We discuss requirements for the multispectral remote sensing (RS) data utilized in the author's technique for estimating plant species concentration to detect arable land colonization by tree and shrubbery vegetation. The study is carried out using available high-resolution remote sensing data of two arable land plots. The paper considers the influence of resolution, combinations of spectral channels of RS data, as well as the season RS data is acquired on the quality of identification of elementary vegetation classes that form the basis of the plant community – a fallow land. A fallow land represents a piece of arable land that has not been cultivated for a long time. The study was conducted using a technology that is based on image superpixel segmentation. We found out that for determining tree and shrub vegetation, it is preferable to use RS data acquired in autumn, namely, in late September. The combination of red and blue spectral channels turned out to be the best for the analysis of tree-shrub vegetation against the background of grassy plant communities, and the presence of a near-infrared channel is necessary to range the various grassy plant communities in different classes. RS data with a spatial resolution of 2.5 m can be used to define tree-shrub plant communities with a high closeness of crowns (90 % or more), but cannot be used to classify isolated trees. Trees and shrubs (with a height of 8 m) can be classified in images with a spatial resolution of 0.8 m. An increase in spatial resolution does not improve the quality of the classification. The highest accuracies achieved for the land areas studied are 90 % and 83 %. Therefore, the suggested technology can be used in arable land expertise.
The protective forest belt system of Samara region consists of several components created from the late 19th to the early 20th century, in the middle of the 20th century, in the 60-70s of the 20 th century, and more recent plantings. In the forest-steppe and steppe regions with a high level of agricultural transformations, the natural biological equilibrium of ecosystems is significantly disturbed. The protective forest belts play an important role in natural and anthropogenic landscapes conservation in Samara region. Because of numerous dispersed forest belt distribution throughout the Samara region territory, their different ownership and the lack of sufficient funds for their monitoring, it is difficult to organize belt state monitoring on the ground. The use of space imagery, which is processed during verification using data obtained from reference polygons, can help to overcome this situation. The peculiarity of forest belts as an extended object of relatively small width actualizes the task of developing the methods for their condition assessing. In this paper, some results of this work are analyzed for reference areas of field shelterbelts and roadside forest belts of the Samara region.
The districts of Samara region are characterized by specific combination of orographic structure, hydrological regimes, soil and vegetation cover features, combined with a high level of anthropogenic pressure. The revealing of negative changes associated with the anthropogenic exploitation regimes incliding salinization and waterlogging after irrigation, soil erosion, transformation of non-cultivated fields into deposits, overgrowing of old quarries etc. seems to be a difficult task when carrying out by ground-based studies related to a large-scale land resources of the region. The use of remote sensing data, resulted by a time series of images for the same territory, opens up wide opportunities, on condition that the regional ground-based standardization is carried out.
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