While constructing a mathematical model of the space observation system for information processing of the data of monitoring the territories on the presence of the waste disposal sites (WDS), we have a stochastic process with a fractal structure. The physical processes of the WDS are formed under the influence of thermal, chemical, etc. factors. There are different methods and approaches for describing the scattering and radiating surfaces of the objects that make up solid household and industrial waste using single-scale and multi-scale correlation radii. With an increase in the order of multi-scale, the multi-scale of the correlation radius also increases, and this, accordingly, complicates the construction of a mathematical model of a space image. The transition to the fractal presentation of the image allows solving the problem of the space images processing. The paper proposes some algorithm for processing the aerospace images using a field of fractal dimension. The theoretical and experimental studies are being held with respect to improving the results of aerospace image classification results while monitoring for the WDS presence. An assessment of the size of the “window” and the magnitude of the “jump” on the parameters of the fractal dimensions is also made. The purpose of the work is to describe the system synergistic approach of multi-scale selection, which allows overcoming the problems of the image processing. This is due to incomplete knowledge of signals, non-stationarity, non- Markov, noise singularity based on preliminary information about the spatial scales of the detected signals. While working with low-contrast images, the usual signal processing technique (contour-texture, spectral methods) does not adequate. There is a need to apply the theory of fractals in the study of processes occurring on the surface of the WDS through remote sensing. An experiment is carried out using the example of fractals, an image is decoded. The features of fractals are considered.
Remote sensing of the Earth allows to receive information of medium, a high spatial resolution from space vehicles and to conduct hyperspectral measurements. In many cases, waste disposal sites (WDS) is not legal. So, it is very important to use the system for automatic detection such places using satellite images. In this paper, a model of the automated space monitoring system for the presence of waste disposal sites is developed. The proposed system includes the following blocks: a database of WDS; a subsystem for detecting unauthorized WDS; a subsystem for monitoring the design, operation and reclamation rules for existing WDS; a subsystem for estimating the parameters of the WDS and their impact on the environment; a subsystem of satellite monitoring. We propose a method of detecting high-rise buildings landfills, such as municipal dumps and solid waste, according to a radar image (the height of the ground level). For system design, we use the apparatus of discrete orthogonal transformations. The impact of the WDS influence on agricultural crops is analyzed, based on the data of the Earth remote space sensing based on the orthogonal transform. The purpose of the work is the modeling of an automated space monitoring system for the presence of waste disposal facilities using regularization method in the problem of filtering of space images from the noise stored in the archives. As a result, the proposed method demonstrates good accuracy in detection the solid waste disposal site on real satellite images.
In this paper, Haar's generalized wavelet functions are applied to the problem of ecological monitoring by the method of remote sensing of the Earth. We study generalized Haar wavelet series and suggest the use of Tikhonov's regularization method for investigating them for correctness. In the solution of this problem, an important role is played by classes of functions that were introduced and described in detail by I.M. Sobol for studying multidimensional quadrature formulas and it contains functions with rapidly convergent series of wavelet Haar. A theorem on the stability and uniform convergence of the regularized summation function of the generalized wavelet-Haar series of a function from this class with approximate coefficients is proved. The article also examines the problem of using orthogonal transformations in Earth remote sensing technologies for environmental monitoring. Remote sensing of the Earth allows to receive from spacecrafts information of medium, high spatial resolution and to conduct hyperspectral measurements. Spacecrafts have tens or hundreds of spectral channels. To process the images, the device of discrete orthogonal transforms, and namely, wavelet transforms, was used. The aim of the work is to apply the regularization method in one of the problems associated with remote sensing of the Earth and subsequently to process the satellite images through discrete orthogonal transformations, in particular, generalized Haar wavelet transforms. General methods of research. In this paper, Tikhonov's regularization method, the elements of mathematical analysis, the theory of discrete orthogonal transformations, and methods for decoding of satellite images are used. Scientific novelty. The task of processing of archival satellite snapshots (images), in particular, signal filtering, was investigated from the point of view of an incorrectly posed problem. The regularization parameters for discrete orthogonal transformations were determined.
The paper proposes a method for fuzzy interactive enhancement of objects identification in the image which allows identifying hidden or no defined details and objects in the images. The application of the method and its difference from other image enhancement techniques are shown. The paper presents the algorithm and describes the basic processing procedures (sampling, scaling, convolution, contrast). The main processing parameters (increasing and reduction of dimensions, convolutions, brightness, and thresholds contrast) are demonstrated. The results from the applied algorithm are explained on an example related to landfill Kutchino in the Moscow region, on the satellite images with low and high spatial resolution.
This study presents a remote sensing application of using time series Landsat satellite images for monitoring the solid waste disposal site (WDS). We propose a method of detecting high-rise buildings landfills, such as municipal dumps and solid waste, according to a radar image (the height of the ground level). For disposal site detection a variety steps of image processing used (calculation image average level of the earth's surface; filtering thresholds spectral brightness coefficients, the size of the connected components, the nature of reducing the level of height with the distance of the maximum level). The spatial geometric features of waste disposal facilities are analytically expressed by linear and radial characteristics from other objects of the earth surface. As a result, the proposed method demonstrates good accuracy in detection the solid waste disposal site on real satellite images.
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