This study proposes an original method for tree species classification by satellite remote sensing. The method uses multitemporal multispectral (Landsat OLI) and hyperspectral (Resurs-P) data acquired from determined vegetation periods. The method is based on an original database of spectral features taking into account seasonal variations of tree species spectra. Changes in the spectral signatures of forest classes are analyzed and new spectralâtemporal features are created for the classification. Study sites are located in the Czech Republic and northwest (NW) Russia. The differences in spectral reflectance between tree species are shown as statistically significant in the sub-seasons of spring, first half of summer, and main autumn for both study sites. Most of the errors are related to the classification of deciduous species and misclassification of birch as pine (NW Russia site), pine as mixture of pine and spruce, and pine as mixture of spruce and beech (Czech site). Forest species are mapped with accuracy as high as 80% (NW Russia site) and 81% (Czech site). The classification using multitemporal multispectral data has a kappa coefficient 1.7 times higher than does that of classification using a single multispectral image and 1.3 times greater than that of the classification using single hyperspectral images. Potentially, classification accuracy can be improved by the method when applying multitemporal satellite hyperspectral data, such as in using new, near-future products EnMap and/or HyspIRI with high revisit time.
The article considers a service for providing consumers with various levels of information about forest taxing indicators based on the processing of multispectral data recorded by modern domestic remote sensing spacecraft in the optical spectrum range.
This work presents the original software to monitor compliance with the established conditions of the protective zone of transmission lines. Remote sensing data in the visible and infrared spectral ranges are used as input. The software provides the computer-aided creation of thematic digital layers using remote sensing multispectral data. The layers contain spatial and attributive information about violations affecting the safe operation of electric grid facilities. There is a brief description of the methods and algorithms developed to solve the problems of estimation of wood overgrowth along transmission lines and identification of typical objects (landfill, oil-contaminated sediment, soil damage) that are prohibited in the protective zone.
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