Fachbereich Geoinformatik

Дипломная работа. В результате работы над дипломным проектом были созданы геоэкологические карты на акватории Баренцева и Печорского морей: Баренцево море: 1.Геоэкологическое районирование Баренцева моря; 2.Содержание Cs-137 в донных осадках Баренцева моря; 3.Распределение нефтеуглеводородов в донных осадках Баренцева моря; 4.Содержание пестицидов и тяжелых металлов в донных осадках Баренцева моря; 5.Содержание ПХБ в донных осадках Баренцева моря. Печорское море:1.Геоэкологическое районирование Печорского моря; 2.Распределение очагов нефтеобразования в донных отложениях Печорского моря; 3.Содержание Cs-137 в донных осадках Печорского моря; 4.Распределение суммарных биомасс диатомей в прибрежной части Печорского моря. При составлении данных карт были изучены общие географические условия акваторий, распространение и особенности отдельных элементов геосистем и процессы переноса вещества между элементами окружающей среды, а также проанализирована их значимость, степень их воздействия на общее экологическое состояние окружающей среды. При этом было акцентировано внимание не только на констатации самого факта загрязнения окружающей среды, но и изучены причины поступления загрязняющих веществ в Баренцево и Печорское моря из различных источников, возможные пути переноса и осаждения тяжелых металлов, пестицидов, нефтяных углеводородов и радионуклидов и других контаминантов по направлению с суши в реки, эстуарии, дельты и на континентальный шельф; в результате было проанализировано итоговое состояние экологической ситуации региона. На итоговых геоэкологических картах были определены зоны сосредоточения загрязняющих веществ (т.е. зоны схождения путей переноса контаминантов) и осаждения загрязняющих веществ в донные отложения. В результате, в рамках дипломной работы были составлены как аналитические и комплексные карты, отражающие взаимосвязи компонентов геосистем, так и карты геоэкологического районирования, которые являюся синтетическими по типологической классификации. Геоэкологические карты были созданы на завершающем этапе работы, являсь итоговой оценкой настоящей, сложившейся на данный этап ситуации изучаемых акваторий.

Methods of GIS mapping of environmental of the Barents and Pechora Seas under the influence of both natural and anthropogenic factors have been devised. For integrated GIS project of the Russian Artic Seas several thematic layers have been created. These layers characterize the natural conditions of the Seas, the information on income of pollutants from different sources, possible ways of their transfer and deposition in bottom sediments. The analysis of the maps of geoecological situation of the Barents and Pechora Seas allows picking out the next geoecological regions: relatively safe, potentially dangerous and of high ecological stress.

Methods of GIS mapping of environmental of the Barents and Pechora Seas under the influence of both natural and anthropogenic factors have been devised. For integrated GIS project of the Russian Artic Seas several thematic layers have been created. These layers characterize the natural conditions of the Seas, the information on income of pollutants from different sources, possible ways of their transfer and deposition in bottom sediments. The analysis of the maps of geoecological situation of the Barents and Pechora Seas allows picking out the next geoecological regions: relatively safe, potentially dangerous and of high ecological stress. PREFACE Methods of GIS mapping of sea territories for the means of estimating their ecological condition formed under the influence of both natural and anthropogenic factors are being developed. Scientists believe that this situation is due to several reasons: lack of firm evaluation criteria of sea pollution, imperfection of modern technologies and methods of ecological monitoring of the sea water areas. The analysis of the information on sea ecology that has been gathered up to now shows dissimilar data coverage of littoral and open water areas. Most of the information is provided for shelf areas of the water objects. Also there is a great diversity in the observation time and space. Retrieving methods of ecological information provide a diverse character of observations. As a result there is a sure lack of primary data and reliable information that is necessary for forming data banks and bases. Among the Arctic seas, Barents and Pechora Seas can be set apart due to the factual material accumulated by environmental departments and scientific groups. The Barents Sea is one of the world's largest fishing water areas and its share in the amount and diversity of bio resources remains the largest among European seas of Russia. But the potential danger for biota is the development of oil and gas deposits in the region. About 172 promising oil and gas structures have been revealed in the seas of the Western Arctic (Barents, Pechora and Kara Seas) and about 30 of them are prepared for deep research drilling. Joint operation of fishing areas, oil and gas retrieving complexes provide new goals for ecological monitoring of the sea water areas. Due to that fact a certain role of GIS mapping in helping to evaluate the ecological condition of the sea areas can be obtained. SOURCES OF DATA AND METHODS For the means of producing a series of analytical and complex maps of Barents and Pechora seas with the use of GIS technologies we have analyzed and worked with different data concerning natural and anthropogenic factors that determine ecological condition of the seas. Also we've developed a method of forming data base that includes maps of different scales, topics and numerous statistics [1, 3]. During the production of analytical and complex maps of seas it is important to refer to the geoecological approach that attributes to sea as a complete hydrodynamic system, inseparably connected with the adjoining territory of the e catchment Thematic maps of the Atlas of the Oceans can show the natural specifics of Barents and Pechora Seas – interaction of hydrodynamic, hydrometeorological, hydrochemical and hydrobiological processes.

Gohl K., Uenzelmann-Neben G., Eagles G., Fahl A., Feigl T., Grobys J., Just J., Leinweber V., Lensch N., Mayr C., Parsiegla N., Rackebrandt N., Schluter P., Suckro S., Zimmermann K., Gauger S., Bohlmann H., Netzeband G., Lemenkova P. 2006. Deep crustal refraction and reflection seismics; Crustal & sedimentary structure & geodynamic evolution of the West Antarctic continental margin & Pine Island Bay. In: Berichte zur Polar- und Meeresforschung // Reports on Polar and Marine Research, 557: 117, p.20-30. ISSN: 1618-3193. Expeditionsprogram No75 of ANT-XXIII/4 Cruise. AWI fu ̈r Polar- und Meeresforschung, Bremerhaven, 11-12.

The reconstruction of the paleoclimatic and paleoceanographic development of the late Quaternary south polar ocean and adjacent continental areas in high temporal and spatial resolution is the main goal of our long-term study. During this expedition the sedimentary budget of biogenic and terrigenous components and their variability will be investigated. One objective of this leg is to continue the studies of former expeditions to gather more detailed paleoceanographic information on the eastern Pacific sector of the Southern Ocean for reconstruction of the distribution of water masses, frontal systems and sea ice, as well as information on high export productivity areas and their impact on global climate evolution. Thus, it will help us to broaden our understanding of the impact of environmental processes in the Southern Ocean on global climate. The second objective is to investigate the response of the West Antarctic Ice Sheet (WAIS) to Quaternary climatic changes. This ice sheet represents the most instable portion of Antarctic ice. The distribution pattern of the WAIS and its development can be deciphered from the sediment deposition in the study area. Previous investigations indicated that the WAIS collapsed once or multiple times during the past 0.75 million years. However there are also controversial findings. Since marine-geological records of glaciomarine deposition proximal to the WAIS are sparse, the exact timing and boundary conditions for such an event, which would result in a rise of the sea level of 5-6 m, are not yet known. The reconstruction of environmental conditions based on a multiproxy approach (this includes the investigations of sediment composition, microfossil assemblages and isotopic measurement of biogenic components) and its stratigraphic dating should substantially add to the knowledge of the WAIS history and its stability during a possibly warmer climate in the future.

The paper focuses on analysis of Central Asian hydro-energetic system and water usage in Tian Shan region. Tian Shan system is important water resource in Central Asia: mountains river waters are intensely taken for hydropower energy, urban systems, irrigation. But geopolitics in Tian Shan is difficult: it crosses five densely populated countries. Current problem consists in water delivery between territories located in the highlands with excellent water supply and those located in valleys with water shortage. Tajikistan and Kyrgyzstan control river basins, and Kazakhstan and Uzbekistan depend on water supply. The problem of water use causes debates among these countries. Besides, climate warming affects glaciers and causes water deficit. Altogether, this leads to difficulties in hydro-energetics. A multidisciplinary analysis was performed in research: geopolitical problems of water supply in Tian Shan, spatial distribution of hydro-energetic resources and climate impact on hydro-energetics. СНАБДЕВАЊЕ ВОДОМ И УПОТРЕБА У СРЕДЊОЈ АЗИЈИ, ТИАН ШАН БАСЕН Резиме: Рад се заснива на анализи Централно-азијског енергетског система и искоришћења воде у региону Tian Shan. Tian Shan је важан извор воде у Централној Азији: воде планинских река се интензивно користе за добијање хидроенергије, урбане системе и наводњавање и тако даље. Али, геополитика у Tian Shan је сложена: ту се сусреће пет густо насељених држава. Тренутни проблем је у достави воде између територија које се налазе у планинским крајевима са одличном снабдевеношћу водом и оних које се налазе у долинама са мањком воде. Tajikistan и Kyrgyzstan контролишу речне басене, док Kazakhstan и Uzbekistan зависе од водоснабдевања. Проблем снабдевања водом узрокује дебате између ових држава. Поред тога, глобално загревање утиче на глечере и узрокује дефицит воде. Све у свему, ово доводи до потешкоћа и водоснабдевању и њеном коришћењу. Мултидисциплинарним анализама су истражени: геополитички проблеми водоснабдевања у Tian Shan, просторна дистрибуција хидро-енергетских извора и климатски утицај на хидро-енергију. Кључне речи: хидроенергија, Тиан Шан, геополитика, вода коришћења

The study area is located in Central Europe and focusing on Mecsek Hills, a low mountain range in the south western part of Hungary. The region of central Europe includes complex mis of elements from mediterranean and continental climate, since the area is located in transitional zone of sub-atlantic and sub-mediterranean climate types. Mecsek Hills is a unique region of the Hungarian environment. Its central European location specifies distribution of diverse landscape types, formed under conditions of transitional climatic settings, mixed from sub-atlantic to sub-mediterranean. The distribution of ecosystems in the region illustrate adaptation of soil properties to actual climate conditions. As determined by the present-day climatic and geomorphological settings, soils in the Mecsek region are rich in nutrients, and landscapes are characterized by various mixed soil types. Brown forest soils predominate on hilltops of Mecsek, while alluvial soils on floodplains [1]. According to the underlying soil types, the landscapes are characterized by mixed vegetation types. The most typical is Pannonian mixed forests of temperate broadleaf and mixed forests, common in Euro-Siberian region. There are also forests of Turkey and hornbeam oak in the catchment area of Mecsek region. The dominating vegetation coverage types on the slopes of Mecsek Hills include beech forests, ravine forests and oaks. Some regions of the Mecsek Hills include unique biogeographic areas with endemic species, not founded elsewhere in Carpathian Basin. The overall climate change, especially the global temperature increase, controls balance of heat and water budget on the Hungarian landscapes, and has considerable impact on the agricultural landscapes. In the past decades there were changes in climate, detected in the Carpathian Basin region, which illustrate general fluctuations in the climatic settings in Hungary and change of overall average air temperatures [2]. Recently, considerable increase in the occurrence of hazards is detected in Carpathian Basin: rainfalls, drought and heat periods in summer. Climate change makes impact on local soil properties, which affects ecosystem structure. Various ecological factors have impact on ecosystems with different impact factor, according to vulnerability and sensitivity: the main impact have temperatures and precipitation, affecting soil water regime, evaporation and water runoff. The overall impact of various factors make a joint effect on ecosystems structure. Recent climate changes mostly influence regional hydrological regime, e.g. increased temperature warming, regime and intensity of precipitation [3, 4]. Hydrology strongly affect soil properties (texture, moisture), nutrient regime (organic matter content) and fertility. The main environmental problems nowadays in Hungary are aridification and desertification. It is reflected in increased annual temperatures and decreased precipitation [5]. A new hydrological and meteorological balance triggers evolution of landscapes and cause landscape dynamics [6]. Reduced availability of water affects ecosystems. Vegetation coverage is the most vulnerable and least resisting elements of landscapes, with the most rapid response to external changes, like water shortage. Hence, since 1961, the net primary production dropped from 67% to 49% [7]. Recently in the Carpathian Basin there is considerable increase in extreme hazardous events: droughts, water shortage and floods. Driving factor is changes in precipitation distribution in the past decades. The local flood hazard risk can be assessed as moderate to high [8]. Thus, lowlands are potentially exposed to floods, since the majority of river discharge is collected by the runoff from the hills [9], which is intensified by the hazards, and lead to floods. Cumulative effects of environmental, climate and anthropogenic factors (intensive agricultural activities) affect Hungarian landscapes. Combination of the satellite images with GIS techniques is a key method for land patterns identification and classification of ecosystems. Research methodology is based on the GIS spatial analysis tools and classification of Landsat TM image, which was used for visualizing landscapes. An ILWIS GIS was applied to perform spatial analysis and mapping. The research algorithm is clustering, which classifies pixels with similar value of Digital Numbers (DNs) to thematic classes. As a result, spatial analysis on distribution of land cover patterns was performed. Data processing include image pre-processing, enhancement, classification, spatial analysis and interpretation. A land cover map was created by classifying study area into land categories. The core method used in the current work for the interpretation of imagery is clustering algorithm. This method is based on the remote sensing general principle that each unique pixel on a multichannel image has spectral signature defined by the reflectance of its DN in each spectral band. The DNs of pixels create unique signatures for various objects, distinguishable from other objects. Multispectral cluster classification was applied for the Landsat TM image, by extracting information about values of the pixels DNs, analyzing their spectral signatures. During classification, digital cells are measured according to the similarity of their * Издается в авторской редакции.

The emphasis of this research is application of spatial analysis using clustering algorithm, and remote sensing data (Landsat TM imagery) for agricultural mapping of land cover types. The study area covers Mecsek Hills region, located in southwestern Hungary. This region is characterized by high land heterogeneity and complex landscape structure, caused by intense agricultural land use in the region with mixed vegetation type and high environmental value. The research data consists in Landsat TM scenes taken for years for years 1992, 1999 and 2006. The methodology is based on cluster classification algorithm available in ILWIS GIS. Based on clustering technique, the agricultural land cover classes were identified by association of pixels on the Landsat TM scenes to thematic clusters. Different land use types were classified, which include natural vegetation coverage, anthropogenic areas and agricultural fields, subdivided to various crop types. Once classification was complete, agricultural thematic maps have been created. The final research output consists in three independent agricultural thematic maps of land cover types for years 1992, 1999 and 2006. 2. Introduction Combination of the satellite images with GIS techniques is a key method for land patterns identification and classification of agricultural land cover types on the land surface. In this paper an ILWIS GIS approach to perform remote sensing based land cover analysis and mapping is presented. The purpose of the current work is application of the ILWIS GIS method of clustering, which assigns pixels with similar value of Digital Numbers (DNs) to clusters, or thematic classes. The main objective is to perform spatial analysis on distribution of land cover patterns in study area. The research data consist in Landsat TM scenes visualizing agricultural areas in Mecsek Hills region in 1992, 1999 and 2006 years. The choice of the Landsat TM data is explained by their well-known advantages of application in land cover mapping and agricultural cartography, free availability, and suitability for spatial analysis according to temporal and spatial parameters (30m mesh size). 3. Methods The research methodology is based on the spatial analysis tools of the open source ILWIS GIS software aimed at classification of Landsat TM scenes. Current work is organized in several research steps summarized in the research workflow (Fig.1). Methods of data processing include import and pre-processing of the images, enhancement, classification, spatial analysis and interpretation. The research aim is creation of land cover maps, performed by classifying research area into a set of land cover categories, and assigning a land use type label to each of these units. Figure 1 Research flow algorithm. The core method used in the current work for the interpretation of imagery is clustering algorithm, which is based on a ground principle of distinguishability of the spectral signatures of the pixels on the raster image. The clustering was chosen, because it is objective technique, enabling to avoid subjectivity and misclassified pixels, and to ignore external factors while classifying, e.g. atmospheric conditions, solar illumination, etc. This method is based on the remote sensing general principle that

This research focuses on landscapes studies with selected research area located in central Slovakia, Sitno area. The research purpose is to perform spatial analysis of the landscapes and patches within the landscapes, in order to assess, which parts of the selected study area have the highest environmental quality and value, for further environmental monitoring and management. This paper presents quantitative ecological assessment of the landscapes within the natural protected area located in Slovakia, central Europe. It contributes to the sustainable development and environmental management of the environmentally protected zones.
The Patch density (PD) shows distribution and concentration of patches in the landscape, with values 11,22 patches per 1000 ha. It is very small value, which indicates large and compact patches. The study area is not fragmented too much, though, notably, as shown in Table 2: A) Number of categories and subcategories, B) Number of patches, C) Patch density and D) Class area (CA) and TA. The Mean patch size (MPS) was determined from the Number of patches and their area.The study area of Sitno Natura 2000 Sites is located in Slovakia, central Europe.
This area belongs to the pan-European Natura 2000 network of ecologically protected areas. Natura 2000 sites are defined as pan- European reserved nature zones, which meet the requirements of high environmental criteria and belong to natural heritage of Europe. These landscapes are under strict environmental protection due to their high ecological value, unique species, rich biodiversity and other characteristics. Selected under Natura 2000 programme, habitats and endangered species of high ecological value and significance are considered as primary targets of nature conservation. Sitno Natura 2000 Sites include unique landscapes with rare and endangered species. Therefore, they have high environmental and natural value, as important part of the Slovakian and European natural heritage. At the same time, there are detected anthropogenic impacts on Sitno Natura 2000 Sites, caused by the uncontrolled tourism and other factors.

Research work analyzes current situation and development of tourism in the region of Baltic Sea. Specific case study of this paper is Pärnu Bay, Estonia. This region is known for unique environmental settings: mild maritime climate, broad beaches, coniferous pine forests on the coastal zone and high esthetic value of the surrounding landscapes. However, after the end of USSR, Estonia survived a difficult period of restructuring of economic and social system. This affected touristic cluster, rapidly developing in new directions. Soviet touristic areas became abandoned and reconstructed , new hotels are being actively created, intensive privatization of recreation houses is actively ongoing. Main problem in the touristic cluster in Estonia consists in its specific location on the Baltic Sea with cold climate in summer period. It causes low popularity among tourists, comparing to Mediterranean. Another problem consists in ongoing development of the country, reflected in low investments into tourism, comparing to other European countries. Therefore, the main perspective for the tourism development in Estonia includes active redirection towards eco-style sustainable tourism: camping, biking, sea side recreation, construction of summer cottages for vacations, organized tours to Natural Parks. This paper, supported by fieldwork, has analytical character reviewing current Estonian tourism dynamics. Sociopolitical effects on current tourism directions are discussed, while modern touristic system in Estonia compared to Soviet. The overview of the recreation resort places was performed in Häädemeeste municipality, Pärnu district, and resulted in series of thematic author photos. The research was performed at the University of Tartu.

The Izmir region in Turkey is extremely valuable for the environment while being used immensely for tourism, agriculture and recreation. The geographic area of western Turkey is known for its unique physical and environmental settings. Due to its location in the Mediterranean climate, the region has certain typical features and is influenced by the local and regional climatic setting. The geography of the region combines diverse landforms, various geomorphological features, natural landscapes, species and vegetation richness: mountainous and hilly landscapes, caves, islands in the coastal area and lakes. The geology of the area of Western Anatolia is characterized by the neotectonic active faulting and high seismicity, which leads to the geomorphic instabilities and landslide formation in the research area. The vegetation in the study area is dominated by typical Mediterranean flora. Fig: Study area within Turkey (Map modified by authors from Britannica Encyclopedia) The current environmental situation within the terrestrial parts of the ecosystems has been well discussed in several works. The main issues concerning deforestation of precious forest communities are desertification, soils erosion and land degradation in the surroundings. For example, plant cover and land degradation on Karuburun Peninsula has been studied and detected by Nurlu et al. (2003) in their remote sensing based research. Karaburun Peninsula is an important part of Aegean Sea ecosystems and is well known in Turkey as one of the major undisturbed sites in western Turkey with precious biodiversity structure, aesthetic landscapes and unique environment. To maintain sustainable development of the Turkish nature, the unique landscapes should be protected for the sustainable coexistence of man and nature. Other sources of environmental threats are radioactive wastes and radionuclides that originate both from natural sources, for instance leaching from minerals, and from pollutant sources, mostly from nuclear power plants, explosions and accidents. These factors of ecological contamination have direct impact on the terrestrial ecosystems.

Presented work illustrates application of the GIS based processing of various geographic data: satellite images and CORINE (Coordination of Information on the Environment) layers at the lessons of geography in the high schools and universities. The research illustrates GIS application for understanding, visualizing and modeling landscapes of the Earth. Practically, the work aims to demonstrate students, how mapping land cover types can be done using GIS and combination of vector and raster geospatial data. Practical example of this work is application of IDRISI GIS and geospatial data towards a study region, located on the coasts of the Baltic Sea: Pärnu region. The GIS project was performed using Landsat TM satellite image and thematic CORINE layers showing land cover and vegetation types. The CORINE project was started in 1985 in the European Union (EU). This is a cartographic database common and standardized for the EU. The project consists of 44 land cover types in classes, presented as a series of maps at a scale of 1:100 000. This database is available for the most areas of Europe (EU) including Estonia. There are numerous examples of Figure 1-Study area: western Estonia, Pärnu region.

The goal of the study is to perform comparative analysis of image processing methods, enabled by means of IDRISI GIS software. The purpose has two aims. First, a spatial analysis of land cover types in the coastal landscapes of western Estonia, Pärnu area, at two various temporal dates. Second, an overview of the technical methods of IDRISI GIS enabling to evaluate image processing. The main research method consists in classification of satellite images for resulting geoecological mapping of landscapes. The ISOCLUST classification enabled to create multi-spatiotemporal thematic maps of Pärnu area. The research method is based on the spatiotemporal analysis of the geospatial data, performed by means of GIS tools and remote sensing data.

This paper focuses on monitoring of landscapes downgrading in specific conditions of Arctic ecosystems with cold climate conditions (marshes, permafrost, high humidity and moisture). The paper has a special focus on spatiotemporal assessment of land cover types changes in using GIS answering question “what exactly happens with land cover types over time ?” and “how the landscapes located in specific cold moisture conditions are affected by the landslides”.

The research focuses on the environmental mapping of the Šumava National Park (ŠNP), the largest of the four national parks (68,064 hectares) located in the south-west of Czech Republic, on the border with Germany. Since 1990 it has been the protected Biospherical Reserve of UNESCO The spatial analysis performed by means of QGIS in combination with remote sensing data (satellite images Landsat TM) for geobotanical studies. The spatio-temporal analysis was applied to raster images taken at 1991 and 2009. Built-in functions of the mathematical algorithms of QGIS enabled to process geospatial data and to derive information for geoecological modelling. The research aim was to analyse how the ecosystem landscapes located within the study area changed since 1991 until 2009 (18-year time span) using remote sensing data and GIS. The data include GIS layers in two forms: raster layers as Landsat TM images with 18-years interval (1991 and 2009), and vector thematic layers in ArcGIS shape-file format. The data were stored in a GIS project. Technically, the GIS project were generated in Quantum GIS (QGIS) software. The images classification was used to analyse changes in the ŠNP area that consist in different geobotanical land cover types. The results of spatial analysis demonstrated that structure, shape and configuration of landscapes in ŠNP changed since 1991. The combination of the remote sensing data and GIS tool for pattern recognition is proved to be effective tool for geo-botanical research, which is demonstrated in the current research.

Calculation of vegetation indices, especially Normalized Difference Vegetation Index (NDVI), has become one of the most successful, popular and traditional attempts in biogeographical research methods, because NDVI has certain advantages over other vegetation indices or band combinations. The results of calculations of vegetation indices for studies of land cover types are being repeatedly reported in various papers [1], [2], [3], [4]. Thus, NDVI is less depending on soil properties of the research area as well as to the daytime illumination comparing to simple red-infrared bands combination [5]. NDVI is well adjusted specially for the analysis of vegetation properties, which can be indirectly interpreted from the objects colors, as shown on the raster image. However, the correlation of the results received from the satellite spectral signals may not necessarily precisely correlate with real data on biomass and vegetation quality which is caused by the local climatic settings and biogeochemical background of the research area.

The study area is Šumava National Park (ŠNP), the largest of the four national parks located in the south-west of the Czech Republic, established as a special regime of environmental protection. A unique mosaic of forest habitats of exceptional natural value of European-wide significance, the ŠNP represents the largest terrestrial significant part of the Natura 2000 network in Czech Republic and Germany with unique mosaic of forest biotopes, rare, endemic and endangered species. It forms one of the largest forested areas between the Atlantic Ocean and the Ural. Recently, the ŠNP experienced changes in the landscapes and ecological community dynamics due to both natural climate changes and human impacts. Some parts of ŠNP are deforested and used for agriculture in the last decades.

Current work is aimed at the deriving of information from the remote sensed VHR data using a priori knowledge in the Object Based Image Analysis (OBIA) approach. OBIA technology is new and effective tool for urban mapping, as it enables dealing with raster images for detailed and precise cartography. Specific focus of this study is selected urban areas of the city of Brussels, Belgium. The study is performed using panchromatic very high resolution (VHR) image processed in the eCognition software. Application of the a priori knowledge in the OBIA approach towards classification of the satellite imagery for solving problem of the land cover studies is the target aim of this research. Some attempts of utilizing knowledge in the classifying map objects are performed [1] describing techniques of the labelling objects in urban environment. The authors developed an open source framework to study urban evolutions using vector based topographic databases as a part of the open GeOpenSim project. Using visualization of the geospatial objects from the database and expert knowledge labelling of the objects and generated the data set has been performed. It included continuous and discontinuous urban fabric, individual houses, high and low density mixed housing surface, hydrographical and communication network (canals, rivers), as well as specific urban surface (industrial wasteland and buildings), etc. Among earlier works, a review of the existing knowledge based approaches and examples in geospatial modelling is presented [2], where current development of this research branch is demonstrated. As it is noticed, the Fig.1. Image classification and objects recognition in eCognition software

The emphasis of this article is placed on the technical application of the remote sensing tools and methods for studies of vegetation coverage in northern ecosystems. The study area is located in Yamal peninsula, the Russian Federation. Landsat imagery covering study area in 1988, 2001 and 2011 has been analyzed using ILWIS GIS. The image processing was performed using semi-automated method of image interpretation. The remote sensing data classification from ILWIS menu enabled to map vegetation coverage over research area, which helped to identify land cover types and distribution in Yamal. Results show that Landsat TM imagery with 30 m mesh spacing is useful for landscape mapping and the interpretation of the vegetation cover types.