Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2023, Vol. 20, No. 2, pp. 166-173
Assessing the dynamics of natural coastal complexes of Lake Bolshoye Topolnoye (Altai Krai) using a time series of multispectral data of different resolution
A.V. Golovin
1 , N.V. Stoyashcheva
1 , N.M. Kovalevskaya
1 1 Institute for Water and Environmental Problems SB RAS, Barnaul, Russia
Accepted: 16.03.2023
DOI: 10.21046/2070-7401-2023-20-2-166-173
The paper presents the assessment results of the dynamics of natural coastal complexes of Lake Bolshoe Topolnoe by remote sensing methods based on studying multi-temporal space images (Sentinel 2, Landsat-5, Landsat-7) of different resolution. Vegetation indices (NDVI, SAVI, MSAVI2, WAVI), parametric and non-parametric classifications were calculated in the Erdas Imagine program for the littoral part of Lake Bolshoe Topolnoe for the years 1990, 2000, 2010, and 2019. It has been found that the lake’s water area and its coast are prone to overgrowth by coastal and shrubby (narrow-leaved oleaster) vegetation over the course of several years. Such a situation can adversely affect natural systems distinguished by a rich resource potential for the tourism development. In 2000–2019, in small and large areas of the lake covered with coastal vegetation these indices increased from 0.4–0.6 to 0.7–0.8 and 0.7–0.8 to 0.8–1.0, respectively. According to the non-parametric classification by 20 classes, the overgrowth area increased from 1 to 2.3 km2. Shrub vegetation was common on the eastern, southeastern, and southern coasts of the lake. Here, the index values increased from 0.4–0.6 to 0.7–0.8 (2010–2019). The parametric classification showed the increase of the overgrowth area within 0 (2000) – 0.6 km2 (2019). Intensive overgrowth of the lake with coastal vegetation is associated with fluctuations in water level regime, shrub vegetation (i.e. narrow-leaved oleaster use in the field-protective forest belts of the steppe parts of the Region), decline in the lake exploitation for fishing purposes and livestock reduction in the Burlinsky region.
Keywords: Lake Bolshoe Topolnoe, Earth remote sensing, Sentinel 2, Landsat-5, Landsat-7, vegetation indices
Full textReferences:
- Evdokimov S. I., Mikhalap S. G., Determination of physical meaning of band combinations of Landsat images for monitoring terrestrial and aquatic ecosystems, Vestnik Pskovskogo gosudarstvennogo universiteta. Ser.: Estestvennye i fiziko-matematicheskie nauki, 2015, No. 7, pp. 21–32 (in Russian).
- Zarubina E. Yu., Sokolova M. I., Hygrophilous flora of Burlinsky lake and river system (Ob-Irtysh Interfluve), Problemy botaniki Yuzhnoi Sibiri i Mongolii, 2017, No. 16, pp. 78–82 (in Russian).
- Zarubina E. Yu., Sokolova M. I., Communication of a specific variety of macrophyte with a morphometry and hydrochemical characteristics of lakes (on example of polytypic river lakes of Burlinsky system, the South of the Ob-Irtysh interfluve), Problemy botaniki Yuzhnoi Sibiri i Mongolii, 2018, No. 17, pp. 66–70 (in Russian).
- Chernaya Kniga flory Sibiri (Black Book of the flora of Siberia), Vinogradova Yu. K., Kupriyanov A. N. (eds.), Novosibirsk: Geo, 2016, 439 p. (in Russian).
- Shibanova A. A., Kurepina N. Yu., Plutalova T. G., Kirina A. O., Territorial features of distribution of communities of alien plant species in the steppe zone of Altai Krai (by the example of the genus Elaeagnus L.), Fundamental’nye issledovaniya, 2013, No. 11(1), pp. 133–137 (in Russian).
- Schowengerdt R. A., Remote sensing. Models and methods of image processing, Elsevier, 2006, 560 p.
- Huete A. R., A soil-adjusted vegetation index (SAVI), Remote Sensing of Environment, 1988, Vol. 25, No. 3, pp. 295–309, DOI: 10.1016/0034-4257(88)90106-X.
- Jaskula J., Sojka M., Assessing Spectral Indices for Detecting Vegetative Overgrowth of Reservoirs, Polish J. Environmental Studies, 2019, Vol. 28, No. 6, pp. 4199–4211, DOI: 10.15244/PJOES/98994.
- Qi J., Chehbouni A., Huete A. R., Keer Y. H., Sorooshian S., A modified soil adjusted vegetation index, Remote Sensing of Eenvironment, 1994, Vol. 48, No. 2, pp. 119–126, DOI: 10.1016/0034-4257(94)90134-1.
- Villa P., Mousivand A., Bresciani M., Aquatic vegetation indices assessment through radiative transfer modeling and linear mixture simulation, Intern. J. Applied Earth Observation and Geoinformation, 2014, Vol. 30, pp. 113–127, DOI: 10.1016/j.jag.2014.01.017.
- Zhou G., Ma Z., Sathyendranath S., Platt T., Jiang C., Sun K., Canopy reflectance modeling of aquatic vegetation for algorithm development: Global sensitivity analysis, Remote Sensing, 2018, Vol. 10, Issue 6, Art. No. 837, DOI: 10.3390/RS10060837.