КФУ. Карточка публикации. Automated detection of illegal nonmetallic minerals mining places according to Sentinel-2 data

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AUTOMATED DETECTION OF ILLEGAL NONMETALLIC MINERALS MINING PLACES ACCORDING TO SENTINEL-2 DATA

Форма представления

Статьи в зарубежных журналах и сборниках

Год публикации

2021

Язык

английский

Авторы, сотрудники КФУ

Ахметзянова Лейсан Габбасовна, автор

Мухарамова Светлана Саясовна, автор

Усманов Булат Мансурович, автор

Другие авторы

Курицын Иван Николаевич, автор

Библиографическое описание на языке оригинала

Bulat M. Usmanov, Liubov S. Isakova, Svetlana S. Mukharamova, Leisan G. Akhmetzyanova, Ivan N. Kuritsin, «Automated detection of illegal nonmetallic minerals mining places according to Sentinel-2 data,« Proc. SPIE 11863, Earth Resources and Environmental Remote Sensing/GIS Applications XII, 118631C (12 September 2021)

Аннотация

Currently, the problem of illegal mining is still acute. Such illegal use of natural resources harms the environment and leads to irrational use of mineral resources. Modern methods with the use of remote sensing technologies will effectively detect such law violations. In the current study, a method for automatically detection of non-metallic mineral extraction sites based on remote sensing data analysis has been developed. The study uses Sentinel-2 satellite images with spatial resolution 10 m and 20 m and considers four types of minerals: sand, clay, carbonate rocks and sand gravel mix. The spectral indices help to determine the specific quantitative characteristics of the mineral resources. The result is probability maps with mineral resourses characteristics in each pixel. In order to determine to which of known classes relates the point, you need to find the covariance matrices for all classes and take the class with the smallest Mahalanobis distance to the point. Based on the obtained probability maps, an analysis of the applicability of the selected spectral indices was performed, as well as a visual assessment of the quality of interpretation. For each spectral channel and index, two frequency histograms were created to determine how different the channels values and spectral indices on the entire scene and at the reference objects. Each object found by the program was checked for it presence on the studied territory. The developed system is a modern, secure, non-contact method for the rational land use monitoring and natural resources extracted by open-pit mining study.

Ключевые слова

remote sensing, mineral resourses, illegal mining, spectral indices, R, natural resources management

Название журнала

Proceedings of SPIE - The International Society for Optical Engineering

URL

https://www.spiedigitallibrary.org/conference-proceedings-of-spie/11863/118631C/Automated-detection-of-illegal-nonmetallic-minerals-mining-places-according-to/10.1117/12.2600315.short

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https://repository.kpfu.ru/?p_id=259953

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Полная запись метаданных

Поле DC	Значение	Язык
dc.contributor.author	Ахметзянова Лейсан Габбасовна	ru_RU
dc.contributor.author	Мухарамова Светлана Саясовна	ru_RU
dc.contributor.author	Усманов Булат Мансурович	ru_RU
dc.contributor.author	Курицын Иван Николаевич	ru_RU
dc.date.accessioned	2021-01-01T00:00:00Z	ru_RU
dc.date.available	2021-01-01T00:00:00Z	ru_RU
dc.date.issued	2021	ru_RU
dc.identifier.citation	Bulat M. Usmanov, Liubov S. Isakova, Svetlana S. Mukharamova, Leisan G. Akhmetzyanova, Ivan N. Kuritsin, «Automated detection of illegal nonmetallic minerals mining places according to Sentinel-2 data,« Proc. SPIE 11863, Earth Resources and Environmental Remote Sensing/GIS Applications XII, 118631C (12 September 2021)	ru_RU
dc.identifier.uri	https://repository.kpfu.ru/?p_id=259953	ru_RU
dc.description.abstract	Proceedings of SPIE - The International Society for Optical Engineering	ru_RU
dc.description.abstract	Currently, the problem of illegal mining is still acute. Such illegal use of natural resources harms the environment and leads to irrational use of mineral resources. Modern methods with the use of remote sensing technologies will effectively detect such law violations. In the current study, a method for automatically detection of non-metallic mineral extraction sites based on remote sensing data analysis has been developed. The study uses Sentinel-2 satellite images with spatial resolution 10 m and 20 m and considers four types of minerals: sand, clay, carbonate rocks and sand gravel mix. The spectral indices help to determine the specific quantitative characteristics of the mineral resources. The result is probability maps with mineral resourses characteristics in each pixel. In order to determine to which of known classes relates the point, you need to find the covariance matrices for all classes and take the class with the smallest Mahalanobis distance to the point. Based on the obtained probability maps, an analysis of the applicability of the selected spectral indices was performed, as well as a visual assessment of the quality of interpretation. For each spectral channel and index, two frequency histograms were created to determine how different the channels values and spectral indices on the entire scene and at the reference objects. Each object found by the program was checked for it presence on the studied territory. The developed system is a modern, secure, non-contact method for the rational land use monitoring and natural resources extracted by open-pit mining study.	ru_RU
dc.language.iso	ru	ru_RU
dc.subject	remote sensing	ru_RU
dc.subject	mineral resourses	ru_RU
dc.subject	illegal mining	ru_RU
dc.subject	spectral indices	ru_RU
dc.subject	R	ru_RU
dc.subject	natural resources management	ru_RU
dc.title	Automated detection of illegal nonmetallic minerals mining places according to Sentinel-2 data	ru_RU
dc.type	Статьи в зарубежных журналах и сборниках	ru_RU