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International Journal of Remote Sensing and Earth Sciences (IJReSES)
ISSN : 02166739     EISSN : 2549516X     DOI : -
Core Subject : Science,
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.
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Articles 7 Documents
Search results for , issue " Vol 9, No 1 (2012)" : 7 Documents clear
LAND COVER CLASSIFICATION ALOS AVNIR DATA USING IKONOS AS REFERENCE Trisakti, Bambang; Ambarwati, Dini Oktaviana
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 9, No 1 (2012)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

Show Abstract | Original Source | Check in Google Scholar | Full PDF (1490.394 KB) | DOI: 10.30536/j.ijreses.2012.v9.a1822

Abstract

Abstract.  Advanced Land Observation Satellite (ALOS) is a Japanese satellite equipped with 3  sensors  i.e.,  PRISM,  AVNIR,  and  PALSAR.  The  Advanced  Visible  and  Near  Infrared Radiometer (AVNIR) provides multi spectral sensors ranging from Visible to Near Infrared to observe  land  and  coastal  zones.  It  has  10  meter  spatial  resolution,  which  can  be  used  to map  land  cover  with  a  scale  of 1:25000.  The  purpose  of  this  research  was  to  determineclassification  for  land  cover  mapping  using  ALOS  AVNIR  data.  Training  samples  were collected  for  11  land  cover  classes  from  Bromo  volcano  by  visually  referring  to  very  high resolution  data  of  IKONOS  panchromatic  data.  The  training  samples  were  divided  into samples  for  classification  input  and  samples  for  accuracy  evaluation.  Principal  component analysis (PCA) was conducted for AVNIR data, and the generated PCA bands were classified using Maximum Likehood  Enhanced Neighbor method. The classification result was filtered and  re-classed  into  8  classes.  Misclassifications  were  evaluated  and  corrected  in  the  post processing  stage.  The  accuracy  of  classifications  results,  before  and  after  post  processing, were  evaluated  using  confusion  matrix  method.  The  result  showed  that  Maximum Likelihood  Enhanced  Neighbor  classifier  with  post  processing  can  produce  land  cover classification  result  of  AVNIR  data  with  good  accuracy  (total  accuracy  94%  and  kappa statistic 0.92).  ALOS AVNIR has been proven as a potential satellite data to map land cover in the study area with good accuracy.
COMPARISON OF THE VEGETATION INDICES TO DETECT THE TROPICAL RAIN FOREST CHANGES USING BREAKS FOR ADDITIVE SEASONAL AND TREND (BFAST) MODEL Darmawan, Yahya; Sofan, Parwati
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 9, No 1 (2012)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

Show Abstract | Original Source | Check in Google Scholar | Full PDF (1823.824 KB) | DOI: 10.30536/j.ijreses.2012.v9.a1823

Abstract

Remotely  sensed  vegetation  indices  (VI)  such  as  the  Normalized  Difference Vegetation Index (NDVI) are increasingly used as a proxy indicator of the state and condition of  the  land  cover/vegetation,  including  forest.  However,  the  Enhanced  Vegetation  Index (EVI)  on  the  outcome  of  forest  change  detection  has  not  been  widely  investigated.  We compared the influence of using EVI and NDVI on the number and time of detected changes by applying Breaks for Additive Seasonal and Trend (BFAST), a change detection algorithm. We  used  MODIS  16-day  NDVI  and  EVI  composite  images  (April  2000-April  2012)  of  three pixels  (pixels  352,  378,  and  380)  in  the  tropical  peat  swamp  forest  area  around  the  flux tower of  Palangka Raya, Central Kalimantan.  The results  of  BFAST method were compared to  the  Normalized  Difference  Fraction  Index  (NDFI)  maps  and  the  maps  were  validated  by the  hotspot  of  the  Infrastructure  and  Operational  MODIS-Based  Near  Real-Time  Fire(INDOFIRE).  Overall,  the  number  and  time  of  changes  detected  in  the  three  pixels  differed with both time series data  because of the  data quality due to the cloud cover.  Nonetheless, we  found  that  EVI  is  more  sensitive  than  NDVI  for  detecting  abrupt  changes  such  as  the forest fires of August 2009-October 2009 that occurred in our study area and it was verified by  the  NDFI  and  the  hotspot  data.  Our  results  demonstrated  that  the  EVI  for  forest monitoring in the tropical peat swamp forest area which is covered by intense cloud cover is better  than  that  NDVI.  Nonetheless,  further  research  with  improving  spatial  resolution  of satellite images for application of NDFI is highly recommended. 
COMBINATION OF SPECKLE DIVERGENCE AND NEIGHBORHOOD ANALYSIS TO CLASSIFY SETTLEMENT FROM TERASAR-X DATA Komarudin, Rokhis; Indrajit, Agung
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 9, No 1 (2012)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

Show Abstract | Original Source | Check in Google Scholar | Full PDF (1407.647 KB) | DOI: 10.30536/j.ijreses.2012.v9.a1820

Abstract

Abstract.  The  objectives  of  this  research  were  to  develop  and  improve  methods  for determination  of  settlements  area  with  focus  on  synthetic  aperture  radar  (SAR)  data. Remote  sensing  settlement  classification  has  made  great  progress,  both  for  optical  and radar  data  as  well  for  their  fusion.  Yet,  in  radar  imagery,  settlement  classification  still contains  some  problems.  Several  studies  on  application  of  radar  imagery  have  been conducted  using  techniques  such  as  textural  analysis,  multi-temporal  analysis,  statistical model,  spatial  indexes,  and  object-based  classification.  Most  of  the  development  methods have several problems in the specific area especially in the tropical country. Several studies also  showed  that  settlement  classification  accuracies  were  just  below  60%.    This  was  not sufficient    enough  to  classify  settlement  areas  using  SAR  imagery.  Therefore,  in  this research, we proposed a new method i.e., the combination of the speckle divergence and the neighborhood  analysis.  The  proposed  method  was  applied  to  classify  settlement  area  in Cilacap  and  Padang  Districts  of  Indonesia.  The  results  showed  that  the  proposed  method produced a good accuracy i.e., 85.5% for Cilacap Districts and 78.1% for Padang Districts. 
ORTORECTIFICATION OF SPOT-4 DATA USING RATIONAL POLYNOMIAL COEFFICIENTS Candra, Danang Surya
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 9, No 1 (2012)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

Show Abstract | Original Source | Check in Google Scholar | Full PDF (794.009 KB) | DOI: 10.30536/j.ijreses.2012.v9.a1827

Abstract

Orthorectification  of  satellite  imagery  can  be  done  in  two  ways  i.e.,  rigorous sensor  model  and  the  approximation  model  of  the  satellite’s  orbit.  Dependence  on  physicalparameters,  to  make  rigorous  sensor  model  is  more  complicated  and  difficult  to  apply.  The approximation  model  can be either  Rational Polynomial Coefficients (RPC)  model  or  parallel projection  system.  RPC  is  a  mathematical  model  which  is  not  depends  on  the  sensor.  It  is used to improve the positioning accuracy when the parameter of the physical sensor model is  unknown.  This  study  assessed  orthorectification  of  SPOT-4  using  the  RPC  model  with  7 coefficients. Root Mean Square Error (RMSE) of GCPs obtained from the study  was less than 1  pixel.  RPC  did  not  depend  on  physical  and  satellite  orbit  parameters.  Thus  the  RPC  was simpler and easier to apply.
ESTIMATION OF RADIOMETRIC PERFORMANCE OF ELEKCTRO-OPTICAL IMAGING SENSOR OF LOW EARTH EQUATORIAL ORBIT LAPAN SATTELITE Maryanto, Ahmad; Indradjad, Andy; Sirin, Dinari Nikken; Widipaminto, Ayom
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 9, No 1 (2012)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

Show Abstract | Original Source | Check in Google Scholar | Full PDF (1187.537 KB) | DOI: 10.30536/j.ijreses.2012.v9.a1825

Abstract

Study  of  spectro-radiometric  performance  of  electro-optical  imager  which  is planned  to  be  launched  on  low  earth  equatorial  orbit  LAPAN  satellite  was  conducted through  simulative  calculation  of  image  irradiance  and  its  associated  generated  voltage  at the image detector output. Simulative calculation was applied to three scenarios of selected spectral  bands.  Those  spectral  bands  were  selected  spectra  (1),  which  consisted  of  spectral bands  B = (390-540 and 790-900) nm,  G = (470-610 and 700-900 )  nm, and R = (590-650 and 650-900) nm; selected spectra (2) consisted  of B1 = (390-540) nm,  G1 = (470-610) nm, and  R1  =  (590-650)  nm;  and  selected  spectra  (3)  consisted  of  B1(Green)  =  (525-605)  nm, B2(Red) = (630-690) nm, and B3(NIR) = (750-900) nm, on three scenarios of optical aperture or f-number (N)  2.8, 4.0, and  5.6.  Green grasses, dry  grasses, and conifers  were examples of the imaged target, chosen as representation of vegetations. Kodak KLI-8023 was used as the  optical  detector.  The  integration  time  was  assumed  3  miliseconds  which  correspond  to about 20 m ground sampling distance (GSD). Solar zenith angle were varying from 90 (early morning)  to  0  (solar  noon).  The  results  showed  that  option  (3)  of  selected  spectra,  as proposed  for  pushbroom  imager  of  LAPAN  satellite,  was  relatively  accepted  to  be implemented  and  complemented  with  f-number  4.0  of  optical  system  used.  Whereas simulation RGB color displayed  composed by R = B2(Red), G = B3(NIR), B = B1(Green) also showed a greenish color sense as expected for vegetation imaged target.
INDENTIFYING PATTERNS OF SATTELITE IMAGERY USING AN ARTIFICIAL NEURAL NETWORK Iskandar, Iskhaq; Affandi, Azhar; Setiabudidaya, Dedi; Irfan, Muhammad; Mardiansyah, Wijaya; Syamsuddin, Fadli
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 9, No 1 (2012)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

Show Abstract | Original Source | Check in Google Scholar | Full PDF (620.1 KB) | DOI: 10.30536/j.ijreses.2012.v9.a1824

Abstract

An artificial neural network analysis based on the self-organizing map (SOM)  was used  to  examine  patterns  of  satellite  imagery.  This  study  used  3  ×  4  SOM  array  to  extract patterns  of  satellite-observed  chlorophyll-a  (chl-a)  along  the  southern  coast  of  the  Lesser Sunda Islands from 1998 to 2006. The analyses indicated two characteristic spatial patterns, namely the northwest and the southeast monsoon patterns. The northwest monsoon pattern was characterized by a low  chl-a concentration. In contrast, the southeast monsoon pattern was  indicated  by  a  high  chl-a  distributed  along  the  southern  coast  of  the  Lesser  Sunda Islands.  Furthermore,  this  study  demonstrated  that  the  seasonal  variations  of  those  two patterns  were  related  to  the  variations  of  winds  and  sea  surface  temperature  (SST).  The winds  were  predominantly  southeasterly  (northwesterly)  during  southeast  (northwest) monsoon, drived  offshore (onshore) Ekman transport and  produced  upwelling (downwelling) along  the  southern  coasts  of  the  Lesser  Sunda  Islands.  Consequently,  upwelling  reduce dSST  and  helped  replenish  the  surface  water  nutrients,  thus  supporting  high  chl-a concentration. Finally, this study demonstrated that the SOM method was very useful for the identifications of patterns in various satellite imageries.
RED TIDE DETECTION USING Seawifs STANDARD CHOLOROPHYLL-a ALGORITHM IN SOUTHEAST KOREAN WATERS Winarso, Gathot
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 9, No 1 (2012)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

Show Abstract | Original Source | Check in Google Scholar | Full PDF (1164.491 KB) | DOI: 10.30536/j.ijreses.2012.v9.a1826

Abstract

Cochlodinium  polykrikoides  red  tides  have  occurred  in  summer  every  year  at coastal  waters  of  the  South  Korea.  Chlorophyll-a  concentration  data  estimated  from  ocean color satellite SeaWiFS (Sea-viewing Wide Field-of-view  Sensor)  were  used to detect the red tide in this study. The high value of chlorophyll-a concentration used  to detect red tide was analyzed  and   compared  with  red  tide  map  produced  by  National  Fisheries  Research  and Development Institute of Korea (NFRDI). Based on SeaWiFS data and NFRDI red tide map, it was  found  that  high  chlorophyll-a concentration  of  ≥  5  mg/m3in  SeaWiFS  images corresponded to the red-tide occurrence with some limitations. 

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