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Дистанционные методы и космические исследования в науках о Земле

Журнальные статьи

Duan, Xueyang; Moghaddam, Mahta 3-D Vector Electromagnetic Scattering From Arbitrary Random Rough Surfaces Using Stabilized Extended Boundary Condition Method for Remote Sensing of Soil Moisture // IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING Volume: 50 Issue: 1 Pages: 87-103 Published: JAN 2012

We develop the stabilized extended boundary condition method (SEBCM) based on the classical EBCM to solve the 3-D vector electromagnetic scattering problem from arbitrary random rough surfaces. Similar to the classical EBCM, we expand the fields in terms of Floquet modes and match the extended boundary conditions at test surfaces away from the actual rough surface to retrieve the surface currents and therefore the scattered fields. However, to solve long-standing stability problems of the classical EBCM, we introduce a z-coordinate transformation to restrict and control the test surface locations explicitly. We also introduce the concepts of moderated test surface locations and balanced k-charts for further stabilization and optimization of the solutions. The computational efficiency is optimized by judicious submatrix decomposition. The resulting bistatic scattering cross sections are validated by comparing with analytical and numerical solutions. Specifically, the solutions are compared with those from the small perturbation method and small-slope approximation within their validity region, and with those from the method of moments outside the validity domains of analytical solutions. It is shown that SEBCM gives accurate, numerically efficient, full-wave solutions over a large range of surface roughnesses and medium losses, which are far beyond the validity range of analytical methods. These properties are expected to make SEBCM a competitive forward solver for soil moisture retrieval from radar measurements.

Gatti, Guido; Tebaldini, Stefano; d'Alessandro, Mauro Mariotti; et al. ALGAE: A Fast Algebraic Estimation of Interferogram Phase Offsets in Space-Varying Geometries // IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING Volume: 49 Issue: 6 Pages: 2343-2353 Part: 2 Published: JUN 2011

This paper deals with the estimation of terrain topography from multipass synthetic aperture radar (SAR) interferometry (InSAR), focusing on the case where variation of the system geometry within the imaged swath is relevant. A typical case is represented by airborne multipass interferometric campaigns where, due to the closeness between the radar sensor and the targets, the incidence-angle sensitivity undergoes a dramatic increase with respect to the spaceborne case, resulting in a high spatial variability of the normal baselines. The space-varying nature of the system geometry gives rise to a major issue in multipass InSAR analyses in that it prevents from compensating for the presence of interferogram phase offsets by simply phase locking the data stack to a reference point, therefore hindering the retrieval of terrain topography. To cope with this issue properly, we propose a novel approach that exploits the algebraic properties of the problem. Such an approach allows casting the problem in terms of identification of a null-space component for terrain topography after which both topography and the interferogram phase offsets are quickly obtained without exploiting calibration points. Experimental results are shown based on a P-band data set acquired by the Experimental SAR (E-SAR) airborne system, operated by the German Aerospace Center (DLR), in the framework of the European Space Agency (ESA) campaign BIOSAR 2008.

Guzel, Esat; Canyilmaz, Murat; Turk, Mustafa Application of wavelet-based denoising techniques to remote sensing very low frequency signals // RADIO SCIENCE Volume: 46 Article Number: RS2013 Published: APR 8 2011

In this paper, we apply wavelet-based denoising techniques to experimental remote sensing very low frequency (VLF) signals obtained from the Holographic Array for Ionospheric/Lightning research system and the Elazig VLF receiver system. The wavelet-based denoising techniques are tested by soft, hard, hyperbolic and nonnegative garrote wavelet thresholding with the threshold selection rule based on Stein's unbiased estimate of risk, the fixed form threshold, the mixed threshold selection rule and the minimax-performance threshold selection rule. The aim of this study is to find out the direct (early/fast) and indirect (lightning-induced electron precipitation) effects of lightning in noisy VLF transmitter signals without discomposing the nature of signal. The appropriate results are obtained by fixed form threshold selection rule with soft thresholding using Symlet wavelet family.

Hobiger, T.; Piester, D.; Baron, P. A correction model of dispersive troposphere delays for the ACES microwave link // RADIO SCIENCE Volume: 48 Issue: 2 Pages: 131-142 Published: MAR-APR 2013

The Atomic Clock Ensemble in Space (ACES) will be a future ESA experiment which utilizes ultra-stable clocks on-board the International Space Station (ISS). This mission is expected to perform tests of fundamental physics (relativity, possible drift of fundamental constants with time) and at the same time allows to compare the ACES time reference with respect to ground stations by using a novel microwave link concept. However, uncorrected dispersive troposphere delays pose the risk of degrading the performance of this microwave link over longer integration periods. Thus, a semi-empirical correction model has been developed which is only based on input from meteorologic sensors at the ground stations. The proposed model has been tested with simulated ISS overflights at different potential ACES ground station sites, and it could be demonstrated that this model is capable to remove biases and elevation dependent features caused by the dispersive troposphere delay difference between the uplink and downlink. The model performs well at all sites by reducing the impact on all reasonable averaging time scales by at least 1 order of magnitude. Similar studies like this might be of importance for other time and frequency transfer instruments or future space geodetic instruments.

Karathanassi, Vassilia; Sykas, Dimitris; Topouzelis, Konstanitnos N. Development of a Network-Based Method for Unmixing of Hyperspectral Data // IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING Volume: 50 Issue: 3 Pages: 839-849 Published: MAR 2012

This paper presents a new nonlinear unmixing method. Based on relative distances which imply nonlinearity, the method introduces the "fractional distance" as a key variable that quantifies interactions between pixels and endmembers. Relationships between fractional distances and abundance fractions are built through networks. Because an equal spectral mixture of ground spectral classes present on the surface sensed is likely impossible, the proposed method, due to its mathematical concept, reveals unknown endmembers. Three versions of the method have been developed: the nonconstrained, the sum-to-one, and the fully constrained versions. Evaluation of the method using synthetic and real data showed that the method is robust with clear and interpretable results and provides reliable abundance fractions, particularly the sum-to-one and the fully constrained versions of the method. The new unmixing method has also been compared with the fully constrained least squares method.

Kaya, Gulsen Taskin; Ersoy, Okan K.; Kamasak, Mustafa E. Support Vector Selection and Adaptation for Remote Sensing Classification // IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING Volume: 49 Issue: 6 Pages: 2071-2079 Part: 1 Published: JUN 2011

Classification of nonlinearly separable data by nonlinear support vector machines (SVMs) is often a difficult task, particularly due to the necessity of choosing a convenient kernel type. Moreover, in order to get the optimum classification performance with the nonlinear SVM, a kernel and its parameters should be determined in advance. In this paper, we propose a new classification method called support vector selection and adaptation (SVSA) which is applicable to both linearly and nonlinearly separable data without choosing any kernel type. The method consists of two steps: selection and adaptation. In the selection step, first, the support vectors are obtained by a linear SVM. Then, these support vectors are classified by using the K-nearest neighbor method, and some of them are rejected if they are misclassified. In the adaptation step, the remaining support vectors are iteratively adapted with respect to the training data to generate the reference vectors. Afterward, classification of the test data is carried out by 1-nearest neighbor with the reference vectors. The SVSA method was applied to some synthetic data, multisource Colorado data, post-earthquake remote sensing data, and hyperspectral data. The experimental results showed that the SVSA is competitive with the traditional SVM with both linearly and nonlinearly separable data.

Liu, Ying; Wong, Alexander; Fieguth, Paul Synthesis of Remote Sensing Label Fields Using a Tree-Structured Hierarchical Model // IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING Volume: 49 Issue: 6 Pages: 2060-2070 Part: 1 Published: JUN 2011

The systematic evaluation of synthetic aperture radar (SAR) data analysis tools, such as segmentation and classification algorithms for geographic information systems, is difficult given the unavailability of ground-truth data in most cases. Therefore, testing is typically limited to small sets of pseudo-ground-truth data collected manually by trained experts, or primitive synthetic sets composed of simple geometries. To address this issue, we investigate the potential of employing an alternative approach, which involves the synthesis of SAR data and corresponding label fields from real SAR data for use as a reliable evaluation testbed. Given the scale-dependent nonstationary nature of SAR data, a new modeling approach that combines a resolution-oriented hierarchical method with a region-oriented binary tree structure is introduced to synthesize such complex data in a realistic manner. Experimental results using operational RADARSAT SAR sea-ice data and SIR-C/X-SAR land-mass data show that the proposed hierarchical approach can better model complex nonstationary scale structures than local MRF approaches and existing nonparametric methods, thus making it well suited for synthesizing SAR data and the corresponding label fields for potential use in the systematic evaluation of SAR data analysis tools.

Montopoli, Mario; Di Carlofelice, Alessandro; Tognolatti, Piero; et al. Remote sensing of the Moon's subsurface with multifrequency microwave radiometers: A numerical study // RADIO SCIENCE Volume: 46 Article Number: RS1012 Published: FEB 9 2011

Within the renewed interest in the study of the Moon, in 2006 the European Space Agency approved a feasibility study for the European Student Moon Orbiter (ESMO) mission. In order to accomplish the ESMO mission objectives, a Microwave Radiometric Sounder (MiWaRS) was selected as a possible payload for flight on the ESMO satellite. This work summarizes the results of a numerical analysis of MiWaRS sounding capabilities. An (inhomogeneous) multilayer model of the microwave emission from the Moon's subsurface is presented, focusing the attention on the Moon's morphological, thermal, and dielectric properties. These properties have been determined and parameterized after a thorough investigation of available measurements and models. To this end, a radiative transfer numerical model, neglecting volume scattering, is coupled with a nonlinear thermal equation to simulate the microwave emission of the Moon's subsurface. Numerical simulations between L and Ka bands are performed to investigate the capability of MiWaRS to sound the characteristics of the Moon's regolith subsurface and detect the presence of rocks and ice under the near-surface regolith layer. Under these forward model assumptions, results show that the Moon's brightness temperature response allows the detection of discontinuities within regolith media down to 2 and 5 m depth when channels at 3 and 1 GHz are used, respectively. Lunar near-surface temperature may be also estimated within an accuracy less than a few kelvins. The discrimination of ice from rock by MiWaRS is hardly practicable and is limited to the presence of ice in the upper layers (with a depth less than 20 cm) beneath the lunar crust.

Moustakidis, Serafeim; Mallinis, Giorgos; Koutsias, Nikos; et al. SVM-Based Fuzzy Decision Trees for Classification of High Spatial Resolution Remote Sensing Images // IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING Volume: 50 Issue: 1 Pages: 149-169 Published: JAN 2012

A novel fuzzy decision tree is proposed in this paper (the FDT-support vector machine (SVM) classifier), where the node discriminations are implemented via binary SVMs. The tree structure is determined via a class grouping algorithm, which forms the groups of classes to be separated at each internal node, based on the degree of fuzzy confusion between the classes. In addition, effective feature selection is incorporated within the tree building process, selecting suitable feature subsets required for the node discriminations individually. FDT-SVM exhibits a number of attractive merits such as enhanced classification accuracy, interpretable hierarchy, and low model complexity. Furthermore, it provides hierarchical image segmentation and has reasonably low computational and data storage demands. Our approach is tested on two different tasks: natural forest classification using a QuickBird multispectral image and urban classification using hyperspectral data. Exhaustive experimental investigation demonstrates that FDT-SVM is favorably compared with six existing methods, including traditional multiclass SVMs and SVM-based binary hierarchical trees. Comparative analysis is carried out in terms of testing rates, architecture complexity, and computational times required for the operative phase.

Mudaliar, Saba Remote sensing of layered random media using the radiative transfer theory // RADIO SCIENCE Volume: 48 Issue: 5 Pages: 535-546 Published: SEP 2013

The radiative transfer (RT) approach is widely used in remote sensing applications. Although this approach involves approximations, they are often not explicitly stated or explained. The RT approach for random media with nonscattering boundaries has been well studied, and the underlying assumptions are clearly documented. In contrast, our problem has scattering boundaries which are randomly rough. In order to better understand the RT approach to our problem, we adopt a statistical wave approach for modeling multiple scattering in the combined problem of random media and rough surfaces. The geometry of our problem consists of a multilayer discrete random medium with rough boundaries which are planar on the average. The statistical characteristics of the random medium in each layer are independent of each other and independent of the statistics describing the rough interfaces. Using the Green's functions of the problem without the volumetric fluctuations, we represent our problem as a system of integral equations. Employing the T-matrix description, we first average with respect to volumetric fluctuations to obtain a system of integral equations. We next average with respect to surface fluctuations, apply the weak surface correlation approximation, and arrive at a closed system of integral equations for the first and second moments of the electric fields. We use the Wigner transforms to relate the coherence functions to radiant intensities. On applying the quasi-uniform field approximation, we hence arrive at a system of equations identical to those used in the RT approach. In this process, we find that there are more conditions involved in the RT approach to our problem than widely believed to be sufficient. The important additional conditions are the following: (a) the thickness of layers are larger than the mean free path of the layer medium, and (b) the character of interface roughness is such that weak surface correlation approximation is applicable.

Rivas, Maria Belmonte; Stoffelen, Ad New Bayesian Algorithm for Sea Ice Detection With QuikSCAT // IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING Volume: 49 Issue: 6 Pages: 1894-1901 Part: 1 Published: JUN 2011

The authors propose a new sea ice detection method for a rotating Ku-band scatterometer with dual-polarization capability, such as SeaWinds on the Quick Scatterometer (QuikSCAT), based on probabilistic distances to ocean wind and sea ice geophysical model functions (GMFs) and evaluate its performance against other active and passive microwave algorithms. All the methods yield similar results during the sea ice growth season but show substantial differences during the spring and summer months. A detailed comparison based on high-resolution synthetic aperture radar and optical imagery shows that major discrepancies relate to newly formed, low-concentration, and water-saturated sea ice species. The new GMF-based algorithm for sea ice detection with QuikSCAT improves on the misclassification scores that affect other algorithms and provides daily sea ice masks at a 25-km resolution for use in ground processors that require the effective removal of sea ice contaminated pixels all year round.

Sellitto, Pasquale; Del Frate, Fabio; Solimini, Domenico; et al. Tropospheric Ozone Column Retrieval From ESA-Envisat SCIAMACHY Nadir UV/VIS Radiance Measurements by Means of a Neural Network Algorithm // IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING Volume: 50 Issue: 3 Pages: 998-1011 Published: MAR 2012

Spaceborne measurements may significantly support monitoring the concentration of atmospheric constituents affecting air quality, such as ozone. However, retrieving tropospheric ozone concentration information from nadir satellite data is an arduous task, given the weak sensitivity of the earth's radiance to ozone variations in the lower part of the atmosphere. We propose a new methodology, based on neural networks (NN), for retrieving the tropospheric ozone column from SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIA-MACHY) nadir UV/VIS measurements. The design of the NN algorithm is based on an analysis of the information content of measurements in both UV and VIS bands, carried out by a combined radiative transfer model and NN extended pruning procedure. The NN was trained and tested with simulated data and with matching World Ozone and Ultraviolet radiation Data Centre ozonesonde data sets and validated by independent data taken over two test sites. A significant improvement of the retrieval capabilities is observed when VIS wavelengths are included into the input vector. Finally, an example of tropospheric ozone map generated automatically by the methodology at a continental scale is provided and critically discussed.

Tebaldini, Stefano; Rocca, Fabio Multibaseline Polarimetric SAR Tomography of a Boreal Forest at P- and L-Bands // IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING Volume: 50 Issue: 1 Pages: 232-246 Published: JAN 2012

Longer wavelength synthetic aperture radars (SARs) are precious in the remote sensing of forested areas, being sensitive to contributions from the whole vegetation layer and from the ground below. The electromagnetic properties of such contributions are retrieved from multipolarimetric acquisitions, whereas their vertical structure is retrieved from multibaseline acquisitions through tomographic imaging. Combining baseline and polarization diversity provides most information, allowing the decomposition of the SAR signal into ground-and volume-only contributions. A formal treatment of this problem is provided with the algebraic synthesis technique, which extends the concepts of PolInSAR. The decomposition, however, is shown to be ambiguous in that different solutions are equally consistent with the data. The main goal of this paper is to discuss this topic in light of the experimental results from a tomographic and polarimetric analysis of the boreal forest within the Krycklan River catchment, Northern Sweden, investigated at P-and L-bands during the ESA campaign BioSAR 2008. Different solutions to the decomposition problem will be discussed by examining the corresponding vertical structures accessible through tomographic techniques. Elements are shown supporting the idea that ground-volume interactions play a nonnegligible role at P-band, and a solution is proposed to isolate contributions from direct volume backscattering. The retrieval of forest top height is discussed as well, leading to the conclusion that such parameter is robust against erroneous choices in the identification of volume-only contributions, thus corroborating the PolInSAR approach for the analysis of single-baseline data.

Wang, Wen-Qin Near-Space Vehicle-Borne SAR With Reflector Antenna for High-Resolution and Wide-Swath Remote Sensing // IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING Volume: 50 Issue: 2 Pages: 338-348 Published: FEB 2012

Near-space is recognized as the atmospheric region from 20 to 100 km above the Earth's surface. Near-space vehicles offer several advantages compared to low earth orbit satellites and airplanes because near-space vehicles are not constrained by orbital mechanics and fuel consumption. These advantages provide potential for future remote sensing applications, but little related work has been published. This paper explains what near-space is and how it should be exploited for remote sensing applications. A near-space vehicle-borne synthetic aperture radar (SAR) with reflector antenna and digital beamforming on receive is proposed for high-resolution and wide-swath (HRWS) remote sensing. The system configuration, signal model, imaging scheme, system performance, and nadir echo suppression are investigated. An example system is conceptually designed, along with its system performance analysis. It is shown that the near-space vehicle-borne SAR with reflector antenna can operate with high flexibility and reconfigurability, thus enabling a satisfactory HRWS remote sensing performance.

Zhang, Lefei; Zhang, Liangpei; Tao, Dacheng; et al. On Combining Multiple Features for Hyperspectral Remote Sensing Image Classification // IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING Volume: 50 Issue: 3 Pages: 879-893 Published: MAR 2012

In hyperspectral remote sensing image classification, multiple features, e. g., spectral, texture, and shape features, are employed to represent pixels from different perspectives. It has been widely acknowledged that properly combining multiple features always results in good classification performance. In this paper, we introduce the patch alignment framework to linearly combine multiple features in the optimal way and obtain a unified low-dimensional representation of these multiple features for subsequent classification. Each feature has its particular contribution to the unified representation determined by simultaneously optimizing the weights in the objective function. This scheme considers the specific statistical properties of each feature to achieve a physically meaningful unified low-dimensional representation of multiple features. Experiments on the classification of the hyperspectral digital imagery collection experiment and reflective optics system imaging spectrometer hyperspectral data sets suggest that this scheme is effective.

Zhao, Xiao-Feng; Huang, Si-Xun; Du, Hua-Dong Theoretical analysis and numerical experiments of variational adjoint approach for refractivity estimation // RADIO SCIENCE Volume: 46 Article Number: RS1006 Published: JAN 28 2011

This paper puts forward possibilities of refractive index profile retrieval using field measurements at an array of radio receivers in terms of variational adjoint approach. The derivation of the adjoint model begins with the parabolic wave equation for a smooth, perfectly conducting surface and horizontal polarization conditions. To deal with the ill-posed difficulties of the inversion, the regularization ideas are introduced into the establishment of the cost function. Based on steepest descent iterations, the optimal value of refractivity could be retrieved quickly at each point over height. Numerical experiments demonstrate that the method works well for low-distance signals, while it is not accurate enough for long-distance propagations. Through curve fitting processing, however, giving a good initial refractivity profile could generally improve the inversions.

Zhong, Yanfei; Zhang, Liangpei An Adaptive Artificial Immune Network for Supervised Classification of Multi-/Hyperspectral Remote Sensing Imagery // IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING Volume: 50 Issue: 3 Pages: 894-909 Published: MAR 2012

The artificial immune network (AIN), a computational intelligence model based on artificial immune systems inspired by the vertebrate immune system, has been widely utilized for pattern recognition and data analysis. However, due to the inherent complexity of current AIN models, their application to multi-/hyperspectral remote sensing image classification has been severely restricted. This paper presents a novel supervised AIN-namely, the artificial antibody network (ABNet), based on immune network theory-aimed at performing multi-/hyperspectral image classification. To construct the ABNet, the artificial antibody population (AB) model was utilized. AB is the set of antibodies where each antibody (ab) has two attributes-its center vector and recognizing radius-thus each ab can recognize all antigens within its recognizing radius. In contrast to the traditional AIN model, ABNet can adaptively obtain these two parameters by evolving the antigens without relying on user-defined parameters in the training step. During the process of training, to enlarge the recognizing range, the immune operators (such as clone, mutation, and selection) were used to enhance the AB model to find better antibody in the feature space, which may recognize as much antigen as possible. After the training process, the trained ABNet was utilized to classify the remote sensing image, exhibiting superior learning abilities. Three experiments with different types of images were performed to evaluate the performance of the proposed algorithm in comparison to other supervised classification algorithms: minimum distance, Gaussian maximum likelihood, back-propagation neural network, and our previously developed artificial immune classifiers-resource-limited classification of remote sensing image and multiple-valued immune network classifier. The experimental results demonstrate that ABNet has remarkable recognizing accuracy and ability to provide effective classification for multi-/hyperspectral remote sensing imagery, superior to other methods.

Аржанников С.Г., Аржанникова А.В. ПОЗДНЕЧЕТВЕРТИЧНАЯ ГЕОДИНАМИКА ХИРГИСНУРСКОЙ ВПАДИНЫ И ЕЕ ГОРНОГО ОБРАМЛЕНИЯ (ЗАПАДНАЯ МОНГОЛИЯ) // Геология и геофизика. - 2011, № 2 (52). - С. 276-288.

Район исследований охватывает центральную часть Котловины Больших Озер (Западная Монголия). Характерной особенностью этой территории является широкое распространение следов существования крупных озер в недалеком прошлом. Они сохранились в виде береговых валов, террасовых комплексов и крупных песчаных массивов. По материалам дистанционного зондирования и полевого изучения получены данные, свидетельствующие об активных тектонических процессах в пределах Котловины Больших Озер. Выявлены многочисленные палеосейсмогенные деформации, расположенные по периферии и в акватории палеоозера Хиргис-Нур, площадь которого в шесть раз превышала площадь одноименного современного озера. Абсолютные высоты максимальной фазы палеоозера составляют 1143 м, что выше отметки береговой линии современного озера на 115 м. Установлено, что в результате тектонических движений часть бывшей акватории палеоозера вместе с береговыми валами были подняты до абсолютной высоты 1175 м. Высказано предположение о формировании палеоцунами в результате схода оползней в акваторию палеоозера Хиргис-Нур.

Аш Е.В. АССОЦИАЦИЯ «ЗЕМЛЯ ИЗ КОСМОСА»: ПРОФЕССИОНАЛЬНОЕ СООБЩЕСТВО КАК ДВИГАТЕЛЬ ОТЕЧЕСТВЕННОЙ ОТРАСЛИ ДЗЗ // Земля из космоса: наиболее эффективные решения. - 2011, № 11. - С. 126-131.

Отечественный рынок дистанционного зондирования Земли на пути своего развития сталкивается с препятствиями различного характера. В 2010 г. основными участниками российского рынка ДЗЗ была создана ассоциация поставщиков и пользователей данных космической съемки «Земля из космоса». Основная цель объединения - содействие развитию технологий получения, обработки, распространения и использования материалов космической съемки Земли путем участия в проведении правовых и структурных преобразований в области ДЗЗ.


Введено понятие «нормализованный дифференциальный объектный индекс», обобщающее элементы объективно существующего множества нормализованных дифференциальных индексов, применяемых в мультиспектральном дистанционном зондировании. Предложена единая эквивалентная форма представления нормализованных объектных дифференциальных индексов. Показано существование интегрального ограничительного условия для переменных предложенной эквивалентной формы нормализованного дифференциального индекса.


Рассмотрены подходы к сжатию с потерями одноканальных изображений дистанционного зондирования (ДЗ) Земли, которые искажены сигнально-зависимыми помехами. Анализ проведен для кодеров на основе дискретного косинусного преобразования и вейвлет-преобразования. Сравнение эффективности сжатия выполнено в соответствии с несколькими критериями как при прямом применении кодеров к изображениям, так и при использовании вариационно-стабилизирующего преобразования. Показано, что различия в эффективности несущественны, но применение вариационно-стабилизирующих преобразований обеспечивает определенные преимущества для применения трехмерных кодеров для сжатия многоканальных данных ДЗ. Предложены процедуры автоматического сжатия в окрестности оптимальной рабочей точки. Проанализированы их достоинства и недостатки.


Оценка льдистости мерзлых грунтов в районах сплошного распространения многолетнемерзлых пород проведена на основе разновременных данных видимого и инфракрасного (ИК) теплового диапазона длин волн в летнее время съемок. Методика основана на выявлении различий в темпах роста сезонной радиационной температуры земной поверхности участков с различной льдистостью. Расчет сезонной радиационной температуры поверхности, соответствующей моментам суточной инверсии, проводился с учетом параметра, характеризующего тепловую инерцию приповерхностного слоя суточных колебаний температуры на основе пар дневных и ночных измерений со спутника NOAA. На примере территории Харасавэйского и Крузенштерновского газоконденсатных месторождений Западного Ямала показано, что различия грунтов по льдистости более достоверно могут быть оценены в границах однотипных природных комплексов. Аномально низкие значения разности сезонных радиационных температур поверхности, рассчитанных по данным съемки в августе и июне в пределах морских террас, предположительно, связаны с залегающими близко к поверхности пластовыми льдами. Разделение участков высокой льдистости мерзлых грунтов и участков высокой влажности талого слоя, характеризуемых одинаковыми разностями сезонных радиационных температур поверхности, предлагается проводить с учетом параметра, характеризующего тепловую инерцию слоя суточных колебаний температуры.

Лагуткин В.Н., Репин В.Г., Старостенко А.М. КОМПЛЕКС АЛГОРИТМОВ ВЫДЕЛЕНИЯ ДИНАМИЧЕСКИХ ОБЪЕКТОВ НА МНОГОСПЕКТРАЛЬНЫХ ВИДЕОИЗОБРАЖЕНИЯХ, ПОЛУЧАЕМЫХ ПРИ ДИСТАНЦИОННОМ ЗОНДИРОВАНИИ ЗЕМЛИ // Успехи современной радиоэлектроники. Зарубежная радиоэлектроника. - 2011, № 8. - С. 57-66.

На основе теории адаптации информационных систем разработан алгоритм выделения неточечных динамически изменяющихся объектов при обработке многоспектральных видеопоследовательностей, получаемых при дистанционном зондировании Земли.

Лазарев Е.Н., Баскакова М.А., Гусакова Е.Н., Жуков Д.М., Коханов А.А. СРАВНИТЕЛЬНЫЙ АНАЛИЗ ДАННЫХ АКТИВНОГО ДИСТАНЦИОННОГО ЗОНДИРОВАНИЯ ДЛЯ КАРТОГРАФИРОВАНИЯ ФОРМ РЕЛЬЕФА ПЛАНЕТ И СПУТНИКОВ СОЛНЕЧНОЙ СИСТЕМЫ // Известия высших учебных заведений. Геодезия и аэрофотосъемка. - 2014, № 2. - С. 84-92.

Выполнен анализ данных дистанционного зондирования (ДДЗ), которые используются в качестве исходных источников для моделирования рельефа планет и спутников земной группы. Для целей данной работы анализировались только результаты активного зондирования - радарная съемка (SAR) и лазерная альтиметрия (MLA, LOLA и MOLA), которые имеют глобальное покрытие поверхности исследуемых тел. Рассматриваются особенности съемочной аппаратуры и приведены характеристики цифровых моделей рельефа (ЦМР). Среди форм рельефа, названных одинаковыми родовыми терминами, выделены семь типов форм, встречающихся на Меркурии, Венере, Марсе и Луне - уступы (rupes), борозды (fossae/rimae), долины (valles), равнины/моря (planitiae/maria), гряды (dorsa), кратеры (craters) и горы (montes). Для этих типов форм рельефа приведены некоторые морфометрические и морфологические особенности, характерные для каждого небесного тела.


Цель данного исследования - изучение эффективности применения нейронных сетей (НС) в задачах классификации данных дистанционного зондирования Земли (ДЗЗ). В работе приводится описание традиционных методов распознавания, дается характеристика нейросетевого подхода. Представляется ретроспектива применения НС для решения различных задач по обработке данных ДЗЗ. Помимо этого, в данной работе приводятся результаты исследования применимости НС на примере классификации реальных данных ДЗЗ, характеризующих территорию высокой степени гетерогенности. Точность распознавания типов растительного покрова, полученная с помощью нейросетевого классификатора, составила 91%, что превосходит показатели других методов: максимального правдоподобия (82%), расстояния Махаланобиса (78%), минимальных расстояний (64%). Результаты исследования показывают, что присущий гетерогенным данным закон нормального распределения не всегда обеспечивает статистическим алгоритмам преимущества в точности классификации. Предложен формат нейросетевого классификатора для обработки данных ДЗЗ, характеризующихся высокой степенью гетерогенности.

Соломонов С.В., Гайкович К.П., Кропоткина Е.П., Розанов С.Б., Лукин А.Н., Игнатьев А.Н. ДИСТАНЦИОННОЕ ЗОНДИРОВАНИЕ АТМОСФЕРНОГО ОЗОНА НА МИЛЛИМЕТРОВЫХ ВОЛНАХ // Известия высших учебных заведений. Радиофизика. - 2011, № 2 (54). - С. 113-122.

Представлены новые результаты дистанционного зондирования вертикального распределения озона на миллиметровых волнах с помощью высокочувствительного спектрорадиометра ФИАН, в состав которого входит новый 96-канальный анализатор спектра АС-96 с улучшенными характеристиками. Регистрируется спектр излучения озона на частоте 142,2 ГГц. Восстановление вертикального профиля озона выполнялось с использованием усовершенствованного алгоритма, основанного на методах Тихонова и статистической регуляризации. Рассмотрены особенности высотно-временного распределения озона, отражающего процессы в озоносфере над умеренными широтами. Показаны изменения вертикального распределения озона во время сильного стратосферного потепления в январе 2009 года. Сделан вывод о необходимости создания отечественной наземной сети мониторинга пространственного распределения озона на миллиметровых волнах.

Старостенко А.М., Лагуткин В.Н. ВЫБОР ОПТИМАЛЬНЫХ ДИАПАЗОНОВ ДЛЯ МНОГОСПЕКТРАЛЬНЫХ НАБЛЮДЕНИЙ ОБЪЕКТОВ ПРИ ДИСТАНЦИОННОМ ЗОНДИРОВАНИИ ЗЕМЛИ // Успехи современной радиоэлектроники. Зарубежная радиоэлектроника. - 2011, № 8. - С. 31-35.

Разработана методика оптимального выбора диапазонов и определения их параметров для наблюдения протяженных объектов с низким уровнем сигнала на многоспектральных изображениях, получаемых при дистанционном зондировании Земли. Критерием оптимизации является максимум вероятности правильного обнаружения при фиксированной вероятности ложной тревоги. Методика учитывает не только соотношения между параметрами сигнала, фона и шума, но и аппаратурные ограничения, возникающие при конструировании аппаратуры наблюдения.


Предложен метод информационной оптимизации для синтеза высокоинформативных изображений дистанционного зондирования с высоким разрешением. Изложен порядок практической реализации предложенного метода.

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