1 Myadzelets A.V.

Sochava Institute of Geography SB RAS

The paper considers the problem of assessment and mapping of natural and anthropogenic geosystem disturbance using processing of remote-sensing data, geoinformation analysis and map-making. The assessment approach is based on automatic processing of images Lansat TM and determining geosystem borders with different disturbance degree. Then different categories of disturbance are classified, and a special thematic legend is worked out. A special mathematical method is used for determining the borders. It is based on the calculation of the Jacob determinant and allows to analyze associations between the brightness features of different spectral channels of remote sensing images. Due to the processing results the best combinations of the image channels for analysis of disturbance forms and degree are ascertained for different geosystem types. Qualitative evaluation of territory disturbance is fulfilled, and hierarchical classification of geosystem disturbance is worked out. According to the classification next categories of disturbance are determined for geosystems: conditionally non-disturbed (climax and supposed climax), naturally modified law disturbed (demiserial), naturally modified high disturbed (serial), anthropogenic modified law disturbed (different stages of reforestation), anthropogenic modified high disturbed (settlement and agricultural lands). The processed geoimages and determined categories are the information base which is used for the map of geosystem disturbance with a corresponding legend on the territory of Slyudyanskii District of Irkutsk Region. The state of the local geosystems is described according to the mapping results. It reflects current environmental situation of the territory.
1.   Belov A.V., Lyamkin V.F., Sokolova L.P. Kartografirovanie antropogennoj narushennosti bioty Predbajkal'ya. Geografiya i prirodnye resursy, 2006, no. 4, pp. 108–115.
2.   Gusev A.P., Sokolov A.S. Informacionno-analiticheskaya sistema dlya ocenki antropogennoj narushennosti lesnyh landshaftov. Vestn. Tomskogo gos. un-ta, 2008, no. 309, pp. 176–179.
3.   Krauklis A.A. Problemy ehksperimental'nogo landshaftovedeniya. Novosibirsk: Nauka, 1979, 233 p.
4.   Konovalova T.I. , Bessolicyna E.P., Vladimirov I.N., i dr. Landshaftno-interpretacionnoe kartografirovanie. Otv. red. A. K. Cherkashin. Novosibirsk: Nauka, 2005, 424 p.
5.   Mironova E.N. Sravnitel'no-geograficheskij analiz rastitel'nosti geosistem Darhatskoj, Hubsugul'skoj i Tunkinskoj kotlovin: Avtoref. dis. na soisk. uch. st. kand. geogr. nauk. Irkutsk: IG SO RAN, 2008, 21 p.
6.   Myadzelec A.V. Geomaticheskie tekhnologii ocenki narushennosti zemel' po kosmicheskim snimkam. Matematicheskoe modelirovanie i informacionnye tekhnologii, Irkutsk: In-ta dinamiki sistem i teorii upravleniya SO RAN, 2007, pp. 122–127.
7.   Myadzelec A.V. Kartografirovanie granic landshaftov s ispol'zovaniem mnogokanal'nyh kosmicheskih snimkov i matematicheskih modelej. Tematicheskoe kartografirovanie dlya sozdaniya infrastruktur prostranstvennyh dannyh, Irkutsk: In-t geografii im. V.B. Sochavy SO RAN, 2010, 2 pp. 50–53.
8.   Myadzelets A.V. (2011) Assesment of disturbed areas on the territory of Southern Baikal based on sattelite images. Geodezia i Kartografia, 72(11), pp. 35–41.
9.   Frolov A.A. Geoinformacionnyj analiz i prognozirovanie izmenchivosti landshaftov Predbajkal'ya: Avtoref. dis. na soisk. uch. st. kand. geogr. nauk. Irkutsk: IG SO RAN, 2011, 24 p.
10.   Istomina E.A. (2009) Functorial models of spatio-temporal landscape field of the Earth: methods of comparativegeographical studies based on data of remote sensing. Modelling of geographical processes and natural resources, Volume 4, no. 5, MMNP, pp. 21–36.
Myadzelets A.V., 
(2016) Mapping of natural and anthropogenic geosystem disturbance of Pribaikalie. Geodesy and cartography = Geodezia i Kartografia, (2), pp. 21–29. (In Russian). DOI: 10.22389/0016-7126-2016-908-2-21-29
Publication History
Received: 20.03.2015
Accepted: 06.08.2015
Published: 11.03.2016


2016 February DOI:

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