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All Journal Jurnal Ilmiah Widya International Journal of Remote Sensing and Earth Sciences (IJReSES) Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital The International Journal of Remote Sensing and Earth Sciences (IJReSES)
Nana Suwargana
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Aerospace Engineering Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Earth & Planetary Sciences Electrical & Electronics Engineering Other

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RESOLUSI SPASIAL, TEMPORAL DAN SPEKTRAL PADA CITRA SATELIT LANDSAT, SPOT DAN IKONOS Suwargana, Nana
Jurnal Ilmiah Widya Vol 1 No 2 (2013)
Publisher : Lembaga Layanan Pendidikan Tinggi Wilayah III Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (79.626 KB)

Abstract

Satellite remote sensing data is one of the data to obtain natural phenomena on Earth's surface obtained by a media device (sensor) mounted on an aircraft or a satellite. The purpose of this study is to elaborate on the technical characteristics of the remote sensing satellite imagery produced by a variety of earth, satellite Landsat, Spot and Ikonos data and the potential applications for various fields. The method used literature study, internet media and the data was analyzed descriptively. The results showed that: (1) The sensor can detect an object through measurements of the Earth's surface reflectance or emission of electromagnetic waves by the medium. (2) Various types of remote sensing satellite data received by the sensor have different characteristics, so the potential utilization also vary. (3) Characteristics generated by satellite images of the earth which are spatial resolution, temporal resolution and spectral resolution.
MONITORING OF LAKE ECOSYSTEM PARAMETER USING LANDSAT DATA (A CASE STUDY: LAKE RAWA PENING) Bambang Trisakti; Nana Suwargana; Joko Santo Cahyono
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 12, No 1 (2015)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (970.375 KB) | DOI: 10.30536/j.ijreses.2015.v12.a2674

Abstract

Most lakes in Indonesia have suffered (decrease in quality) caused by land conversion in the catchment area, soil erosion, and water pollution from agriculture and households. This study utilizes remote sensing data to monitor several parameters used as ecosystem status assessors in accordance with the guidelines of Lake Ecosystem Management provided by the Ministry of Environment. The monitoring was done at Lake Rawa Pening using Landsat TM/ETM+ satellite data over the period of 2000-2013. The data standardization was done for sun angle correction and also atmospheric correction by removing dark pixels using histogram adjustment method. RGB color composites (R: NIR + SWIR, G: NIR, B: NIR-RED) were used for water hyacinth identification; thus, the lake water surface area can be delineated. Further samples were collected for water hyacinth and water classification with Maximum Likelihood method. Total Suspended Matter (TSM) by Doxaran model and the water clarity from field measurement was correlated to build water clarity algorithm. The results show that Lake Rawa Pening was deterioting in term of quality during the period of 2000-2013; it can be seen from the dynamic rate of the shrinkage and the expansion of the lake water surface area, the uncontrolled distribution of water hyacinth which it covered 45% of the lake water surface area in 2013, the increased of TSM concentration, and the decreased of water clarity. Most parts of Rawa Pening’s water have clarity less than 2.5 m which indicated that the thropic status is hypertrophic class.
PENENTUAN SUHU PERMUKAAN LAUT DAN KONSENTRASI KLOROFIL UNTUK PENGEMBANGAN MODEL PREDIKSI SST/FISHING GROUND DENGAN MENGGUNAKAN DATA MODIS Suwargana, Nana; Arief, Muchlisin
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 1 No. 1 (2004)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/inderaja.v1i1.3086

Abstract

Research on oceanography application either in global scale or mesoscale requires sea surface temperature observation and imagery ocean color from satellite. LAPAN has done some observation on oceanography by using NOAA-AVHRR Satelit Data, as in determining the implemented sea surface temperature to determine fishing ground (fish catching area), etc. However, by launching the new satellite that TERRA Satellite that brings spectral multi sensor (MODIS data/Moderate Imaging Spectroradiometer), the research is tried by using MODIS data. The aim of this research is to determine sea surface temperature distribution and to see klorofill content distribution by using MODIS data in order to determine the phenomena of upwelling and front. The method that is carried out in this research is by using algoritma from (Minnet, 2001) for sea surface temperature and (Relly, 1998) for klorofill concentration, and to converse the radiance value [band 21 and band 32] of MODIS image to sea surface temperature value and conversion of two-channel ratio of visible area [band 9 and 12] to the value of the klorofill content. The result of the research shows that algoritma development model whether for sea surface temperature or cholorophyll concentration gives the value of spatial distribution that generally is close to what has been obtained from NOAA-AVHRR satellite data or SeaWhifs. However, the above result still require the detailed development and validation.
ANALISIS PERUBAHAN HUTAN MANGROVE MENGGUNAKAN DATA PENGINDERAAN JAUH DI PANTAI BAHAGIA, MUARA GEMBONG, BEKASI Suwargana, Nana
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 5 No. 1 (2008)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/inderaja.v5i1.3238

Abstract

Mangrove forests grow near the big river estuary where the river delta gives a lot of sediment (sand and mud). Mangrove roots collect sediments and slow the water flow to protect the coastline and prevent the erosion. Along the time, the roots can collect mud to extend the edge of the coastline. The purpose of this study was to analyze the changes of mangrove forests, coastline, and its effect on the income of fishermen on the Bahagia coast, Muara Gembong, Bekasi, West Java Province during 17 years between 1990 and 2007. Observations were made by using two series of multitemporal (Landsat-TM 1990 and SPOT-4 2007) data. Information about the distribution, extent and land cover changes to analyze the value was obtained by the spectral based (RGB 453 Landsat-TM and RGB 143 SPOT-4) color composite image, image classification, and field data. While information on the coastline change based on the 2007 classified images was overlayed with the classified images. The results show that: 1). mangrove forest changes during the 17 years (1990-2007) has decreased from 34.89 hectares to 33.23 hectares and the results of overlaying the image of the coastline of classification image in 2007 with the coastline of classification image in 1990 found that there coastline abrasion occurs and accretion; 2). conditions of the existence of mangrove forests in coast Bahagia with a dwindling population have affected the income of fishermen nearby.
BATHYMETRY EXTRACTION FROM SPOT 7 SATELLITE IMAGERY USING RANDOM FOREST METHODS Kuncoro Teguh Setiawan; Nana Suwargana; Devica Natalia BR Ginting; Masita Dwi Mandini Manessa; Nanin Anggraini; Syifa Wismayati Adawiah; Atriyon Julzarika; Surahman; Syamsu Rosid; Agustinus Harsono Supardjo
International Journal of Remote Sensing and Earth Sciences Vol. 16 No. 1 (2019)
Publisher : BRIN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2019.v16.a3085

Abstract

The scope of this research is the application of the random forest method to SPOT 7 data to produce bathymetry information for shallow waters in Indonesia. The study aimed to analyze the effect of base objects in shallow marine habitats on estimating bathymetry from SPOT 7 satellite imagery. SPOT 7 satellite imagery of the shallow sea waters of Gili Matra, West Nusa Tenggara Province was used in this research. The estimation of bathymetry was carried out using two in-situ depth-data modifications, in the form of a random forest algorithm used both without and with benthic habitats (coral reefs, seagrass, macroalgae, and substrates). For bathymetry estimation from SPOT 7 data, the first modification (without benthic habitats) resulted in a 90.2% coefficient of determination (R2) and 1.57 RMSE, while the second modification (with benthic habitats) resulted in an 85.3% coefficient of determination (R2) and 2.48 RMSE. This research showed that the first modification achieved slightly better results than the second modification; thus, the benthic habitat did not significantly influence bathymetry estimation from SPOT 7 imagery
MONITORING OF LAKE ECOSYSTEM PARAMETER USING LANDSAT DATA (A CASE STUDY: LAKE RAWA PENING) Bambang Trisakti; Nana Suwargana; Joko Santo Cahyono
International Journal of Remote Sensing and Earth Sciences Vol. 12 No. 1 (2015)
Publisher : BRIN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2015.v12.a2674

Abstract

Most lakes in Indonesia have suffered (decrease in quality) caused by land conversion in the catchment area, soil erosion, and water pollution from agriculture and households. This study utilizes remote sensing data to monitor several parameters used as ecosystem status assessors in accordance with the guidelines of Lake Ecosystem Management provided by the Ministry of Environment. The monitoring was done at Lake Rawa Pening using Landsat TM/ETM+ satellite data over the period of 2000-2013. The data standardization was done for sun angle correction and also atmospheric correction by removing dark pixels using histogram adjustment method. RGB color composites (R: NIR + SWIR, G: NIR, B: NIR-RED) were used for water hyacinth identification; thus, the lake water surface area can be delineated. Further samples were collected for water hyacinth and water classification with Maximum Likelihood method. Total Suspended Matter (TSM) by Doxaran model and the water clarity from field measurement was correlated to build water clarity algorithm. The results show that Lake Rawa Pening was deterioting in term of quality during the period of 2000-2013; it can be seen from the dynamic rate of the shrinkage and the expansion of the lake water surface area, the uncontrolled distribution of water hyacinth which it covered 45% of the lake water surface area in 2013, the increased of TSM concentration, and the decreased of water clarity. Most parts of Rawa Pening’s water have clarity less than 2.5 m which indicated that the thropic status is hypertrophic class.
WATER CLARITY MAPPING IN KERINCI AND TONDANO LAKE WATERS USING LANDSAT 8 DATA Bambang Trisakti; Nana Suwargana; I Made Parsa
International Journal of Remote Sensing and Earth Sciences Vol. 12 No. 2 (2015)
Publisher : BRIN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2015.v12.a2693

Abstract

Land conversion occurred in the lake catchment area caused the decreasing of water quality in many lakes of Indonesia. According to Lake Ecosystem Management Guidelines from Ministry of Environment, tropic state of lake water is one of parameters for assessing the lake ecosystem status. Tropic state can be indicated by the quantity of nitrogen, phosphorus, chlorophyll, and water clarity. The objective of this research is to develop the water quality algorithm and map the water clarity of lake water using Landsat 8 data. The data were standardized for sun geometry correction and atmospheric correction using Dark Object Subtraction method. In the first step, Total Suspended Solid (TSS) distributions in the lake were calculated using a semi empirical algorithm (Doxaran et al., 2002), which can be applied to a wide range of TSS values. Secchi Disk Transparency (SDT) distributions were calculated using our water clarity algorithm that was obtained from the relationship between TSS and SDT measured directly in the lake waters. The result shows that the water clarity algorithm developed in this research has the determination coefficient that reaches to 0,834. Implementation of the algorithm for Landsat 8 data in 2013 and 2014 showed that the water clarity in Kerinci Lake waters was around 2 m or less, but the water clarity in Tondano Lake waters was around 2 – 3 m. It means that Kerinci Lake waters had lower water clarity than Tondano Lake waters which is consistent with the field measurement results.
Co-Authors Agustinus Harsono Supardjo Atriyon Julzarika Bambang Trisakti Devica Natalia BR Ginting I Made Parsa Joko Santo Cahyono Kuncoro Teguh Setiawan Masita Dwi Mandini Manessa Muchlisin Arief Nanin Anggraini Surahman Syamsu Rosid Syifa Wismayati Adawiah