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All Journal HAYATI Journal of Biosciences Indonesian Journal of Geography Jurnal Teknik ITS IPTEK Journal of Proceedings Series IPTEK The Journal for Technology and Science Forum Geografi Jurnal Geosaintek Journal of Applied Geospatial Information Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Jurnal Penginderaan Jauh Indonesia Jurnal Ners SEWAGATI: Jurnal Pengabdian Kepada Masyarakat Jurnal Geosaintek Jurnal Penginderaan Jauh Indonesia Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Geoid - Journal of Geodesy and Geomatics
Jaelani, Lalu Muhamad
Departemen Teknik Geomatika Institut Teknologi Sepuluh Nopember
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WorldView-2 Satellite Image Classification using U-Net Deep Learning Model Ilyas Ilyas; Lalu Muhamad Jaelani; Muhammad Aldila Syariz; Husnul Hidayat
Journal of Applied Geospatial Information Vol 5 No 2 (2021): Journal of Applied Geospatial Information (JAGI)
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jagi.v5i2.3150

Abstract

Land cover maps are important documents for local governments to perform urban planning and management. A field survey using measuring instruments can produce an accurate land cover map. However, this method is time-consuming, expensive, and labor-intensive. A number of researchers have proposed using remote sensing, which generates land cover maps using an optical satellite image with various statistical classification procedures. Recently, artificial intelligence (AI) technology, such as deep learning, has been used in multiple fields, including satellite image classification, with satisfactory results. In this study, a WorldView-2 image of Terangun in Aceh Province, which was acquired on Aug 2, 2016, was classified using a commonly used deep-learning-based classification, namely, U-net. There were eight classes used in the experiment: building, road, open land (such as green open space, bare land, grass, or low vegetation), river, farm, field, aquaculture pond, and garden. For comparison, three classification methods: maximum-likelihood, random forest, and support vector machine, were performed compared to U-Net. A land cover map provided by the government was used as a reference to evaluate the accuracy of land cover maps generated using two classification methods. The results with 100 randomly selected pixels revealed that U-Net was able to obtain a 72% and 0.585 for overall and kappa accuracy, respectively; whereas, overall accuracy and kappa accuracy for the maximum likelihood, random forest and support vector machine methods were 49% and 0.148; 59% and 0.392; and 67% and 0. 511; respectively. Therefore, U-Net outperformed those three of classification methods in classifying the image.
PENGARUH ALGORITMA LYZENGA DALAM PEMETAAN TERUMBU KARANG MENGGUNAKAN WORLDVIEW-2, STUDI KASUS: PERAIRAN PLTU PAITON PROBOLINGGO (THE EFFECT OF LYZENGAS ALGORITHM ON CORAL REEF MAPPING USING WORLDVIEW-2, A CASE STUDY: COASTAL WATERS OF PAITON PROBOLINGGO) Lalu Muhamad Jaelani; Nurahida Laili; Yennie Marini
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 12 No. 2 Desember 2015
Publisher : Indonesian National Institute of Aeronautics and Space (LAPAN)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (807.824 KB)

Abstract

Peta ekosistem terumbu karang sebagai salah satu data pendukung pengelolaan wilayah pesisir bisa diperoleh dengan memanfaatkan citra satelit resolusi tinggi. Berbagai metode ekstraksi informasi dasar laut telah dikembangkan dan dapat dimanfaatkan, salah satunya adalah menggunakan algoritma Lyzenga. Algoritma ini mensyaratkan adanya variasi kedalaman pada wilayah pesisir perairan yang akan dipetakan. Tujuan penelitian ini adalah untuk mengetahui pengaruh penggunaan algoritma dalam pemetaan ekosistem terumbu karang dengan melakukan perbandingan hasil ekstraksi kenampakan dasar laut antara citra yang diproses menggunakan algoritma Lyzenga dan citra tanpa algoritma Lyzenga. Proses klasifikasi citra dengan algoritma Lyzenga menunjukkan kenampakan obyek di bawah permukaan laut yang lebih mudah dikenali dalam format nilai indeks Lyzenga yang telah terbebas dari pengaruh kedalaman. Dalam penelitian ini dihasilkan beberapa kelas tutupan dasar perairan dangkal di sekitar PLTU Paiton yakni kelas lautan, daratan, pasir, dan terumbu karang. Estimasi luasan tutupan terumbu karang di perairan PLTU Paiton berdasarkan data Worldview dua ini adalah 8,26 Ha. Pemetaan terumbu karang dengan memanfaatkan citra satelit resolusi tinggi sangat membantu memberikan kenampakan mencakup wilayah lebih luas dibandingkan dengan pengamatan langsung di lapangan.Kata Kunci: Lyzenga, Pesisir, Terumbu karang, Worldview 2
An Extensive Coverage Anoa Distribution Modelling in Sulawesi Using Maximum Entropy Lalu Muhamad Jaelani; Benedict; Diah Ardiani; Mangapul Parlindungan Tambunan; Mochamad Indrawan; Andri A. Wibowo
HAYATI Journal of Biosciences Vol. 30 No. 4 (2023): July 2023
Publisher : Bogor Agricultural University, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.4308/hjb.30.4.716-724

Abstract

As an endangered species, Anoa (Bubalus depressicornis and Mountain Bubalus quarlesi) inhabiting the Sulawesi island requires proper conservation both in and out of their native habitat. The study of anoa habitat is mainly conducted through field studies based on firsthand observations of anoa appearance, footprints, or excrement or through social surveys from residents who saw it directly. The studies are carried out specifically in a particular area with a relatively narrow. However, in practice, this method has limitations, such as the research location determined based on the possibility of anoa, limited research area, and inefficient use of resources. Therefore, this study aimed to model the potential habitat of anoa in the whole of Sulawesi island. This study was based on physical and environmental independent variables such as DEM, surface slope, LST, NDVI, and access to inland water, as well as in-situ species distribution retrieved from scientific papers and reports. This study discovered the likely anoa distribution on Sulawesi island, both inside and outside of its native habitat. LST is the most important independent variable in determining habitat suitability, accounting for 80% of the total, followed by water (15.3%), NDVI (2.9%), DEM (1.6%), and slope (0.3%).
Estimation of Sea Surface Salinity Concentration from Landsat 8 OLI Data in The Strait of Madura, Indonesia Muhsi Muhsi; Bangun Muljo Sukojo; Muhammad Taufik; Pujo Aji; Lalu Muhamad Jaelani
Forum Geografi Vol 36, No 2 (2022): December 2022
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/forgeo.v36i2.19941

Abstract

Remote sensing technique to estimate the sea surface salinity has been widely implemented in the seas of various regions. The interface between them was developed using a regression equation like the algorithm in previous research. However, the use of this algorithm for waters in Indonesia, especially in Madura Strait, still requires some adjustment since it is related to the characteristics of different areas in which the algorithm was developed. The development of an applicable local algorithm was performed by finding the best coefficient value in estimating sea surface salinity by considering the value of its lowest NMAE (Normalized Mean Absolute Error). By using salinity and in-situ Rrs(l) (Reflectance of remote sensing) data, we found that the coefficient for the slope was -0.0092, and the intercept was 1.4903. The developed algorithm produces higher accuracy than the existing algorithm, with an NMAE of 0.51%. This NMAE value is smaller than previous research, so this new model can be used to estimate sea surface salinity, particularly in Indonesian sea waters.
Estimation of Nitrogen Content of Rice Crops Using Sentinel-2 Data Agustina, Heni; Jaelani, Lalu Muhamad; Sanjaya, Hartanto
Indonesian Journal of Geography Vol 56, No 3 (2024): 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.88571

Abstract

Nitrogen (N) is one of the most essential nutrients for rice crops. Farmers generally provide Nitrogen requirements in rice through fertilization, but the fertilization process is only based on an estimation without calculating the amount needed first. However, neither insufficient nor excessive nitrogen content is good for rice crops, and the nitrogen needs of rice crops are different at each growth stage. The nitrogen requirement in the generative phase is relatively high because the process of panicle formation and grain filling occurs at this stage. Several methods can be used to monitor nitrogen content in rice, one of which is using remote sensing methods. With the vegetation index approach, the nitrogen content of rice plants is estimated through data analysis of the light spectrum reflected by the leaf. Sentinel-2 satellite imagery was used in this research, and several vegetation indexes such as OSAVI, GNDVI, and SRRE were applied to form an estimation model using the regression method. From the results, three vegetation indexes positively correlate with nitrogen content in rice crops. The SRRE index gives the highest correlation coefficient value of 0.692, while the correlation coefficient value for GNDVI is 0.498, and OSAVI is only 0.470. The estimation map of the nitrogen content of rice crops was obtained based on the estimation model made by linear regression between SPAD-based nitrogen content data and the best vegetation index using the SRRE index. The analysis shows that the nitrogen content of rice plants estimated in the paddy fields of Karangjati Subdistrict is dominated by nitrogen values with optimum classification.
Estimasi Konsentrasi Klorofil-a menggunakan Refined Neural Network (Studi Kasus: Perairan Danau Kasumigaura) Muhammad Aldila Syariz; Lino Garda Denaro; Salwa Nabilaha; Dewinta Heriza; Lalu Muhamad Jaelani; Chao-Hung Lin
Jurnal Penginderaan Jauh Indonesia Vol 1 No 1 (2019)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/jpji.v1i1.253

Abstract

Klorofil-a menjadi salah satu bagian penting dalam merepresentasikan tingkat kesahatan suatu perairan. Beberapa peneliti menggunakan metode neural network untuk mengestimasi konsentrasi klorofil-a di wilayah perairan. Namun, dikarenakan oleh tidak mumpuninya jumlah sampel data pada beberapa stasiun, keakuratan hasil estimasi menjadi kurang dapat dipercaya. Inverse distance weighting (IDW) akan digunakan dalam penelitian untuk menginterpolasi konsentrasi klorofil-a di wilayah perairan non stasiun sehingga dapat memperkaya data sampel. Data sampel non stasiun ini selanjutnya digunakan dalam proses training pada neural network; dan selanjutnya, data sampel pada stasiun akan digunakan dalam proses network refinement sehingga tingkat akurasi dalam mengestimasi konsentrasi klorofil-a menjadi meningkat. Citra MERIS akan digunakan dalam penelitian ini. Berdasarkan hasil analisa statistik, nilai RMSE sebelum dan sesudah network refinement menurun dari 6,7872 mg m-3 menjadi 6,5606 mg m-3.
Analisis Pengaruh Tutupan Lahan terhadap Distribusi Suhu Permukaan: Kajian Urban Heat Island di Jakarta, Bandung dan Surabaya Handis Muzaky; Lalu Muhamad Jaelani
Jurnal Penginderaan Jauh Indonesia Vol 1 No 2 (2019)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/jpji.v1i2.258

Abstract

Pada tahun 2015, lebih dari setengah penduduk Indonesia tinggal di kawasan perkotaan hingga menyebabkan tumbuhnya kawasan kedap air di perkotaan. Material kedap air merupakan penyimpan panas yang baik. Akibatnya suhu udara di daerah ini menjadi lebih tinggi dibandingkan dengan daerah sekitarnya. Fenomena ini dikenal dengan istilah Urban Heat Island (UHI). Untuk mengetahui dampak UHI, diperlukan pemantauan suhu secara terus-menerus. Pemantauan suhu menggunakan stasiun cuaca memiliki keterbatasan dari segi cakupan wilayah, sehingga metode penginderaan jauh digunakan untuk mendapatkan data dengan sebaran spasial yang luas. Penelitian ini mengkaji fenomena UHI di tiga kota terpadat di Indonesia (Kota Jakarta, Bandung, dan Surabaya) menggunakan data citra satelit Landsat 8 OLI/TIRS. Perhitungan Suhu Permukaan Tanah (LST) menggunakan metode algoritma Single Channel (SC) serta identifikasi penutupan lahan menggunakan indeks spektral: Normalized Difference Vegetation Index (NDVI), Modified Normalized Difference Water Index (MNDWI), dan Visible red Near Infrared-Buildup Index (VrNIR-BI). Nilai suhu permukaan rata-rata untuk Jakarta, Bandung, dan Surabaya secara berurutan sebesar 35,21°C, 28,52°C, dan 31,69°C. Hubungan antara tutupan lahan dengan LST dianalisis menggunakan uji korelasi sederhana pearson product moment. Nilai korelasi antara LST dengan NDVI di Kota Jakarta, Bandung, dan Surabaya sebesar -0,49; -0,51; dan -0,49 sementara LST dan VrNIR-BI masing-masing sebesar 0,49; 0,51; dan 0,48.
Identifikasi Fase Pertumbuhan Tanaman Jagung Menggunakan Citra SAR Sentinel-1A (Studi Kasus: Kecamatan Gerung, Lombok Barat, NTB) Baiq Arasya Wulandari; Lalu Muhamad Jaelani
Jurnal Penginderaan Jauh Indonesia Vol 1 No 2 (2019)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/jpji.v1i2.259

Abstract

PENGARUH ALGORITMA LYZENGA DALAM PEMETAAN TERUMBU KARANG MENGGUNAKAN WORLDVIEW-2, STUDI KASUS: PERAIRAN PILU PAITON PROBOLINGGO Lalu Muhamad Jaelani; Nurahida Laili; Yennie Marini
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 12 No. 2 (2015)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/inderaja.v12i2.3314

Abstract

Mapping the coral reef ecosystems to support the coastal management can be carried out using a high-resolution satellite imagery. Various methods of sea bottom features extraction have been developed and can be implemented to support the mapping process, one of them is Lyzenga's algorithm. This algorithm requires a depth variation of the area. The objective of this research is to investigate the effect of Lyzenga's algorithm on coral reef mapping. In this research, we compared the classification results of coral ecosystem between image with and without Lyzenga's algorithm. The image classification with this algorithm showing the appearance of sea bottom features were more differentiated and turn into Lyzenga index values which have been free from the water column effect. It produced several classes, they were oceans, land, sand, and coral reefs. The estimated area of coral reefs ecosystems in the waters of Paiton Probolinggo based on Worldview-2 classification result was 8.26 ha. Mapping coral reef ecosystem by using a high-resolution satellite imagery was very helpful giving the visualization of a wider area than the field observations.
STUDI PERUBAHAN SUHU PERMUKAAN LAUT DALAM RANGKA PEMBUATAN SISTEM INFORMASI KELAUTAN (STUDI KASUS: PEMBUANGAN LUMPUR LAPINDO DI SELAT MADURA) Sukojo , Bangun Muljo; Pratomo, Danar Guruh; Jaelani, Lalu Muhamad
GEOID Vol. 4 No. 2 (2009)
Publisher : Departemen Teknik Geomatika ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Peristiwa semburan lumpur panas di lokasi pengeboran PT. Lapindo Brantas di Desa Renokenongo, Kecamatan Porong, Kabupaten Sidoarjo, Jawa Timur, terjadi sejak 27 Mei 2006. Semburan lumpur ini membawa dampak yang luar biasa bagi masyarakat sekitar maupun bagi aktivitas perekonomian di Jawa Timur. Salah satu skenario penanganan teknis untuk menghentikan semburan lumpur panas adalah dengan membuang langsung lumpur panas tersebut ke Selat Madura melalui Kali Porong. Usaha ini diindikasikan membawa perubahan terhadap Suhu Permukaan Laut (SPL) di sekitar Muara Kali Porong dan Selat Madura. Pada penelitian ini untuk mengetahui kecenderungan SPL di sekitar Muara Kali Porong dan Selat Madura sebelum dan setelah pembuangan lumpur panas ke Kali Porong, dilakukan dengan menggunakan teknologi penginderaan jauh. Citra satelit yang digunakan untuk melakukan monitoring SPL adalah citra ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) multitemporal tahun 2005, 2006,2007 dan 2008. Nilai SPL yang diperoleh pada penelitian ini dilakukan dengan menggunakan algoritma Kishino. Berdasarkan hasil pengolahan data citra ASTER dan pengamatan langsung di lapangan terdapat adanya perbedaan nilai SPL. Perbedaan ini disebabkan oleh perbedaan kondisi saat pencitraan dan pada saat pengambilan data lapangan. Pada penelitian ini juga dapat diketahui bahwa perubahan SPL dari citra ASTER yang terjadi pada saat sebelum dan sesudah lumpur panas dibuang melalui Kali Porong terjadi secara  tidak konsisten. Hal ini disebabkan adanya perbedaan kondisi cuaca pada saat dilakukannya proses pencitraan pada masing-masing citra.  
Co-Authors Abdul Rasam, Abdul Rauf Adillah Alfatinah Afifi , Zulfahmi Agnes Rusnalia T. Agung Budi Cahyono Agustina, Heni Ahyudanari, Ervina Aji, Pujo Albertus Sulaiman Albertus Sulaiman, Albertus Alina, Aldea Noor Amalia Putri Rivani Andie Setiyoko Andika Yudha Gutama Andri A. Wibowo Ari Matiur Aries Sulisetyono Arik Yumna Pratiwi Aryasandah H. Dewantoro Aryasandah H. Dewantoro, Aryasandah H. Azmi, Rahajeng Aulia Bachtiar, Jayed Ali Baiq Arasya Wulandari Bangun Muljo Sukojo Bangun Muljo Sukojo, Bangun Muljo Benedict Budi Prasetyo Chao-Hung Lin Denaro, Lino Garda Dewinta Heriza Diah Ardiani Eddy Setyo Koenhardono, Eddy Setyo erika yuniar tyastiti Fahlefi , Rizha Faisal Adam Yudithia Faradila, Naura Annisa Feny Arafah Filsa Bioresita, Filsa Firmansyah Maulana Azhali Fitriana Kartikasari Fitriana Kartikasari Fultriasantri, Indah Gathot Winarso Gathot Winarso Gathot Winarso, Gathot Gilang Amrullah Sayono Gutama, Andika Yudha Hanansyah, Megivareza Putri Handis Muzaky Harliyanti, Novi Ika Hepi Hapsari Handayani Hepi Hapsari Handayani Hepi Hapsari Handayani, Hepi Hapsari Heriza, Dewinta Hidayat, Arfico Rizky Hidayat, Husnul Husnul Hidayat, Husnul Ilyas Ilyas Irma'atus Sholihah Jayed Ali Bachtiar Jayeng Rangga Bhirawa Kartikasari, Fitriana Kristina Putri Lena Sumargana Lena Sumargana Lin, Chao-Hung Lino Garda Denaro Loryena Ayu Karondia Loryena Ayu Karondia, Loryena Ayu M. Aldila Syariz, M. Aldila M. Nur Cahyadi M. Nur Cahyadi, M. Nur Martanti Aji Pangestu Mochamad Indrawan Muhammad Aldila Syariz Muhammad Aldila Syariz Muhammad Hanif Muhammad Rizka Arief Pratama Muhammad Rizka Arief Pratama, Muhammad Rizka Arief Muhammad Taufik Muhammad Wildan Bobsaid Muhsi Muzaky, Handis Nabilah, Salwa Nadzir, Zulfikar Adlan Nia Kurniadin Niken rahayuningtyas Noorlaila Hayati, Noorlaila Norida Maryantika Novi Ika Harliyanti Nur Aina Rizki Rahmadani Nurahida Laili Nurahida Laili Nurgiantoro, Nurgiantoro Oktavianto G. Pamungkas, Adjie Pangestu, Martanti Aji Pratomo, Danar Guruh Pratomo, Danar Guruh Putri, Rizky Annisa Rahmansyah, Ferdian Zaki Ramadhanni, Rizky Fitria Resti Limehuwey Ricko Andrew FG. Rivani, Amalia Putri Rizha Fahlefi Romadina Indah Wardani Rossita Yuli Ratnaningsih Salam Tarigan Salwa Nabilaha Sanjaya, Hartanto Sayono , Gilang Amrullah Sekartadji, Ratih Sri Ratna Ningsih, Sri Ratna Sukojo , Bangun Muljo Sulaiman, Albertus Sulistiawati Sulistiawati Sulistyah, Umroh Dian Sulistyah, Umroh Dian Tambunan, Mangapul Parlindungan tyastiti , erika yuniar Wardani , Romadina Indah Wulandari, Baiq Arasya Yennie Marini Yennie Marini Zulfahmi Afifi