Detecting Water Hyacinth Infestation in Kuttanad, India, Using Dual-Pol Sentinel-1 SAR Imagery
Water hyacinth (<i>Pontederia crassipes</i>, also known as <i>Eichhornia crassipes</i>) 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 socia...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-06-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/14/12/2845 |
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| author | Morgan David Simpson Vahid Akbari Armando Marino G. Nagendra Prabhu Deepayan Bhowmik Srikanth Rupavatharam Aviraj Datta Adam Kleczkowski J. Alice R. P. Sujeetha Girish Gunjotikar Anantrao Vidhu Kampurath Poduvattil Saurav Kumar Savitri Maharaj Peter D. Hunter |
| author_facet | Morgan David Simpson Vahid Akbari Armando Marino G. Nagendra Prabhu Deepayan Bhowmik Srikanth Rupavatharam Aviraj Datta Adam Kleczkowski J. Alice R. P. Sujeetha Girish Gunjotikar Anantrao Vidhu Kampurath Poduvattil Saurav Kumar Savitri Maharaj Peter D. Hunter |
| author_sort | Morgan David Simpson |
| collection | DOAJ |
| description | Water hyacinth (<i>Pontederia crassipes</i>, also known as <i>Eichhornia crassipes</i>) 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). |
| first_indexed | 2024-03-09T22:36:58Z |
| format | Article |
| id | doaj.art-b77627723e39483e9efa80390e4588a2 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-09T22:36:58Z |
| publishDate | 2022-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-b77627723e39483e9efa80390e4588a22023-11-23T18:47:48ZengMDPI AGRemote Sensing2072-42922022-06-011412284510.3390/rs14122845Detecting Water Hyacinth Infestation in Kuttanad, India, Using Dual-Pol Sentinel-1 SAR ImageryMorgan David Simpson0Vahid Akbari1Armando Marino2G. Nagendra Prabhu3Deepayan Bhowmik4Srikanth Rupavatharam5Aviraj Datta6Adam Kleczkowski7J. Alice R. P. Sujeetha8Girish Gunjotikar Anantrao9Vidhu Kampurath Poduvattil10Saurav Kumar11Savitri Maharaj12Peter D. Hunter13Faculty of Natural Sciences, University of Stirling, Stirling FK9 4LA, UKDepartment of Computing Science and Mathematics, University of Stirling, Stirling FK9 4LA, UKFaculty of Natural Sciences, University of Stirling, Stirling FK9 4LA, UKCentre for Research on Aquatic Resources, Sanatana Dharma College, University of Kerala, Alleppey 688011, IndiaDepartment of Computing Science and Mathematics, University of Stirling, Stirling FK9 4LA, UKInternational Crops Research Institute for the Semi-Arid Tropics, Hyderabad 500007, IndiaInternational Crops Research Institute for the Semi-Arid Tropics, Hyderabad 500007, IndiaMathematics and Statistics, University of Strathclyde, Glasgow G1 1XQ, UKNational Institute of Plant Health Management, Hyderabad 500030, IndiaNational Institute of Plant Health Management, Hyderabad 500030, IndiaNational Institute of Plant Health Management, Hyderabad 500030, IndiaCentral Scientific Instruments Organisation, Chandigarh 160030, IndiaDepartment of Computing Science and Mathematics, University of Stirling, Stirling FK9 4LA, UKFaculty of Natural Sciences, University of Stirling, Stirling FK9 4LA, UKWater hyacinth (<i>Pontederia crassipes</i>, also known as <i>Eichhornia crassipes</i>) 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).https://www.mdpi.com/2072-4292/14/12/2845water hyacinthSentinel-1SARchange detection |
| spellingShingle | Morgan David Simpson Vahid Akbari Armando Marino G. Nagendra Prabhu Deepayan Bhowmik Srikanth Rupavatharam Aviraj Datta Adam Kleczkowski J. Alice R. P. Sujeetha Girish Gunjotikar Anantrao Vidhu Kampurath Poduvattil Saurav Kumar Savitri Maharaj Peter D. Hunter Detecting Water Hyacinth Infestation in Kuttanad, India, Using Dual-Pol Sentinel-1 SAR Imagery Remote Sensing water hyacinth Sentinel-1 SAR change detection |
| title | Detecting Water Hyacinth Infestation in Kuttanad, India, Using Dual-Pol Sentinel-1 SAR Imagery |
| title_full | Detecting Water Hyacinth Infestation in Kuttanad, India, Using Dual-Pol Sentinel-1 SAR Imagery |
| title_fullStr | Detecting Water Hyacinth Infestation in Kuttanad, India, Using Dual-Pol Sentinel-1 SAR Imagery |
| title_full_unstemmed | Detecting Water Hyacinth Infestation in Kuttanad, India, Using Dual-Pol Sentinel-1 SAR Imagery |
| title_short | Detecting Water Hyacinth Infestation in Kuttanad, India, Using Dual-Pol Sentinel-1 SAR Imagery |
| title_sort | detecting water hyacinth infestation in kuttanad india using dual pol sentinel 1 sar imagery |
| topic | water hyacinth Sentinel-1 SAR change detection |
| url | https://www.mdpi.com/2072-4292/14/12/2845 |
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