International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

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Volume 8 Issue 4
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Detection, Monitoring, And Mapping of Invasive Species

Author(s) Ms. Mahima M Hebbar, Ms. K U Dikshitha, Dr. Lakshmi Bhaskar
Country India
Abstract Invasive aquatic species pose serious ecological and economic threats by disrupting native biodiversity, degrading water quality, and altering ecosystem dynamics. Early detection is essential to prevent their spread; however, conventional field-based monitoring methods are time consuming, expensive, and spatially limited. This study proposes a satellite-based framework that integrates chlorophyll concentration analysis, geospatial mapping, and machine learning for the detection and monitoring of invasive species in aquatic environments. Chlorophyll data extracted from satellite imagery are preprocessed, georeferenced, and used as input features along with spatial coordinates to train a Support Vector Machine (SVM) classifier. The model achieved a classification accuracy of 99.982%, indicating high separability between invasive and non-invasive regions based on chlorophyll gradients. Spatial visualizations such as heat maps, scatter plots, and histograms revealed clear clustering patterns and invasion hotspots. The findings indicate that chlorophyll concentration serves as a dependable indicator for identifying the presence of invasive species. They further show that combining remote sensing techniques with artificial intelligence enables a monitoring framework that is both scalable and economically efficient. This integrated approach holds significant promise for real-time ecosystem monitoring and contributes to better-informed decision-making in environmental conservation and sustainable resource management.
Keywords Invasive aquatic species, chlorophyll concentration, remote sensing, machine learning, Support Vector Machine (SVM), geospatial analysis, satellite imagery, environmental monitoring, ecosystem management.
Field Engineering
Published In Volume 8, Issue 4, July-August 2026
Published On 2026-07-02
DOI https://doi.org/10.36948/ijfmr.2026.v08i04.82876
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CrossRef DOI prefix of IJFMR is 10.36948/ijfmr

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