Latent concepts for area enhancement of mangrove forest: A novel approach through geospatial studies

S R Gowda; S Pazhanivelan; R Kumaraperumal; M Raju; P C Prabu

doi:10.14719/pst.6011

Authors

Sanketh R Gowda Department of Remote Sensing and Geographic Information System, Tamil Nadu Agricultural University, Coimbatore 641 003, India https://orcid.org/0009-0004-8768-6195
S Pazhanivelan Centre for Water and Geospatial Studies, Tamil Nadu Agricultural University, Coimbatore 641 003, India https://orcid.org/0000-0002-3596-3232
R Kumaraperumal Department of Remote Sensing and Geographic Information System, Tamil Nadu Agricultural University, Coimbatore 641 003, India https://orcid.org/0000-0001-6659-9587
M Raju Centre for Water and Geospatial Studies, Tamil Nadu Agricultural University, Coimbatore 641 003, India https://orcid.org/0000-0001-9026-5106
P C Prabu Centre for Water and Geospatial Studies, Tamil Nadu Agricultural University, Coimbatore 641 003, India https://orcid.org/0000-0002-7237-9481

DOI:

https://doi.org/10.14719/pst.6011

Keywords:

geospatial techniques, mangrove, modelling, potential areas

Abstract

Despite their vital roles in carbon sequestration, biodiversity conservation and coastal protection, mangrove ecosystems have historically faced degradation from pollution, deforestation and human activity. Mangrove restoration faces several challenges, including deforestation due to unsustainable logging for timber and fuelwood, as well as habitat loss from coastal development projects such as ports and resorts. The expansion of aquaculture, particularly shrimp farming, has led to the large-scale conversion of mangrove areas into degraded or unproductive land. Huge restoration projects have been started all over the world to deal with these issues. Geospatial technologies such as GIS (Geographic Information System), GPS (Global Positioning System), remote sensing and satellite imagery have made it easier to find suitable sites for restoration, which was a challenging task in the past. These technologies also enable the acquisition of large amounts of data. Topography, soil quality, land use and biodiversity are some of the factors that influence the process of identifying possible restoration sites. Although obstacles like ecosystem complexity, lack of data and methodological constraints still exist, developments in machine learning and radar remote sensing provide promising paths to obtaining vital information. Conservation efforts are being bolstered by data integration and predictive modeling-driven evidence-based rehabilitation strategies. This review examines the cutting-edge geospatial technologies and their critical role in surmounting obstacles and promoting the rehabilitation and re-establishment of mangrove habitats.

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