Method for automating estimation of surface indices and their time changes using space images. application of the method in assessing the environment state in the vicinity of solid waste landfills

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.