Identification of Aquatic Plants in the Muncheon Water Reservoir Using Drone-based Information

Lee, Geun-Sang; Kim, Sung-Wook; Lee, Khil-Ha

doi:10.5322/jesi.2017.26.5.685

Cited by 2 publications

(2 citation statements)

References 5 publications

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“…Using this, Chabot et al (2013) [31] found their classification algorithm to have an accuracy of 84% when classifying submerged vegetation and an overall accuracy of 92% when classifying abovesurface aquatic vegetation. Lee et al (2017) [32] found that the use of drone-based imagery could accurately identify the existence of aquatic plants in the Muncheon water reservoir, South Korea, when a Normalised Difference Vegetation Index (NDVI) and Surface Algal Bloom Index (SABI) were applied.…”

Section: Remote Sensing As a Means Of Monitoring Aquatic Plants 21 Op...mentioning

confidence: 99%

Detecting Water Hyacinth Infestation in Kuttanad, India, Using Dual-Pol Sentinel-1 SAR Imagery

et al. 2022

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Water hyacinth (Pontederia crassipes, also known as Eichhornia crassipes) is a highly invasive aquatic macrophyte species, indigenous to Amazonia, Brazil and tropical South America. It was introduced to India in 1896 and has now become an environmental and social challenge throughout the country in community ponds, freshwater lakes, irrigation channels, rivers and most other surface waterbodies. Considering its large speed of propagation on the water surface under conducive conditions and the adverse impact the infesting weed has, constant monitoring is needed to aid civic bodies, governments and policy makers involved in remedial measures. The synoptic coverage provided by satellite imaging and other remote sensing practices make it convenient to find a solution using this type of data. While there is an established background for the practice of remote sensing in the detection of aquatic plants, the use of Synthetic Aperture Radar (SAR) has yet to be fully exploited in the detection of water hyacinth. This research focusses on detecting water hyacinth within Vembanad Lake, Kuttanad, India. Here, results show that the monitoring of water hyacinth has proven to be possible using Sentinel-1 SAR data. A quantitative analysis of detection performance is presented using traditional and state-of-the-art change detectors. Analysis of these more powerful detectors showed true positive detection ratings of ~95% with 0.1% false alarm, showing significantly greater positive detection ratings when compared to the more traditional detectors. We are therefore confident that water hyacinth can be monitored using SAR data provided the extent of the infestation is significantly larger than the resolution cell (bigger than a quarter of a hectare).

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Section: Remote Sensing As a Means Of Monitoring Aquatic Plants 21 Op...mentioning

confidence: 99%

Detecting Water Hyacinth Infestation in Kuttanad, India, Using Dual-Pol Sentinel-1 SAR Imagery

et al. 2022

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“…These practices can provide valuable guidelines for managing the Otamiri River sustainably.2.9.1 Drones and Arti cial Intelligence in Water Quality Monitoring:The integration of arti cial intelligence (AI) with drone technology is an innovative area in water quality monitoring. Research byLee & Kim (2023) demonstrated how AI algorithms can process drone-captured imagery to identify pollution sources and assess water quality parameters e ciently. Implementing AI in the Otamiri River study could signi cantly enhance data analysis and interpretation.2.9.2 Global Warming and Its Impact on Water Quality: Global warming poses a signi cant threat to water quality, altering hydrological cycles and affecting pollution dynamics.…”

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confidence: 99%

Assessment of Water Quality of Otamiri River Along Selected Reach Using Drone Technology

Nmecha,

Okereke,

Egwuonwu

et al. 2024

Preprint

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research work focuses on the study of water quality in the Otamiri River in Imo State, Nigeria. It highlights the concerns about pollution due to anthropogenic and industrial activities, the need for innovative monitoring methods like drone technology, and the global challenges in water quality. The study emphasizes the implications for public health and environmental policies, aiming to assess and monitor the distribution of contaminants along the river using drones, and compare these findings with laboratory analyses. This approach is seen as a transformative step in water management practices, contributing to international knowledge in water quality management. The document also discusses the integration of drone technology in environmental monitoring to bridge local challenges with global solutions.

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Identification of Aquatic Plants in the Muncheon Water Reservoir Using Drone-based Information

Cited by 2 publications

References 5 publications

Detecting Water Hyacinth Infestation in Kuttanad, India, Using Dual-Pol Sentinel-1 SAR Imagery

Detecting Water Hyacinth Infestation in Kuttanad, India, Using Dual-Pol Sentinel-1 SAR Imagery

Assessment of Water Quality of Otamiri River Along Selected Reach Using Drone Technology

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