The normalized change index and split-based approach methods have been applied in this research to create the semiautomatic unsupervised change-detection areas affected by flood using multi-temporal Advanced Land Observing Satellite Phased Array L-band Synthetic Aperture Radar (ALOS PALSAR) remotely sensed data. This research is focused to provide information related to the flood inundation event that occurred in March 2010, in Karawang, West Java, Indonesia. The objectives of this research are as follows:(1) to generate a flood inundation map as rapid mapping steps in disaster mitigation effort and (2) to identify and assess the environmental damage caused by flood inundation event in the research area. ALOS PALSAR remotely sensed data with the acquisition pre-flood (March 09, 2010) and post-flood (March 26, 2010) were used for mapping flood inundation event. Flood inundation map and land-use data are used for the identification and assessment of the environmental damage caused by flood inundation event, which is done with GIS environment tools. The flood inundation event is estimated to have an impact of 7,158 ha for settlements; 20,039 ha for paddy fields; 668 ha for plantations; 1,641 ha for farms; 198 ha for agricultural cultivations; 1,161 ha for shrubberies; 1,022 ha for industrials; and 1,019 ha for road areas. The total number of building damages is estimated to be around 16,350 units. In general, this method can be used to assist emergency response efforts, through an inventory of areas affected by floods. In addition, the use of this method can be applied and it is recommended for future research in different locations, which are consistent and reliable to detect areas affected by other disasters such as flash floods, landslide, tsunami, volcano eruptions, and forest fire.
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.
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 multithreshold 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 multithreshold model is a model that has the potential to be applied to detect forest and land fire smoke.
Himawari-8 is the last generation of the low spatial resolution satellite imagery that has capability to detect the thermal variation on the earth of every 10 minute. This must be very potential to be used for detecting land/forest fire. This paper has explored the spectral prospective of the Himawari-8 for detecting land/forest fire hotspot. The main objective for this study is to identify the potential use of Himawari-8 for detecting of land forest fire hotspot. The study area was performed in Ogan Komering Ilir, South of Sumatra, which on 2015 occur great forest/land fire event. The main process included in this study are image projection, training sample collection and spectral statistical analysis measured by calculate statistic, they are average values, standard deviation values from reflectance visible band value and brightness temperature value, beside that validation of data obtained from medium resolution data of Landsat 8 with the similar acquisition time. The study found that the Himawari-8 has good capacity to identify land/forest fire hotspot as expressed for high accuracy assessment using band 3 and band 7.
ABSTRAKInformasi luas area kebakaran sangat diperlukan sebagai salah satu pendekatan untuk penghitungan emisi gas rumah kaca. Data Landsat merupakan salah satu jenis citra penginderaan jauh optis resolusi menengah yang banyak dipergunakan untuk memetakan luas dan sebaran areal kebakaran. Tujuan penelitian adalah melakukan verifikasi hasil deteksi lahan bekas kebakaran hutan/lahan guna tersedianya hasil verifikasi burned area (BA) dari data Landsat-8 untuk dukungan penyusunan pedoman identifikasi BA. Pada penelitian ini dilakukan analisis verifikasi lahan bekas kebakaran yang diperoleh dari data satelit Landsat-8 sensor Operational Land Imager (OLI) menggunakan metode Normalized Burn Area (NBR). Data referensi yang digunakan dalam proses verifikasi adalah data lahan bekas kebakaran yang didelineasi dari citra SPOT-5. Citra ini memiliki resolusi spasial lebih tinggi dibandingkan dengan Landsat-8 OLI. Hasil penelitian menunjukkan bahwa tingkat akurasi Burned Area BA Landsat-8 OLI dengan metode ∆NBR memiliki nilai akurasi (overall accuracy) sebesar 87%, dengan commision error sebesar 2%, dan ommision error sebesar 11%. Tingkat akurasi burned area (BA) hasil estimasi dari data Landsat-8 dengan menggunakan metode ∆NBR memiliki nilai koefisien korelasi (r) 0,98 dengan persamaan Y = 0,928X -21,07 dan koefisien determinasi (R 2 ) = 0,96. Hasil ini menunjukkan bahwa sebesar 96% wilayah yang diklasifikasikan atau diestimasi sebagai wilayah yang terbakar adalah benar sebagai wilayah yang terbakar. Dengan demikian dapat disimpulkan bahwa metode ∆NBR yang diaplikasikan pada data Landsat-8 terbukti dapat digunakan untuk mendeteksi burned area. Kata Kunci: areal kebakaran, Landsat-8, Normalized Burn Area (NBR) ABSTRACT Information of burned area is needed as one among approaches on the calculation of greenhouse gas emissions. Landsat is one of the main types of remote sensing imageries frequently used to map the distribution of burned area.The purpose of this research is to verify the result of burned area (BA) analysis obtained from Landsat-8 satellite data acquired with
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