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Alves, M.

Publications and source records attributed to Alves, M..

Data Quality of the JERS-1 SAR Global Rain Forest Mapping (GRFM) Project

The National Space Development Agency of Japan's (NASDA) JERS-1 SAR began collecting data in 1995 for the Global Rain Forest Mapping Project (GRFM). The GRFM data quality has been examined for products resulting from both the NASDA and Alaska SAR facility's (ASF) processing facilities.

JERS-1 SAR Rain Forest Mapping

The JERS-1 Amazon Multi-Season Mapping Study (JAMMS)

Regional mapping of the Amazon basin using imaging radar is described. Two 60-day periods of radar mapping will be conducted, one in 1995, and one in 1996. One period will view the low-water season, and the other will view during the high-flood season. The main objective of the JAMMS project is to generate a regional map showing inundation throughout the Amazon Basin by comparing the two data sets.

Amazon Radar Mapping Earth Satellite JAMMS flood p

Amazon Rain Forest Classification Using J-ERS-1 SAR Data

The Amazon rain forest is a region of the earth that is undergoing rapid change. Man-made disturbance, such as clear cutting for agriculture or mining, is altering the rain forest ecosystem. For many parts of the rain forest, seasonal changes from the wet to the dry season are also significant. Changes in the seasonal cycle of flooding and draining can cause significant alterations in the forest ecosystem.Because much of the Amazon basin is regularly covered by thick clouds, optical and infrared coverage from the LANDSAT and SPOT satellites is sporadic. Imaging radar offers a much better potential for regular monitoring of changes in this region. In particular, the J-ERS-1 satellite carries an L-band HH SAR system, which via an on-board tape recorder, can collect data from almost anywhere on the globe at any time of year.In this paper, we show how J-ERS-1 radar images can be used to accurately classify different forest types (i.e., forest, hill forest, flooded forest), disturbed areas such as clear cuts and urban areas, and river courses in the Amazon basin. J-ERS-1 data has also shown significant differences between the dry and wet season, indicating a strong potential for monitoring seasonal change. The algorithm used to classify J-ERS-1 data is a standard maximum-likelihood classifier, using the radar image local mean and standard deviation of texture as input. Rivers and clear cuts are detected using edge detection and region-growing algorithms. Since this classifier is intended to operate successfully on data taken over the entire Amazon, several options are available to enable the user to modify the algorithm to suit a particular image.

J-ERS-1

Calibration Results for J-ERS-1 SAR Data Produced by the Alaska SAR Facility

The Alaska SAR Facility has been receiving and processing SAR data from the J-ERS-1 satellite since Spring 1992. Corner reflectors have been set up for J-ERS-1 SAR calibration at a site near Delta Junction, in central Alaska. Image quality and calibration analysis results from the Delta Junction site and others will be presented in this paper. The impact of the 3-bit Analog-to-Digital Converter and the automatic stepping of the gain as a function of range in the J-ERS-1 radar receiver on calibration performance has been assessed. Preliminary observations on J-ERS-1 SAR data are that the average Signal-to-Noise ratio is generally fairly low, in the range 5-6dB. Azimuth ambiguity levels are higher than preflight analysis indicated. Over land, the dynamic range in the backscatter at L-band for approximately 36 degree incidence angle is often fairly high.

Freeman, A.

Calibration Results for J-ERS-1 SAR Data Produced by the Alaska SAR Facility

The Alaska SAR Facility has been receiving and processing SAR data from the J-ERS-1 satellite since Spring 1992. Corner reflectors have been set up for J-ERS-1 SAR calibration at a site near Delta Junction, in central Alaska. Image quality and calibration analysis results from the Delta Junction site and others will be presented in this paper. The impact of the 3-bit Analog-to-Digital Converter and the automatic stepping of the gain as a function of range in the J-ERS-1 radar receiver on calibration performance has been assessed. Preliminary observations on J-ERS-1 SAR data are that the average Signal-to-Noise ratio is generally fairly low, in the range 5-6 dB. Azimuth ambiguity levels are higher than preflight analysis indicated. Over land, the dynamic range in the backscatter at L-band for approximately 36 degree incidence angle is often fairly high...

Freeman, A.

Overall evaluation of Skylab imagery for mapping of Latin America

The author has identified the following significant results. Skylab imagery is both desired and needed by the Latin American catographic agencies. The imagery is cost beneficial for the production of new mapping and maintenance of existing maps at national topographic series scales. If this information was available on a near time routine coverage basis, it would provide an excellent additional data base to the Latin American cartographic community, specifically Argentina, Bolivia, Chile, Colombia, Dominican Republic, Guatemala, Paraguay, and Venezuela.

Staples, J. E.