Utilizing of aerial photography to study the distribution of seaweed in Saphan Hin Park, Mueang District, Phuket Province, Thailand

Main Article Content

Kumlom, T.
Phewphan, U.
Ponganan, N.
Rakasachat, C.

Abstract

Seaweed is essential in ecosystems for producing oxygen and absorbing carbon dioxide, thereby reducing the greenhouse effect. It also provides habitat and food for various aquatic species and helps mitigate coastal erosion. The periodic surveys identified seaweed was done in four periods in January, April, August, and October covered the areas of 897.96 sq.km, 9,164.26 sq.km, 6,462.12 sq.km, and 14,678.95 sq.km, respectively. For Seaweed lumps, the areas were 30.12 sq.km, 310.54 sq.km, 903.28 sq.km, and 1,552.02 sq.km, respectively. The classification results were invaluable for effective natural resource planning and management. While the overall seaweed distribution remained stable, and some areas showed density changes. The resulting maps highlighted the advantages of using UAV aerial snapshots and MLC techniques for accurately identifying seaweed in shallow waters. The findings are anticipated to serve as a model for monitoring changes to support seaweed conservation and restoration and can be applied to other contexts involving natural resource and environmental management.

Article Details

How to Cite
Kumlom, T., Phewphan, U., Ponganan, N., & Rakasachat, C. (2025). Utilizing of aerial photography to study the distribution of seaweed in Saphan Hin Park, Mueang District, Phuket Province, Thailand. International Journal of Agricultural Technology, 21(1), 73–84. retrieved from https://li04.tci-thaijo.org/index.php/IJAT/article/view/4075
Section
Original Study

References

Akkajit, P., Jaileak, K., Suteersak, T. and Prueksakorn, K. (2018). Assessment of heavy metals in sediment at Saphan Hin, Phuket. Chemical Engineering Transactions, 63:301-306.

Chayhard, S., Manthachitra, V., Nualchawee, K. and Buranapratheprat, A. (2018a). Application of unmanned aerial vehicle to estimate seagrass biomass in Kung Kraben Bay, Chanthaburi province, Thailand. International Journal of Agricultural Technology, 14:1107-1114.

Chayhard, S., Manthachitra, V., Nualchawee, K. and Buranapratheprat, A. (2018b). Multi-temporal mapping of seagrass distribution by using integrated remote sensing data in Kung Kraben Bay, Chanthaburi Province, Thailand. International Journal of Agricultural Technology, 14:161-170.

Chen, J., Wang, K., Zhao, X., Cheng, X., Zhang, S., Chen, J. and Li, X. (2023). Satellite imagery-estimated intertidal seaweed biomass using UAV as an intermediary. Remote Sensing, 15:4428.

Congalton, R. G. and Green, K. (2019). Assessing the accuracy of remotely sensed data: Principles and practices (3rd ed.). CRC Press. Retried from https://doi.org/10.1201/9780429052729

Dadon, J. R. and Oldani, J. I. (2017). Interjurisdictional coastal management in metropolitan areas. Ocean & Coastal Management, 148:260-271.

De Kock, M. E., Pohůnek, V. and Hejcmanová, P. (2022). Semi-automated detection of ungulates using UAV imagery and reflective spectrometry. Journal of Environmental Management, 320:115807.

Diruit, W., Le Bris, A., Bajjouk, T., Richier, S., Helias, M., Burel, T. and Ar Gall, E. (2022). Seaweed habitats on the shore: Characterization through hyperspectral UAV imagery and field sampling. Remote Sensing, 14:3124.

FAO (2020). The global status of seaweed production, trade, and utilization. Food and Agriculture Organization of the United Nations. Retried from https://doi.org/10.4060/ca9229en

Krumhansl, K. A., Okamoto, D. K., Rassweiler, A., Novak, M., Bolton, J. J., Cavanaugh, K. C. and and Byrnes, J. E. K. (2016). Global patterns of kelp forest change over the past half-century. Proceedings of the National Academy of Sciences, 113:13785-13790.

Lakshani, M. M. T. B., Thilakarathna, M. K. S., Kumarasinghe, D. C. H. S. and Jayasooriya, R. G. P. T. (2024). Role of seaweed as a biofertilizer. In The Role of Seaweeds in Blue Bioeconomy (pp. 292-311). Bentham Science Publishers. https://doi.org/10.2174/9789815223644124010017

Mamun Abdullah Al, Akhtar, A., Rahman, M. F., Kamal, A. H. M., Karim, N. U. and Hassan, M. L. (2020). Habitat structure and diversity patterns of seaweeds in the coastal waters of Saint Martin’s Island, Bay of Bengal, Bangladesh. Regional Studies in Marine Science, 33:100959.

Matos, J., Cardoso, C., Serralheiro, M. L., Bandarra, N. M. and Afonso, C. (2024). Seaweed bioactives potential as nutraceuticals and functional ingredients: A review. Journal of Food Composition and Analysis, 133:106453.

Mohamed, M. A. (2017). Monitoring of temporal and spatial changes of land use and land cover in metropolitan regions through remote sensing and GIS. Natural Resources, 8:353-369.

Muangsong, C., Phewphan, U., Kongsombat, P., Meengoen, N., Thongdeephan, T., Chanhom, D. and Pumijumnong, N. (2024). Estimation of aboveground carbon stock in service area of Ubon Ratchathani Zoo, Ubon Ratchathani province, Northeastern Thailand. International Journal of Agricultural Technology, 20:197-212.

Nurdin, N., Alevizos, E., Syamsuddin, R., Asis, H., Zainuddin, E. N., Aris, A., Oiry, S., Brunier, G., Komatsu, T. and Barillé, L. (2023). Precision Aquaculture Drone Mapping of the Spatial Distribution of Kappaphycus alvarezii Biomass and Carrageenan. Remote Sensing, 15(14), Article 14. https://doi.org/10.3390/rs15143674

Richards, J. A. (2013). Remote sensing digital image analysis (5th ed.). Springer-Verlag. Retried from https://doi.org/10.1007/978-3-642-30062-2

Román, A., Tovar-Sánchez, A., Olivé, I. and Navarro, G. (2021). Using a UAV-mounted multispectral camera for the monitoring of marine macrophytes. Frontiers in Marine Science, 8. https://doi.org/10.3389/fmars.2021.722698

Singh, M. and Tyagi, K. D. (2021). Pixel-based classification for Landsat 8 OLI multispectral satellite images using deep learning neural network. Remote Sensing Applications: Society and Environment, 24:100645.

Thomsen, M. S., Wernberg, T., South, P. M. and Schiel, D. R. (2016). Non-native seaweeds drive changes in marine coastal communities around the world. In Z.-M. Hu & C. Fraser (Eds.), Seaweed phylogeography: Adaptation and evolution of seaweeds under environmental change. Springer Netherlands, pp.147-185.

Taddia, Y., Russo, P., Lovo, S. and Pellegrinelli, A. (2020). Multispectral UAV monitoring of submerged seaweed in shallow water. Applied Geomatics, 12:19-34.

Waqas, M. A., Hashemi, F., Mogensen, L. and Knudsen, M. T. (2024). Environmental performance of seaweed cultivation and use in different industries: A systematic review. Sustainable Production and Consumption, 48:123-142.