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The relevance of the work due to the simplification of the procedures for receiving and processing satellite images through processing automation and calculation of various indices of the underlying surface, and their temporal changes. The proposed method allows a high speed, and on a large scale to detect signs of soil degradation, in particular, the size of the waste disposal facilities, the multiple spatial resolution images, calculating respective indices underlying surface. The main drawback of the existing detection methods of waste disposal sites is that their search and discovery, environmental assessment carried out by ground, «manual» methods. All this is primarily self identifying objects gives low productivity in landfills monitoring. As a result of the automation of security detection method of waste disposal facilities can be significantly improved protection of the territory from the impact of negative factors. These factors, inter alia, debris environmental factor, in terms of space images may be expressed in a variety of indices of the underlying surface. The main aim of the study is to develop a method for obtaining automatically the underlying surface indices and time series using satellite images linked to UTM geographical projection and their metadata. The methods used in the study: methods of getting cloud masks (threshold filtering method) and regression analysis (method of standard deviation) for temporal processing. The results. The paper introduces the algorithm of automatic data processing and describes the main steps of its operation. The authors define the model of conversion parameters of underlying surface indices change when adding new values ??of the spectral brightness coefficients or deleting the previous ones. The algorithm operation is shown by the example of calculation of NDVI time-series of the given observation area and their application to the analyze the processing data, in particular, the NDVI images are automatically calculated in neighborhood landfill of Torbeevo Lyubertsky district for 2003-2011. The paper illustrates structural changes in soil bio-productivity within four municipal landfills of Zheleznodorozhny urban district in Moscow region: Kuchino, Savvino, Licyi Gory, Nekrasovka.

For work materials used multispectral satellite imagery Landsat (7 channels), medium spatial resolution (14,25-90 m) and a digital elevation model (data SRTM).For interpretation of satellite images and especially their infrared and thermal channels allocated buried paleovalleys pre-paleogene age. Their total length is 228 km. By manifestation of the content of remote sensing paleovalleys distinctly divided into two types, long ribbon-like read in materials and space survey highlights a network of small lakes. By the nature of the relationship established that the second type of river paleovalleys flogs first. On this basis, proposed to allocate two uneven river paleosystem. The most ancient paleovalleys first type can presumably be attributed to karst erosion, blurry chalk and carbon deposits foundation. Paleovalleys may include significant groundwater resources as drinking and industrial purposes. Also we can control the position paleovalleys zinc and bauxite mineralization area and alluvial deposits include uranium mineralization valleys infiltration type and placer gold. Direction paleovalleys choppy, but in general they have a north-east orientation, which is controlled by tectonic zones of the foundation. These zones are defined as the burial place themselves paleovalleys and position of karst cavities in areas interfacing with other structures orientation. The association of mineralization to the caverns in the beds paleovalleys could generally present conditions of formation of mineralization and carry it to the «Niagara» type. The term is obviously best reflects the mechanism of formation of these ores. [ABSTRACT FROM AUTHOR]

Two methods of determining changes of objects (structures) using remote sensing data obtained in different times are considered in this article. The comparison of the percentage of destroyed buildings as a consequence of the earthquake in L'Aquila city (Italy) was implemented. For comparison two ways of data collection were used: obtaining data by the digitalization of objects before and after the disaster (using MapInfo software) and by automatic image classification using a special module Delta Cue (Erdas software). [ABSTRACT FROM AUTHOR]

Space information, or information obtained by means of space remote sensing, is widely and effectively used by many countries to solve a lot of scientific, technical and applied problems. Most manufacturers of space remote sensing systems declared the high resolution values of their systems. However, these values are computed theoretically, without considering the various factors affected them. To determine the real resolution of the system, we have considered mathematical modeling which describes the influence of different factors on the satellite images resolution. Some of these factors are: atmosphere turbulence, image shift, residual defocusing, and diffraction. One of the most important characteristic of the images resolution is the modulation transfer function (MTF) which allows the estimation of different factors affected on the image resolution. The modulation transfer function (MTF) is a fundamental tool for assessing the performance of imaging systems. Various authors [Zhang et al. 2012, Hwang et al. 2008, Ryan et al. 2003] investigate different MTF assessment methods of high resolution satellite images: a slant-edge method, a knife-edge method, a sine wave method and a grill pattern. We propose a generalized approach for MTF assessment based on theoretical assumptions which allows to determine the influence of different factors. A comparative analysis of the modulation transfer function(s) for different space imaging systems shows that the image resolution depends mainly on the atmosphere turbulence and size of a sensor element. Additionally, we established that atmospheric turbulence significantly reduces the transmitting possibility of images. The parameters which describe the influence of turbulence required additional studies. The main goal of our researches is to show that real spatial image(s) resolution is much "inferior" than the value provided by the manufacturers of space remote sensing systems. [ABSTRACT FROM AUTHOR]