Gas Emission Craters (GEC) represent a new phenomenon in permafrost regions discovered in the north of West Siberia. In this study we use very-high-resolution Worldview satellite stereopairs and Resurs-P images to reveal and measure the geomorphic features that preceded and followed GEC formation on the Yamal and Gydan peninsulas. Analysis of DEMs allowed us to: (1) distinguish different terrain positions of the GEC, at the foot of a gentle slope (Yamal), and on an upper edge of a terrace slope; (2) notice that the formation of both Yamal and Gydan GECs were preceded by mound development; (3) measure a funnel-shaped upper part and a cylindrical lower part for each crater; (4) and measure the expansion and plan form modification of GECs. Although the general characteristics of both craters are similar, there are differences when comparing both key sites in detail. The height of the mound and diameter of the resulting GEC in Yamal exceeds that in Gydan; GEC-1 was surrounded by a well-developed parapet, while AntGEC did not show any considerable accumulative body. Thus, using very-high-resolution remote sensing data allowed us to discriminate geomorphic features and relief positions characteristic for GEC formation. GECs are a potential threat to commercial facilities in permafrost and indigenous settlements, especially because at present there is no statistically significant number of study objects to identify the local environmental conditions in which the formation of new GEC is possible.
Работа посвящена анализу рельефа, предшествовавшего возникновению Антипаютинской воронки га-зового выброса на полуострове Гыдан, а также его изменению вследствие образования воронки. Для этого соз-даны разновременные цифровые модели рельефа, построенные на основе обработки стереопар космических снимков сверхвысокого пространственного разрешения как до, так и после образования воронки. С относи-тельной точностью 0,35-0,55 м получены морфометрические характеристики форм рельефа рассматривае-мого участка. Установлено, что воронка приурочена к бровке склона эрозионной формы -балки, врезанной в террасовидную поверхность высотой 30-50 м. Образованию Антипаютинской воронки предшествовало су-ществование бугра высотой около 2 м, диаметром основания около 20 м. Размеры бугра, а также началь-ный диаметр цилиндрической части воронки меньше, чем у изученной ранее подобной формы на Централь-ном Ямале. Для Антипаютинской воронки характерно отсутствие выраженных в рельефе (высотой более 1 м) аккумулятивных тел из выброшенного материала, зафиксированных на цифровой модели рельефа, что также отличает ее от Ямальской воронки. Полученные данные показали, что поиск бугров-предшественников воро-нок газового выброса не может основываться на размерах бугров из-за их значительных вариаций.Ключевые слова: воронка газового выброса, полуостров Гыдан, криогенный рельеф, дистанционное зондирование, стереосъемка, цифровая модель рельефа Одобрена к печати:
The detection and identification of plant diseases is a fundamental task for sustainable crop production. Septoria tritici and Stagonospora nodorum blotch (STB and SNB) are two of the most common diseases of cereal crops that cause significant economic damage. Both pathogens are difficult to identify at early stages of infection. Determining the degree of the disease at a late infection stage is useful for assessing cereal crops before harvesting, as it allows the assessment of potential yield losses. Hyperspectral sensing could allow for automatic recognition of Septoria harmfulness on wheat in field conditions. In this research, we aimed to collect information on the hyperspectral data on wheat plants with different lesion degrees of STB&SNB and to create and train a neural network for the detection of lesions on leaves and ears caused by STB&SNB infection at the late stage of disease development. Spring wheat was artificially infected twice with Septoria pathogens in the stem elongation stage and in the heading stage. Hyperspectral reflections and brightness measurements were collected in the field on wheat leaves and ears on the 37th day after STB and the 30th day after SNB pathogen inoculation using an Ocean Insight “Flame” VIS-NIR hyperspectrometer. Obtained non-imaging data were pre-treated, and the perceptron model neural network (PNN) was created and trained based on a pairwise comparison of datasets for healthy and diseased plants. Both statistical and neural network approaches showed the high quality of the differentiation between healthy and damaged wheat plants by the hyperspectral signature. A comparison of the results of visual recognition and automatic STB&SNB estimation showed that the neural network was equally effective in the quality of the disease definition. The PNN, based on a neuron model of hyperspectral signature with a spectral step of 6 nm and 2000–4000 value datasets, showed a high quality of detection of the STB&SNB severity. There were 0.99 accuracy, 0.94 precision, 0.89 recall and 0.91 F-score metrics of the PNN model after 10,000 learning epochs. The estimation accuracy of diseased/healthy leaves ranged from 88.1 to 97.7% for different datasets. The accuracy of detection of a light and medium degree of disease was lower (38–66%). This method of non-imaging hyperspectral signature classification could be useful for the identification of the STB and SNB lesion degree identification in field conditions for pre-harvesting crop estimation.
In the last two decades in most regions of the country there has been a restoration of abandoned lands during the crisis of the 1990s. and higher yields due to a significant increase in state support for the agricultural sector and structural changes such as the emergence of agricultural holdings. As a result of modern reforms, Russia has become a leading player in the foreign food market. However, these positive developments take place against the background of a process of deepening regional differences in the productivity of the agricultural sector. The aim of the study is a comparative analysis of the dynamics of the withdrawal from circulation of sown areas in the Kirov province during the crisis of the 1990s. and post-crisis period 2000–2020. The analysis of spatio-temporal dynamics of the withdrawal from circulation and restoration of croplands was carried out by remote sensing methods for three agro-climatic zones and the main types of soils in the Kirov province. The main resource of the region is soddy-podzolic soils, which accounted for more than 77 % of the cropland in 1990 and about 70 % in 2020. The reduction in the area of cropland with this type of soil reached 90 % in the northern and 80 % in the central and southern zones, regardless of their differences in heat supply. Crisis period 1990–2000 characterized by the highest rate of withdrawal of agricultural land from circulation. In the post-crisis period, the reduction in sown areas only continued. Against this background, there is an extremely slight recovery of cropland (about 5 % of the 1990 level). There are natural differences in the restoration of sown areas in agro-climatic zones and by soil types, but they are poorly reflected in the overall negative dynamics of cropland, due to the low agro-climatic potential of the entire Kirov province.
<p>The activation of retrogressive thaw slumps is associated with slope surface stability disturbances, or with an increase in the depth of seasonal thawing, that can reach the top of surface-near ground ice. Most retrogressive thaw slumps are confined to terraced slope surfaces that have been undercut and started to retreat due to lateral river erosion or wave action along lake, river or sea shores. Subsequent long-term retrogressive that slump growth depends on constant removal of material from the slope foot by river water or sea waves.</p><p>We have studied the current dynamics of coastal destruction and retrogressive thaw slumps in the western (Kolguev Island) and one of the eastern-most (Novaya Sibir&#8217; Island) occurrences of tabular ground ice in the Eurasian Arctic. A wide set of multi-temporal optical earth observation data of high and very-high spatial resolution (SPOT 6 & 7, GeoEye, WorldView, Kompsat, Prism, Formosat, and Resurs) was used. We modified the TanDEM-X DEM (12 m) for relief reconstruction of earlier stage relief settings to ensure consistent orthorectification of oblique viewing satellite imagery. All raw images were terrain-corrected and georeferenced using a comprehensive block adjustment.</p><p>In the western part of Kolguev Island retrogressive thaw slump average retreat rates of different thermocirque features varied from 0.7 to 7.9 m/year in 2002-2018. Maximum rates reached 14.5-15.1 m/year. On the Novaya Sibir&#8217; Island thermocirques averaged retreat rates in 2007-2018 varied from 3.3 to 8.5 m/year, maximum rates were up to 15.5 m/year.</p><p>Besides dependence of thermocirque occurrence on local ground ice conditions, external forcing on coastal dynamics and thermocirque retreat has been analysed for air temperature and sea ice fluctuations through sums of positive daily mean air temperature and the duration of the open-water period variability for specific periods bracketed by image acquisition dates. Ice conditions in the coastal zone (app. near 50 km of coastal line) of the studied areas were analyzed according to microwave satellite OSI-450 and OSI-430 datasets. We assumed the open-water season as the period when sea ice concentration was less than 15%. Around Kolguev Island, over the 2006-2018 there has been not statistically significant linear trend for open-water period - median value of linear trend is 2.5 days/year with different sea ice conditions off the south and north coasts of the island. At the same time, an increase in the annual sum of positive daily mean &#160;air temperature is noted. For the period 2006-2018, the linear trend was 23.2 degree/year. That is why, for Kolguev Island, we expect at least a sustained level of substantially stronger retreat rates when compared with the past, if not a further increase in thermal denudation intensity and thermocirque growth, and strong and steady rates of coastal destruction due to wave action. Further research will focus on identifying commonalities and differences between the two study regions with respect to hydrometeorological and permafrost conditions.</p><p>Supported by RFBR grants &#8470; 18-05-60080 and 18-05-60221, and by DFG grant &#8470; WE4390/7-1.</p>
Thermodenudation on the Kara seacoast, the Yugorsky Peninsula, Russia, is studied by analyzing remote-sensing data. Landforms resulting from the thaw of tabular ground ice, referred to as thermocirques, are formed due to polycyclic retrogressive thaw slumps, during the last decade 2010–2020. We calculate the retreat rate of the thermocirque edge using various statistical approaches. We compared thermocirque outlines by the end of each time interval defined by the dates of available very-high-resolution imagery. Six thermocirques within two key sites on the Yugorsky peninsula are monitored. We correlate each of the thermocirque edge’s retreat rates to various climatic parameters obtained at the Amderma weather station to understand the interrelation patterns better. As a result, we find a very low correlation between the retreat rate of each thermocirque and summer warmth, rainfall, and wave action. In general, the activity of thermodenudation decreases in time from the previous decade (2001–2010) to 2010–2020, and from 2010 towards 2020, although the summer warmth trend increases dramatically. A single thermocirque or series of thermocirques expand in response to environmental and geological factors in coastal retreat caused by thermodenudation.
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