KFU. Card publication. Automated detection of illegal nonmetallic minerals mining places according to Sentinel-2 data

KAZAN
FEDERAL UNIVERSITY

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

Form of presentation

Articles in international journals and collections

Year of publication

2021

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Authors, employees of KFU

Akhmetzyanova Leysan Gabbasovna, author

Mukharamova Svetlana Sayasovna, author

Usmanov Bulat Mansurovich, author

Other authors

Kuricyn Ivan Nikolaevich, author

Bibliographic description in the original language

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)

Annotation

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.

Keywords

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

The name of the journal

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

Please use this ID to quote from or refer to the card

https://repository.kpfu.ru/eng/?p_id=259953&p_lang=2

Resource files

File name	Size (MB)	Format
118631C.pdf	0,99	pdf	show / download

Full metadata record

Field DC	Value	Language
dc.contributor.author	Akhmetzyanova Leysan Gabbasovna	ru_RU
dc.contributor.author	Mukharamova Svetlana Sayasovna	ru_RU
dc.contributor.author	Usmanov Bulat Mansurovich	ru_RU
dc.contributor.author	Kuricyn Ivan Nikolaevich	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/eng/?p_id=259953&p_lang=2	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	Articles in international journals and collections	ru_RU