Experience and results of a remote study of lakes in the permafrost zone of Western Siberia from satellite images of various resolutions over a 50-year period

Modeling Spatial Structure of Thermokarst Lake Fields in Siberian Arctic by Satellite Imagery Based on Geo-Simulation and Heuristic Approaches

“…Such histograms of the distribution of lake areas can be constructed only on the basis of the integration of data on the areas of water bodies obtained from both medium and high resolution of satellite images. The developed methodology for combining (synthesizing) data on the areas of lakes obtained from images of different spatial resolution in order to construct synthesized histograms of the distribution of areas of lakes in a very wide range of their sizes is described in [14,16]. In accordance with this methodology, the synthesized histogram of the distribution of lakes by area was obtained by "stitching" two initial histograms, the first of which is based on Landsat-8 data and represents large lakes (ranging in size from 0.5 to 20,000 hectares).…”

“…The synthesized histograms of the distribution of the number and total area of lakes, obtained in the manner described above according to the results of the studies conducted in the permafrost zone of Western Siberia, are presented in [10]. The determination of the type of the law of the lake size-distribution was carried out on the basis of an approximation of the obtained sinthesized histogram of the distribution of lakes, which showed [16,17] that the empirical distribution corresponds to a lognormal law. The conformity check was performed with help of the Excel software package using Pearson's criterion confirmed that the histogram of the lake size-distribution obtained in a wide range of their sizes corresponds to a lognormal law with a high probability of 0.99.…”

The System of Geo-Simulation Modeling of Thermokarst Lakes Fields Based on the Log-Normal Distribution of Their Sizes

“…However, the model developed in [8,9] was based on the results of remote studies of the properties of fields of thermokarst lakes from satellite images of medium resolution (30 m) Landsat, on which lakes of relatively large sizes (above 0.5 ha) are visible. In our more recent investigations of thermokarst lakes [10][11][12][13] using images of high (1-10 m) and ultrahigh resolution (less than 1 m), the presence in real fields of thermokarst lakes in permafrost (on the example of Western Siberia) of huge the number of small-sized lakes that are not found in medium resolution images. The methodology for integrating data from medium and high / ultra-high resolution images developed in [10,11] made it possible to construct synthesized histograms of the distribution of lakes by area over a very wide range of sizes (from units m2 to tens of km2).…”

“…The methodology for integrating data from medium and high / ultra-high resolution images developed in [10,11] made it possible to construct synthesized histograms of the distribution of lakes by area over a very wide range of sizes (from units m2 to tens of km2). An analysis of these histograms showed [12,13] that the distribution of real lakes in the permafrost zone does not satisfy the exponential, but the lognormal law.…”

Methodological Issues of Using the Randomized Machine Learning for Forecasting the Dynamics of Thermokarst Arctic Lakes

“…Разработка таких мер на региональном уровне для арктических регионов невозможна без формирования обоснованных прогнозов объемов эмиссии метана и углекислого газа, которые могут быть основаны на знаниях о пространственно-временной динамике полей термокарстовых озер как важных источников эмиссии природного метана и углекислого газа на территории регионов. Известно, что наибольший вклад в глобальную эмиссию парниковых газов вносят территории вечной мерзлоты арктических регионов, что подтверждается многочисленными экспериментальными исследованиями в Сибири и в других северных регионах [1][2][3][4][5][6][7][8].…”