Kovjazin Vasilij Fedorovich, Doctor of biological sciences, professor, deputy head of sub-department of engineering geodesy, Saint-Petersburg Mining University (2 21st line of Vasylyevsky island, Saint-Petersburg, Russia), firstname.lastname@example.org
Lepikhina Olga Yurjevna, Candidate of engineering sciences, associate professor, sub-department of engineering geodesy, Saint-Petersburg Mining University (2 21st line of Vasylyevsky island, Saint-Petersburg, Russia), Olgalepikhina1984@gmail.com
Zimin Viktor Pavlovich, Postgraduate student, Saint-Petersburg Mining University (2 21st line of Vasylyevsky island, Saint-Petersburg, Russia), email@example.com
Background. At the present time in the Russian Federation there are more than 300 settlements referring to single-industry towns. Cadastral valuation of their lands is carried out by the standard methodology. As a rule, the most important factors of a dominant enterprise are not taken into account. The presence of a dominant enterprise in the city territory influences functioning of a town, development of its social and economic infrastructure, and forms real estate prices. The grouping of settlements according to social and economic parameters is an important stage of cadastral valuation. The method of grouping of lands of single-industry towns is proposed in the study. It takes into account the most important factors of a dominant enterprise.
Materials and methods. Single-industry towns of the North-Western Federal District have been investigated in the work. The following indicators are proposed for the town grouping implementation: population, distance to the center of a constituent entity of the Russian Federation, the level of social and economic development of a city, the category of threats to a dominant enterprise. The values of the indicators were collected using legal documents and information published on official sites of the towns. To classify settlements the cluster analysis method was used. The validation of the obtained results was performed using the K-means method.
Results. Four groups of single-industry towns have been identified. They are cities with the most difficult social and economic situation having non-hazardous production; cities with a stable social and economic situation or the risk of its deterioration having non-hazardous production; cities with risks of a deteriorating social and economic situation located at the distance of over 450 km from the centre of a subject; cities with the most difficult social and economic situation or the risk of its development having dangerous production.
Conclusions. The classification of lands of single-industry towns takes into account the most important factors of a dominant enterprise. It can be used to group lands of single-industry towns for cadastral valuation thereof. The latter will improve the quality of appraisal works in these towns.
cadastral valuation, grouping, single-industry town, cluster analysis, tree clustering, K-means method
1. Ob utverzhdenii Metodicheskikh ukazaniy po gosudarstvennoy kadastrovoy otsenke zemel' naselennykh punktov: prikaz Minekonomrazvitiya RF ot 15.02.2007 № 39 [On approval of methodological guidelines to state cadaster valuation of settlement lands: the order of the Ministry of Economic Development of Russia from 15.02.2007 № 39]. Available at: http://docs.cntd.ru/document/902030095 (accessed March 15, 2016).
2. Ob utverzhdenii Federal'nogo standarta otsenki «Opredelenie kadastrovoy stoimosti» (FSO № 4): prikaz Minekonomrazvitiya Rossii ot 22.10.2010 № 508 [On approval of the Federal valuation standard “Cadastre value determination” (FVS № 4): the order of the Ministry of Economic Development of Russia from 22.10.2010 № 508]. Available at: http://base.consultant.ru/cons/cgi/online.cgi?req=doc;base= LAW;n=181651; fld= 134; from=113247-4;rnd=189271. 221497012302279 47; ;ts=01892719 665711291600019 (accessed March 15,2016).
3. Gribovskiy S. V., Sivets S. A. Matematicheskie metody otsenki stoimosti nedvizhimogo imushchestva: ucheb. posobie [Mathematical methods of real estate value estimation]. Moscow, 2008, 368 p.
4. Sivets S. Obzor vozmozhnosti primeneniya statisticheskikh metodov v otsenke nedvizhimosti i biznesa [Reviewing a possibility of statistical methods application in real estate and business evaluation]. Available at: http://www.analystsoft.com/ru/products/statplus/ lib/statinbus_ru.php (accessed October 15, 2016).
5. Ustinov A. Yu. Teoretiko-metodicheskie aspekty klassifikatsii monogorodov [Theoretical and methodological aspects of monotowns classification]. Available at: http:// vestnik.uapa.ru /ru/issue/ 2012/04/15/ (accessed October 15, 2016).
6. Il'ina I. N. Razvitie monogorodov Rossii: monogr. [Development of monotowns in Russia: monograph]. Moscow: Finansovyy universitet, 2013, 168 p.
7. Ob utverzhdenii perechnya monoprofil'nykh munitsipal'nykh obrazovaniy Rossiyskoy Federatsii (monogorodov): rasporyazhenie Pravitel'stva RF ot 29.07.2014 № 1398-r. [On approval of the list of monoprofile municipal units in the Russian Federation (monotowns): the directive of the RF Government from 29.07.2014 № 1398-r]. Available at: http://docs.cntd.ru/document/420210942 (accessed March 15, 2016).
8. Sanitarno-zashchitnye zony i sanitarnaya klassifikatsiya predpriyatiy, sooruzheniy i inykh ob"ektov: sanitarno-epidemiologicheskie pravila i normativy SanPiN 2.2.1/22.214.171.1240-03 [Sanitary safety zones and sanitary classification of enterprises, facilities and other objects: sanitary-epidemiological rules and standards SanPiN 2.2.1/126.96.36.1990-03]. Available at: http://docs.cntd.ru/document/902065388 (accessed March 15, 2016).
9. Rubakov S. V. Al'manakh «Nauka. Innovatsii. Obrazovanie» [A miscellany “Science. Innovation. Education”]. 2008, no. 7, pp. 165–176. 10. Oldenderfer M. S., Bleshfild R. K. Faktornyy, diskriminantnyy i klasternyy analiz: per. s angl. [Factor, discriminant and cluster analysis: translation from English]. Moscow: Finansy i statistika, 1989, 215 p.
11. Suslov S. A. Vestnik NGIEI [Bulletin of NNSEEU]. 2010, vol. 1, no. 1, pp. 51–56.
12. Ayvazyan S. A., Mkhitaryan V. S. Prikladnaya statistika v zadachakh i uprazhneniyakh: ucheb. dlya vuzov [Applied statistics in problems and exercises: textbook for universities]. Moscow: YuNITI-DANA, 2001, 270 p.
13. Kazanskaya A. Yu., Kompaniets V. S. Izvestiya Yuzhnogo federal'nogo universiteta. Tekhnicheskie nauki [Proceedings of Souther Federal University. Engineering sciences]. 2009, no. 3 (92), pp. 103–110.
14. Bureeva N. N. Mnogomernyy statisticheskiy analiz s ispol'zovaniem PPP “STATISTICA”: ucheb.-metod. material po programme povysheniya kvalifikatsii «Primenenie programmnykh sredstv v nauchnykh issledovaniyakh i prepodavanii matematiki i mekhaniki» [Multidimensional statistical analysis using the STATISTICA program package: tutorial for the advanced study program “Application of program products in research and teaching mathematics and mechanics”]. Nizhniy Novgorod, 2007, 112 p.