ИЗУЧЕНИЕ МОРФОЛОГИЧЕСКОЙ СТРУКТУРЫ МИКРОЛАНДШАФТОВ ВАСЮГАНСКОГО БОЛОТНОГО КОМПЛЕКСА НА ОСНОВЕ ДЕШИФРИРОВАНИЯ КОСМИЧЕСКИХ СНИМКОВ

• Main Author: Слабухина, Светлана
• Format: Text
• Language: unknown
• Published: Федеральное государственное бюджетное образовательное учреждение высшего профессионального образования "Национальный исследовательский Томский государственный университет" 2014
• Subjects: КОСМИЧЕСКИЕ СНИМКИ; МИКРОЛАНДШАФТ; ВЕРХОВОЕ БОЛОТО; МОРФОЛОГИЧЕСКАЯ СТРУКТУРА; СПЕКТРАЛЬНАЯ КЛАССИФИКАЦИЯ; Krapivnaya; taiga
• Online Access: http://cyberleninka.ru/article/n/izuchenie-morfologicheskoy-struktury-mikrolandshaftov-vasyuganskogo-bolotnogo-kompleksa-na-osnove-deshifrirovaniya-kosmicheskih; http://cyberleninka.ru/article_covers/15666048.png

Статья посвящена опыту картографирования ландшафтов участка Крапивинского нефтяного месторождения с использованием данных дистанционного зондирования (ДДЗ). Проведена спектральная классификация снимка RapidEye в специализированном программном обеспечении ENVI с помощью инструмента Decision Tree Classifier. Приведены алгоритмы обработки и значения яркостей спектральных каналов, используемые в автоматизированной классификации изображения. Выявлены наиболее значимые каналы КС RapidEye для идентификации различных поверхностей. The Great Vasyugan Mire is a unique natural formation. Located in the area of two natural zones (taiga and parvifoliate forest), it has a complicated landscape structure. Such factors as the large terrain, high bogginess are obstacles to a detailed integrated study. The only source of reliable and current information on the ecosystem condition is remote sounding data. Consequently, at present the method of automatic decoding of aerospace images has become relevant. The research is aimed at studying the landscape structure of the Vasyugan peat with the use of geoinformation technologies. The object of study is the south-eastern edge of the Vasyugan peat, the interfluve area between the Bolshoy Unkul and the Krapivnaya Rivers ( the left tributaries of the Yagiliakh River). The subject of research is the microlandscape morphological structure of the top peat on the territory of the key site. RapidEye and Landsat satellite images, on-site research data, digital base map at the 1: 25000 scale, Tomsk Region quaternary deposits map at the 1: 500000 scale were used. Visual decoding of RapidEye and Landsat satellite images based on on-site research data was made. The satellite images data were chosen basically on account of the near infrared region. During visual decoding in ArcGIS software by Landsat-7 ETM+ satellite images around the study peat, four types of geobiocoenosis were found: 1) lakelet-ridge-pattern; 2) pinaceous-scrubby-sphagnum; 3) sphagnum-scrubby-pinaceous; 4) eriophorum-sphagnum. The vegetation cover was further studied by RapidEye satellite images in ENVI software. The values of the Normalised Difference Vegetation Index (NDVI) were calculated for each every geobiocoenosis using the tools of the given program. The map of NDVI values, the types of geobiocoenosis were used to create the spectral classification of satellite images together with green, red and near infrared regions. In order to divide images into pixel classes the ENVI Decision Tree Classifier tool was used. It was noted that the usage of the Decision Tree Classifier tool to produce classified satellite images made it possible to define precisely the boundaries of microlandscapes of the peat as compared to visual decoding. The analysis of plant association spectral albedo by RapidEye satellite images allowed identifying the most preferable channels as well as spectral channel intensity values for identification of different types of geobiocoenosis. Therefore, the analysis of resulting classified satellite images made it possible to identify the morphological structure of microlandscapes of the peat under study.