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All Journal AGRIVITA, Journal of Agricultural Science Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan (Journal of Natural Resources and Environmental Management) MAJALAH ILMIAH GLOBE International Journal of Remote Sensing and Earth Sciences (IJReSES) Makara Journal of Technology Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital
Sayidah Sulma, Sayidah
Lembaga Penerbangan dan Antariksa Nasional, Jakarta 13710, Indonesia
Aerospace Engineering Agriculture, Biological Sciences & Forestry Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Earth & Planetary Sciences Education Electrical & Electronics Engineering Engineering Environmental Science Materials Science & Nanotechnology Mechanical Engineering

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Pemanfaatan Citra VIIRS untuk Deteksi Asap Kebakaran Hutan dan Lahan di Indonesia Zubaidah, Any; Sulma, Sayidah; Suwarsono, Suwarsono; Prasasti, Indah
Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan (Journal of Natural Resources and Environmental Management) Vol 9 No 4 (2019): Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan
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.9.4.929-945

Abstract

The observation of smoke because of land and forest fires in some regions in Indonesia mostly use the composite image visually. This study aims to develop the detection model of forest and land fire smoke using a digital analysis, which will be faster in supporting spatial information on emergency response in monitoring forest and land fire smoke. The method used is multi-threshold method and compare it with the existing model that is by modification of method Li et al. (2015). The data used is Suomi NPP-VIIRS satellite imagery. The results concluded that the VIIRS image can be used to detect the smoke and smoke distribution of forest fire and digital smoke. The multi-threshold model uses reflectance data obtained from the M4 visible channel, and the brightness temperature data obtained from the LWIR VIIRS M14 channel, with an average accuracy of 82.2% with a Commision error of 9.8% and an Ommision error of 10%. While the model of modification Li is based only on reflectance of visible-channel data i.e. channel M1, M2, M3, and SWIR VIIRS M11 channel, which has an average accuracy of 72.3% with a Commision error of 0.3% and an Ommision error of 27.4%. The multi-threshold model is a model that has the potential to be applied to detect forest and land fire smoke.
Co-Authors Amalo, Luisa Febrina Any Zubaidah Atriyon Julzarika Chulafak, Galdita Aruba Eko Kusratmoko Febrianti, Nur Hana Listi Fitriana, Hana Listi Hidayat Hidayat Indah Prasasti, Indah Jalu Tejo Nugroho, Jalu Tejo Johannes Manalu, Johannes Junita Monika Pasaribu Kuncoro Teguh Setiawan, Kuncoro Teguh Muchlisin Arief Nanik Suryo Haryani Rahmat Hidayat Rahmi, Khalifah Insan Nur Rahmi, Khalifah Insan Nur Ratna Saraswati, Ratna Sitorus, Jansen Sri Harini Suhadha, Argo Sulyantoro, Heri Suryo H, Nanik Suwarsono Suwarsono