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Maninjau Lake is one of Indonesia's lakes for hydroelectric power plants, tourism, and fish farming activities. Some activities around the lake cause pollution, leading to massive fish kill. Therefore, it is necessary to monitor water quality regularly. One of the critical water quality parameters is biochemical oxygen demand (BOD). This study aimed to analyze BOD changes using a remote sensing approach during massive fish kills in Maninjau Lake, Indonesia. Multi-temporal Landsat-8 satellite images are processed to estimate the BOD level based on Wang Algorithm. After that, the estimated BOD value is validated using in situ data measurement. The results of the average BOD concentration that occurred in Lake Maninjau was 1.85 mg/L and showed that R2 was 0.8334, and the standard error was 0.076 between the estimated BOD and in situ data. Furthermore, the average concentration of BOD obtained on 23rd August 2017, 13th December 2017, 30th January 2018, 19th March 2018, and 7th July 2018 are 4.96 mg/L, 4.82 mg/L, 5.31 mg/L, 6.94 mg/L, and 6.60 mg/L, respectively. Increased BOD concentration in January 2018 indicates moderate pollution in the waters. BOD concentration increases after the massive fish kill due to the decaying fish across the lake.

ABSTRAK Indramayu merupakan salah satu lumbung padi Indonesia yang ada di wilayah Jawa Barat dimana Badan Pusat Statistik mencatat pada tahun 2014, Indramayu menghasilkan padi sebesar 1.361.374 ton. Untuk memantau produksi padi, sangat diperlukan pemantauan fase pertumbuhan tanaman padi, salah satu metodenya dengan teknologi penginderaan jauh sistem RADAR menggunakan citra RADARSAT-2 quad polarimetrik. Penelitian ini bertujuan untuk mengklasifikasi daerah fase pertumbuhan tanaman padi menggunakan metode Cloude Pottier H/A/α (entropi/anisotropi/sudut alfa) dan mengevaluasi metode tersebut dalam klasifikasi fase pertumbuhan tanaman padi. Hasil dari penelitian ini yaitu peta klasifikasi fase pertumbuhan tanaman padi dimana dari keseluruhan akuisisi citra, luas lahan tertinggi adalah fase germination/laut yang berjumlah 2.368.242 m2 (22 September 2014). Hasil klasifikasi ini disesuaikan dengan bidang H-α classification plane untuk mengetahui pada zona mana yang memiliki hamburan paling dominan. Hasil pada 18 Juni 2014 dan 5 Agustus 2014 menunjukkan zona 7 (fase panicle initiation/inisiasi malai), zona 8 (fase milk stage/gabah matang susu), dan zona 9 (fase germination/perkecambahan benih atau fase seeding/pertunasan) menjadi zona yang dominan dimana ketiga mekanisme memiliki arti double-bounce scattering (Z7), volume scattering (Z8), dan surface scattering (Z9) sedangkan pada 22 September 2014 dan 16 Oktober 2014 hamburan yang paling dominan terdapat pada Z8 (fase milk stage/gabah matang susu) dengan mekanisme volume scattering dan Z9 (fase germination/perkecambahan benih atau fase seeding/pertunasan) dengan mekanisme surface scattering. Kata kunci: Pertumbuhan Padi, Klasifikasi, RADARSAT-2, H/A/α ABSTRACT Indramayu is one of Indonesia's granary in West Java where Statistic Data Center noted that in 2014 Indramayu produced 1.361.374 tons of rice. It’s necessary to monitor growth phase of rice plant for monitoring rice production, one of the method is remote sensing technology is the RADAR system with RADARSAT-2 image quad-polarimetric. This study aims to classify the phase of growth of rice plants using the Cloude Pottier H / A / α method (entropy / anisotropy / alpha angle) and evaluate these methods in classification of rice plant growth phases. The results of this study are the classification map of the rice plant phase where from the overall image acquisition, the highest land area is the germination / sea phase, which amounts to 2,368,242 m2 (22 September 2014). The classification results are adjusted with the H-α classification plane to find out which zone has the most dominant scattering. The result on 18 June 2014 and 5 August 2014 showed zone 7 (panicle initiation phase), zone 8 (milk stage phase), and zone 9 (germination/seeding) to be the dominant zone where the three mechanisms mean double-bounce scattering (Z7), volume scattering (Z8), and surface scattering (Z9) while on 22 September 2014 and 16 October 2014 the most dominant scattering is in Z8 (milk stage phase) with volume scattering mechanism and Z9 (germination/seeding phase) with surface scattering mechanism Keywords: Rice Growth , Classification, RADARSAT-2, H/A/α.

ABSTRAK Pada umumnya lahan basah dikelola menjadi area pertanian ataupun perkebunan. Fungsi lahan basah memiliki fungsi ekologis seperti pengendali banjir, pencegah intrusi air laut, erosi, pencemaran, dan pengendali iklim global. Data pengindraan jauh yang digunakan pengelolaan lahan basah yaitu pengindraan jauh optik dan radar. Tujuan dari penelitian ini adalah mengeksplorasi korelasi potensial dari data optik dan radar untuk mengamati dinamika pada kawasan lahan basah tersebut dan melakukan pemetaan. Metode yang digunakan pada pengindraan jauh optik yaitu LST (Land Surface Temperature) berdasarkan Citra Satelit Landsat-8 dan metode yang digunakan pada pengindraan jauh radar yaitu estimasi kelembaban tanah berdasarkan Citra Satelit Sentinel-1A. Hasil pengamatan dinamika dan pemetaan pada wilayah Kabupaten Bandung Raya memiliki nilai kelembaban tanah tertinggi pada Bulan Mei dengan nilai kelembapan tanah tanah rata-rata sebesar 20,9 % pada polarisasi VH. Suhu permukaan tanah terendah terjadi pada bulan Mei dengan nilai suhu rata-rata sebesar 19.5 °C. Kolerasi antara nilai kelembapan tanah tanah dan suhu permukaan tanah pada wilayah Kabupaten Bandung Raya berdasarkan metode koefisien determinasi sebesar R2=0.705 didapatkan bahwa semakin tinggi nilai kelembapan tanah tanah maka nilai suhu permukaan tanah akan semakin rendah. Kata kunci: Kawasan lahan basah, Pengindraan Jauh Optik, Pengindraan Jauh Radar, Pengamatan Dinamika, Pemetaan. ABSTRACT In general wetlands managed become an area of agriculture or plantations. The extent of wetland that has been used can be damaged if it is not managed properly and integrated.. The purpose of this research is to explore the potential correlations between several parameters of optical and radar data to observe the dynamics of wetlands area and mapping the wetlands area. The methodology that was used in optical remote sensing is LST (Land Surface Temperature) based on Landsat-8 Satellite Image and the method used in remote radar sensing is estimation of soil moisture based on Sentinel-1A Satellite Image. The result of the observation in the area and mapping the dynamics in Bandung Raya District had the highest soil moisture values in May with 27% of soil water level in VH polarization and 78.1% in VV polarization and the lowest value in each month is 11.8% and the highest soil surface temperature in August with a value 37.9 ° C and the minimum value 19 ° C.. Keywords: Wetland Area, Optical Remote Sensing, Remote Radar Sensing, Dynamics Observation, Mapping.

ABSTRAK Indonesia mempunyai 127 gunung api aktif yang tersebar dari Sabang sampai Merauke. Oleh karena itu, perlu adanya pemantauan aktivitas gunung api yang dapat digunakan untuk acuan mitigasi bencana. Pada penelitian ini menggunakan metode deformasi, metode deformasi merupakan perubahan bentuk, posisi, dan dimensi dari suatu benda. Tujuan dari pemantauan deformasi ini untuk mengetahui perubahan gunung api yang disebabkan oleh aktivitas gunung api. Pemantauan aktivitas gunung api metode deformasi dilakukan dengan menggunakan citra Sentinel-1A yang diolah dengan teknologi Differential Interferometry SAR (DInSAR). Dalam penelitian ini dilakukan pengolahan dengan teknologi DInSAR metode two-pass dari empat buah citra satelit sentinel-1A 10 Januari 2018, 27 Februari 2018, 10 Mei 2018 dan 22 Januari 2019 serta data Digital Elevation Model (DEM) SRTM dengan ketelitian 30 meter .Hasil dari penelitian ini yaitu peta deformasi pra 1 erupsi yang diolah dari pasangan citra 10 Januari 2018 dengan citra 27 Februari 2018 yang menghasilkan deflasi sebesar -0,12 meter, dan peta deformasi pra 2 erupsi yang diolah dari pasangan citra 27 Februari 2018 dan 10 Mei 2018 menghasilkan deflasi sebesar -0,27 meter serta peta pasca erupsi yang diolah dari pasangan citra 10 Mei 3018 dan 22 Januari 2019 menghasilkan deflasi sebesar -0,194 meter. Kata kunci: Deformasi, Gunung Merapi, Sentinel-1A, DInSAR. ABSTRACT Indonesia has 127 active volcanoes spread over from Sabang to Merauke. Therefore, it is necessary to monitor volcanic activity that can be used as a reference for disaster mitigation. In this study, deformation method was used to reflect a change in the shape, position, and dimensions of an object. The purpose of monitoring this deformation is to find out volcanic changes caused by volcanic activity. Monitoring the volcanic activity of the deformation method is carried out using Sentinel-1A images processed with Differential Interferometry SAR (DInSAR) technology. In this research, two-pass method of DInSAR technology was processed using four sentinel-1A satellite images on January 10, 2018, February 27, 2018, May 10, 2018 and January 22, 2019 and SRTM Digital Elevation Model (DEM) data with 30 meters accuracy. This research processed pre-eruption deformation map from the 10 January 2018 imagery pair with the 27 February 2018 image which resulted in a deflation of 0.12 meters. Pre- eruption 2 deformation map was processed from the 27 February 2018 and 10 May 2018 image pairs and resulted in a deflation of 0.27 meters while post-eruption map processed from the 10 May 3018 and 22 January 2019 image pairs resulted in deflation of 0.194 meters. Keywords: Deformation, Merapi Mountain, Sentinel-1A, DinSAR.

Drought monitoring is important for the paddy planting planning. Remote sensing is one tool can be used for it. Paddy field monitoring based on the soil moisture gives much knowledge related to the water content in the soil. Soil moisture analysis in this study is using Normalized Different Water Index (NDWI), Linear Soil Moisture (LSM), and Tasseled Cap. Soil moisture change could explain based on calculation results of NDWI, Linear Soil Moisture (LSM), and Tasseled Cap Transformation (TCT). Based on the results has explained that the driest year occurs in 2015 and June 2016 has a higher soil moisture. Comparison with the radar shows that the results of soil moisture analysis with Landsat was effective can be used with results relatively close to the radar results.

Monitoring at every growth of rice plants is an important information for determining the grain pro-duction estimation of rice. Monitoring must to be have timely work on the rice plant development. However, timely monitoring and the high accuracy of information is a challenge in remote sensing based on rice agriculture monitoring and observation. With increased quality of synthetic aperture radar (SAR) systems utilizing polarimetric information recently, the development and applications of polarimetric SAR (PolSAR) are one of the current major topics in radar remote sensing. The ad-vantages provided by PolSAR data for agricultural monitoring have been extensively studied for applications such as crop type classification and mapping, crop phenology monitoring, productivity assessment based on the sensitivity of polarimetric parameters to indicators of crop conditions. Freeman and Durden successfully decomposed fully PolSAR data into three components: Single bounce, double bounce, and volume scattering. The three-component scattering provide features for distinguishing between different surface cover types. These sensitivities assist in the identification of growing phase. The observed growing phase development in time series, reflected in the consistent temporal trends in scattering, was generally in agreement with crop phenological development stages. Supervised classification was performed on repeat-pass Radarsat-2 images, with an overall classification accuracy of 77.27% achieved using time series Fine beam data. The study demonstrated that Radarsat-2 Fine mode data provide useful information for crop monitoring and classification of rice plants.

Indonesia is a tropical country which has dominant cloud coverage, and some of the area has cloud cover almost all year long. Mapping by optical sensors, especially with Photogrammetric method shows a very good result, but the main constraint is cloud cover conditions, and this was the weakness point of this method.This study describe the technique for deriving Topographic data from Radarsat Synthetic Aperture Radar stereo image pair and apply it to an image pair over West Kalimantan, Indonesia. This paper contains also brief discussion of the use of stereo SAR to derive Digital Elevation Model, the site condition and the source of validation data. The result shows that Radarsat data recommended only for 1 : 100.000 or smaller.