Article

Mapping and Monitoring Of Water Hyacinth In Lake Victoria Using Polarimetric Radar Data

Details

Citation

Felix IK, Armando M, Simpson MD, Vahid A, Silva TSF, Datta A, Nagendra PG, Pranuthi G & Srikanth R (2024) Mapping and Monitoring Of Water Hyacinth In Lake Victoria Using Polarimetric Radar Data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. https://doi.org/10.1109/jstars.2024.3476938

Abstract
Water hyacinth, an invasive species originating from South America, has become a significant concern since its introduction in Lake Victoria (Kenya), particularly in the Winam Gulf, where large annual blooms are observed. Monitoring the occurrence and location using in situ methods is expensive and challenging due to the lake's vastness. Remote sensing monitoring methods offer an alternate option due to the ability to cover vast areas. This study explores the potential of polarimetric Synthetic Aperture Radar (PolSAR), specifically utilising Sentinel-1 VV-VH data to map and monitor water hyacinth cover. The change detection method based on Optimisation of Power Difference (OPDiff) and minimum eigenvalue selection achieves a remarkable accuracy of 98.89% in separating clear and water hyacinth-infested water. Using polarimetric data offered better separability, enabling spatial and temporal monitoring. The analysis reveals that in 2018 water hyacinth cover peaked, spanning over 200 km 2 . Temporal variability showcases a seasonal rise and peak from September to December. This research demonstrates the capability of using PolSAR data to accurately map and monitor water hyacinth's spatial and temporal dynamics, offering valuable insights for effective management strategies.

Keywords
SAR polarimetry; optimisation of power difference; water hyacinth monitoring; change detection

Journal
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

StatusIn Press
FundersRoyal Academy of Engineering
Publication date online31/10/2024
Date accepted by journal05/10/2024
URLhttp://hdl.handle.net/1893/36387
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
ISSN1939-1404
eISSN2151-1535

People (5)

Dr Vahid Akbari

Dr Vahid Akbari

Lect in Artificial Intelligence/Data Sci, Computing Science and Mathematics - Division

Mr Felix Isundwa

Mr Felix Isundwa

Tutor, Biological and Environmental Sciences

Dr Armando Marino

Dr Armando Marino

Associate Professor, Biological and Environmental Sciences

Dr Thiago Silva

Dr Thiago Silva

Senior Lecturer, Biological and Environmental Sciences

Mr Morgan Simpson

Mr Morgan Simpson

Radar Remote Sensing Scientist, Biological and Environmental Sciences