By Anja Rösel
The Arctic sea ice is characterised by means of profound adjustments as a result of floor melting strategies and the formation of soften ponds in summer time. soften ponds give a contribution to the ice-albedo suggestions as they decrease the outside albedo of sea ice, and for that reason speed up the decay of Arctic sea ice. To quantify the melting of the whole Arctic sea ice, satellite tv for pc established observations are beneficial. as a result of diversified spectral houses of snow, ice, and water, theoretically, multi-spectral optical sensors are important for the research of those particular floor kinds. This learn demonstrates the potential for optical sensors to become aware of soften ponds on Arctic sea ice. For the 1st time, an Arctic-wide, multi-annual soften pond facts set for the years 2000-2011 has been created and analyzed.
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Additional resources for Detection of Melt Ponds on Arctic Sea Ice with Optical Satellite Data
11 Refrozen and partly snow covered melt ponds on Arctic sea ice. The photo was taken during the Polarstern cruise ARK-XXII/2 in 2007. Photo: Stefan Kern Melt ponds are nearly salt free and the density maximum of the ponded water lies well above the freezing point . Consequently, radiative heating favors convection within the pond: due to the density anomalies of water, the warmer water will sink down and thus causes further melting. Convection and mixing of the water is additionally enhanced by wind .
Each line represents a 185 km long and 480 m wide sweep on the surface . The inclination of the orbit is 98:2ı . This allows acquisitions of data up to a latitude of 82ı N. 5 m. The received electromagnetic energy is converted into 256 discrete levels referred to as digital numbers (DN). The ETMC has an additional panchromatic band with 15 m spatial resolution. In contrast to SPOT or Terra, Landsat is not able to look at any position other than directly downward, therefore the revisiting period is fixed at 16 days.
The color of a melt pond is not only depending on the depth but also on the texture of the underlaying surface . Within this subset, reference areas for further analysis are defined. The reference areas or training areas cover all necessary features such as open water (A), snow covered ice (B), and two types of melt ponds (C and D). These features are visually identified from Fig. 2. We assume, that they are suitable to represent the specific classes. gov; both accessed in February 2012. A.