Local Feature Detectors Performance Analysis on Digital Image

Smelyakov, Kirill; Tovchyrechko, Dariia; Рубан, Ігор; Chupryna, Anastasiya; Ponomarenko, Oleksandr

doi:10.1109/picst47496.2019.9061331

Cited by 11 publications

(2 citation statements)

References 8 publications

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“…Various acquisition methods and algorithms for processing original images help accurately determine the qualitative and quantitative characteristics of the state of different territories of our planet. Works [5,6] described the method of obtaining data based on correlation theory, which makes it possible to effectively recognize and classify them. It is shown that the construction of a suitable classifier could significantly improve the efficiency of further image processing operations: localization, recognition, search, and tracking of covered by fires and forecasting the future occurrence of this natural disaster with further consequences was not considered.…”

Section: Literature Review and Problem Statementmentioning

confidence: 99%

“…Thus, our review of literary sources [5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21] revealed that they lack analysis based on a mathematical apparatus that detects the influence of harmful factors, and it is not specified where and how the information obtained and processed is stored. The issues of efficiency in determining forest areas that were affected by forest fires, with their further classification, assessment of burned areas, and analysis of relationships between parameters that negatively affect the tree stand remain unsolved.…”

Section: Literature Review and Problem Statementmentioning

confidence: 99%

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Development of the information system for monitoring time changes in forest plantations based on the analysis of space images

Svynchuk

Bandurka

Барабаш

et al. 2022

EEJET

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This study considers the issue of assessing the time changes in forest plantations and constructing an algorithmic and software system for monitoring these changes. Modern systems that study vegetation changes do not have the necessary functionality and do not cover the range of observations discussed in this paper. Existing research methods are intended only to record changes that occur in forest ecosystems and take into consideration the peculiarities of a certain natural zone, which limits their use. At the same time, it should be understood that the requirements for modern systems should include additional components that could make the system universal and mobile. A comparative analysis of satellite images acquired from remote sensing by the Landsat 8 satellite system has been carried out to determine the areas affected by forest fires. During the classification, spectral analysis was used, and an index of fires was determined to indicate the burned areas. To analyze the changes that occur in forests due to fires, correlation-regression analysis is used. It has been proven that the area of sanitary felling after fires and the area of forest land traversed by fires demonstrated the greatest interconnection. The extrapolation and forecasting were carried out using a regression data model, the effectiveness of which is confirmed by a coefficient of determination of 0.87. The dependences built make it possible to conclude that by 2030 the number of forest fires will increase while the area of burned forests will not decrease. The developed mobile application could be popular among a significant group of users to monitor fire events. The practical result is the introduction of the built system, which makes it possible to quickly monitor forest plantations after fires and assess the areas that were affected.

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Section: Literature Review and Problem Statementmentioning

confidence: 99%