Next Article in Journal
Spatial Analysis of Land Subsidence in the San Luis Potosi Valley Induced by Aquifer Overexploitation Using the Coherent Pixels Technique (CPT) and Sentinel-1 InSAR Observation
Previous Article in Journal
Manhole Cover Detection on Rasterized Mobile Mapping Point Cloud Data Using Transfer Learned Fully Convolutional Neural Networks
Open AccessArticle

UAV-Derived Data Application for Environmental Monitoring of the Coastal Area of Lake Sevan, Armenia with a Changing Water Level

1
Institute of Geography, Russian Academy of Sciences; Staromonetny pereulok, 29, 119017 Moscow, Russia
2
Faculty of Geography and Geoinformation Technology, National Research University “Higher School of Economics”, Myasnitskaya Ulitsa 20, 101100 Moscow, Russia
3
Centre for Ecological-Noosphere Studies, National Academy of Sciences, Abovyan Street 68, Yerevan 0025, Armenia
*
Author to whom correspondence should be addressed.
Remote Sens. 2020, 12(22), 3821; https://doi.org/10.3390/rs12223821
Received: 29 September 2020 / Revised: 12 November 2020 / Accepted: 18 November 2020 / Published: 21 November 2020
(This article belongs to the Section Environmental Remote Sensing)
The paper presents the range and applications of thematic tasks for ultra-high spatial resolution data from small unmanned aerial vehicles (UAVs) in the integral system of environmental multi-platform and multi-scaled monitoring of Lake Sevan, which is one of the greatest freshwater lakes in Eurasia. From the 1930s, it had been subjected to human-driven changing of the water level with associated and currently exacerbated environmental issues. We elaborated the specific techniques of optical and thermal surveys for the different coastal sites and phenomena in study. UAV-derived optical imagery and thermal stream were processed by a Structure-from-Motion algorithm to create digital surface models (DSMs) and ortho-imagery for several key sites. UAV imagery were used as additional sources of detailed spatial data under large-scale mapping of current land-use and point sources of water pollution in the coastal zone, and a main data source on environmental violations, especially sewage discharge or illegal landfills. The revealed present-day coastal types were mapped at a large scale, and the net changes of shoreline position and rates of shore erosion were calculated on multi-temporal UAV data using modified Hausdorff’s distance. Based on highly-detailed DSMs, we revealed the areas and objects at risk of flooding under the projected water level rise to 1903.5 m along the west coasts of Minor Sevan being the most popular recreational area. We indicated that the structural and environmental state of marsh coasts and coastal wetlands as potential sources of lake eutrophication and associated algal blooms could be more efficiently studied under thermal UAV surveys than optical ones. We proposed to consider UAV surveys as a necessary intermediary between ground data and satellite imagery with different spatial resolutions for the complex environmental monitoring of the coastal area and water body of Lake Sevan as a whole. View Full-Text
Keywords: UAV; highly-detailed spatial data; thermal survey; coastal processes; shoreline position; coastal wetlands; eutrophication; multi-platform environmental monitoring UAV; highly-detailed spatial data; thermal survey; coastal processes; shoreline position; coastal wetlands; eutrophication; multi-platform environmental monitoring
Show Figures

Graphical abstract

MDPI and ACS Style

Medvedev, A.; Telnova, N.; Alekseenko, N.; Koshkarev, A.; Kuznetchenko, P.; Asmaryan, S.; Narykov, A. UAV-Derived Data Application for Environmental Monitoring of the Coastal Area of Lake Sevan, Armenia with a Changing Water Level. Remote Sens. 2020, 12, 3821. https://doi.org/10.3390/rs12223821

AMA Style

Medvedev A, Telnova N, Alekseenko N, Koshkarev A, Kuznetchenko P, Asmaryan S, Narykov A. UAV-Derived Data Application for Environmental Monitoring of the Coastal Area of Lake Sevan, Armenia with a Changing Water Level. Remote Sensing. 2020; 12(22):3821. https://doi.org/10.3390/rs12223821

Chicago/Turabian Style

Medvedev, Andrey; Telnova, Natalia; Alekseenko, Natalia; Koshkarev, Alexander; Kuznetchenko, Pyotr; Asmaryan, Shushanik; Narykov, Alexey. 2020. "UAV-Derived Data Application for Environmental Monitoring of the Coastal Area of Lake Sevan, Armenia with a Changing Water Level" Remote Sens. 12, no. 22: 3821. https://doi.org/10.3390/rs12223821

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop