Classification Methods for Mapping Mangrove Extents and Drivers of Change in Thanh Hoa Province, Vietnam during 2005-2018
Versions
- 2020-04-26 (2)
- 2020-04-26 (1)
Additional Files
Deprecated: json_decode(): Passing null to parameter #1 ($json) of type string is deprecated in /home/journal33/public_html/plugins/generic/citations/CitationsPlugin.inc.php on line 49
Mangrove forests have been globally recognised as their vital functions in preventing coastal erosion, mitigating effects of wave actions and protecting coastal habitats and adjacent shoreline land-uses from extreme coastal events. However, these functions are under severe threats due to the rapid growth of population, intensive shrimp farming and the increased intensity of severe storms in Hau Loc and Nga Son districts, Thanh Hoa province. This research was conducted to monitor spatial-temporal changes in mangrove extents using Landsat and Sentinel imageries from 2005 to 2018. Unsupervised and supervised classification methods and vegetation indices were tested to select the most suitable classification method for study sites, then to quantify mangrove extents and their changes in selected years. The findings show that supervised classification was the most suitable in study sites compared to vegetation indices and unsupervised classification. Mangrove forest extents increased by 7.5 %, 38.6 %, and 47.8 % during periods of 2005 - 2010, 2010 - 2015 and 2015 - 2018, respectively. An increase of mangrove extents resulted from national programs of mangrove rehabilitation and restoration during 2005- 2018, increased by 278.0 ha (123.0 %).
Abdullah, K., Said, A. M., & Omar, D. (2014). Community-based conservation in managing mangrove rehabilitation in Perak and Selangor. Procedia-Social and Behavioral Sciences, 153, 121-131. doi: https://doi.org/10.1016/j.sbspro.2014.10.047
Aheto, D. W., Kankam, S., Okyere, I., Mensah, E., Osman, A., Jonah, F. E., & Mensah, J. C. (2016). Community-based mangrove forest management: Implications for local livelihoods and coastal resource conservation along the Volta estuary catchment area of Ghana. Ocean and Coastal Management, 127, 43-54. doi: https://doi.org/10.1016/j.ocecoaman.2016.04.006
Alsaaideh, B., Al-Hanbali, A., Tateishi, R., Kobayashi, T., & Hoan, N. T. (2013). Mangrove forests mapping using Landsat ETM+ with DEM. Journal of Geographic Information System, 5, 369-377. doi: https://doi.org/10.4236/jgis.2013.54035
Agarwal, N., Bonino, C., Deligny, A., Festa, C., Ghislain, M., Homolova, K., Velasquez, A. K., Kurtev, L., Pinto, A. O., Virat, V., Serban-Penhoat, J., & Thomas, M. (2019). Getting the shrimp’s share mangrove deforestation and shrimp consumption assessment and alternatives. Sciences Po- Paris School of International Affairs (IDDRI), 102pp
Batadlan, B. D., Paringit, E. C., Santillan, J. R., Caparas, A. S., & Fabila, J. L. (2009). Analysis of background variations in computed spectral vegetation indices and its implications for mapping mangrove forests using satellite imagery. In 4th ERDT Conference, Manila, Philippines.
Buffle, P., Nguyen, T. Y., & Morten, F. T. (2011). Community-based Mangrove Reforestation and Management in Da Loc, Vietnam. Ecosystems and livelihoods adaptation network (ELAN). 11p
Chen, B., Xiao, X., Li, X., Pan, X., Doughty, R., Ma, J., Dong, J., Qin, Y., Zhao, B., Wu, Z., Sun, R., Lan, G., Xie, G., Clinton, N., & Giri, C. (2017). A mangrove forest map of China in 2015: Analysis of time series Landsat 7/8 and Sentinel 1A imagery in Google Earth Engine cloud computing platform. ISPRS Journal of Photogrammetry and Remote Sensing. 131, 104- 210. doi: https://doi.org/10.1016/j.isprsjprs.2017.07.011
Dat, P. T., Yoshino, K., Le, N. N., & Bui, D. T. (2018). Estimating aboveground biomass of a mangrove plantation on the Northern coast of Vietnam using machine learning techniques with an integration of ALOS-2 PALSAR-2 and Sentinel-2A data. International Journal of Remote Sensing, 39(22), 7761-7788. doi: https://doi.org/10.1080/01431161.2018.1471544
Dat, P. T., Anh, N. K., & Yoshino, K. (2000). Mapping wetland cover types using remote sensing and GIS in Can Gio Mangrove Biosphere Reserve, Vietnam. Lecture note in Earth Science: 66-74
Datta, D., Chattopadhyyay, R. N., & Guha, P. (2012). Community based mangrove management: a review on status and sustainability. Journal of Environmental Management, 107, 84-95. doi: https://doi.org/10.1016/j.jenvman.2012.04.013
Duke, N., Nagelkerken, I., Agardy, T., Wells, S., & Van Lavieren, H. (2014). The importance of mangroves to people: a call to action. United Nations Environment Programme World Conservation Monitoring Centre (UNEP-WCMC3). 128pp
Duke, N., Wilson, N., Mackenzie, J. R., Hai-Hoa, N., & Pullar, D. (2010). Assessing mangrove forests, shoreline condition and feasibility of REDD for Kien Giang province, Vietnam. Technical Report. 137pp. doi: 10.13140/RG.2.1.1032.5367
Exner, A., Fleissner, P., Kranzl, L., & Zitel, W. (2014). Land and resource scarcity: Capitalism, struggle and well-being in a world without fossil fuels. Routledge Taylor and Francis Group. 320pp
Field, C., Osborn, J., Hoffman, L., Polsenberg, J., Ackerly, D., Berry, J., Bjorkman, O., Held, A., Matson, P., & Mooney, H. (1998). Mangrove biodiversity and ecosystem function. Global Ecology & Biogeography Letters, 7(1), 3-14. doi: 10.2307/2997693
Green, E. P., Clark, C. D., Mumby, P. J., Edwards, A. J., & Ellis, A. C. (1998). Remote sensing techniques for mangrove mapping. International Journal of Remote Sensing, 19(5), 935-956. doi: https://doi.org/10.1080/014311698215801
Gupta, K., Mukhopadhyay, A., Giri, S., Chanda, A., Majumdar, S. D., Samanta, S., & Hazra, S. (2018). An index for discrimination of mangroves from non-mangroves using LANDSAT 8 OLI imagery. MethodsX, 5, 1129-1139. doi:https://doi.org/10.1016/j.mex.2018.09.011
Ha,T. T., Van, D. P. H., & Visser, L. (2014). Impacts of changes in mangrove forest management practices on forest accessibility and livelihood: A case study in mangrove-shrimp farming system in Ca Mau Province, Mekong Delta, Vietnam. Land Use Policy, 36, 89-101. doi: https://doi.org/10.1016/j.landusepol.2013.07.002
Hai-Hoa, N. (2016). Using Landsat imagery and vegetation indices differencing to detect mangrove change: A case in Thai Thuy district, Thai Binh province. Journal of Forest Science and Technology, 5, 59-66.
Hai-Hoa, N. (2014). The relation of coastal mangrove changes and adjacent land-use: A review in Southeast Asia and Kien Giang, Vietnam. Ocean and Coastal Management, 90, 1-10. doi: https://doi.org/10.1016/j.ocecoaman.2013.12.016
Hawkins, S., To, P. X., Phuong, P. X., Thuy, P. T., Tu, N. D., Cuong, C. V., Brown, S., Dart, P., Robertson, S. M., Vu, N., & McNally, R. (2010). Roots in the Water: Legal Frameworks for Mangrove PES in Vietnam. Katoomba Group's Legal Initiative Country Study Series. Forest Trends: Washington, DC. 55pp
Hoa, S. L. T., Suzuki, R., & Thomsen, M. F. (2012). Adapting to natural disasters and contributing to climate change mitigation: mangrove community forestry in Viet Nam. Sharing Lessons on Mangrove Restoration. Proceedings and a Call Action from an MFF Regional Colloquium 30- 31 August 2012, Mamallapuram, India, 265-275.
Hong, P. N., & San, H. T. (1993). Mangroves of Vietnam. IUCN, Vol. 7.
Islam, M. M., Borgqvist, H., & Kumar, L. (2018). Monitoring mangrove forest land cover changes in the coastline of Bangladesh from 1976 to 2015. Geocarto International, 34(13), 1458-1476. doi: https://doi.org/10.1080/10106049.2018.1489423
International Federation of Red Cross and Red Crescent Societies. (2011). Breaking the waves: Impact analysis of coastal afforestation for disaster risk reduction in Vietnam. 60pp
Jiang, Z., Raghavan, S. V., Hur, J., Sun, Y., Liong, S., Nguyen, V. Q., & Dang, T. V. P. (2018). Future changes in rice yields over the Mekong River Delta due to climate change- alarming or alerting? Theoretical and Applied Climatology, 137, 545- 555. doi:https://doi.org/10.1007/s00704-018-2617-z
Kongwongjan, J., Suwanprasit, C., & Thongchumnum, P. (2012). Comparison of vegetation indices for mangrove mapping using THEOS data. Proceedings of the Asia-Pacific Advanced Network, 33, 56-64.
Kongkeaw, C., Kittitornkool, J., Vadergeest, P., & Kittiwatanawong, K. (2019). Explaining success in community based mangrove management: Four coastal communities along the Andaman Sea, Thailand. Ocean and Coastal Management, 178, doi: https://doi.org/10.1016/j.ocecoaman.2019.104822
Lee, S. Y., Primavera, J. H., Dahdouh-Guesbas, F., Mckee, K., Bosire, J. O., Cannicci, S., & Mendelssohn, I. (2014). Ecological role and services of tropical mangrove ecosystems: A reassessment. Global Ecology and Biogeography, 23(7), 726-743. doi:https://doi.org/10.1111/geb.12155
Li, P., Jiang, L., & Feng, Z. (2013). Cross-comparison of vegetation indices derived from Landsat-7 enhanced thematic mapper plus (ETM+) and Landsat-8 operational land imager (OLI) sensors. Remote Sensing, 6(1), 310-329. doi: https://doi.org/10.3390/rs6010310
Long, J. B., & Giri, C. (2011). Mapping the Philippines’ mangrove forests using Landsat imagery. Sensors, 11(3), 2972-2981. doi: https://doi.org/10.3390/s110302972
Lu, D., Mausel, P., Brondizio, E., & Morab, E. (2004). Change detection techniques. International Journal of Remote Sensing, 25(12), 2365-2401. doi: https://doi.org/10.1080/0143116031000139863
Muhsoni, F. F., Sambah, A., Mahmudi, M., & Wiadnya, D. (2018). Comparison of different vegetation indices for assessing mangrove density using sentinel-2 imagery. Int. J. Geomate, 14, 42-51. doi: https://doi.org/10.21660/2018.45.7177
Norjamaki, I., & Tokola, T. (2007). Comparison of atmospheric correction methods in mapping timber volume with multi-temporal Landsat images in Kainuu, Finland. Photogrammetric Engineering & Remote Sensing, 73(2), 155-163. doi:https://doi.org/10.14358/PERS.73.2.155
Peneva-Reed, E. (2014). Understanding land-cover change dynamics of a mangrove ecosystem at the village level in Krabi Province, Thailand, using Landsat data. GIScience & Remote Sensing, 51(4), 403-426. doi: https://doi.org/10.1080/15481603.2014.936669
Pham, T. T., Bennet, K., Vu, T. P., Brunner, J., Le, N. D., & Nguyen, D. T. (2013). Payments for forest environmental services in Vietnam: from policy to practice. Occasional Paper 93. Borgor, Indonesia, CIFOR. 96pp
Phuc, T. X., Nghi, T. H., & Zagt, R. (2013). Forest land allocation in Viet Nam: implementation processes and results. Tropenbos International Vietnam: 1-10.
Phuc, T. X., & Nghi, T. H. (2014). Forest land allocation in the context of forestry sector restructuring: opportunities for forestry development and upland livelihood improvement, Vietnam. Tropenbos International Vietnam. 86pp
Primavera, J. H. (2000). Development, and conservation of Philippine mangroves: institutional issues. Ecological Economics, 35(1), 91-106. doi: https://doi.org/10.1016/S0921-8009(00)00170-1
The Prime Minister. (2015). Approving the project on protection and development of coastal forests to cope with climate change in 2015-2020 period. Decision No 120/QĐ-Ttg, dated 22 January 2015. 32pp
Quang, N. V., & Noriko, S. (2008). Forest allocation policy and level of forest dependency of economic household groups: A case study in northern central Vietnam. Small-scale Forestry, 7(1), 49-66. doi:https://doi.org/10.1007/s11842-008-9040-8
Raghavan, S. V., Vu, M. T., & Liong, S. Y. (2015). Regional climate simulations over Vietnam using the WRF model. Theoretical and Applied Climatology, 126(1-2), 161–182. doi: https://doi.org/10.1007/s00704-015-1557-0
Ramdani, F., Rahman, S., & Giri, C. (2018). Principal polar spectral indices for mapping mangroves forest in South East Asia: study case Indonesia. International Journal of Digital Earth, 12, 1103-1117. doi: https://doi.org/10.1080/17538947.2018.1454516
Rogan, J., & Chen, D. (2004). Remote sensing technology for mapping and monitoring land-cover and land-use change. Progress in Planning, 61(4), 301-325. doi: https://doi.org/10.1016/S0305-9006(03)00066-7
Reed, S. O., Nghi, N. V., Minh, N. A., Lien, H. T. K., Hung, T. M., Thien, N. V., & Anh, N. K. (2015). Building Coastal Resilience in Vietnam: An integrated, community-based approach to mangrove management, disaster risk reduction, and climate change adaptation. CARE international in Vietnam. 80pp
Richards, D. R., & Friess, D. A. (2016). Rates and Drivers of mangrove deforestation in Southeast Asia, 2000- 2012. Proceedings of the National Academy of Sciences of the United States of America (PNAS), 113(2), 344-349. doi:https://doi.org/10.1073/pnas.1510272113
Salem, M. E., & Mercer, D. E. (2012). The economic value of mangroves: A meta-analysis. Sustainability, 4(3), 359-383. doi: https://doi.org/10.3390/su4030359
Saleh, M. (2007). Mangrove vegetation on Abu Minqar Island of the Red Sea. International Journal of Remote Sensing, 28(23), 5191-5194. doi:https://doi.org/10.1016/j.jaridenv.2006.05.016
Singh, A. (1989). Review article digital change detection techniques using remotely-sensed data. International Journal of Remote Sensing, 10(6), 989-1003. doi:https://doi.org/10.1080/01431168908903939
Song, C., Woodcock, C. E., Seto, K. C., Lenney, M. P., & Macomber, S. A. (2001). Classification and change detection using Landsat TM data: when and how to correct atmospheric effects. Remote Sensing of Environment, 75(2), 230-244. doi: https://doi.org/10.1016/S0034-4257(00)00169-3
Sommerville, M. (2016). Mangrove payment for environmental services in Vietnam: Opportunities and challenges. Washington, DC: USAID Tenure and Global Climate Change Program. 34pp
Thanh Hoa DARD (Department of Agriculture and Rural Development). (2018). Reviewing coastal mangrove forest land in districts to participate in projects to restore and develop coastal protective forests. Report No.62/BC-SNN&PTNT (In Vietnamese).
Tran Thi, V., Tien Thi Xuan, A., Phan Nguyen, H., Dahdouh, F., & Koedam, N. (2014). Application of remote sensing and GIS for detection of long-term mangrove shoreline changes in Mui Ca Mau, Vietnam. Biogeosciences, 11, 3781-3795. doi: https://doi.org/10.5194/bg-11-3781-2014
Treadal, L. T., & Vedeld, P. O. (2017). Livelihoods and land uses in environmental policy approaches: the case of PES and REDD+ in the Lam Dong province of Vietnam. Forest, 8, 39. doi:https://doi.org/10.3390/f8020039
Van Lavieren, H., Spalding, M., Alongi, D. M., Kainuma, M., Clusener-Godt, M., & Adeel, Z. (2012). Securing the future of mangroves. A policy brief. UNU-INWEH, UNESCO-MAB with ISME, ITTO, FAO, UNEP-WCMC and TNC. 53pp
Viswanathan, P. K., Pathak, K. D., & Mehta, I. (2011). Socio-economic and ecological benefits of mangrove plantation: A study of community based mangrove restoration activities in Gujarat. Gujarat Institute of Development Research. 164p.
Wang, F. M., Huang, J. F., Tang, Y. L., & Wang, X. Z. (2007). New vegetation index and its application in estimating leaf area index of rice. Rice Science, 14(3), 195-203. doi: https://doi.org/10.1016/S1672-6308(07)60027-4
Wang, Y., Bonynge, G., Nugranad, J., Traber, M., Ngusaru, A., Tobey, J., & Makota, V. (2003). Remote sensing of mangrove change along the Tanzania coast. Marine Geodesy. 26(1-2), 35-48. doi: https://doi.org/10.1080/01490410390181243
Xia, Q., Qin, C., Li, H., Huang, C., & Su, F. (2018). Mapping mangrove forests based on multi-tidal high resolution satellite imagery. Remote Sens, 10, 1343. doi:https://doi.org/10.3390/rs10091343
Zhang, X., Treitz, P. M., Chen, D., Quan, C., Shi, L., Li, Z. (2017). Mapping mangrove forests using multi-tidal remotely-sensed data and a decision-tree based procedure. Int J Appl Earth Obs Geoinformation, 62, 201-214. doi:https://doi.org/10.1016/j.jag.2017.06.010
Zhang, K., Dong, X., Liu, Z., Gao, W., Hu, Z., & Wu, G. (2019). Mapping flats with Landsat 8 images and Google Earth Engine: A case study of the China’s Eastern coast zone circa 2015. Remote Sensing, 11, 924. doi: https://doi.org/10.3390/rs11080924
Copyright (c) 2020 Forest and Society
This work is licensed under a Creative Commons Attribution 4.0 International License.
This is an open access journal which means that all contents is freely available without charge to the user or his/her institution. Users are allowed to read, download, copy, distribute, print, search, or link to the full texts of the articles in this journal without asking prior permission from the publisher or the author. This is in accordance with the BOAI definition of open access.
Submission of an article implies that the work described has not been published previously (except in the form of an abstract or as part of a published lecture or academic thesis), that it is not under consideration for publication elsewhere, that its publication is approved by all authors and tacitly or explicitly by the responsible authorities where the work was carried out, and that, if accepted, will not be published elsewhere in the same form, in English or in any other language, without the written consent of the Publisher. An article based on a section from a completed graduate dissertation may be published in Forest and Society, but only if this is allowed by author's(s') university rules. The Editors reserve the right to edit or otherwise alter all contributions, but authors will receive proofs for approval before publication.
Forest and Society operates a CC-BY 4.0 © license for journal papers. Copyright remains with the author, but Forest and Society is licensed to publish the paper, and the author agrees to make the article available with the CC-BY 4.0 license. Reproduction as another journal article in whole or in part would be plagiarism. Forest and Society reserves all rights except those granted in this copyright notice