Анізотропний метадіелектричний перетворювач

Purpose. Investigation of the peculiarities of the electric field energy conversion by an anisotropic meta-medium with a negative value of the dielectric constant in one of the selected main crystallographic directions. Methodology. Research was carried out using methods of physical and mathematical modeling of anisotropic metadielectric converter; using methods to optimize the function of the dependence of the conversion factor m, anisotropic metadielectric converter, on the angle α between one of the crystallographic axes and the edge of the platinum a, at fixed anisotropy coefficients of metadielectric material. Findings. For the first time, the peculiarities of the  electric field transformation by an anisotropic meta-medium with a negative value of the dielectric constant in one of the selected main crystallographic directions were studied. It is established that at the moment of application to the upper and lower faces  of the anisotropic metadielectric plate, which is the basis of the anisotropic metadielectric converter, some potential difference leads to polarization of its volume and the emergence of both longitudinal  and transverse components of the vortex electric field. This situation leads to axial folding of its internal field, which in turn causes the appearance of micro-vortices of the electric field, given by the expression , where  - the circular time of rotation of the micro-vortex, and signs "+" and "-" - indicate the direction of its rotation. Such axial electric micro vortices are an efficient mechanism that pumps energy between the physical vacuum and, in our case, the anisotropic metadielectric plate of the transducer. The dependence of the transformation coefficient m of this medium on the value of anisotropy  is analyzed. Studies have shown that in the interval   the value of m is characterized by a negative value, and in the interval  – positive, this allowed us to determine the areas of stable existence of different types of energy. The use of metadielectric material in comparison with the classical one is characterized by values of m>1. Note that in some cases there is an abnormal increase in the coefficient. Originality. Using the representations of vortex electrodynamics, the mechanism of energy interaction between the vortex electric field of an anisotropic metaenvironment and the physical vacuum is proposed. Practical value.  A model of the original design of an anisotropic metadielectric converter is proposed. Areas of its practical use in the form of generators of electricity, heat and cold are determined, calculated expressions for their efficiency are in the range η = 0.5 ÷ 0.98, and the cooling temperature can reach the temperature of liquid helium.Цель работы. Исследование особенностей преобразования энергии электрического поля анизотропной метасредой при отрицательном значении диэлектрической проницаемости в одном из выбранных главных кристаллографических направлений. Методы исследования. Проведены исследования с применением методов физико-математического моделирования анизотропного метадиэлектрического преобразователя; с использованием методов оптимизации функции зависимости коэффициента преобразования m, анизотропного метадиэлектрического преобразователя, от угла α между одной из кристаллографических осей и ребром пластитин а, при фиксированных коэффициентах анизотропии метадиэлектрического материала.  Полученные результаты. Впервые исследованы особенности преобразования электрического поля анизотропной метасредой при отрицательном значении диэлектрической проницаемости в одном из выбранных главных кристаллографических направлений. Установлено, что в момент приложения к верхней и нижней граням анизотропной метадиэлектрической пластины, которая является основой анизотропного метадиэлектрического преобразователя, некоторой разности потенциалов приводит к поляризации ее объема и возникновению как продольной, так и поперечной составляющих вихревого электрического поля. Такая ситуация ведет к аксиальному сворачиванию ее внутреннего поля, что в свою очередь приводит к появлению микровихрей электрического поля, которые описываются выражением  где   – круговая частота вращения микровихря, а знаки «+» и «–» – обозначают направление его вращения. Такие аксиальные электрические микровихри являются эффективным механизмом, перекачивающим энергию между физическим вакуумом и в нашем случае, анизотропной метадиэлектрической  пластиной преобразователя. Проведен анализ зависимости коэффициента преобразования m этой среды от значения анизотропии . Исследования продемонстрировали, что в интервале  величина m характеризуется отрицательным значением, а в интервале  – положительным, это позволило определить области стабильного существования разных видов энергий. Использование метадиэлектрического материала по сравнению с классическим характеризуется значениями m>1. Отметим, что в редких случаях наблюдается аномальный рост упоминаемого коэффициента. Научна новизна. С использованием представлений вихревой электродинамики предложен механизм энергетического взаимодействия между энергиями электрического поля анизотропной метасреды и физического вакуума. Практическая ценность. Предложена модель оригинальной конструкции анизотропного метадиэлектрического преобразователя. Определены области практического использования анизотропного метадиэлектрического преобразователя в виде генераторов электричества, тепла и холода, получены расчетные выражения для их коэффициента полезного действия, находящегося в интервале η = 0,5÷0,98, а температура охлаждения может достигать температуры жидкого гелия.Мета роботи. Дослідження особливостей перетворення енергії електричного поля анізотропним метасередовищем при від’ємному значенні діелектричної проникності в одному з обраних головних кристалографічних напрямків. Методи дослідження. Проведено дослідження із застосуванням методів фізико-математичного моделювання анізотропного метадіелектричного перетворювача; з використанням методів оптимізації функції залежності коефіцієнта перетворення m, анізотропного метадіелектричного перетворювача, від кута α між однією з кристалографічний осей і ребром пласитини а, при фіксованих коефіцієнтах анізотропії метадіелектричного матеріалу. Отримані результати. Вперше досліджено особливості перетворення електричного поля анізотропним метасередовищем при від’ємному значенні діелектричної проникності в одному з обраних головних кристалографічних напрямків.  Установлено, що у момент прикладання до верхньої та нижньої граней анізотропної метадіелектричної пластини, яка є основою анізотропного метадіелектричного перетворювача, деякої різниці потенціалів  призводить до поляризації її об’єму та виникнення як поздовжньої , так і поперечної  складових вихрового електричного поля. Така ситуація веде до аксіального згортання її внутрішнього поля, яка у свою чергу зумовлює появу мікровихорів електричного поля, що подаються виразом         , де  – кругова частота обертання мікровихору, а знаки «+» та «–» – позначають напрямок його обертання. Такі аксіальні електричні мікровихори є ефективним механізмом, що перекачує енергію між фізичним вакуумом і в нашому випадку, анізотропною метадіелектричною пластиною переретворювача. Проведено аналіз залежності коефіцієнта перетворення m цього середовища від значення анізотропії . Дослідження продемонстрували, що у інтервалі  величина m характеризується від’ємним значенням, а в інтервалі  – додатнім, це дозволило визначити області стабільного існування різних видів енергій. Використання метадіелектричного матеріала в порівнянні із класичним характеризується значеннями m>1. Зазначимо, що в окремих випадках спостерігається аномальне зростання згадуваного коефіцієнта. Наукова новизна. З використанням уявлень вихрової електродинаміки запропоновано механізм енергетичної взаємодії між  вихровим електричним полем анізотропного метасередовища та фізичним вакуумом. Практична цінність. Запропоновано модель оригінальної конструкції анізотропного метадіелектричного перетворювача.  Визначено області його практичного використання у вигляді генераторів електрики, тепла та холоду, отримано розрахункові вирази для їх коефіцієнта корисної дії, що знаходиться в інтервалі η=0,5÷0,98, а температура охолодження може досягати температури рідкого гелію

U-Net Model for Logging Detection Based on the Sentinel-1 and Sentinel-2 Data

Illegal logging in Ukraine is a big problem that negatively affects both environmental and socio-economic indicators of the country. The main reason for this problem is the lack of independent control over the forest industry. Lack of control, in turn, makes it possible to provide inaccurate information about the permitted logging and to hide the fact of logging. The solution to this problem is the use of modern approaches of Remote Sensing and deep learning to implement mechanisms for forestry monitoring and logging detection based on the satellite data. Most researches on satellite-based logging detection technology are based on the optical satellite missions. However, for countries with temperate and cold climates, the use of such approaches is problematic in winter and autumn due to the lack of vegetative biomass and the high percentage of clouds and snow in satellite images. In this study, we assessed a methodology for detecting logging based on optical and radar images of Copernicus satellite missions, namely Sentinel-l and 2. The obtained results show that when using this approach, it is possible to monitor and detect logging with high accuracy both in summer and in winter with the frequency of data updates once a week. The basis of this methodology is a convolutional neural network with U -Net architecture, which input is a stack of optical and radar images in summer and spring, and works on radar images only in winter and autumn

Is Soil Bonitet an Adequate Indicator for Agricultural Land Appraisal in Ukraine?

Agriculture land appraisal analysis is an important component of the land market. This task is especially essential for Ukraine, which plans to lift the moratorium on land transactions and legalize farmland sales in 2021. Most post-Soviet countries adopted the notion of a soil bonitet—a quantitative score representing natural soil fertility. This score is also proposed in Ukraine to perform agricultural land appraisals. However, this is a static parameter and does not account for the dynamics of actual crop production on the agricultural lands. Moreover, the bonitet score is not crop-specific. Therefore, in this study, we use maps of bonitet based on the soil map and natural-agricultural districts of Ukraine and crop yields at the village scale to explore the relationships between bonitet values and actual crop production in Ukraine. We found that land appraisal is not correlated with the actual soil bonitet

Despeckling of Multitemporal Sentinel SAR Images and Its Impact on Agricultural Area Classification

This chapter addresses an important practical task of classification of multichannel remote sensing data with application to multitemporal dual-polarization Sentinel radar images acquired for agricultural regions in Ukraine. We first consider characteristics of dual-polarization Sentinel radar images and discuss what kind of filters can be applied to such data. Several examples of denoising are presented with analysis of what properties of filters are desired and what can be provided in practice. It is also demonstrated that the use of preliminary denoising produces improvement of classification accuracy where despeckling that is more efficient in terms of standard filtering criteria results in better classification

Automatic Deforestation Detection based on the Deep Learning in Ukraine

Ukraine's big problem is the disappearance of forest cover. According to the international forest monitoring project Global Forest Watch, Ukraine lost 1.08Mha of forests from 2000 to 2020. Such sad statistics are possible only due to the lack of monitoring tools for the forest industry in Ukraine. Such a tool can be created by combining Remote Sensing and Deep Learning approaches. To implement such approach for the automatic use, we combine Optical and Synthetic Aperture Radar images of the Sentinel-2 and Sentinel-1 satellite missions on which object-detection is performed using a U-Net-based neural network trained with use of the semi-supervised learning technique. This approach is being tested and shows its effectiveness in Kyiv region and going to be implemented in the same way for the Lviv, Odessa and Zakarpatya oblasts

Advanced Method of Land Cover Classification Based on High Spatial Resolution Data and Convolutional Neural Network

National Research foundation of Ukraine within the project 2020.02/0284 «Geospatial models and information technologies of satellite monitoring of smart city problems», which won the competition “Leading and Young Scientists Research Support”Based on modern satellite products Planet with high spatial resolution 3 meters, authors of this paper improved the neural network methodology for constructing land cover classification maps based on satellite data of high spatial resolution using the latest architectures of convolutional neural networks. The process of information features formation for types of land cover is described and the method of land cover type classification on the basis of satellite data of high spatial resolution is improved. A method for filtering artificial objects and other types of land cover using a probabilistic channel is proposed, and a convolutional neural network architecture to classify high-resolution spatial satellite data is developed. The problem of building density maps for the quarters of the city atlas construction is solved and the metrics for estimating the accuracy of classification map construction methods are analyzed. This will make it possible to obtain high-precision building maps to calculate the building area by functional segments of the Urban Atlas and monitor the development of the city in time. This will make it possible to create the first geospatial analogue of the product Copernicus Urban Atlas for Kyiv using high spatial resolution data. This Urban Atlas will be the first such product in Ukraine, which can be further extended to other cities in Ukraine. As a further development, the authors plan to create a methodology for combining satellite and in-situ air quality monitoring data in the city based on the developed Urban Atlas, which will provide high-precision layers of PM10 and PM2.5 concentrations with high spatial and temporal resolution of Ukraine

Super resolution approach for the satellite data based on the generative adversarial networks

In the past few years, medium and high-resolution data became freely available for downloading. It provides great opportunity for researchers not to select between solving the task with high-resolution data on small territory or on global scale, but with low-resolution satellite images. Due to high spectral and spatial resolution of the data, Sentinel-1 and Sentinel-2 are very popular sources of information. Nevertheless, in practice if we would like to receive final product in 10 m resolution we should use bands with 10 m resolution. Sentinel-2 has four such bands, but also has other bands, especially red-edge 20 m resolution bands that are useful for vegetation analysis and often are omitted due to lower resolution. Thus, in this study we propose methodology for enhancing resolution (super-resolution) of the existing low-resolution images to higher resolution images. The main idea is to use advanced methods of deep learning - Generative Adversarial Networks (GAN) and train it to increase the resolution for the satellite images. Experimental results for the Sentinel-2 data showed that this approach is efficient and could be used for creating high resolution products

Losses Assessment for Winter Crops Based on Satellite Data and Fuzzy Logic

This paper considers the method of the winter crop classification map producing in terms of climatic and weather abnormal conditions in 2020. Given that the traditional method of construction involves the use of a training sample, which is collected in ground surveys along the roads. This sample could not be collected under the strict quarantine regime, that is why the classification map was created based on the sample obtained as a result of the photointerpretation. Both, optical Sentinel-2 and SAR Sentinel-1 satellite data were used. This is due to the fact, that the period of the winter crop classification map producing fell exactly on the period of time (April and May 2020), when the area of study Odesa region (as well as the whole territory of Ukraine) had a high percentage of cloud cover. At the same time, radar imaging techniques allow us to bypass obstacles such as clouds, but also have lower sampling quality. Therefore, it was decided to combine the obtained classification maps based on radar and optical data by fuzzy logic, considering the degree of belonging of each pixel by the value of the normalized difference vegetation index (NDVI). As a result, the obtained classification maps based on photointerpretation sample have an accuracy close to 95%. The fuzzy logic method allows to increase this value by selecting only the best pixels from classification maps based on radar and optical satellite data

Biophysical Impact of Sunflower Crop Rotation on Agricultural Fields

Crop rotation is an important determining factor of crop productivity. Sustainable agriculture requires correct rules of crop rotation. Failure to comply with these rules can lead to deterioration of soil biochemical characteristics and land degradation. In Ukraine as well as in many other countries, sunflower monocropping is common practice and the impact of this fact should be studied to find the most precise rules to save the economic potential of land and minimize land degradation factors. This research provides an evaluation of the sunflower monocropping effect on the vegetation indices obtained from MODIS vegetation indices datasets for Ukraine as one of the countries with the biggest sunflower export in Europe. The crop rotation schemes are represented by their area proportions at the village level calculated based on the crop classification maps for 2016 to 2020. This representation gives the possibility to use regression models and f-test feature importance analysis to measure the impact of 3-year and 5-year crop rotation sequences. For these purposes, we use several models: a four-year binary representation model (model A1) and a model with all possible three-year crop rotation scheme representations (model B). These models gave the possibility to evaluate crop rotation schemes based on their biophysical impact on the next sunflower plantings and found that sunflower planting with an interval of three or more years is optimal in terms of the sustainability of soil fertility