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    Review of 'Multi-Spatiotemporal Analysis of Changes in Mangrove Forests in Palawan, Philippines: Predicting Future Trends Using Support Vector Machine Algorithm and Markov Chain Model'

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    Multi-Spatiotemporal Analysis of Changes in Mangrove Forests in Palawan, Philippines: Predicting Future Trends Using Support Vector Machine Algorithm and Markov Chain ModelCrossref
    Average rating:
        Rated 4 of 5.
    Level of importance:
        Rated 4 of 5.
    Level of validity:
        Rated 4 of 5.
    Level of completeness:
        Rated 4 of 5.
    Level of comprehensibility:
        Rated 3 of 5.
    Competing interests:
    None

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    • Article: found
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    Multi-Spatiotemporal Analysis of Changes in Mangrove Forests in Palawan, Philippines: Predicting Future Trends Using Support Vector Machine Algorithm and Markov Chain Model

    Multi-temporal remote sensing imagery can be used to explore how mangrove assemblages are changing over time and facilitate critical interventions for ecological sustainability and effective management. This study aims to explore the spatial dynamics of mangrove extents in Palawan, Philippines, specifically in Puerto Princesa City (PPC), Taytay, and Aborlan, and facilitate future prediction for Palawan using the Markov Chain model. The multi-date Landsat imageries during the period 1988–2020 were used for this research. The Support Vector Machine algorithm was sufficiently effective for mangrove feature extraction to generate satisfactory accuracy results (>70% Kappa coefficient values; 91% average overall accuracies). In Palawan, a 5.2% (2,693 ha) decrease was recorded during 1988–1998 and an 8.6% increase in 2013–2020 to 4,371 ha. In PPC, 95.9% (2,758 ha) increase was observed during 1988–1998 and 2.0% (136 ha) decrease during 2013–2020. The mangroves in Taytay and Aborlan both gained an additional 2,138 ha (55.3%) and 228 ha (16.8%) during 1988–1998 but also decreased from 2013 to 2020 by 3.4% (247 ha) and 0.2% (3 ha), respectively. However, projected results suggest that the mangrove areas in Palawan will likely increase in 2030 (to 64,946 ha) and 2050 (to 66,972 ha). This study demonstrated the capability of the Markov Chain model in the context of ecological sustainability involving policy intervention. However, since this research did not capture the environmental factors that may had influenced the changes in mangrove patterns, it is suggested the addition of Cellular Automata in future Markovian mangrove modelling.
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      Review information

      10.14293/S2199-1006.1.SOR-EARTH.AATWRS.v1.RJURJZ
      This work has been published open access under Creative Commons Attribution License CC BY 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Conditions, terms of use and publishing policy can be found at www.scienceopen.com.

      Remote sensing,Earth & Environmental sciences,Quantitative & Systems biology,General earth science,Environmental change,Environmental studies
      Change detection,Environmental modelling,Support Vector Machine,Markov Chain Model, Landsat,Environmental science,Spatial dynamics,Image classification,Land use/land cover,Environmental protection

      Review text

      The paper mapped the spatio-temporal trends of mangrove forests in the city of Palawan, Phillipnes using Markov chain model highlighting the response of mangrove forests to policy interventions, thus speaking to the role of protective mechanisms in impacting health and abundance of mangrove forests.

      Overall, the manuscript is a great attempt by Cayetano et al., Following are a few suggestions for the authors' consideration.

      Line 10: I think the authors meant "titled" not "entitled"

      Line 16: Mangrove conservation isnt the right term I feel. One can not conserve mangroves using remote sensing, rather study mangroves and thus promote conservation

      Line 124: This sentence can be improved, reflecting the exact reasons why repeated, accurate on-ground sampling exercises cant be done. For instance, talking about the inaccessibility of mangrove forests, distance from monitoring locations etc, cost associated with the field visits and high technical skills required to navigate these ecosystems make in-situ sampling difficult for mangrove forests.

      Line 125: If the above suggestions are accepted, then consider changing "however" to "thus"

      Line 136-141: Consider rewording "The mangroves of Palawan have been protected under the direct human inventions through the International Union for Conservation of Nature (IUCN) protected area Category I-IV (Long and Giri 2011) and 1992 Republic Act No.7611, commonly known as the Strategic Environmental Plan for Palawan Act (SEP Law, FAO 2021); yet this unique ecosystem remains under threat due to climate change and associated rising sea levels (Gilman et al. 141 2008; Giri et al. 2011)."

      Line 143: replace "for" with "in"

      Line 161-163: sentence hard to understand; may consider rewording

      Line 196-197: Repeated info as Introduction Para 2 Line 4

      Line 285: If the abbreviation has not been elaborated before, then recommend you to write Electromagnetic spectrum here

      Line 371: a brilliant explaination of the Markov tool, nice!

      Line 378: replace "have been" with "is"

      Line 425: consider adding "diagram of multi-temporal mangrove change detection"

      Line 481: Figure description: please do mention the time frame as well

      Line 674: Please elaborate the ECAN abbreviation

      Line 728: replace "caused" to "cause"

      Line 757: replace "may had" with "may be"

      Line 788: replace "becomes slightly shifting" to "starts to shift"

      Line 814: Maybe you meant "vitally important" instead of "viably important"

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