scholarly journals Classification of the NOAA Satellite Image Data by Unsupervised Neural Network

1993 ◽  
Vol 29 (3) ◽  
pp. 281-287 ◽  
Author(s):  
Goutam CHAKRABORTY ◽  
Jun-ichi KUDOH ◽  
Norio SHIRATORI ◽  
Shoichi NOGUCHI
Keyword(s):  
Neural Network ◽  
Satellite Image ◽  
Image Data ◽  
Noaa Satellite ◽  
Unsupervised Neural Network ◽  
Satellite Image Data

scholarly journals Level II Vegetation Classification of Satellite Image Data using PCA Method

IJARCCE ◽  
2017 ◽  
Vol 6 (4) ◽  
pp. 297-301
Author(s):  
Mayur Kolhe ◽  
Yogesh Kadam ◽  
Ninad Chousalkar ◽  
Sunny Chordiya
Keyword(s):  
Satellite Image ◽  
Image Data ◽  
Vegetation Classification ◽  
Level Ii ◽  
Pca Method ◽  
Satellite Image Data

scholarly journals Verification of multispectral data processing for the Sentinel-2A bands, field ASD FieldSpec® 3FR and UAV with the DJI STS-VIS

2019 ◽  
pp. 29-39 ◽  
Author(s):  
Stanislav Dugin ◽  
Oksana Sybirtseva ◽  
Stanislav Golubov ◽  
Yelizaveta Dorofey
Keyword(s):  
Pearson Correlation ◽  
Plant Cover ◽  
Satellite Image ◽  
Vegetation Indices ◽  
Image Data ◽  
Multispectral Data ◽  
Maximum Value ◽  
Substantial Correlation ◽  
Satellite Image Data ◽  
Sentinel 2A

The study of plant cover have been performed by the hyperspectral remote sensing method using ASD FieldSpec® 3FR and DJI STS-VIS measurements. The orthophotoplans are compiled for the test plots of interest at the spatial resolution of 2.5 cm. The substantial correlation for the results of terrestrial verification for the satellite image data in the range of Sentinel-2A bands are confirmed. 15 vegetation indices for the Sentinel-2А wavelength bands were drawn at the Pearson correlation coefficient r > 0.97, with a maximum value of the correlation error of 0.07.

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