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Alors que les appels en faveur de l’interdisciplinarité se multiplient, en particulier dans les études sur le changement climatique et ses impacts, cette démarche reste encore un objet méconnu pour de nombreux chercheurs. Au-delà des débats épistémologiques sur la définition de l’interdisciplinarité, sa mise en œuvre pratique reste également peu discutée. Dans la lignée des réflexions sur l’interdisciplinarité comme approche forgée au moyen d’interactions et de dialogues, cet article propose de revenir sur le rôle de l’animation scientifique dans la construction de cette démarche, en décrivant l’expérience du GIS CES (Groupement d’intérêt scientifique Climat Environnement Société). Nous présentons les réflexions au sein du groupement ainsi que les initiatives et outils développés et testés pour renforcer le dialogue interdisciplinaire. Scientific facilitation in interdisciplinary practice: the experience of the French Research Consortium Climate-Environment-Society (2007-2015)While calls for interdisciplinarity are increasing, especially in the study of climate change and its impacts, many researchers are still unfamiliar with such approach. Also, beyond the epistemological debates on the definition of interdisciplinarity, its practical implementation is seldom discussed. Defining interdisciplinarity as a practice based on interactions and dialogues, this article proposes to reconsider the role of scientific facilitation in the construction of interdisciplinary approaches. It draws on the experience of the GIS CES (Groupement d’intérêt scientifique Climat Environnement Société), a French interdisciplinary consortium focused on the study of climate change and its impacts. First, we describe the reflections and challenges within the organization to build a common objective around interdisciplinary research. Second, we discuss the different initiatives and tools developed and tested to strengthen the interdisciplinary practices of the group.

CHRIS (Compact High Resolution Imaging Spectrometer) - new imaging spectrometer carried on board a space platform PROBA (Project for On Board Autonomy) The satellite was successfully launched in late October 2001, Shriharikota (India) Region of interest – Thorney Island (UK), Chichester harbour Chichester harbour has unique wetland environment : place for rare bird colonies. Monitoring this place - important ecological task for environmental managers. To obtain a good-quality natural-coloured image of wetlands we need: nadir-taken colour CHRIS image with bands combination of corresponding spectral channels. For the quality of CHRIS images .hdr files were examined: 1) CHRIS...47AO_41.hdr (taken at +36°) 3) CHRIS...47A2_41.hdr (taken at +55°) 2) CHRIS...47A1_41.hdr (taken at -36°) 4) CHRIS...47A3_41.hdr (taken at -55°) 5) CHRIS...479F_41.hdr (taken at nadir) Images taken at the nadir are of good quality, while those at different angles have defects. The work demonstrated CHRIS/PROBA application for Earth Observation purposes, environmental mapping and GIS.

Proceedings of the International Conference. Volga State University of Technology, Mar. 19, 2015 (eds Kusakin, A. V. & Efimova, T. N.) (VolgaTech Press, Yoshkar-Ola, Russia, 2015), 110–113. isbn: 978-5- 9903856-9-6. in Russian. Целью исследования является картографирование заболоченных областей п-ова Ямал на основе применения разновременных спутниковых снимков Landsat TM и программного обеспечения (ПО) ILWIS GIS. Задача исследования — визуализировать экологическую динамику изменения избранных ландшафтов на Крайнем Севере России методами ГИС. Полуостров Ямал является важным биогеографическим регионом Арктики, расположенным в пределах субарктической континентальной климатической зоны пересекая два основных физико-географических региона: субарктическая и арктическая тундры. Геоморфологическая особенность Ямала — практически плоская равнинная поверхность — создает прекрасные условия для формирования здесь густой сети взаимосообщающихся небольших озер и неглубоких рек, а также заболоченной местности, районов с топями и местностей с повышено влажной почвой, которые подвергаются регулярному ежегодному сезонному затапливанию, характерному в весенне время. Статистические результаты вычислений типов растительного покрова были получены в полуавтоматическом режиме в ПО ILWIS GIS. Представленная работа продемонстрировала успешное применение ГИС-технологий для обработки данных спутниковых снимков, а также проиллюстрировала изменение тундровых ландшафтов в заболоченной местности п-ова Ямал.

International audience; 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 south-western 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, sub-divided 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.

International audience; While calls for interdisciplinarity are increasing, especially in the study of climate change and its impacts, many researchers are still unfamiliar with such approach. Also, beyond the epistemological debates on the definition of interdisciplinarity, its practical implementation is seldom discussed. Defining interdisciplinarity as a practice based on interactions and dialogues, this article proposes to reconsider the role of scientific facilitation in the construction of interdisciplinary approaches. It draws on the experience of the GIS CES (Groupement d’intérêt scientifique Climat Environnement Société), a French interdisciplinary consortium focused on the study of climate change and its impacts. First, we describe the reflections and challenges within the organization to build a common objective around interdisciplinary research. Second, we discuss the different initiatives and tools developed and tested to strengthen the interdisciplinary practices of the group.; Alors que les appels en faveur de l’interdisciplinarité se multiplient, en particulier dans les études sur le changement climatique et ses impacts, cette démarche reste encore un objet méconnu pour de nombreux chercheurs. Au-delà des débats épistémologiques sur la définition de l’interdisciplinarité, sa mise en œuvre pratique reste également peu discutée. Dans la lignée des réflexions sur l’interdisciplinarité comme approche forgée au moyen d’interactions et de dialogues, cet article propose de revenir sur le rôle de l’animation scientifique dans la construction de cette démarche, en décrivant l’expérience du GIS CES (Groupement d’intérêt scientifique Climat Environnement Société). Nous présentons les réflexions au sein du groupement ainsi que les initiatives et outils développés et testés pour renforcer le dialogue interdisciplinaire.

Работа оценивает изменения в типах растительного покрова российского Севера в течение последних двух десятилетий. Результаты проведенной классификации спутниковых снимкой показывают экологические аспекты изменения лесотундровых экосистем. Технически, обработка данных была выполнена в ПО ГИС ILWIS, с использованием методов дешифрирования и контролируемой классификации. Результаты позволяют выявить изменения в типах и распределении растительного покрова. This paper focuses on the assessment of the changes in land cover types in Yamal peninsula over the past two decades, which shows local environmental aspects of the climate change in North. Technically, the data processing was performed in ILWIS GIS, using semi-automated methods of image interpretation and supervised classification. The results of the classification analysis enable to identify changes in land cover types and their distribution in Yamal.

International audience; Environmental mapping is a necessary tool for the geoscience research in the university classes of geography, GIS cartography and mapping. However, GIS methods of processing remote sensing data are often being discussed, and the optimal approaches are disputed. This work reports innovative approach of the processing Landsat TM satellite image in ILWIS GIS software using unsupervised and supervised classification methods. The methods of ILWIS GIS are compared and the results described in this paper. The methodology is based on the use of supervised classification of the satellite image, an innovative method in geographic research. Supervised classification of the raster imagery aimes at the recognizing of the class membership for each pixel during image analysis. The supervised classification of the multi-spectral imagery has been performed using 'Classify' operator in ILWIS applied to Landsat TM 1988. The classification process included following steps. First, the models of the classes were defined by creating a "sample sat" in ILWIS GIS. Namely, the training pixels with similar spectral values were defined and selected as representations for various classes. These pixels have contrasting colors, visually visible and distinguishable on the image, which serve as training areas for diverse classes. The sample pixels were defined in the Sample Set Editor in ILWIS, which was initially created in the main menu. A created Sample Set has a reference to the set of Landsat bands (1-7), which are needed to create sample statistics. After assigning pixel sets, a raster polygon map was automatically created with .mpr file extension. It contained sample pixels, location and legend, i.e. the names of the classes allocated to pixels. Easy interpretation of the image strongly depends on the optimal color composite map. The classification has been completed in interactive way, using several attempts of creating training samples, selecting various sample sets and respective pixels selected in Sample Set Editor using domain for classification ―Landclasses. The classification was repeated the until the final results were achieved. Shadows of green colors represent grass, shrub vegetation coverage and forest canopy. The results demonstrate successful application of the innovative approach of technical satellite image processing for the studies of the environment. The presented methods can be used by students of geography.

International audience; 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. Most of the fields and meadow areas have been abandoned. Many species are threatened by the land-use changes. During the last decades some ecosystems` components are being gradually changed, degrading, some endangered, rare, unique and important species are under extinction. As a result, the vegetation in the forest ecosystems is gradually changing and degrading. Human effects include fragmentation, and deforestation of original floodplain forests. Therefore, the questions of environmentally sustainable management is highly important and the future of nature conservation of ŠNP caused discussions and worries. Current paper contributes to the environmental mapping of this precious forest area. The research aim was to analyse how the forest landscapes has changed from 1991 up to 2009 (18- years) using remote sensing data and GIS. The data include GIS layers: raster Landsat TM images and vector thematic layers in ArcGIS format. Technically, the GIS project was made in Quantum GIS environment. Methodologically, spatial analysis was used to test the importance of the land cover changes in forest areas. The results include two maps showing the geographic distribution of land cover types within the 18-year period. The results visualized forest landscape dynamics in 1991 and 2009. They demonstrated effective application of QGIS software with multi-source geospatial data for environmental mapping of precious forest areas. The combination of remote sensing data and GIS tools for pattern recognition proved to be effective for geo-botanical forest research.

International audience; The study region is located in western Turkey, Izmir surroundings. The research examines spatiotemporal changes in landscapes of Izmir region, during the decade 1995-2005. Methods entail raster processing, spatial analysis and mapping by means of geospatial techniques and Erdas Imagine software. The Landsat TM images were geo-processed for detection of changes in the land cover types. It demonstrated effective use of the remote sensing data and spatial analysis for vegetation studies: a combination of digital satellite images, GIS cartographic tools and methods of spatial analysis of vegetation coverage are highly suitable and efficient for the monitoring of highly heterogeneous landscapes located in the area of intensive anthropogenic activities (western Turkey). The study contributes towards technical development of cartographic methods of the environmental monitoring.

The study area is 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. Being a unique mosaic of natural and secondary habitats of exceptional natural value of European-wide significance, the components of the ŠNP represent is the largest terrestrial significant part of the Natura 2000 network in Czech Republic and Germany. For instance, the fauna species of ŠNP include protected important examples, such as e.g. lynx, otter and peregrine 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. Methodologically, the applied workflow used in this research included following steps: 1) Data capture, unpacking and storage. 2) Organizing GIS project. 3) Geo- referencing and re-projection. 4) Activating GDAL and GRASS remote sensing plugins. 5) Preliminary data processing. 6) Generating contour layers from DEM. 7) Colour composition from 3 Landsat TM bands. 8) Defining Region of Interest: raster mosaicing and clipping. 9) False colour composites (bands 4-3-2). 10) Setting up parameters for classification. 11) Image classification using K-Means algorithm. 12) Pattern recognition. 13) Spatial analysis. The detailed illustrations of these steps are shown in the proposed presentation. The GIS analysis is used to test the importance of the natural and human-induced land used changes for survival of the important floristic locations in several case studies. Thus, landscape level predictors of commons (their location, size, borders) are evaluated using geospatial data: vector GIS layers and aerial images. The information received from these data includes digital model of the terrain (altitudes), vertical heterogeneity, slope, topographical related moisture index, heat load index and solar radiation index. The information on local geology and soil conditions (based on soil profiles), history of the colonization of the study area, and borders of land cadasters and private properties is taken from the auxiliary data. The land cover structure is calculated using Patch Analyst function embedded into the ArcGIS which is used to describe various aspects of landscape heterogeneity, habitat diversity and fragmentation. The outcomes are illustrated by two maps showing geographic distribution of land cover types within the study area in given time periods of 18-year time span. The results demonstrate visualization of the ecosystems in 1991 and 2009 showing dynamics of land cover types in the given time. The work demonstrated effective application of QGIS software combined with multi-source data (remote sensing and geoinformatics) for the purpose of environmental protection of precious areas of the Šumava National Park.

The article deals with effective method of building up a GIS project. The types of the spatial thematic information is divided by blocks, according to the data types. Each block contains information on natural characteristics of the ecosystem with its structural components. While mapping a series of geoecological maps, the basic information about the natural features of the region creates a basis of the project. It is derived from the thematic maps collected as cartographic data base of the project. All integrated thematic data about the natural resources and characteristics of the region is structured in the database, subdivided by specific geographic region, according to the thematic blocks to which it belongs topologically and semantically., Рассмотрены типы тематических информационных блоков природных характеристик экосистемы с ее структурными составляющими, необходимые при разработке ГИС-проекта. При составлении серии геоэкологических карт базовой является информация о природных особенностях региона, которая получена при изучении тематических карт, формирующих картографический фонд банка данных проекта. При этом вся полученная тематическая информация о природных ресурсах региона структурируется в базе данных по региону соответственно тематическим блокам, к которым она генетически принадлежит.В данные о геоморфологической структуре побережья включены сведения о генетическом типе берега, структуре пляжной зоны: ее ширине, рельефе, уклоне, поперечном профиле берега, составе грунтов побережья. В блоке гидрологической информации о регионе используется информация о районах погружения вод поверхностных течений Атлантического и Тихого океанов под холодные глубинные Арктические воды, т.е. их ассимиляция и растворение, районы смешения вод, теплые и холодные течения Арктики. Важной составляющей гидрологического блока является информация о структуре течений Северного Ледовитого океана, отражающей основные источники происхождения течений в регионе: воды Атлантических течений, течений Тихого океана, выносы речных вод, атмосферные осадки, собственно Арктические течения и направления глубинных течений. При оценке экологического состояния моря необходимо учитывать экологический вклад выноса рек бассейна данной акватории, поэтому в проект должны быть включены карты речного стока Арктики и их гидрологические параметры. Экологический блок данных включает показатели значимых факторов с учетом степени их проявления. К ним относятся разрушение берегов, дефляция, нарушения жизнедеятельности арктической фауны. Данный блок показателей характеризует антропогенную нагрузку на природные комплексы акваторий, приводящих к развитию негативных процессов, оценивает их проявление и является базовым при дальнейшем комплексном исследовании экологического состояния акваторий и их районирования.

International audience; 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. The images were downloaded from the Earth Science Data Interface, Global Land Cover Facility. The Landsat TM imagery include scenes of June 2006 and June 1992. Both images cover summer months, thus enabling vegetation coverage to be easily recognized.; 74 кулонометрия) и другие методы. Большое количество часов лабораторных ра-бот (70% от общего количества часов отведенных на изучение дисциплины), позволяют студентам на практике самостоятельно изучить основные современ-ные аналитические методы. Значительное внимание уделяется радиохимиче-скому анализу природных объектов, что связано с загрязнением окружающей среды естественными и искусственными радионуклидами. Поэтому в данном курсе предусмотрены работы по изучению методов дозиметрического контро-ля. Лабораторный практикум курса «Аналитические методы в геоэкологии» представлен следующими расчетно-аналитическими занятиями:-взвешивание на весах различных типов;-методы фильтрования растворов;-титриметрический метод определения общей щелочности и карбонатной жесткости воды;-спектрофотометрический метод определения концентрации вещества;-фотометрический метод определения нитритов с использованием реак-тива Грисса;-измерение рН раствора потенциометрическим методом;-оценка радиационной обстановки в помещениях и на открытом воздухе дозиметрическими методами. В рамках освоения каждого расчетно-аналитического занятия студенты свободно ориентируются в современных методах физико-химического анализа, могут выбирать аппаратуру в соответствии с типом образца, областью примене-ния, требуемой чувствительностью и точностью, использовать методы количе-ственного определения концентрации различных веществ и применять полу-ченные знания на практике для решения различных прикладных геоэкологиче-ских проблем. 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 (fig. 1). The research method is based on the spatiotem-poral analysis of the geospatial data, performed by means of GIS tools and remote

International audience; The research aim is application of GIS and spatial analysis of satellite images for agricultural mapping. The study area is located in Mecsek Hills, Hungary. These landscapes represent unique part of Hungarian environment in the Carpathian Basin. Diverse landscape structure with complex biogeographic composition characterizes this region. However, this region is intensely used in agriculture, which causes high land heterogeneity.The research method consists in using ILWIS GIS and Landsat TM satellite imagery (1992, 1999 and 2006). The methodology includes clustering, spatial analysis, interpretation and classification. Clustering algorithm is based on the analysis of the similarity of the spectral signatures of pixels, and grouping pixels into thematic categories of classes of the land cover types in study area.This paper contributes to the development of the agricultural monitoring in region of central Europe. The distribution of the landscapes in the Mecsek Hills area was analyzed. Land cover types were interpreted by association of pixels on the image to different thematic classes: vegetation, categories of agricultural land and other areas (in total, 12 classes). The results consists in thematic land cover maps of the study area in 1992, 1999, 2006 showing landscape dynamics.

International audience; This paper details changes in land cover types and vegetation distribution in tundra landscapes during the past two decades. The main method of the work is classification of the Landsat TM scenes for land cover change detection. The new approach of the current work is application of GIS and remote sensing tools for Bovanenkovo region, since there is no previous remote sensing and GIS-based studies performed in the same area focusing research problem of land cover changes. The research area is geographically located on the Bovanenkovo region, the northwestern part of Yamal Peninsula, West Siberia, Russia. The Yamal Peninsula is the world's largest high-latitude wetland system covering in total 900,000 km² of peatlands, since lowland region creates ideal conditions for the development of wetlands, dense lake and river network (Kremenetski et al. 2003). The geomorphology of Yamal Peninsula is flat homogeneous land and low-lying plains with maximal elevations lower than 90 meters (Walker et al. 2009). Such environmental settings of Yamal facilitate seasonal flooding, active erosion processing, permafrost distribution and intensive local landslides formation.The dominating vegetation types on Yamal include different types of shrubs and willows, heath, grasses, moss, and lichens. Changes in land cover types in the Russian North are caused by various reasons. These include multiple ecological and social factors, such as permafrost degradation, reindeer grazing and gas-field development, as well as overall environmental changes, including climate (Walker et al. 2009). One of the factors causing changes in vegetation types in landslide formation. Thus, the early-stage vegetation, such as pioneering mosses or lichens usually follows recent landslide formation, while meadows and willow shrubs with high canopy points indicate later stages of vegetation regeneration after landslide activities. Therefore, distribution of the willow shrubs on bare slopes may indicate that these areas were landslide-affected in the past (Ukraintseva and Leibman, 2007; Leibman and Kizyakov, 2007). Current research focuses on application of remote sensing data and GIS methods for land cover change detection in Bovanenkovo region. Technically, the data processing was performed in ILWIS GIS, using methods of image interpretation and supervised classification applied for Landsat TM scenes (1988 and 2011). The classification results indicate changes in land cover types in Yamal ecosystems, namely, the overall increase in woody plants, such as willows and shrub tundra (e.g. "short shrub tundra", "sparse short shrub tundra" and "dry short shrub tundra"), and slight decrease in grasses, heath and peatland. The main detected trend in these changes demonstrates process of greening in Arctic tundra, which indicates structural variations in ecosystems within the Bovanenkovo district. These changes can be explained by the complex ecological processes as well as anthropogenic influence, caused by Bovanenkovo gas field exploration and its consequences. Methods The research methods consist of the application of the remote sensing and geoinformation tools for land cover studies. The technical implementation of the imagery processing, spatial analysis and GIS mapping was performed in ILWIS GIS. The research data include two Landsat TM scenes for the years 1988 and 2011. The Landsat data were selected due to their suitability for land cover mapping they enable recurrent remote sensing observations, interpretation and assessment of temporal changes in land cover types in the high north. The research methodology includes supervised classification of the Landsat scenes, GIS mapping highlighting changes in land cover types. And calculation of the areas of various land cover types in 1988 and in 2011. The pre-processing of the imagery includes data import and visual settings of colours and contrast. The images were imported to ILWIS from .img into ILWIS raster map format (ASCII) using GDAL and processed. Final maps are displayed showing land cover changes in 1988-2011.

Current poster presents remote sensing and GIS workflow applied for environmental monitoring of the Páramo National Park. Páramo National Park, located in Ecuador, is known for its unique natural resources in high altitude grasslands. The ecosystems of Páramo consist mostly of rare species and are the key protected area for exceptionally high endemism. ENVI software enables to make an analysis of the area and to produce a map based on 2 criteria: vegetation amount and altitude. We need to show vegetation growing on different heights and to create 3D-Visualization of our analysis. The workflow consists in following 9 steps: 1) displaying the Landsat TM satellite image. 2) Enhancing the Contrast of the Image (Enhance-Gaussian). 3) Uploading the SRTM-Data. 4) 3 D-Visualising the Landscape. 5) Calculating the Greenness Index. 6) Creating the Vegetation Layer ROI – Region of Interest. 7) Creating the Altitude Layer. 8) Mapping and Design. 9) 3D-Mapping (Final Map + DEM).

Final report for the student internship at Joanneum Research Forschungsgesellschaft mbH, Institut für Digitale Bildverarbeitung, Graz, Austria.