TY - GEN
T1 - Analysis of modified starfm as suitable fusion method for remote sensing satellite data between pleiades-1b and landsat-8
AU - Widipaminto, Ayom
AU - Hestrio, Yohanes Fridolin
AU - Monica, Donna
AU - Safitri, Yuvita Dian
AU - Chandra, Danang Surya
AU - Rokhmatuloh,
AU - Triyono, Djoko
AU - Adiningsih, Erna Sri
N1 - Publisher Copyright:
© 2020 ACRS 2020 - 41st Asian Conference on Remote Sensing. All rights reserved.
PY - 2020
Y1 - 2020
N2 - Data fusion is used in remote sensing to increase the spatial and spectral resolution of an image. A common fusion method is to combine multispectral images with the panchromatic band from the same satellite with a higher spatial resolution, to create high-resolution multispectral imagery. Research has been undertaken to analyze and develop a suitable fusion method that can combine medium resolution satellite imagery having a sufficiently varied spectral range with high-resolution imagery having a sufficiently high spatial resolution. The basic fusion methods used in this study include Wavelet-PCA and High Pass Filtering which are usually used to combine multispectral images with panchromatic bands from the same satellite and use a spatial and temporal adaptive reflectance fusion model (STARFM) which is generally only for combines Landsat-8 data with MODIS. Combining data from different satellites allows us to increase not only the spatial and spectral resolution but also the temporal resolution which is important for many remote sensing applications such as soil monitoring and phenology. The dataset we used in the experiment was imaging from Pleaides-1B and Landsat-8. To measure the performance of the proposed method, we conducted an evaluation using several measurements such as peak signal-to-noise ratio (PSNR), universal quality image index (UQI), spectral angle mapper (SAM), visual information fidelity (VIF), and block sensitive PSNR (PSNRB). From this study, data on Fusion Pleiades-1B and Landsat-8 with a spatial resolution of 0.5m, which equivalent to the resolution of Pleiades-1B, with the visible spectral range VIS, NIR, and SWIR.
AB - Data fusion is used in remote sensing to increase the spatial and spectral resolution of an image. A common fusion method is to combine multispectral images with the panchromatic band from the same satellite with a higher spatial resolution, to create high-resolution multispectral imagery. Research has been undertaken to analyze and develop a suitable fusion method that can combine medium resolution satellite imagery having a sufficiently varied spectral range with high-resolution imagery having a sufficiently high spatial resolution. The basic fusion methods used in this study include Wavelet-PCA and High Pass Filtering which are usually used to combine multispectral images with panchromatic bands from the same satellite and use a spatial and temporal adaptive reflectance fusion model (STARFM) which is generally only for combines Landsat-8 data with MODIS. Combining data from different satellites allows us to increase not only the spatial and spectral resolution but also the temporal resolution which is important for many remote sensing applications such as soil monitoring and phenology. The dataset we used in the experiment was imaging from Pleaides-1B and Landsat-8. To measure the performance of the proposed method, we conducted an evaluation using several measurements such as peak signal-to-noise ratio (PSNR), universal quality image index (UQI), spectral angle mapper (SAM), visual information fidelity (VIF), and block sensitive PSNR (PSNRB). From this study, data on Fusion Pleiades-1B and Landsat-8 with a spatial resolution of 0.5m, which equivalent to the resolution of Pleiades-1B, with the visible spectral range VIS, NIR, and SWIR.
KW - Data fusion
KW - Remote sensing
KW - STARFM
UR - http://www.scopus.com/inward/record.url?scp=85107174067&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85107174067
T3 - ACRS 2020 - 41st Asian Conference on Remote Sensing
BT - ACRS 2020 - 41st Asian Conference on Remote Sensing
PB - Asian Association on Remote Sensing
T2 - 41st Asian Conference on Remote Sensing, ACRS 2020
Y2 - 9 November 2020 through 11 November 2020
ER -