• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.310-315
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• 1999

We extracted narrow open water streams from JERS-1 SAR images of the Amazon rain forest. The extracted range of these streams were almost comparable to a high level extraction of the same streams from near-IR images of JERS-1 VNIR data notwithstanding that these features in SAR images show the strong dependence of the observation angle. Large water bodies are relatively easy to extract from JERS-1 SAR images, as they tend to appear as very dark areas; but streams whose width is nearly equal to or less than the spatial resolution no longer appear as very dark features. By using strong scatterers distributed sparsely along the radar facing sides of the streams, we can successfully estimate approximate ranges of waterways and then extract relatively dark line-like features within these ranges.

• Korean Journal of Remote Sensing
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• v.14 no.1
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• pp.95-101
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• 1998

This paper describes an algorithm which was developed for removing along-track and across-track striping effect shown in JERS-1 OPS/VNIR images. A statistical algorithm was implemented based on the mean brightness value of each along-track and across-track line. Different from any filtering techniques in either spatial or frequency domain, the developed algorithm does not change the radiometric characteristics of image pixels. The algorithm will be inserted to the JERS-1 OPS image data processing chain in the Satellite Technology Research Center direct receiving station.

• Korean Journal of Remote Sensing
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• v.10 no.2
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• pp.161-170
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• 1994

The JERS-1 is an Earth Resources Satellite launched by NASDA (Natinal Space Development Agency) of Japan, in February in 1992 and has two sensors; SAR(L-Band Synthetic Aperture Radar) and OPS (SWIR and VNIR radiometers). In this research note, the basic properties and data characteristics of the SAR data are summarized based on the observations made on the data sets received for the Nahanni Canadian test site, Northwest Territories. The JERS-1 SAR data quality. including the spatial resolution of the data, is, in general, excellent for most geological applications.