Article
Article name	Geoecological Mapping of Buildings in Flood-Prone Areas Shilka and Nerchinsk (Transbaikalia), Using the NDBI Spectral Index and a Neural Network
Authors	Kochev D.. ,
Bibliographic description	Kochev D. V. Geoecological Mapping of Buildings in Flood-Prone Areas Shilka and Nerchinsk (Transbaikalia), Using the NDBI Spectral Index and a Neural Network // Transbaikal State University Journal. 2024. Vol. 30, no. 1. P. 28–39. DOI: 10.2109/2227-9245-2024-30-1-28-39.
Category	Earth and Environmental Sciences
DOI	502/504; 528.88
DOI	10.2109/2227-9245-2024-30-1-28-39
Article type	Original article
Annotation	At all times, the problem of floods has been relevant due to their destructiveness, frequency and poor predictability. The situation is complicated by the fact that floodplains are used for economic, recreational and other activities, thereby exposing the risk of destruction and degradation of any objects and human waste products during floods. Therefore, mapping and spatiotemporal monitoring of flood-prone areas in order to analyze and predict the likely material and economic damage to facilities of economic activity from the threat of floods is an urgent scientific problem that can be solved by geographic information systems using satellite data processed by spectral indices and convolutional neural networks. The object of the study is the flood-prone territories of Shilka and Nerchinsk (Transbaikal Region). The purpose is to assess the accuracy of economically developed territories decryption in flood-prone areas of Shilka and Nerchinsk in order to determine the effective threshold for separation of the studied facilities. Research objectives are as follows: collection and formation of an archive of Earth remote sensing data of the Landsat-8 OLI program; inference of satellite images on a neural network and their use as a reference image; calculation of NDBI spectral indices based on Landsat-8 data; determination of the areas of built-up and economically developed territories in the images; assessment of the accuracy and comparative analysis of the results of the development facilities allocation and economic activity; identification of advantages, disadvantages, applicability limits of the methods used to decrypt buildings and objects of economic activity in flood-prone areas. The accuracy and reliability of the results of the decrypting buildings and objects of economic activity by calculating the NDBI spectral index, the inference of a convolutional neural network according to Landsat 8 OLI data in flood-prone areas of Shilka and Nerchinsk have been evaluated. The most effective methods, parameters and thresholds for decrypting buildings and objects of economic activity have been determined in order to monitor the development of flood-prone areas and control the flood-prone situation.
Key words	decryption, floods, flood-prone areas, spectral indices, remote sensing of the Earth, Landsat-8 OLI, convolutional neural networks, geoinformation analysis, accuracy assessment, kappa
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Full article	Geoecological Mapping of Buildings in Flood-Prone Areas Shilka and Nerchinsk (Transbaikalia), Using the NDBI Spectral Index and a Neural Network