Sources of spatial data in advancing technologies of subsoil use

The difference between the raster and vector data is studied. The basic types of data used in geo-spatial representations are determined. Advantages and disadvantages of the rastertype data storage are identified. The attributes, some key functions and types of the raster data are described. There are many sources of data for describing both space and attributes. The most popular sources of spatial data are: maps, air photos, remote sensing images, sample data of surveys and digitized information. Spatial data can exist in multiple formats and contain more various information rather than simply facts on a specific mineral deposit. There are two types of data in accordance with the storage technology, namely, raster and vector data. Spatial data can be classified as crude data and derived data. As data are being collected from the environment, map-makers use their perception to find patterns and to prepare the data for further mapping. Statistical data are the attributes of spatial objects. All sources of spatial data are formed by different classes of systems. The main difference between the spatial data and all other types of data, when we speak about the statistical analysis, is the requirement to take into account such factors as height, distance and area in the analysis.

Keywords: web-scraping, spatial data, geo-spatial modeling, automated control, analytical ecosystem.
For citation:

Nekrasov G. A., Polivoda D. E., Prokofeva E. N. Sources of spatial data in advancing technologies of subsoil use. MIAB. Mining Inf. Anal. Bull. 2020;(5):164-176. [In Russ]. DOI: 10.25018/0236-1493-2020-5-0-164-176.

Acknowledgements:

The publication has been prepared during implementation of Project No. 20-04-033 in the framework of the Program of the Scientific Foundation of the National Research University—Higher School of Economics in 2020–2021 and under governmental support of the leading universities of the Russian Federation, Project 5–100.

Issue number: 5
Year: 2020
Page number: 164-176
ISBN: 0236-1493
UDK: 303.645.063
DOI: 10.25018/0236-1493-2020-5-0-164-176
Article receipt date: 08.02.2020
Date of review receipt: 17.03.2020
Date of the editorial board′s decision on the article′s publishing: 20.04.2020
About authors:

G.A. Nekrasov1, Student, e-mail: alax-27@mail.ru,
D.E. Polivoda1, Student, e-mail: depolivoda@edu.hse.ru,
E.N. Prokofeva1, Cand. Sci. (Eng.), Professor, e-mail: eprokofyeva@hse.ru,
1 Higher School of Economics. National Research University, 143072, Moscow, Russia.

 

For contacts:

E.N. Prokofeva, e-mail: eprokofyeva@hse.ru.

Bibliography:

1. Chadalawada J., Espinoza-Molina D., Datcu M. Assessment of earth observation data content based on data compression — application to settlements understanding. IEEE International Geoscience and Remote Sensing Symposium. 2012, pp. 6130—6133. DOI: 10.1109/igarss.2012.6352207.

2. Lionel Gueguen Classifying compound structures in satellite images: a compressed representation for fast queries. IEEE Transactions on Geoscience and Remote Sensing, 2014, Vol. 53, pp. 1803—1818. DOI: 10.1109/tgrs.2014.2348864.

3. Hansaem Park, Kwangseob Kim, Kiwon Lee Geo-data visualization on online and offline mode of mobile web using HTML5 / 4th International Workshop on Earth Observation and Remote Sensing Applications (EORSA). 2016. pp. 237—240. DOI: 10.1109/eorsa.2016.7552804.

4. Scrapy 1.4 documentation. 2019. Available at: https://docs.scrapy.org/en/latest (accessed 21 May 2019).

5. Olston C., Najork M. Web crawling. Foundations and Trends in Information Retrieval, 2010, vol. 4, no 3, pp. 175—246.

6. Hsieh J. M., Gribble S. D., Levy H. M. The architecture and implementation of an extensible web crawler / Proceedings of the 7th USENIX Symposium on Networked Systems Design and Implementation, NSDI 2010, April 28—30, 2010, San Jose, CA, USA.

7. Boyko V.V., Savinkov V. M. Proektirovanie baz dannykh informatsionnykh sistem. 2-e izd. [Designing databases of information systems. 2nd edition], Moscow, Finansy i statistika, 1989, 350 p.

8. Tiori T., Fry J. Proektirovanie struktur baz dannykh [Designing database structures], Moscow, Mir, 1985.

9. Jibo Xie, Guoqing Li Implementing next-generation national earth observation data infrastructure to integrate distributed big earth observation data. IEEE International Geoscience and Remote Sensing Symposium (IGARSS). 2016. DOI: 10.1109/IGARSS.2016.7729042.

10. Mamatha Y. N., Ananth A. G. Content based image retrival of satellite imageris using soft quiery based color composite techniques. International Journal of Computer Applications. 2010, Vol. 7, No 5. DOI: 10.5120/1156-1379.

11. Vostrikov A. V., Prokofeva E. N., Goncharenko S. N., Gribanov I. V. Analytical modeling for the modern mining industry. Eurasian Mining. 2019. No 2(32). Pp. 30—35. DOI: 10.17580/ em.2019.02.07.

12. Goncharenko S. N., Le Binh Duong, Stoyanova I. A., Petrov M. V. Modeling of parameters of innovation water-protection measures on the basis of industrial-technological indices of coal mining at Vietnam enterprises. Gornyi Zhurnal, 2014, no 9, pp. 143—146.

13. Goncharenko S.N., Korostelev D. B. System analysis and prediction of performance efficiency figures and indicators in the area of environmental protection and nature management. Gornyy informatsionno-analiticheskiy byulleten’. 2018, no 9, pp. 104–110. [In Russ]. DOI: 10.25018/0236-1493-2018-9-0-104-110.

14. Goncharenko S.N., Korostelev D.B. Methods and models for integrated estimation of system connection between the nature protection policy efficiency and managerial solutions in the field of use of natural resources. Gornyy informatsionno-analiticheskiy byulleten’. 2018, no 11, pp. 70—76. [In Russ]. DOI: 10.25018/0236-1493-2018-11-0-70-76.

15. Umerbekov Zh. Zh., Goncharenko S. N. Validation of efficiency of the target production safety management model introduction in the mining industry. MIAB. Mining Inf. Anal. Bull. 2019;(8):225-234. [In Russ]. DOI: 10.25018/0236-1493-2019-08-0-225-234.

16. Prokofeva E. N., Vostrikov A. V., Shapovalenko G. N., Alvarez A. The development of effective geomonitoring for mining area with industrial review. Eurasian Mining. 2017. No 2. Pp. 61—63. DOI: 10.17580/em.2017.02.15.

17. Alvarez A., Fernandez E., Prokofeva E. N., Vostrikov A. V. The building of effective systems of training and development for mining engineers with the basis of digital technologies. Eurasian Mining. 2019. No 1(31). Pp. 49—52. DOI: 10.17580/em.2019.01.12.

18. Zotov L., Frolova N., Shum C. Gravity changes over russian river basins from GRACE. Planetary Exploration and Science: Recent Results and Advances. Berlin: Birkhauser/Springer, 2015, pp 45—59.

19. Shepel T., Grafe B., Hartlieb P., Drebenstedt C., Malovyk A. Evaluation of cutting forces in granite treated with microwaves on the basis of multiple linear regression analysis. International Journal of Rock Mechanics and Mining Sciences. 2018, Vol. 107, Pp. 69—74. DOI:10.1016/j. ijrmms.2018.04.043.

20. Temkin I., Deryabin S., Konov I. Soft computing models in an intellectual open-pit mines transport control system. Procedia Computer Science, 2017. Vol. 120, pp. 411—416. DOI: 10.1016/j.procs.2017.11.257.

21. Temkin I. O., Klebanov D. A., Deryabin S. A., Konov I. S. Method of determining the state of the haul road career in the management of the interaction between robotic elements of the mining transportation complex. Gornyi Zhurnal. 2018, no 1, pp. 78—82. [In Russ].

22. Prokofeva E. N., Vostrikov A. V., Fernandez E., Borisov N. Navigation satellite systems as the audit foundation for mining companies. Eurasian Mining. 2017. No 1. Pp. 30—32. DOI: 10.17580/em.2017.01.08.

23. Ryl'nikova M. V., Galchenko Yu. P. Vozobnovlyaemye istochniki energii pri kompleksnom osvoenii nedr [Renewable sources of energy in integrated subsoil development], Moscow, IPKON RAN, 2015, 122 p.

24. Rylnikova M., Ainbinder I., Radchenko D. Role of safety justification of mining development for the regulatory framework formation and mineral resources management. E3S Web of Conferences. 2018. 41, Article 01033. DOI: 10.1051/e3sconf/20184101033.

Subscribe for our dispatch