- 1University of Twente, ITC, WRS, (f.b.munch@utwente.nl)
- 2Royal Netherlands Institute for Sea Research, NIOZ, the Netherlands
Many people depend on inland water bodies as water resource. However, fundamental ecosystem services, like the provision of water for drinking and irrigation purposes, can be affected by eutrophication, climate change and invasive species. This challenge requires the regular observation and monitoring of freshwater bodies to take measures that preserve their valuable ecosystem services and warn the local population in the event of water-related health risks. Aquatic macrophytes and phytoplankton can be detected from space and used as a proxy to monitor the trophic state and water quality, for example by using vegetation indices such as NDVI or FAI. However, these indices fail to discriminate reliably between floating vegetation (like water hyacinth) and submerged vegetation.
The Aquatic Macrophyte Index (AMI) presented in this paper uses information from the green and shortwave infrared (SWIR) part of the electromagnetic spectrum to distinguish between aquatic macrophytes and phytoplankton. The respective plant’s water content causes a detectable absorption in the SWIR, which allows to differentiate aquatic macrophytes from phytoplankton. A fixed threshold of the AMI allows classification of aquatic macrophytes and phytoplankton, respectively, without the need to select a threshold for different study areas as it is the case for currently applied state of the art spectral indices. Satellite sensors of the Landsat and Sentinel-2 mission have the required bands for the computation of the AMI. Cloud free records of a harmonized dataset that combines imagery from both missions favor the performance of close to real time monitoring as well as timeseries analysis of the past decades.
The AMI can be applied to monitor the distribution of aquatic weed such as water hyacinth. The application of the AMI is exemplified using Lake Chivero (Zimbabwe) as case study representing the issue of hypertrophic lakes that are infested with rapidly expanding invasive species and algal blooms.
How to cite: Münch, F., Penning de Vries, M., and van der Wal, D.: Remote sensing based Water Hyacinth monitoring using the novel Aquatic Macrophyte Index (AMI), EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-4184, https://doi.org/10.5194/egusphere-egu25-4184, 2025.