Back to Search Start Over

Monitoring Water Diversity and Water Quality with Remote Sensing and Traits

Authors :
Angela Lausch
Lutz Bannehr
Stella A. Berger
Erik Borg
Jan Bumberger
Jorg M. Hacker
Thomas Heege
Michael Hupfer
András Jung
Katja Kuhwald
Natascha Oppelt
Marion Pause
Franziska Schrodt
Peter Selsam
Fabian von Trentini
Michael Vohland
Cornelia Glässer
Source :
Remote Sensing, Vol 16, Iss 13, p 2425 (2024)
Publication Year :
2024
Publisher :
MDPI AG, 2024.

Abstract

Changes and disturbances to water diversity and quality are complex and multi-scale in space and time. Although in situ methods provide detailed point information on the condition of water bodies, they are of limited use for making area-based monitoring over time, as aquatic ecosystems are extremely dynamic. Remote sensing (RS) provides methods and data for the cost-effective, comprehensive, continuous and standardised monitoring of characteristics and changes in characteristics of water diversity and water quality from local and regional scales to the scale of entire continents. In order to apply and better understand RS techniques and their derived spectral indicators in monitoring water diversity and quality, this study defines five characteristics of water diversity and quality that can be monitored using RS. These are the diversity of water traits, the diversity of water genesis, the structural diversity of water, the taxonomic diversity of water and the functional diversity of water. It is essential to record the diversity of water traits to derive the other four characteristics of water diversity from RS. Furthermore, traits are the only and most important interface between in situ and RS monitoring approaches. The monitoring of these five characteristics of water diversity and water quality using RS technologies is presented in detail and discussed using numerous examples. Finally, current and future developments are presented to advance monitoring using RS and the trait approach in modelling, prediction and assessment as a basis for successful monitoring and management strategies.

Details

Language :
English
ISSN :
20724292
Volume :
16
Issue :
13
Database :
Directory of Open Access Journals
Journal :
Remote Sensing
Publication Type :
Academic Journal
Accession number :
edsdoj.2db94e8f24b80b58a459f3814e304
Document Type :
article
Full Text :
https://doi.org/10.3390/rs16132425