Remote Sensing and Invasive Plants in Coastal Ecosystems: What We Know So Far and Future Prospects

Priscila Villalobos Perna, Mirko Di Febbraro, Maria Laura Carranza (), Flavio Marzialetti and Michele Innangi
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Priscila Villalobos Perna: Envix-Lab, Department of Biosciences and Territory, Molise University, Contrada Fonte Lappone, snc, 86090 Pesche, Italy
Mirko Di Febbraro: Envix-Lab, Department of Biosciences and Territory, Molise University, Contrada Fonte Lappone, snc, 86090 Pesche, Italy
Maria Laura Carranza: Envix-Lab, Department of Biosciences and Territory, Molise University, Contrada Fonte Lappone, snc, 86090 Pesche, Italy
Flavio Marzialetti: Envix-Lab, Department of Biosciences and Territory, Molise University, Contrada Fonte Lappone, snc, 86090 Pesche, Italy
Michele Innangi: Envix-Lab, Department of Biosciences and Territory, Molise University, Contrada Fonte Lappone, snc, 86090 Pesche, Italy

Land, 2023, vol. 12, issue 2, 1-16

Abstract: Coastal environments are highly threatened by invasive alien plants (IAP), and Remote Sensing (RS) may offer a sound support for IAP detection and mapping. There is still a need for an overview of the progress and extent of RS applications on invaded coasts that can help the development of better RS procedures to support IAP management. We conducted a systematic literature review of 68 research papers implementing, recommending, or discussing RS tools for IAP mapping in coastal environments, published from 2000 to 2021. According to this review, most research was done in China and USA, with Sporobolus (17.3%) being the better studied genus. The number of studies increased at an accelerated rate from 2015 onwards, coinciding with the transition from RS for IAP detection to RS for invasion modeling. The most used platforms in the 2000s were aircraft, with satellites that increased from 2005 and unmanned aerial vehicles after 2014. Frequentist inference was the most adopted classification approach in the 2000s, as machine learning increased after 2009. RS applications vary with coastal ecosystem types and across countries. RS has a huge potential to further improve IAP monitoring. The extension of RS to all coasts of the world requires advanced applications that bring together current and future Earth observation data.

Keywords: passive sensors; active sensors; invasion ecology; literature metadata; coastal ecosystem types; spatial and spectral resolution; life forms; analysis algorithms (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2023
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