SPATIO-TEMPORAL ANOMALIES IN SURFACE BRIGHTNESS TEMPERATURE PRECEDING VOLCANO ERUPTIONS DETECTED BY THE LANDSAT-8 THERMAL INFRARED SENSOR (CASE STUDY: KARANGETANG VOLCANO)

Indonesia's geological as part of the “ring of fire” includes the consequence that community life could be affected by volcanic activity. The catastrophic incidence of volcanic eruptions in the last ten years has had a disastrous impact on human life. To overcome this problem, it is necessary to conduct research on the strengthening of the early warning system for volcanic eruptions utilising remote sensing technology.  This study analyses spatial and temporal anomalies of surface brightness temperature in the peak area of Karangetang volcano during the 2018-2019 eruption. Karangetang volcano is an active volcano located in North Sulawesi, with a magmatic eruption type that releases lava flow. We analyse the anomalies in the brightness temperature from channel-10 of the Landsat-8 TIRS (Thermal Infrared Scanner) time series during the period in question. The results of the research demonstrate that in the case of Karangetang Volcano the eruptions of 2018-2019 indicate increases in the surface brightness temperature of the crater region. As this volcano has many craters, the method is also very useful to establish in which crater the center of the eruption occurred

Peranan Teknologi Penginderaan Jauh Dalam Mempercepat Perolehan Data Geografis Untuk Keperluan Pembangunan Nasional

Ketersediaan data geografis atau data spasial mempunyai peran penting dalam pembangunan nasional, mulai dari perencanaan tata ruang sampai pada penentuan tingkat kerawanan bencana. Ketersediaan dan kelengkapan data yang dimiliki akan berpengaruh terhadap efisiensi dan efektifitas pembangunan, mendorong pertumbuhan ekonomi, meningkatkan kualitas pengambilan keputusan serta tersedianya platform dalam membangun e-Goverment. Saat ini teknologi penginderaan jauh sangat besar perannya dalam pengumpulan data geografis suatu wilayah karena jumlah satelit/sensor yang beredar di orbit relatif banyak dan proses akuisisi data dapat dilakukan dengan cepat. Keuntungan lain teknologi penginderaan jauh ini adalah kemampuannya dalam menyajikan gambaran obyek atau fenomena di permukaan bumi dengan resolusi spasial sangat detail (misalnya 60 cm pada citra QuickBird) serta kemampuan dalam menyajikan liputan wilayah (area coverage) yang cukup luas (misalnya 2.000 km2 pada citra MODIS). Berbagai keuntungan ini sangat membantu proses pengumpulan dan revisi data geografis yang sangat diperlukan dalam pembangunan nasional Indonesia yang wilayahnya cukup luas

ANALISIS METODE KOMPRESI BERDOMAIN WAVELET PADA CITRA SATELIT RESOLUSI SANGAT TINGGI

Masalah yang kerap terjadi pada citra satelit penginderaan jauh, terutama citra resolusi sangat tinggi, salah satunya adalah besarnya media penyimpanan dan bandwidth yang dibutuhkan saat data ditransmisi ke tempat lain. Pada pengolahan citra satelit, kompresi data perlu dilakukan pada data citra satelit yang ada demi memudahkan transmisi dan penyimpanan citra. Makalah ini melakukan komparasi pada metode-metode kompresi domain wavelet yaitu metode wavelet, bandelet, dan CCSDS agar ditemukan metode terbaik untuk mengompresi data citra satelit resolusi sangat tinggi Pleiades. Hasil percobaan menunjukkan bahwa metode wavelet dan bandelet lebih baik dalam hal mempertahankan kualitas citra dengan PSNR di kisaran 50 dB, sementara metode CCSDS lebih baik dalam hal mereduksi ukuran citra menjadi seperdelapan citra asli

Percent of building density (PBD) of urban environment: a multi-index approach based study in DKI Jakarta Province

This study developed a model to identify the percent of building density (PBD) of DKI Jakarta Province in each pixel of Landsat 8 imageries through a multi-index approach. DKI Jakarta province was selected as the location of the study because of its urban environment characteristics.  The model was constructed using several predictor variables i.e.  Normalized Difference Built-up Index (NDBI), Soil-adjusted Vegetation Index (SAVI), Normalized Difference Water Index (NDWI), and surface temperature from thermal infrared sensor (TIRS). The calculation of training sample data was generated from high-resolution imagery and was correlated to the predictor variables using multiple linear regression (MLR) analysis. The R values of predictor variables are significantly correlated. The result of MLR analysis shows that the predictor variables simultaneously have correlation and similar pattern to the PBD based on high-resolution imageries. The Adjusted R Square value is 0,734, indicates that all four variables influences predicting the PBD by 73%

Roof materials identification based on pleiades spectral responses using supervised classification

The current urban environment is very dynamic and always changes both physically and socio-economically very quickly. Monitoring urban areas is one of the most relevant issues related to evaluating human impacts on environmental change. Nowadays remote sensing technology is increasingly being used in a variety of applications including mapping and modeling of urban areas. The purpose of this paper is to classify the Pleiades data for the identification of roof materials. This classification is based on data from satellite image spectroscopy results with very high resolution. Spectroscopy is a technique for obtaining spectrum or wavelengths at each position from various spatial data so that images can be recognized based on their respective spectral wavelengths. The outcome of this study is that high-resolution remote sensing data can be used to identify roof material and can map further in the context of monitoring urban areas. The overall value of accuracy and Kappa Coefficient on the method that we use is equal to 92.92% and 0.9069

A Preliminary Study of the Physico-Chemical Parameters and Potential Pollutant Sources in Urban Lake Rawa Besar, Depok, Indonesia

Lake Rawa Besar is an urban lake surrounded by dense settlements and commercial areas that are currently experiencing physical and ecological pressures due to uncontrolled land-use change around the lake. Therefore, this preliminary study aimed to investigate the sustainable management of the lake in order to create a recreational destination area. It was carried out by ascertaining the lake water quality status through the analysis of the physical and chemical parameters and identifying the potential pollutant sources due to land use and human activities. The physical parameters include TDS, TSS, Turbidity, while the chemical parameters include Nitrate-N, Total Phosphate-P, and BOD. Furthermore, field surveys on 30 water samples were conducted once at noon and statistical analysis was used to ascertain the correlation between the physical and chemical parameters. Finally, Geographic Information System (GIS) tools were used to investigate the spatial distribution of the Physico-chemical parameters and the potential pollutant sources. The results showed that based on the six parameters of the water quality status, the lake was lightly polluted. It also showed that three parameters such as Turbidity, BOD, and TSS exceed the permissible limit with 93.3, 66.7, 43.7% of the total samples, respectively. Additionally, a strong correlation existed between BOD and Turbidity with r=0.95, while a medium correlation existed between Nitrate-N and Phosphate-P with r=0.40. The spatial distribution of the concentration of the physico-chemical parameters generally had a varied pattern,  however, Turbidity and BOD had a similar pattern, especially in the bank areas. Finally, domestic and organic wastes were indicated as pollutant sources, which increased eutrophication in the lake

Rice Crop Phenology Model to Monitor Rice Planting and Harvesting Time using Remote Sensing Approach

Rice is one of the most significant food commodity products in Indonesia. The production of rice in 2019 reached 49.8 million tons. On a global scale, rice is consumed by half of the human population around the world. This study will support the development of sustainable natural resources management, which is an important thing to the realization of the Sustainable Development Goals in zero poverty and zero hunger. Remote sensing is a useful instrument to monitor natural resources. This study used Sentinel-2 imageries to extract rice phenology using vegetation indices (NDVI and NDWI), then acquired the planting and harvesting time using the temporal analysis. The NDVI value is showing a parabolic curve regarding the planting stage of the rice. The value of NDVI is high in the transplanting stage but decreases in the harvesting phase. Besides that, in the seedling and transplanting stage, NDWI has a higher value than NDVI. However, in tillering until the harvesting phase, NDWI has a similar characteristic but lower value than NDVI. Based on the spatial and temporal distribution of rice planting and harvesting date, it is known that climate is not a resistant factor, especially the irrigated rice field. Nevertheless, in the rainfed rice field, the planting time depends on climate conditions

PENGEMBANGAN MODEL IDENTIFIKASI DAERAH BEKAS KEBAKARAN HUTAN DAN LAHAN (BURNED AREA) MENGGUNAKAN CITRA MODIS DI KALIMANTAN (MODEL DEVELOPMENT OF BURNED AREA IDENTIFICATION USING MODIS IMAGERY IN KALIMANTAN)

Kebakaran hutan dan lahan telah menjadi ancaman cukup serius bagi masyarakat secara global pada dua dekade terakhir, terutama terkait dengan degradasi aspek-aspek lingkungan dan sumberdaya alam. Kalimantan merupakan daerah di Indonesia yang paling rawan terhadap bencana kebakaran hutan dan lahan. Penelitian ini bertujuan untuk mengembangkan model-model algoritma untuk mengidentifikasi area terbakar yang paling sesuai diaplikasikan di Kalimantan menggunakan citra MODIS. Metode penelitian dilakukan dengan menggunakan variabel indeks vegetasi (NDVI), indeks kebakaran (NBR), dan reflektansi dari citra MODIS untuk mengidentifikasi area terbakar. Identifikasi area terbakar dilakukan dengan metode pengambangan (thresholding), yaitu perhitungan nilai ambang batas dari perubahan nilai-nilai variabel NDVI, NBR, dan reflektansi untuk piksel-piksel yang dinyatakan sebagai area terbakar. Kemudian dilakukan perhitungan tingkat separabilitas dan akurasi untuk menguji validitas tiap-tiap model. Hasil penelitian ini menunjukkan bahwa pada dasarnya semua model algoritma baik perubahan NDVI, NBR dan reflektansi memiliki kemampuan yang baik dalam mendeteksi area terbakar di Kalimantan. Namun demikian, dari semua model algoritma tersebut, hanya model algoritma perubahan NBR yang memberikan tingkat akurasi paling tinggi, yaitu sebesar 0,635 atau 63,5%. Dengan demikian, model algoritma identifikasi area terbakar yang paling sesuai diaplikasikan untuk daerah Kalimantan dengan menggunakan citra MODIS adalah model algoritma perubahan NBR.Kata kunci: Identifikasi, Area terbakar, NBR, MODIS, Kalimanta