Remote sensing of macrophyte morphological traits: Implications for the management of shallow lakes

Submitted: 23 February 2017
Accepted: 23 February 2017
Published: 7 March 2017
Abstract Views: 2962
PDF: 1006
Supplementary: 285
Publisher's note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

Authors

Macrophytes are important elements of freshwater ecosystems, fulfilling a pivotal role in biogeochemical cycles. The synoptic capabilities provided by remote sensing make it a powerful tool for monitoring aquatic vegetation characteristics and the functional status of shallow lake systems in which they occur. The latest generation of airborne and spaceborne imaging sensors can be effectively exploited for mapping morphologically – and physiologically – relevant vegetation features based on their canopy spectral response. The objectives of this study were to calibrate semi-empirical models for mapping macrophyte morphological traits (i.e., fractional cover, leaf area index and above-water biomass) from hyperspectral data, and to investigate the capabilities of remote sensing in supporting macrophyte monitoring and management. We calibrated spectral models using in situ reflectance and morphological trait measures and applied them to airborne hyperspectral imaging data, acquired over two shallow European water bodies (Lake Hídvégi, in Hungary, and Mantua lakes system, in Italy) in two key phenological phases. Maps of morphological traits were produced covering a broad range of aquatic plant types (submerged, floating, and emergent), common to temperate and continental regions, with an error level of 5.4% for fractional cover, 0.10 m2 m-2 for leaf area index, and 0.06 kg m-2 for above-water biomass. Based on these maps, we discuss how remote sensing could support monitoring strategies and shallow lake management with reference to our two case studies: i.e., by providing insight into spatial and species-wise variability, by assessing nutrient uptake by aquatic plants, and by identifying hotspot areas where invasive species could become a threat to ecosystem functioning and service provision.

Dimensions

Altmetric

PlumX Metrics

Downloads

Download data is not yet available.

Citations

Supporting Agencies

European Community's 7th Framework Programme, EuFAR

How to Cite

Villa, Paolo, Monica Pinardi, Viktor R. Tóth, Peter D. Hunter, Rossano Bolpagni, and Mariano Bresciani. 2017. “Remote Sensing of Macrophyte Morphological Traits: Implications for the Management of Shallow Lakes”. Journal of Limnology 76 (s1). https://doi.org/10.4081/jlimnol.2017.1629.

List of Cited By :

Crossref logo