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International Journal of Remote Sensing and Earth Sciences (IJReSES)

ijreses
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Published by Lembaga Penerbangan dan Antariksa Nasional

ISSN : 02166739 EISSN : 2549516X DOI : -

Core Subject : Science,

Earth & Planetary Sciences

International Journal of Remote Sensing and Earth Sciences (IJReSES) is expected to enrich the serial publications on earth sciences, in general, and remote sensing in particular, not only in Indonesia and Asian countries, but also worldwide. This journal is intended, among others, to complement information on Remote Sensing and Earth Sciences, and also encourage young scientists in Indonesia and Asian countries to contribute their research results. This journal published by LAPAN.

Arjuna Subject : -

Articles 320 Documents

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RESEARCH ON TECHNOLOGY DEVELOPMENT FOR FISHING VESSELS IDENTIFICATION BY SATELLITE REMOTE SENSING - STATUS IN DEVELOPED COUNTRIES AND JAPANESE PATROL SYSTEM T. MORIYAMA; H. TAMEISHI; J. SUWA; S. KANNO; Y. SUGIMORI
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 1,No. 1(2004)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

Current status and trends ov vessel detection, identification technology development and application in major countries were surveyed. According to increasing the number of foreign poaching and suspicious vessels intrusion into EEZ, patroliling by vessel and airplane does not satisfy the needs because of narrow coverege and observation frequncey. The satellite monitoring by SAR and optical sensor has been studied and partially used, but there are several disavantages such as observation frequncy, geometric occuracy and weather dependence to adopt for operational use. This paper describes an optimize system for vessel detection and identification by combining patrolling vessel, airplane and satellite. Keyword: vessel identification by satellite image, IKONOS visible image, JERS-1, Synthetic Apature Reader

THE UTILIZATION OF REMOTE SENSING DATA TO SUPPORT GREEN OPEN SPACE MAPPING IN JAKARTA, INDONESIA Hana Listi Fitriana; Sayidah Sulma; Nur Febrianti; Jalu Tejo Nugroho; Nanik Suryo Haryani
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 15, No 2 (2018)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

Green open space becomes critical in maintaining the balance of the environment and improving the quality of urban living for a healthy life. The use of remote sensing data for calculation of green open space has been done notably using NDVI (Normalized Difference Vegetation Index) method from Landsat 8 and SPOT data. This research aims to calculate the accuracy of the green open space classification from multispectral data of Landsat 8 and SPOT 6 using the NDVI methods. Green open space could be assessed from the value NDVI. The value of NDVI generated from Landsat 8 and SPOT 6’s Red and NIR channels. The accuracy of NDVI values is then examined by comparing with Pleiades data. Pleiades data which has 50 cm panchromatic resolution and 2 m multispectral with 4 bands (B, G, R, NIR) can precisely visualize objects. So, it can be used as the reference in the calculation of the green open space based on NDVI. The results of the accuracy testing of Landsat 8 and SPOT 6 image could be used to identify the green open space by using NDVI SPOT of 6 can increase the accuracy of 5.36% from Landsat 8.

DETECTION OF ACID SLUDGE CONTAMINATED AREA BASED ON NORMALIZED DIFFERENCE VEGETATION INDEX (NDVI) VALUE Nanik Suryo Haryani; Sayidah Sulma; Junita Monika Pasaribu
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 11, No 1 (2014)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

The solid form of oil heavy metal waste is known as acid sludge. The aim of this research is to exercise the correlation between acid sludge concentration in soil and NDVI value, and further studying the Normalized Difference Vegetation Index (NDVI) anomaly by multi-temporal Landsat satellite images. The implemented method is NDVI. In this research, NDVI is analyzed using the remote sensing data on dry season and wet season. Between 1997 to 2012, NDVI value in dry season is around – 0.007 (July 2001) to 0.386 (May 1997), meanwhile in wet season NDVI value is around – 0.005 (November 2006) to 0.381 (December 1995). The high NDVI value shows the leaf health or thickness, where the low NDVI indicates the vegetation stress and rareness which can be concluded as the evidence of contamination. The rehabilitation has been executed in the acid sludge contaminated location, where the high value of NDVI indicates the successfull land rehabilitation effort.

IDENTIFICATION OF LAND SURFACE TEMPERATURE DISTRIBUTION OF GEOTHERMAL AREA IN UNGARAN MOUNT BY USING LANDSAT 8 IMAGERY Udhi C. Nugroho; Dede Dirgahayu Domiri
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 12, No 2 (2015)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

Indonesia located at the confluence of Eurasian tectonic plate, Australian tectonic plate and the Pacific tectonic plate. Therefore, Indonesia has big geothermal potential. One of the areas that has geothermal potential is Ungaran Mount. Remote sensing technology can have a role in geothermal exploration activity to map the distribution of land surface temperatures associated with geothermal manifestations. The advantages of remote sensing are able to get information without having to go directly to the field with a large area, and it takes quick, so that the information can be used as an initial reference exploration activities. This study aimed to obtain the distribution of land surface temperature as a regional analysis of geothermal potential. The method of this research was a correlation of brightness temperature (BT) Landsat 8 with land surface temperature (LST) MODIS. The results of correlation analysis showed the R2 value was equal to 0.87, it shows that between BT Landsat 8 and LST MODIS has a very high correlation. Based on Landsat 8 LST imagery correction, the average of fumarole temperature and hot spring is 240C. Fumarole and hot spring are located in dense vegetation land which has average temperature around 26.90C. Land surface temperature Landsat 8 can not be directly used to identify geothermal potential, especially in the dense vegetation area, due to the existence of dense vegetation which can absorb heat energy released by geothermal surface feature.

LAND COVER CLASSIFICATION OF ALOS PALSAR DATA USING SUPPORT VECTOR MACHINE Katmoko Ari Sambodo; Novie Indriasari
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 10, No 1 (2013)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

Land cover classification is one of the extensive used applications in the field of remote sensing. Recently, Synthetic Aperture Radar (SAR) data has become an increasing popular data source because its capability to penetrate through clouds, haze, and smoke. This study showed on an alternative method for land cover classification of ALOS-PALSAR data using Support Vector Machine (SVM) classifier. SVM discriminates two classes by fitting an optimal separating hyperplane to the training data in a multidimensional feature space, by using only the closest training samples. In order to minimize the presence of outliers in the training samples and to increase inter-class separabilities, prior to classification, a training sample selection and evaluation technique by identifying its position in a horizontal vertical–vertical horizontal polarization (HV-HH) feature space was applied. The effectiveness of our method was demonstrated using ALOS PALSAR data (25 m mosaic, dual polarization) acquired in Jambi and South Sumatra, Indonesia. There were nine different classes discriminated: forest, rubber plantation, mangrove & shrubs with trees, oilpalm & coconut, shrubs, cropland, bare soil, settlement, and water. Overall accuracy of 87.79% was obtained, with producer’s accuracies for forest, rubber plantation, mangrove & shrubs with trees, cropland, and water class were greater than 92%.

IDENTIFICATION OF FISHERY RESOURCES IN MADURA STRAIT BASED ON THE IMPLEMENTATION OF POTENTIAL FISHING ZONE INFORMATION FROM REMOTE SENSING Bidawi Hasyim; Maryani Hartuti; Sayidah Sulma
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 6,(2009)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

Spatial information of Potential Fishing Zone (PFZ) was used to identify the prospective location in the Madura Strait, where the fishermen from Fish Landing Port (FLP) around the Madura Strait conducted fishing activities. PFZ was aimed to determine fishing location, to identify the type of pelagic fish resources which were dominantly caught in the MAdura Strait. Fish resources data were obtained by observing the FLP in the east of Madura Strait especially in Pondok Mimbo, Jangkar, Besuki, Probolinggo, Pamekasan, and Sumenep. Based on the application of PFZ spatial information and observation, the types of pelagic fish caught on west monsoon were dominated by Euthynnus spp, Decapterus spp, Ratsrellinger spp, and Trichiurus spp. In the first transition season, types of fish resources were a mix between Euthynnus spp, Decapterus spp, Rastrellinger spp, Sardinella longiceps, and Trichiurus spp, however Sardinella longiceps were still dominated the catches. During the east monsoon fish resources at the Madura Strait was also dominated by Sardinella longiceps. This condition occurred until the second month of the second transition season followed by the mixing among Sardinella longiceps, Euthynnus spp, Decapterus spp, Rastrellinger spp and Trichiurus spp. Keywords: Fish Landing Port, NOAA-AVHRR, Potential fishing zone

SPECTRAL ANALYSIS OF THE HIMAWARI-8 DATA FOR HOTSPOT DETECTION FROM LAND/FOREST FIRES IN SUMATRA Hana Listi Fitriana; Sayidah Sulma; nFN suwarsono; Any Zubaidah; Indah Prasasti
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 15, No 1 (2018)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

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.

UTILIZATION OF NEAR REAL-TIME NOAA-AVHRR SATELLITE OUTPUT FOR EL NIÑO INDUCED DROUGHT ANALYSIS IN INDONESIA (CASE STUDY: EL NIÑO 2015 INDUCED DROUGHT IN SOUTH SULAWESI) Amsari Mudzakir Setiawan; Yonny Koesmaryono; Akhmad Faqih; Dodo Gunawan
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 13, No 2 (2016)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

Drought is becoming one of the most important issues for government and policy makers. National food security highly concerned, especially when drought occurred in food production center areas. Climate variability, especially in South Sulawesi as one of the primary national rice production centers is influenced by global climate phenomena such as El Niño Southern Oscillation or ENSO. This phenomenon can lead to drought occurrences. Monitoring of drought potential occurrences in near real-time manner becomes a primary key element to anticipate the drought impact. This study was conducted to determine potential occurrences and the evolution of drought that occurred as a result of the 2015 El Niño event using the Vegetation Health Index (VHI) from the National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) satellite products. Composites analysis was performed using weekly Smoothed and Normalized Difference Vegetation Index (or smoothed NDVI) (SMN), Smoothed Brightness Temperature Index (SMT), Vegetation Condition Index (VCI), Temperature Condition Index (TCI), and Vegetation Health Index (VHI). This data were obtained from The Center for Satellite Applications and Research (STAR) - Global Vegetation Health Products (NOAA) website during 35-year period (1981-2015). Lowest potential drought occurrences (highest VHI and VCI value) caused by 2015 El Niño is showed by composite analysis result. Strong El Niño induced drought over the study area indicated by decreasing VHI value started at week 21st. Spatial characteristic differences in drought occurrences observed, especially on the west coast and east coast of South Sulawesi during strong El Niño. Weekly evolution of potential drought due to the El Niño impact in 2015 indicated by lower VHI values (VHI < 40) concentrated on the east coast of South Sulawesi, and then spread to another region along with the El Nino stage.

ESTIMATION OF CHLOROPHYLL-A CONCENTRATION FROM THE ATMOSPHERIC CORRECTION OF MISR DATA Sisir Kumar Dash; Tasuku Tanaka; Hiroyuki Hachiya; Yashuhiro Sugimori
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 3,(2006)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

Multi Angle Imaging Spectro Radiometer (MISR) has a capability to observe the ocean surface from different viewing directions. Attempts were made to estimate the ocean surface reflectance and chlorophyll-a concentration using MISR data. The aerosol optical thickness (OAT), available from the MISR archive is compared with the results simulated using the 6S radiation transfer code. It turns out that the AOT values agree with each other up to 85 percent in certain areas in case-1 waters. Substituting the archive values of AOT into the radiative transfer process, we obtain the surface reflectance. This surface reflectance, in turn, is employed together with the in-water algorithm, to obtain the clhorophyll concentration maps for three viewing directions (aft, nadir and forward). The pattern of obtained chlorophyll map is reasonable. It is estimated that an error of about 35 percent is involved in the radiance calibration and AOT , Hence, with best possibility, the surface reflectance is quantified and the chlorophyll maps were generated. When it is compared with the nadir observation, the forward viewing camera overestimates and the aft viewing camera underestimates the chlorophyll-a concentrartion especially in case-1 waters. In case 2 waters, the chlorophyll-a concentration shows similiar patterns for the three different viewing directions. Due to lack of in-situ data, absolute chlorophyll values were ignored but errors were quatified for the surface reflectance and the aerosol optical thickness with the 6S simulated results. Keywords: MISR, 6S, AOT, Surface reflectance, Chlorophyll-a

A COMPARISON OF OBJECT-BASED AND PIXEL-BASED APPROACHES FOR LAND USE/LAND COVER CLASSIFICATION USING LAPAN-A2 MICROSATELLITE DATA Jalu Tejo Nugroho; . Zylshal; Nurwita Mustika Sari; Dony Kushardono
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 14, No 1 (2017)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

In recent years, small satellite industry has been a rapid trend and become important especially when associated with operational cost, technology adaptation and the missions. One mission of LAPAN-A2, the 2nd generation of microsatellite that developed by Indonesian National Institute of Aeronautics and Space (LAPAN), is Earth observation using digital camera that provides imagery with 3.5 m spatial resolution. The aim of this research is to compare between object-based and pixel-based classification of land use/land cover (LU/LC) in order to determine the appropriate classification method in LAPAN-A2 dataprocessing (case study Semarang, Central Java).The LU/LC were classified into eleven classes, as follows: sea, river, fish pond, tree, grass, road, building 1, building 2, building 3, building 4 and rice field. The accuracy of classification outputs were assessed using confusion matrix. The object-based and pixel-based classification methods result for overall accuracy are 31.63% and 61.61%, respectively. According to accuracy result, it was thought that blurring effect on LAPAN-A2 data may be the main cause ofaccuracy decrease. Furthermore, the result is suggested to use pixel-based classification to be applied inLAPAN-A2 data processing.

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