172
views
2
recommends
+1 Recommend
0
shares
    • Review: found
    Is Open Access

    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'

    Bookmark
    4
    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 3 of 5.
    Level of validity:
        Rated 4 of 5.
    Level of completeness:
        Rated 4 of 5.
    Level of comprehensibility:
        Rated 4 of 5.
    Competing interests:
    None

    Reviewed article

    • Record: found
    • Abstract: found
    • Article: found
    Is Open Access

    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.
      Bookmark

      Review information

      10.14293/S2199-1006.1.SOR-EARTH.A3RGAV.v1.RLSJNW
      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

      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

      by Xiongjie Deng

       

       

      This manuscript mapped the extent of mangrove forests in Palawan over multiple years using the Support Vector Machine (SVM) method, conducted change detection analysis across three periods, and predicted the trends of mangrove forests based on the Markov Chain model in the future. The generated accuracies demonstrated satisfactory classification results, and the Markov Chain model was evaluated to be a helpful tool for projecting mangrove forest areas in Palawan. Furthermore, I enjoy the analyses that involve policies and management interventions.

       

       

      Still, I notice that several same descriptions are in different format. For example, “modeling” in line 420 but “modelling” in lines 87, 380, Figure 2, etc.; “e.g.” are in italic type in line 128 and 146, etc., but are in roman type in line 151 and 153, etc. I would be really delighted if the authors could keep the style consistent across the whole article. Besides, for the entire article, I think it would be better to add a comma behind “et al.” and the author’s name, for example, (Brown et al., 2006; Mukherjee et al., 2014) (line 94), (Ball and Pidsley, 1995) (line 96).

       

       

      What’s more, I find some errors in this manuscript, and please find my suggestions and doubts below:

       

      Line 85: I think “may had” should be “may have”.

       

      Line 100: I think the comma behind “intrusion” is redundant.

       

      Line 124: The phrase “to do” may be wordy, consider removing it.

       

      Line 149: Perhaps there should be a comma between “technique” and “training”; consider modifying “time consuming” to “time-consuming”.

       

      Line 148 - 150: It confused me that you specified “Landsat imagery”. I agree that extracting training samples is time-consuming when using supervised classification methods, but I do not think it is only for Landsat imagery, so I would advise you to modify “Landsat imagery” to a more general term, like remotely sensed imagery.

       

      Line 154: I think you should add “of” between “one” and “many”.

       

      Line 167: Perhaps you should modify “(c)” to “(3)” since you used “(1)” and “(2)” before.

       

      Line 178: I think “borders” should be “border”.

       

      Line 193: It seems the “ecosystem” should be in plural format.

       

      Line 226, 243, 249, 259, 272, 391: It looks like you typed the letter “x” instead of the multiplication sign “×”.

       

      Line 254: The “Lmin – (Lmax Lmin)” confused me, I guess you want to explain Qmin and Qmax here?

       

      Line 319: Perhaps “was” should be “were”.

       

      Line 344: The comma behind “where” may be unnecessary.

       

      Line 358, 360: Please keep both “Kappa” consistent.

       

      Line 361: It seems that “qualify” does not agree with the subject.

       

      Line 420 – 426: I would advise you to move this part to the beginning of Section 2.

       

      Figure 2: In the left box, I would advise you to modify “7 ETM+” to “Landsat 7 ETM+”; you mentioned LULC classification using SVM in this figure, but in the title, you missed this part, so I would advise you to describe it more specifically.

       

      Line 438: Perhaps “were” should be “was”.

       

      Line 445: Perhaps “are” should be “is”.

       

      Figure 4: As I understand, the left y-axis is for Palawan, and the right y-axis is for the other three cities. If so, I would advise you to specify it in the title of this figure, or consider mapping them separately. The original figure is confusing to me.

       

      Figure 5: I would advise you to add ticks to the y-axis.

       

      Figure 6: Please add a legend to indicate bars in different colours.

       

      Line 493: I think it would be more precise to say “SPOT satellite sensor’s data” or “SPOT satellite sensor’s images”.

       

      Line 494: Perhaps “Based on”.

       

      Line 521: “in” may be unnecessary.

       

      Table 2: Is it normal that the estimates in 2018 and 2020 from this study are exactly the same in Puerto Princesa City and Taytay?

       

      Line 537, 538: The first sentence is ambitious to me, I guess you tried to mean that the total mangrove forests extent in Puerto Princesa City at 3,201.8 ha in 2003 was estimated by Pagkalinawan and Ramos (2013)? If so, I would advise you to modify the place of the term “in 2003” because if it presents at the beginning of the sentence, it may mislead readers that Pagkalinawan and Ramos conducted their research in 2003.

       

      Line 562 - 564: I only found “WRSP/R” information in Table 2; I would advise you to add cloud cover percentages of the two images you mentioned to make this sentence more compelling.

       

      Figure 8 (a) and (b), (c) and (d): It will be better if the x-axis of (b) and (d) can align with the x-axis of (a) and (c), respectively.

       

      Line 757: I think “had” is not in the correct form.

       

      Line 763: It seems that “presumed” does not appear to be in the proper form.

       

      Line 764: I think the “is” after “there” is not in the correct form.

       

      Line 774: It seems the “and” before “infrastructure” is unnecessary.

       

      Line 788: The word “shifting” may be in the wrong form.

       

      Line 805: I think it would be more precise to add “an” before “increase”.

       

      Line 812: It seems that “continues” should be “continue”.

       

      Line 819 - 823: You state that integrating Cellular Automata in Markov Chain modelling can evaluate the impacts of different policies. Still, I suggest you to explain why you recommend future research should integrate the Cellular Automata in Markov Chain modelling more specifically, for example, you can provide more details about the advantages, capabilities, and effectiveness of Cellular Automata in mangroves-related research to assess policies.

       

      Line 830: Two “also” in a sentence seem unnecessary.

      Comments

      Comment on this review