Ketut Wikantika

Impact of Topography and Tidal Height on ALOS PALSAR Polarimetric Measurements to Estimate Aboveground Biomass of Mangrove Forest in Indonesia

This study is focused on investigating the impact of topography and tidal height on ALOS PALSAR polarimetric measurements on HH and HV for estimating aboveground biomass (AGB) of mangrove forest in Indonesia. We used multitemporal ALOS PALSAR polarimetric measurement that covered mangrove zone in Banyuasin, Cilacap, and Teluk Bintuni and also collected tidal height data within the same acquisition date with multitemporal ALOS PALSAR polarimetric measurement. We analyzed the distribution of flooding and nonflooding areas based on tidal height and SRTM topography data, created three profiles as region of interest (ROI), and got characteristics of backscatter value on HH and HV with different tidal height. The result of this study showed backscatter of the open mangrove zones during high tide with HH value less than −20 dB and HV value less than −25 dB whereas during low tide it showed an HH value around −20 to −10 dB and HV value around −25 to −10 dB. Backscatter of the middle mangrove zones at Cilacap, with low and flat topography, showed a deviation of backscatter on HV value of 1.6 dB. Finally, the average AGB of mangrove forest in Indonesia was estimated based on ALOS PALSAR polarimetric measurements.

Characterization of mangrove forest types based on ALOS-PALSAR in overall Indonesian archipelago

Indonesia has largest mangrove forest in the world, total area around 3.5 million ha or 17% – 23% from mangrove forest in the world. Mangrove forest provides products and services, such as carbon balance of the coastal zone. Mapping and monitoring biomass of mangrove is very important but field survey of mangrove biomass and productivity in overall Indonesia is very difficult. Global-scale mosaics with HH and HV backscatter of Advanced Land Observing Satellite (ALOS) Phased Array L-band Synthetic Aperture Radar (PALSAR) which is 50-m spatial resolution has been generated. This image available for identification and monitoring mangrove forest. The Objective of this research to investigate characterization of mangrove forest types based on ALOS-PALSAR in overall Indonesian archipelago. Methodology consists of collecting ALOS-PALSAR image for overall Indonesian archipelago, preprocessing and mosaicking, collecting region of interest of mangrove forest, plotting, ground survey, characterization and classification. The result of this research has showed characterization of mangrove forest types based on ALOS-PALSAR. Indonesian mangrove forest types has HH value around -10 dB until -7 dB and HV value around -17 dB until -13 dB. Higher of HH and HV backscatters value indicated higher of level biomass. Based on scatter plot of HH and HV, Indonesian mangrove forest can be classified in three level biomass. Generally level biomass of mangrove forest in Indonesia archipelago is moderate.

Seasonal analysis of precipitation, drought and Vegetation index in Indonesian paddy field based on remote sensing data

Paddy field is important agriculture crop in Indonesia. Rice is a food staple for 237,6 million Indonesian people. Paddy field growth is strongly influenced by water, but the amount of precipitation is unpredictable. Annual and interannual climate variability in Indonesia is unusual. In recent years remote sensing data has been used for measurement and monitoring of precipitation, drought and vegetation index such as Global Satellite Mapping of Precipitation (GSMaP), Multi-purpose Transmission SATellite (MTSAT) and Moderate Resolution Imaging Spectroradiometer (MODIS). The objective of this research is to investigate seasonal variability of precipitation, drought and vegetation index in Indonesian paddy field based on remote sensing data. The methodology consists of collecting of enhanced vegetation index (EVI) from MODIS data, mosaicking of image, collecting of region of interest of paddy field, collecting of precipitation and drought index based on Keetch Bryam Drought Index (KBDI) from GSMaP and MTSAT, and seasonal analysis. The result of this research has showed seasonal variability of precipitation, KBDI and EVI on Indonesia paddy field from 2007 until 2012. Precipitation begins from January until May and October until December, and KBDI begins to increase from June and peak in September only in South Sumatera precipitation almost in all month. Seasonal analysis has showed precipitation and KBDI affect on EVI that can indicate variety phenology of Indonesian paddy field. Peak of EVI occurs before peak of KBDI occurs and increasing of KBDI followed by decreasing of EVI. In 2010 all province got higher precipitation and smaller KBDI so EVI has three peaks such as in West Java that can indicated increasing of rice production.

Impact of oil and gas field in sugar cane condition using landsat 8 in Indramayu area and its surrounding, West Java province, Republic of Indonesia

This study tried to monitor sugar cane condition surrounding of oil and gas field area. The spectral approaches were conducted for mapping sugar cane stress. As an initial stage Landsat-8 was corrected radiometrically and geometrically. Radiometric correction is an important stages for spectral approaching. Then all pixel values were transformed to the surface reflectance. Several vegetation indices were calculated to monitor vegetation stress surrounding of oil and gas field. NDVI, EVI, DVI, GVI, GRVI, GDVI and GNDVI were applied for generating tentative sugar cane stress images. The results indicated that sugar cane surrounding of oil and gas field has been influenced by oil and gas field.

PENGOLAHAN DATA LANDSAT 8 UNTUK EKSTRAKSI OBJEK DI PERMUKAAN LAUT

Kenampakan objek di permukaan laut seperti kapal, b agan, platform migas dan lainnya secara umum mudah dipetakan menggunakan data citra satelit resolusi tinggi . Akan tetapi, harga citra satelit resolusi tinggi tersebut r elatif lebih mahal. Penggunaan citra satelit resolusi menengah dan regional secara umum hanya untuk pemetaan permukaan laut masih didominasi untuk pemetaan kondisi fisik dan kimia air laut. Penelitian ini bertujuan untuk mengolah data Landsat 8 dalam rangka mengidentifikasi objek di permukaan laut. Berdasarkan hasil kajian objek di laut seperti kapal yang sandar di Pelabuhan Tanjung Emas, Semarang, kapal yang bergerak di Utara Delta Wulan dan b agan t ancap di perairan Jepara dapat diidentifikasi menggunakan NDVI dan penisbahan saluran ((SWIR-RED)/(SWIR+RED)). Kenampakan kapal tampak lebih baik menggunakan NDVI dan penisbahan saluran ((SWIR-RED)/(SWIR+RED)) dibandingkan pada citra komposit warna dengan kombinasi band 653 (RGB). Kapal yang bergerak terlihat jelas dengan buih gelombang dibelakangnya, sedangkan pada citra komposit warna dengan kombinasi band 653 (RGB), buih gelombang tidak dapat dilihat. Demikian juga dengan b agan t ancap yang tidak terlihat pada citra komposit warna dengan kombinasi band 653 (RGB). Namun demikian b agan t ancap dapat diidentifikasi dengan jelas pada NDVI dan penisbahan saluran ((SWIR-RED)/(SWIR +RED)). Kemampuan Landsat 8 untuk memetakan objek di laut dengan baik ini, dapat dimanfaatkan se cara optimal untuk perencanaan kegiatan di bidang migas dan peluang mencari kapal yang hilang ataupun untuk monitoring daerah rawan illegal fishing . Kata kunci: Landsat 8 , kapal, pelabuhan, bagan tancap, NDVI, penisbahan saluran, RGB Abstract The appearance of the object on the sea surface like a ship, charts, and other oil and gas platforms are generally easily mapped using high-resolution satellite imagery data. However, the prices of high-resolution satellite images are relatively expensive. The use of medium resolution satellite imagery and regional general for mapping the sea surface is still dominated for mapping the physical and chemical conditions of seawater. The objective of this research is conducting a processing of Landsat 8 data for identifying objects on the sea surface. Based on the results, objects on the sea, such as ship that is docked at Tanjung Emas Harbour, Semarang and moving ship in North Wulan Delta, Demak, as well as b agan at Jepara sea can be identified using NDVI and Rationing band ((SWIR-RED)/(SWIR +RED)). The appearance of ship is better identified using NDVI and Rationing band ((SWIR-RED)/(SWIR +RED)) than on the composite imageries using combination bands of 653 (RGB). The moving ship seen more clearly with ripple wave in the backside, whereas its cannot be seen in the composite imageries using combination bands of 653 (RGB). Similarly, b agan cannot be seen in the composite imageries using combination bands of 653 (RGB). However, b agan can be identified clearly using NDVI and rationing band ((SWIR-RED)/(SWIR +RED)). Landsat 8 Ability to map the object in the sea with this good, can be used optimally for planning activities in the field of oil and gas and the opportunities to look for the missing ship or for monitoring areas prone to illegal fishing. Keyw o rds: Landsat 8, ship, harbour, b agan, NDVI, rationing band, RGBPengukuran beda tinggi dapat dibagi menjadi dua macam, yaitu beda tinggi dengan menggunakan Sipat Datar dan beda tinggi menggunakan Total Station atau biasa disebut dengan beda tinggi metode Trigonometri. Pengukuran beda tinggi dengan Sipat Datar lebih teliti dibandingkan dengan metode Trigonometri. Hal ini dikarenakan ketelitian beda tinggi dengan Total Station bergantung pada besaran-besaran yang harus diukur , seperti ketelitian hasil ukuran sudut vertikal, jarak, tinggi instrumen dan tinggi reflektor. Melalui penelitian ini, d iharapkan kedepannya pengukuran beda tinggi dengan Total Station dapat menghasilkan beda tinggi dengan ketelitian yang mendekati dengan pengukuran dengan Sipat Datar. Penelitian ini bertujuan untuk mengetahui pengaruh dari penerapan model koreksi beda tinggi metode Trigomometri yaitu y = 0,000126x+0,0014 terhadap ketelitian penentuan tinggi yang dihasilkan, dengan mengambil kasus jaring pemantau stabilitas Candi Borobudur. Penilitian dilakukan dengan menggunakan data jaring verti k al Sipat Datar Leica SPRINTER-100 Candi Borobudur tahun 2011 dan data jaring verti k al Total Station Nikon DTM-322 Candi Borobudur tahun 2012. Pada jaring vertikal Total Station diberikan model koreksi y= 0,000126x+0,0014. Data diproses menggunakan hitung perataan kuadrat terkecil dengan metode parameter terkendala minimal. Pengujian untuk analisis hasil dilakukan dengan menggunakan Uji Fisher dan Uji-t dengan tingkat kepercayaan 95%. Proses pengujian dilakukan pada varian masing-masing data yang dihasilkan, kemudian dilakukan pengujian tinggi titik yang diestimasi untuk melihat hasil penentuan tinggi dengan Total Station yang dibandingkan dengan Sipat Datar. Hasil dari p enerapan model koreksi beda tinggi pada jaring vertikal Total Station Nikon DTM-322 ini bersifat sistematis. Dalam penelitian ini model koreksi tersebut tidak secara signifikan memberikan perubahan pada ketelitian pengukuran tersebut. Kata kunci : j aring vertikal Candi Borobudur, model koreksi beda tinggi, ketelitian tinggi ABSTRACT Measurement of height differences can be obtained by two approaches, t h at is leveling and trigonometric methods using Total Station . The leve l ling method is more accurate than t rigonometric because t he accurac y depends on the precision of the vertical angle, distance, instrument’s height and reflector’s height data. In the future, the Total Station measurements expected could provide the accuracy of height differences approach the levelling. This research aims to find out the impact of giving the height difference model corrections using Trigonometric method, that is y = 0,000126x + 0,0014 to the precision and accuracy of the height determination using Total Station at Borobudur vertical monitoring network. Data used in this research are leveling data using Leica SPRINTER-100 of Borobudur network in 2011 and trigonometric leveling data using Nikon DTM-322 Total Station in 2012. Correction Model y = 0,000126x + 0,0014 was given height data of Borobudur network in 2012. The data was processed using l east square adjustment with minimum constraint . Statistic test to analyze the result provides using Fisher and student t-test with 95% level of confidence. The test was done in each varian data, then the height test estimation conducted to find the Total Station measurement result compared by levelling. Evaluation result indicated that giving correction using model to height differences measured by TS Nikon DTM-322 can not improve the measurements accuracy, because the correction is systematic evaluation. In this study, the correction model is not significantly change in the measurement accuracy. Keywords : v ertical n etwork Borobudur Temple, correction model of height difference, height accuracy

Observing lava dome roughness on synthetic aperture radar (SAR) data: Case study at Mt. Sinabung and Merapi — Indonesia

Detecting ground surface changes at active volcanoes is crucial for better hazard mitigation. Ground based measurements are commonly used to detect surface changes especially on the flanks near to the summit. However, the selection of observation points is limited by field conditions such as rough terrain and topographical barrier. The few number of observation points may lead to miss-interpretation when the displacements related to magma ascent occurred beneath unobserved flanks. This classical problem is common for dormant volcanoes. Overcoming the problem, we used the Synthetic Aperture Radar (SAR) data to observe surface roughness changes at the summit of active volcanoes. This paper discussed the potential capability of the SAR backscattering intensity to observe ground surface changes in view point of surface roughness around the summit. We presented two study cases at Mt. Sinabung in North Sumatra and Mt. Merapi in Central Java - Indonesia. Mt. Merapi was selected for comparison following published references. Mt. Sinabung is currently active since the first phreatic eruption has been occurred in August 2010. Time series of lava dome roughness on SAR (drSAR) method were used to detect ground surface changes prior to the eruption. Based on this method, the ground surface at the summit of Mt. Sinabung changed from 5121 to 6584 m2. The temporal pattern slightly agreed to the ground surface changes at summit of Mt. Merapi prior to the 2010 eruptions. Observing ground surface changes related to surface roughness at the summit might be used as new tools for observing volcanic activity.

Modeling of coastal upwelling using spatiogram and structuring elements

Upwelling is an oceanographic phenomenon where the mass of water from the sea floor, cold temperature and nutrient rich, moving up to the sea surface Upwelling could be happened due to the interaction between the surface water with the wind, ocean currents, Ekman transport, and the Coriolis force, so there is a special characteristic of the upwelling waters. Nevertheless, a common indicator of upwelling is the sea surface temperature (SSI) lower than the surrounding areas, high concentrations of chlorophyll-a, as well as high salinity and density. In coastal upwelling, a lower temperature will be detected near the coast, while warmer temperatures towards offshore. This condition leads to form unique patterns contour of sea surface temperature By using the data of SST derived from satellites, SST can be represented with the color and/or contour. Each color pixel value represents a particular SST. The initial phase of this research is to develop a model for the identification of upwelling based on the pixel and contour patterns. By using sea surface temperature data, the average SST (each month) were analyzed and generate contour lines. Contour lines are formed from the pixels that have the same temperature value. By calculating the distance between pixels in the same temperature class and the distance to the surrounding pixels, we have been developing a model for the detection of upwelling.