NDVI as a proxy for sedimentation and vegetation spread in artificial lakes: New paper in Remote Sensing

Our new paper by Loránd Szabó and Szilárd Szabó (University of Debrecen, Department of Physical Georgraphy and Geoinformation Systems) has recently been accepted in Remote Sensing.

The citation of the paper is:

Szabó, L., Deák, B., Bíró, T., Dyke, G.J., Szabó, Sz. (2020): NDVI as a Proxy for Estimating Sedimentation and Vegetation Spread in Artificial Lakes – Monitoring of Spatial and Temporal Changes by Using Satellite Images Overarching Three Decades. Remote Sensing 12: 1468. [IF2018: 4.740]

The article is freely available at the journal's homepage; please click here to access the paper. 

Freshwater ecosystems are threatened biodiversity hotspots worldwide. Lakes in Hungary are under threat for several reasons, including the increasing aridity rates due to global climate change, scarce water supply and the infiltration of nutrients and pollutants. Depending on the available nutrient surplus, lake succession and the spread of vegetation can accelerate eutrophication. Several methods are available for monitoring lake sedimentation, such as analyzing sediment cores using radionuclides, heavy metals, or bioindicators. These methods provide valuable information on sedimentation but do not give a complex picture on the spatial dimensions of the sedimentation as generally a limited number of points can be sampled and the results are extrapolated. A direct spatial method involves mapping the bottom of lakes, which can be conducted using probe rods, sonar, or bathymetric LiDAR (Light Detection and Ranging). The common limitation of these techniques is their uncertainty despite the high level of expenditure involved. Also, for monitoring purposes, the assessment should be repeated regularly. The goal of our study was to develop an optical remote sensing based monitoring system to track sedimentation and eutrophication processes, using the  Normalized Difference Vegetation Index (NDVI) and the Modified Normalized Difference Water Index (MNDWI). The developed methodology can be a useful tool for monitoring sedimentation and eutrophication processes in a cost-effective way.

The water caltrop (Trapa natans) is a protected macrophyte species in Hungary. Interestingly, it is a protected and disappearing species in many parts of Europe, but in the Lake Tisza, it is very abundant and present a potential threat to biodiversity.

The yellow floating-heart (Nymphoides peltata) is a protected, but still abundant species of the study site.

Another protected species, the European white water lily (Nymphaea alba).

Abstract

Observing wetland areas and monitoring changes are crucial to understand hydrological and ecological processes. Sedimentation-induced vegetation spread is a typical process in the succession of lakes endangering these habitats. We aimed to survey the tendencies of vegetation spread of a Hungarian lake using satellite images, and to develop a method to identify the areas of risk. Accordingly, we performed a 33-year long vegetation spread monitoring survey. We used the Normalized Difference Vegetation Index (NDVI) and the Modified Normalized Difference Water Index (MNDWI) to assess vegetation and open water characteristics of the basins. We used these spectral indices to evaluate sedimentation risk of water basins combined with the fact that the most abundant plant species of the basins was the water caltrop (Trapa natans) indicating shallow water. We proposed a 12-scale Level of Sedimentation Risk Index (LoSRI) composed from vegetation cover data derived from satellite images to determine sedimentation risk within any given water basin. We validated our results with average water basin water depth values, which showed an r = 0.6 (p < 0.05) correlation. We also pointed on the most endangered locations of these sedimentation-threatened areas, which can provide crucial information for management planning of water directorates and management organizations.