DETEKSI KEBAKARAN HUTAN DAN LAHAN MENGGUNAKAN CITRA SATELIT HIMAWARI-8 DI KALIMANTAN TENGAH
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Abstract
Intisari
Kebakaran hutan dan lahan terjadi hampir setiap tahun di Indonesia, terutama di wilayah Sumatera dan Kalimantan saat musim kemarau. Deteksi kebakaran hutan dan lahan dengan citra satelit menggunakan indikator yang disebut titik panas. Titik panas yang digunakan saat ini di Indonesia diperoleh dari pengolahan data citra satelit berorbit polar (MODIS dan VIIRS) dengan resolusi temporal yang rendah, yaitu hanya 6 kali dalam sehari. Tujuan dari penelitian ini adalah memanfaatkan data citra satelit Himawari-8 untuk deteksi kebakaran hutan dan lahan yang menghasilkan titik panas dengan resolusi temporal 10 menit, dimana hasilnya di validasi dengan citra polar dan data kebakaran lapangan. Lokasi penelitian berada di Provinsi Kalimantan Tengah dan waktu penelitian adalah bulan September 2019. Data yang digunakan untuk pengolahan adalah 5 saluran Advanced Himawari Imager, peta batas administrasi dan tutupan lahan. Pemrosesan data citra satelit mencakup pemilihan piksel penutup lahan dan batas administrasi, penentuan waktu pengamatan, eliminasi piksel awan, Algoritma Pemantau Kebakaran Aktif, dan validasi hasil. Data citra Himawari-8 dapat diolah menjadi titik panas dengan temporal 10 menit. Validasi terhadap citra polar memiliki tingkat akurasi 66,2%-75,4%, comission error 28,2-46,9% dan omission error 24,6-33,8%. Tingginya comision error terhadap citra VIIRS dikarenakan citra VIIRS memiliki resolusi spasial yang jauh lebih tinggi dibandingkan dengan citra Himawari-8.
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Abstract
Forest and land fires occur almost every year in Indonesia, especially in Sumatra and Kalimantan during the dry season. Detection of forest and land fires with satellite imagery uses an indicator called a hotspot. The hotspots used today in Indonesia are obtained from the processing of polar orbital satellite image data (MODIS and VIIRS) with a low temporal resolution, which is only six times a day. The purpose of this study is to utilize Himawari-8 satellite imagery data for the detection of forest and land fires that produce hotspots with a temporal resolution of 10 minutes, where the results are validated with polar imagery and field fire data. The research location is in Central Kalimantan Province, and the time of the study is September 2019. Data used for processing are 5 Advanced Himawari Imager channels, administrative boundary maps, and land cover. Processing of satellite imagery data includes the selection of cover pixels and administrative boundaries, determination of observation time, elimination of cloud pixels, Active Fire Monitoring Algorithm, and validation of results. Himawari-8 image data can be processed into hotspots with a temporal 10 minutes. Validation of polar images has an accuracy rate of 66.2% -75.4%, commission error 28.2-46.9% and omission error 24.6-33.8%. The high commission error on the VIIRS image is because the VIIRS image has a much higher spatial resolution compared to the Himawari-8 image.Â
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References
Bessho, K., Date, K., Hayashi, M., Ikeda, A., Imai, T., Inoue, H., Kumagai, Y., Miyakawa, T., Murata, H., Ohno, T., Okuyama, A., Oyama, R., Sasaki, Y., Shimazu, Y., Shimoji, K., Sumida, Y., Suzuki, M., Taniguchi, H., Tsuchiyama, H. Uesawa, D., Yokota, H., Yoshida, R. (2016). An Introduction to Himawari-8/9 Japans New-Generation Geostationary Meteorological Satellites. Journal of the Meteorological Society of Japan. Ser. II, 94(2), 151–183. doi: 10.2151/jmsj.2016-009
Fatkhuroyan., Wati, T., Panjaitan, A. (2017). Forest Fires Detection in Indonesia Using Satellite Himawari-8 (Case Study: Sumatera and Kalimantan on August-October 2015). IOP Conference Series: Earth and Environmental Science, 54, 012053. doi: 10.1088/1755-1315/54/1/012053
Fitriana, H.L., Sulma, S., Zubaidah, A., Suwarsono., Prasasti, I. (2018). Spectral Analysis of the Himawari-8 Data for Hotspot Detection from Land/Forest Fires in Sumatra. International Journal of Remote Sensing and Earth Sciences, 15(1), 15-28. doi: 10.30536/j.ijreses.2018.v15.a2836
Giglio, L., Schroeder, W., Justice, C.O. (2016). The Collection 6 MODIS Active Fire Detection Algorithm and Fire Products. Remote Sensing of Environment, 178, 31–41. doi: 10.1016/j.rse.2016.02.054
Hassini, A., Benabdelouahed, F., Noureddine, B., Belbachir, A.H. (2009). Active Fire Monitoring with Level 1 . 5 MSG Satellite Images. American Journal of Applied Sciences, 6(1), 157–166. doi: 10.3844/ajas.2009.157.166
Hyer, E.J., Reid, J.S., Prins, E.M., Hoffman, J.P., Schmidt, C.C., Miettinen, J.I., Giglio, L. (2013). Patterns of Fire Activity over Indonesia and Malaysia from Polar and Geostationary Satellite Observations. Atmospheric Research, 122, 504–519. doi: 10.1016/j.atmosres.2012.06.011
Japan Meteorological Agency. (2015). Himawari Standard Data User’s Guide.
Lembaga Penerbangan dan Antariksa Nasional. (2016). Panduan Teknis (V.01) Informasi Titik Panas (Hotspot) Kebakaran Hutan/Lahan (Vol. 01). Indonesia.
Manyangadze, T. (2009). Forest Fire Detection for Near Real-Time Monitoring Using Geostationary Satellites. Thesis. International Institute for Geo-Information Science and Earth Observation.
Matson, M., Dozier, J. (1981). Identification of Subresolution High Temperature Sources Using a Thermal IR Sensor. Photogrammetric Engineering and Remote Sensing, 47(2), 1311–1318.
Milne, A.K. (1986). The Use of Remote Sensing in Mapping and Monitoring Vegetational Change Associated with Bushfire Events in Eastern Australia. Geocarto International, 1(1), 25–32. doi: 10.1080/10106048609354022
NOAA. (n.d.). Calculating zenith and azimuth angles for GridSat-B1. https://www.ncdc.noaa.gov/gridsat/docs/Angle_Calculations.pdf
Schmidt, C.C., Prins, E.M. (2003). GOES Wildfire ABBA applications in the Western Hemisphere. 2nd International Wildland Fire Ecology and Fire Management Congress, AMS 5th Symposium Fire and Forest Meteorology, (November), 4.
Wickramasinghe, C., Wallace, L., Reinke, K., Jones, S. (2018). Intercomparison of Himawari-8 AHI-FSA with MODIS and VIIRS Active Fire Products. International Journal of Digital Earth. doi: 10.1080/17538947.2018.1527402
Yulianti, N., Hayasaka, H., Sepriando, A. (2013). Recent Trends of Fire Occurrence in Sumatra (Analysis Using MODIS Hotspot Data): A Comparison with Fire Occurrence in Kalimantan. Open Journal of Forestry, 3(4), 129–137. doi: 10.4236/ojf.2013.34021