ANALISIS KARAKTERISTIK TEMPERATUR AREA TERBAKAR (BURNED AREA) MENGGUNAKAN DATA LANDSAT-8 TIRS DI KALIMANTAN (ANALYZING THE TEMPERATURE CHARACTERISTICS OF BURNED AREA USING LANDSAT-8 TIRS IN KALIMANTAN)

suwarsono suwarsono, Any Zubaidah, Parwati Parwati, M. Rokhis Khomarudin

Abstract

Biomass burning in an area will leave traces of fire such as charcoal, ash, and outcrop of land in the area known as the burned area. The burnt area is thought to have a relatively higher temperature than the surrounding area were not burned. This study aims to determine the characteristics of the temperature of the burned area using remote sensing data of Landsat-8 TIRS (Thermal Infra Red Sensor). The selected research locations are parts of Central Kalimantan and South Kalimantan incoming Landsat scene-8 path / row 118/062. The research method is a data processing Landsat-8 TIRS (channels 10 and 11) to produce an image of the brightness temperature as well as data analysis includes a statistical analysis of central tendency of the values of the brightness temperature of the sample (calculation of mean and standard deviation) as well as distance calculation (D-value). The results showed that the brightness temperature data either channel 10 or channel 11 Landsat-8 TIRS has good ability in separating the burned area and bare soil, but has a low ability to separate the burned areas and settlements. Thus, the brightness temperature parameter cannot be used as a single variable for the extraction of burned areas in a scene image of a single acquisition.

 

ABSTRAK

Peristiwa kebakaran biomassa pada suatu daerah akan menyisakan bekas-bekas kebakaran seperti arang, abu, serta singkapan tanah pada daerah tersebut yang dikenal dengan burned area. Daerah bekas kebakaran tersebut diduga memiliki temperatur yang relatif lebih tinggi dibandingkan dengan daerah sekitarnya yang tidak terbakar. Penelitian ini bertujuan untuk mengetahui karakteristik temperatur burned area menggunakan data penginderaan jauh Landsat-8 Thermal Infra Red Sensor (TIRS). Lokasi penelitian yang dipilih adalah sebagian wilayah Kalimantan Tengah dan Kalimantan Selatan yang masuk scene Landsat-8 path/row 118/062. Metode penelitian yang dilakukan adalah pengolahan data Landsat-8 TIRS (kanal 10 dan 11) untuk menghasilkan citra suhu kecerahan serta analisis data yang meliputi analisis statistik tendensi sentral dari nilai-nilai suhu kecerahan dari sampel (perhitungan rerata dan standar deviasi) serta perhitungan jarak (D-value). Hasil penelitian menunjukkan bahwa data suhu kecerahan baik kanal 10 maupun kanal 11 Landsat-8 TIRS memiliki kemampuan yang baik dalam memisahkan burned area dan lahan terbuka, namun memiliki kemampuan yang rendah untuk memisahkan burned area dan permukiman. Dengan demikian, parameter suhu kecerahan belum bisa dipergunakan sebagai variabel tunggal untuk ekstraksi burned area pada suatu scene citra perekaman tunggal.

Keywords

Burned area; Temperatur; Landsat-8 TIRS

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References

Aryanti, I, N. Sinukaban dan I N S Jaya, 2007.

Forest Fire Vulnerability index in West

Kalimantan Province, Tropical Forest

Management Journal, Bastarrika A,

Chuvieco E, Martin, M.P (2011).

Mapping burned areas from Landsat

TM/ETM+ data with a two-phase

algorithm: Balancing omission and

commission errors. Remote Sensing of

Environment 115:1003–1012.

Caselles V, Rubio E, Coll C, Valor E., 1998.

Thermal Band Selection for the PRISM

Instrument 3, Optimal band

configuration. Journal of Geophysical

Research 103: 17.057–17.067.

Chuvieco E., Englefield P., Trishchenko A. P,

dan Luo Y., 2008. Generation of Long

Time Series of Burn Area Maps of the

Boreal Forest from NOAA–AVHRR

Composite Data, Remote Sensing of

Environment 112: 2381 −2396.

Eggleston, S., Buendia, L., Miwa, K., Ngara, T.,

and Tanabe, 2006. 2006 IPCC

Guidelines for National Greenhouse Gas

Inventories. K. (Eds), Intergovernmental

Panel on Climate Change (IPCC), IPCC,

Hayama, Japan.

Irons J.R, Dwyer J.L, Barsi J.A., 2012. The Next

Landsat Satellite: The Landsat Data

Continuity Mission, Remote Sensing of

Environment 122: 11-21.Jaya, I N.S.,

Detecting Burnt Forest Damage

Using Digital Spot Imagery. Tropical

Forest Management Journal. Vol. 6 (l):

-23.

Jaya, I N. S. M. Ikhwan dan Nurhendra, 2000.

Teknik Mendeteksi Kebakaran Hutan

Melalui Citra Satelit Multi Waktu: Studi

kasus di Propinsi Sumatera Selatan dan

Riau, Tropical Forest Management

Journal. Vol VI(2):25-37.

Kaufman Y.J, Remer L.A., 1994. Detection of

Forest Fire using Mid-IR Reflectance:

and Application Fro Aerosols Study,

IEEE Transactions on Geoscience and

Remote Sensing 32: 672-683.

Kurnia, E, I N S Jaya, Widiatmaka, 2016.

Satellite-based Land Surface

Temperature Estimation of Bogor

Municipality, Indonesia, Indonesian

Journal of Electrical Engineering and

Computer Science. Volume 2 No 1. Pp

-228

Purnama, E.S dan I N S Jaya, 2006. Forest

Fire Vulnerabiility index in Riau Province,

Tropical Forest Management Journal.

Roy D.P, Wulder M.A, Loveland T.R, Woodcock

C.E, Allen R.G, Anderson M.C, Helder D,

Irons J.R, Johnson D.M, Kennedy R.,

Scambos T.A, Schaaf, C.B, Schott J.R,

Sheng Y., Vermote E.F, Belward A.S,

Bindschadler R., Cohen W.B, Gao F,

Hipple J.D, Hostert P, Huntington J,

Justice C.O, Kilic A, Kovalskyy V, Lee

Z.P, Lymburner L, Masek J.G, McCorkel

J, Shuai Y, Trezza R, Vogelmann J,

Wynne R.H, Zhu Z., 2014. Landsat-8:

Science and Product Vision for

Terrestrial Global Change Research,

Remote Sensing of Environment 145:

-172.

Samsuri, Jaya INS, Syaufina L., 2012. Model

Spasial Tingkat Kerawanan Kebakaran

Hutan dan Lahan (Studi Kasus Propinsi

Kalimantan Tengah, Foresta, Vol No (1)

Spatial model of forest and land

fire risk (A case study in Central

Kalimantan Province, Foresta, Vol No

(1) 2012 (in Indonesian). Faperta USU -

Persatuan Peneliti Kehutanan Sumut;

No.ISSN: 2089-9890; Vol.1; No.1;

Maret;2012;12-18, http://kehutanan.

usu.ac.id

Stroppiana D, Bordogna G, Carrara P,

Boschetti M, Bosschetti L, Brivio P.A.,

A Method for Extracting Burned

Areas from Landsat TM/ETM+ Images

by Soft Aggregation of Multiple Spectral

Indices and a Region Growing Algorithm,

ISPRS Journal of Photogrammetry and

Remote Sensing 69:88–102.

Suwarsono, 2014. Deteksi Daerah Bekas

Kebakaran Hutan/Lahan (Burned Area)

Menggunakan Citra Penginderaan Jauh,

Crestpent Press.

Suwarsono, Rokhmatuloh, dan Waryono T.,

Pengembangan Model Identifikasi

Daerah Bekas Kebakaran Hutan dan

Lahan (Burned Area) Menggunakan

Citra MODIS di Kalimantan, Jurnal

Penginderaan Jauh dan Pengolahan

Data Citra Digital 10(2): 93-112.

Thonicke K, Spessa A, Prentice I. C, Harrison S.

P, Dong L, Carmona-Moreno C., 2010.

The Influence of Vegetation, Fire Spread

and Fire Behaviour on Biomass Burning

and Trace Gas Emissions: Results from

a Process-Based Model, Biogeosciences

(7): 697 −743.

USGS, 2015. Landsat 8 (L8) Data Users,

Handbook Version 1.0. EROS Sioux

Falls, South Dakota.

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