943 resultados para Russia--Maps


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magno studio plurimis in locis aucta, edita ... a Nicolao Ioannis Piscatore.

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door Isaak Tirion ; J. Keyser get. on gesn.

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Charten, Reisen und astronomischen Orstbestimugen gezeichnet von I. C. M. Reinecke.

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Report for the scientific sojourn at the Research Institute for Applied Mathematics and Cybernetics, Nizhny Novgorod, Russia, from July to September 2006. Within the project, bifurcations of orbit behavior in area-preserving and reversible maps with a homoclinic tangency were studied. Finitely smooth normal forms for such maps near saddle fixed points were constructed and it was shown that they coincide in the main order with the analytical Birkhoff-Moser normal form. Bifurcations of single-round periodic orbits for two-dimensional symplectic maps close to a map with a quadratic homoclinic tangency were studied. The existence of one- and two-parameter cascades of elliptic periodic orbits was proved.

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Julkaisussa: Geographia universalis, vetus et nova, complectens Claudii Ptolemaei Alexandrini enarrationis libros VIII

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Julkaisussa: Tabellae geographicae

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Julkaisussa: Dell' arcano del mare di Ruberto Dudleo ... parte seconda del tomo terzo contenente il libro sesto. Vol III

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Wetlands store large amounts of carbon, and depending on their status and type, they release specific amounts of methane gas to the atmosphere. The connection between wetland type and methane emission has been investigated in various studies and utilized in climate change monitoring and modelling. For improved estimation of methane emissions, land surface models require information such as the wetland fraction and its dynamics over large areas. Existing datasets of wetland dynamics present the total amount of wetland (fraction) for each model grid cell, but do not discriminate the different wetland types like permanent lakes, periodically inundated areas or peatlands. Wetland types differently influence methane fluxes and thus their contribution to the total wetland fraction should be quantified. Especially wetlands of permafrost regions are expected to have a strong impact on future climate due to soil thawing. In this study ENIVSAT ASAR Wide Swath data was tested for operational monitoring of the distribution of areas with a long-term SW near 1 (hSW) in northern Russia (SW = degree of saturation with water, 1 = saturated), which is a specific characteristic of peatlands. For the whole northern Russia, areas with hSW were delineated and discriminated from dynamic and open water bodies for the years 2007 and 2008. The area identified with this method amounts to approximately 300,000 km**2 in northern Siberia in 2007. It overlaps with zones of high carbon storage. Comparison with a range of related datasets (static and dynamic) showed that hSW represents not only peatlands but also temporary wetlands associated with post-forest fire conditions in permafrost regions. Annual long-term monitoring of change in boreal and tundra environments is possible with the presented approach. Sentinel-1, the successor of ENVISAT ASAR, will provide data that may allow continuous monitoring of these wetland dynamics in the future complementing global observations of wetland fraction.

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Based on the map of landscapes and permafrost conditions in Yakutia (Merzlotno-landshaftnaya karta Yakutskoi0 ASSR, Gosgeodeziya SSSR, 1991), rasterized maps of permafrost temperature and active-layer thickness of Yakutia, East Siberia were derived. The mean and standard deviation at 0.5-degree grid cell size are estimated by assigning a probability density function at 0.001-degree spatial resolution. Spatial pattern of both variables are dominated by a climatic gradient from north to south, and by mountains and the soil type distribution. Uncertainties are highest in mountains and in the sporadic permafrost zone in the south. The maps are best suited as a benchmark for land surface models which include a permafrost module.

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The video FireMovie_2000-2011.avi shows an animation with all MODIS fire product maps of the area sequenced over time. Colors in the video describe MODIS classes as follows: MODIS classification and color scale: Class 0 - not processed - Dark blue (1 frame) Class 3 - water - Light Blue (rivers and some lakes) Class 4 - clouds - Green blue Class 5 - non fire land - Yellow green Class 8 - nominal confidence fire - Red Class 9 - high confidence fire - Dark red