Remote sensing of forest belt flooded areas
PDF (Русский)
XML (Русский)


belt forest
forest pathology
flooding of forests
forest degradation
remote sensing
processing of remote sensing data
Novichikhinskiy forestry
Altai Krai

How to Cite

Dolgacheva, L., & Rotanova, I. (2019). Remote sensing of forest belt flooded areas. Acta Biologica Sibirica, 5(4), 83-88.


The article deals with the application of remote sensing data in the study of flooding of forests on the example of band boron in Novichikhinsky forestry of the Altai Krai. The results of research are presented, in particular, using the method of object-oriented classification of space images of the earth's surface, which combines the possibility of clustering, qualitatively distinguishes connected objects in the image, and classification with training, which allows to refer the selected objects to pre-defined classes. According to remote sensing data, the areas of flooding and the forest pathology state of the Barnaul belt forest were estimated.
PDF (Русский)
XML (Русский)


Blaschke T, Johansen K, Tiede D, Weng Q, ed. 2011. Object-based image analysis for vegetation mapping and monitoring. In: Advances in environmental remote Sensing: sensors, algorithms, and applications. CRC Press. p. 1–272. DOI: 10.1201/b10599-13

Fedorova TA. 2011. Forest pest monitoring system of Kurgan region. Bulletin of Kurgan State University 2:46-49.

Gurchenkov АА, Murynin AB, Trekin AN, Ignatiev VYu. 2017. Object-Oriented Classification of Substrate Surface Objects in Arctic Impact Regions Aerospace Monitoring. Herald of the Bauman Moscow State Tech. Univ., Nat. Sci. 3: 135–146. DOI: 10.18698/1812-3368-2017-3-135-146.

Ignatiev VYu, Murynin AB, Trekin AN. 2015. Object oriented space images classification method for impact regions monitoring. Scientific discoveries and achievements. Proc. Int. Sc. Conf.: 176–186.

State Report On the state and environmental protection in the Altai region in 2016. 2017. Barnaul.

Rotanova IN, Koshkarev AV, Medvedev AA. 2014. Use of remote sensing data for digital terrain modelling as part of the regional infrastructure of spatial data. Computational technologies 19(3): 38-47.

Zolotov DV. 2009. Summary of the flora of the Barnaul river basin. Novosibirsk: Nauka.

Acta Biologica Sibirica is a golden publisher, as we allow self-archiving, but most importantly we are fully transparent about your rights.

Authors may present and discuss their findings ahead of publication: at biological or scientific conferences, on preprint servers, in public databases, and in blogs, wikis, tweets, and other informal communication channels.

ABS allows authors to deposit manuscripts (currently under review or those for intended submission to ABS) in non-commercial, pre-print servers such as ArXiv.

Authors who publish with this journal agree to the following terms:


    1. Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License (CC BY 4.0) that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
    2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
    3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).


Download data is not yet available.


Metrics Loading ...