Analisis Perubahan Curah Hujan Satelit Tropical Measuring Mission (Trmm) Tahun 2009 dan Tahun 2010

The utilization of a combination of sensor data PR (Precipitation Radar) and TMI (TRMM Microwave Imager) satellite carriedby the TRMM (Tropical Rainfall Measuring Mission) can be used to analyze the characteristics and mechanisms of rainfall in tropicalregions. It was applied in the territory of Indonesia. The aim of this study was to analyze the rainfall of TRMM data in 2009 and 2010in order to understand each characteristic and phenomenon that occurs. TRMM data that were used was type of 3B43.. The researchmethod that applied included a search pattern of spatial and temporal rainfall obtained from the processing of TRMM rainfall data.The results showed that the rainfall data in 2009 and 2010 from TRMM satellite monitoring is able to represent the rainfall conditionsduring extreme conditions in the territory of Indonesia, either at the time of El Niño and La Niña. In 2009 occurred the phenomenonof El Nino, while the year 2010 was phenomenon of La Nina

Dinamika Siklon Tropis di Asia Tenggara Menggunakan Data Penginderaan Jauh

Tropical cyclone is the form of extreme weather disturb. The growth of tropical cyclone is originated by tropical depressionor the center of an intensive low pressure above the ocean, triggering convection process and the intensive forming of cloud. Theaim of the research is to obtain the information of the extreme weather condition in the form of tropical depression and tropicalcyclones particularly the movement location of tropical cyclones and the influence coverage area in Indonesia. This method usedobservation and analyzing the impact of tropical cyclones in Indonesia area, and mapping its position based on latitude and longitudeof cyclone Centrum. The result of tropical cyclone monitoring in 2010 shows that tropical cyclone in Southern Indonesian area orIndian Ocean lasted in January, part of March and December 2010. Meanwhile, the tropical cyclone in Northern Indonesian areaon South China Sea and West Pacific was lasted in April , May, July, August, September, October, November and part of March 2010.Tropical cyclone on March 2010 did not show an orderly pattern. On May 2010, the tropical cyclones are simultaneously happen inthe northern and southern of Indonesia. In 2010 the concentration of tropical cyclone is heavily taken place in northern part ofIndonesia

SPECTRAL ANALYSIS OF THE HIMAWARI-8 DATA FOR HOTSPOT DETECTION FROM LAND/FOREST FIRES IN SUMATRA

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

VALIDASI HOTSPOT MODIS DI WILAYAH SUMATERA DAN KALIMANTAN BERDASARKAN DATA PENGINDERAAN JAUH SPOT-4 TAHUN 2012 (MODIS HOTSPOT VALIDATION OVER SUMATERA AND KALIMANTAN BASED ON REMOTE SENSING DATA SPOT-4 IN 2012)

Indikator kebakaran hutan dan lahan dapat ditunjukkan dengan adanya hotspot dan asap kebakaran. Saat ini informasi hotspot sebagai indikator kebakaran hutan/ lahan sudah digunakan dengan baik oleh masyarakat, namun masih diragukan akurasi dari informasi tersebut. Oleh karena itu informasi tentang hotspot yang tervalidasi sangat dibutuhkan dalam upaya penanggulangan kebakaran hutan/lahan secara tepat. Penelitian ini bertujuan untuk menguji akurasi titik hotspot dari beberapa sumber data, yaitu IndoFire Map Service (Indofire) dan Fire Information for Resource Management System (FIRMS). Validasi dilakukan dengan membandingkan data hotspot dengan kenampakan citra yang resolusinya lebih tinggi, yaitu SPOT-4. Hasil penelitian menunjukkan bahwa persentase hasil akurasi hostpot FIRMS sebesar 64% dengan tingkat Commision error dan Ommision error masing-masing 18%. Sedangkan persentase hasil akurasi hostpot Indofire ditemukan sebesar 42% dengan tingkat Commision error 20% dan Ommision error 38%. Analisis lebih lanjut di lahan gambut, telah diperoleh nilai akurasi hotspot Firms sebesar 66% dengan commision error 19% dan ommision error 15%, sedangkan hotspot Indofire ditemukan sebesar 46% dengan commision error 19% dan ommision error sekitar 35%. Nilai akurasi hotspot yang bersumber dari FIRMS lebih tinggi dibandingkan dengan hotspot Indofire. Hal ini dapat disebabkan oleh penggunaan semua tingkat kepercayaan hotspot (confidence level) mulai dari 5 hingga 100% yang berbeda dengan Indofire (confidence level>80%). Tingginya nilai ommision error disebabkan oleh kabut asap tebal dan awan yang tidak bisa dideteksi oleh algoritma MODIS. Disamping itu, tingginya nilai ommision error disebabkan oleh kebakaran asap kecil yang dideteksi di SPOT-4 dan juga kebakaran yang baru terjadi yang ditandai oleh asap yang belum menyebar luas, namun hotspot tidak terpantau oleh satelit. Berdasarkan hasil penelitian ini dapat disimpulkan bahwa penggunaan semua confidence level hotspot perlu dipertimbangkan untuk digunakan khususnya pada lahan gambut dibandingkan hanya menggunakan yang lebih besar dari 80% saja.Kata kunci: Hotspot, MODIS, Confidence level, Indofire, FIRMS-NASA, Penginderaan jau

DETECTION OF GREEN OPEN SPACE USING COMBINATION INDEX OF LANDSAT 8 DATA (CASE STUDY: DKI JAKARTA)

Spatial information about the availability and presence of green open space in urban areas to be up to date and transparent was a necessity. This study explained the technique to get the green open spaces of spatial information quickly using an index approach of Landsat 8. The purpose of this study was to evaluate the ability of the method to detect the green open spaces, especially using Landsat 8 with a combination of several indices, namely Normalized Difference Build-up Index (NDVI), Normalized Difference Water Index (NDWI), Normalized Difference Build-up Index (NDBI) and Normalized Difference Bareness Index (NDBaI) with a study area of Jakarta. This study found that the detection and identification of green open space classes used a combination of index and band gave good results with an accuracy of 81%

Pemanfaatan Citra VIIRS untuk Deteksi Asap Kebakaran Hutan dan Lahan di Indonesia

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

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)

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. ABSTRAKPeristiwa 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

DISTRIBUSI SPASIAL HOT SPOT DAN SEBARAN ASAP INDIKATOR KEBAKARAN HUTAN/LAHAN DI PULAU SUMATERA DAN KALIMANTAN TAHUN 2002

Forest/land fire in Indonesia occurs almost every year. Itis merely due to natural factor, but due to human's activity as well like in opening of new land for agriculture purpose or plantation, or forming of land/land clearing. Fire that is indicated by the existenceof hot spot can be monitored daily using near infra-red channel and thermal (channel 3 and 4) from NOAA-AVHRR satellite data (National Oceanic and Atmospheric Radiometer-Advanced Very High Resolution Radiometer). Pursuant to the daily hot spot monitoring in Sumatera in the year 2002, forest/land fire has occurred since January until December, while in Kalimantan, it start in March until December. The fluctuation of hot spot in the year 2002 has almost the same pattern with the year 1997's, where the peak of fire occurred in September in Kalimantan Island and in October in Sumatera Island. Besides, pursuant to NOOA and Feng Yun data, haze distribution that occurred in the year 2002 was not too significant and haze distributions that mostly took place in September in Kalimantan and in October in Sumatera. Degradation of fire activity occurs in the following month where the fire in the two island drop along with the increasing of rainfall in the two island