Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2009. Issue.6. Vol.1. P. 206-215
Information content enhancement for multispectral and
hyperspectral airspace remote sensing data while solving applied
problems of quantative assessment of natural and anthropogenic
objects condition
Т.В. Кондранин1, В.В. Козодеров2, О.Ю. Казанцев3, В.И. Бобылев3, В.В. Борзяк2, Е.В. Дмитриев4, В.Д. Егоров4, В.П. Каменцев5, А.Ю. Беляков5, С.Б. Логинов5
1 Московский физико-технический институт (государственный университет)
2 Московский государственный университет им. М.В.Ломоносова
3 НПО «Лептон»
Московский физико-технический институт (государственный университет)
4 Институт вычислительной математики РАН
5 Технопарк Тверского государственного университета
Examples are shown of data processing from an air-borne hyperspectrometer (produced by the MIPT
basic enterprise called as the SPO Lepton) of visual and near infrared bands testing for two selected
sites in Tver region as a development of the previous results of multispectral space imagery processing
with medium and high spatial resolution. The hyperspectral remotely sensed data were synchronized
with air-survey camera data for the selected region while using aviation vehicles (a glider and a light
aircraft). The hyperspectral imagery processing results are presented in terms of the observed objects
classification and the condition parameters assessment of the soil-vegetation cover for each pixel of the
relevant images. Characteristic features are revealed of color coding of the obtained information products
of the hyperspectral imagery processing. Examples are demonstrated of the discrimination procedure to
select objects with specific spectral properties on the processed hyperspectral images.
Keywords: multispectral space imagery processing, remote sensing hyperspectral systems, natural objects pattern recognition, soil-vegetation cover condition parameters assessment
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