ade Santi Nurwadjedi Nurwadjedi Omo Rusdiana Pebriandi Pebriandi Putu Ananta Wijaya Ricca Rohani Hutauruk Rosima Wati Dewi Sri Lestari Munajati Syamsu Rijal Teddy Rusolono Umara Firman Rizidansyah Uus Saepul Mukarom Wang Xuenjun Yudi Armanda Syahputra Yudi Setiawan Zhang Yuxing

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