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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) MEDIA KONSERVASI Mechatronics, Electrical Power, and Vehicular Technology Bulletin of Electrical Engineering and Informatics International Journal of Advances in Intelligent Informatics Register: Jurnal Ilmiah Teknologi Sistem Informasi EMITTER International Journal of Engineering Technology Applied Engineering and Technology
Kohei Arai
Graduate School of Science and Engineering, Saga University, Saga City, Japan
Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Earth & Planetary Sciences Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology

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Journal : MEDIA KONSERVASI

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Cellular Automata on GIS Method for Forest Fire Spreading Simulation Arai, Kohei
Media Konservasi Vol. 29 No. 2 (2024): Media Konservasi Vol 29 No 2 May 2024
Publisher : Department of Forest Resources Conservation and Ecotourism - IPB University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/medkon.29.2.161

Abstract

A method for prediction and simulation based on the Cell Based Geographic Information System (CBGIS) as Cellular Automata (CA) is proposed together with required data system systems, in particular metasearch engine usage in a unified way. It is confirmed that the proposed CBGIS as CA has flexible usage of the attribute information that is attached to the cell in concern with location information and does work for disaster of forest fire spreading simulation and prediction.
Experimental Study on Tree Shape Identification and Interaction Among Trees Arai, Kohei
Media Konservasi Vol. 29 No. 4 (2024): Media Konservasi Vol 29 No 4 September 2024
Publisher : Department of Forest Resources Conservation and Ecotourism - IPB University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/medkon.29.4.653

Abstract

Forests play a crucial role in mitigating global warming and maintaining climate balance, necessitating a comprehensive understanding of forest dynamics. However, many optical characteristics related to forests remain poorly understood, particularly models for determining forest parameters such as tree species, shape, and inter-tree distances. Although several models exist for estimating leaf area index and photosynthetically active radiation, fewer models address structural forest parameters. This research aims to develop a model using visible and near-infrared radiometer data from Earth observation satellites to estimate forest parameters, including tree species, shape, height, and spacing. Results show that as the distance between trees increases, the impact of multiple reflections decreases significantly. Elliptical tree shapes exhibit approximately three times higher multiple reflection effects compared to conical shapes, indicating potential for distinguishing tree shapes through radiometric data. For canopy shapes, shorter, thicker trees experience more significant reflection effects than taller, thinner trees, suggesting the feasibility of estimating tree height. Overall, the impact of multiple reflections ranges from a few to 10% of TOA radiance, necessitating its consideration when calculating forest reflectance to ensure accurate forest parameter retrieval from satellite observations.
Co-Authors Aji Prasetya Wibawa Ali Ridho Barakbah Andrie Asmara, Rosa Anik Nur Handayani Ariyanta, Nadindra Dwi Burhanuddin, Mohd Aboobaider Damayanti, Farradila Ayu Daud, Nathan Dimas Wahyu Wibowo Faqih, Kamil Heru Wahyu Herwanto Hitipeuw, Emanuel Indriati Indriati Jevri Tri Ardiansah Kurnianingtyas, Diva Marji Marji Mustika Mentari Nugraha, Agil Zaidan Priharta, Ari Primadi, Wahyu Rahmat Samudra Anugrah, Muhammad Resty Wulanningrum Rosa Andrie Asmara Sakti Oktafiansyah, Haidar Salsabila, Reni Fatrisna