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LIU Dazhao, LI Shanshan, FU Dongyang, SHEN Chunyan. Remote sensing analysis of mangrove distribution and dynamics in Zhanjiang from 1991 to 2011[J]. HaiyangYuHuZhao, 2018, 36(5): 1597-1603

Remote sensing analysis of mangrove distribution and dynamics in Zhanjiang from 1991 to 2011

LIU Dazhao1, LI Shanshan2, FU Dongyang1, SHEN Chunyan1
1 Guangdong Ocean University, Zhanjiang 524088, China;
2 School of Tourism and Geographical Sciences, Guangdong University of Finance & Economics, Guangzhou 510320, China
Mangrove forests provide valuable societal and ecological services and goods. However, they have been experiencing high annual rates of loss in many parts of the world. In order to evaluate a long-term wetland conservation strategy that compromises urban development with comprehensive wetland ecosystem management, remote sensing techniques were used to analyze the changing mangrove distribution in the Zhanjiang Mangrove Forest National Nature Reserve. Between 1991 and 2000, the mangrove area within the study region declined from 2 264.9 to 2 085.9 ha consistent with an annual decrease of 0.79%. However, there was an overall 34.3% increase in mangrove coverage from 2 085.9 to 2 801.8 ha between 2000 and 2011. Major causes of forest loss include local human pressures in the form of deforestation, conversion to agriculture, and natural forces such as erosion. The recent gain in mangrove forest cover is attributed to effective conservation management in the nature reserve area, including intensive mangrove plantation efforts and increased local awareness of wetland conservation.
Key words:    mangrove|landsat TM/ETM+|HJ-1A|conservation|remote sensing   
Received: 2017-02-19   Revised:
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Alongi D M. 2002. Present state and future of the world's mangrove forests. Environ. Conserv., 29(3):331-349.
Alongi D M. 2008. Mangrove forests:resilience, protection from tsunamis, and responses to global climate change.Estuarine Coastal Shelf Sci., 76(1):1-13.
Carney J, Gillespie T W, Rosomoff R. 2014. Assessing forest change in a priority West African mangrove ecosystem:1986-2010. Geoforum, 53:126-135.
Cornforth W A, Fatoyinbo T E, Freemantle T P et al. 2013.Advanced land observing satellite phased array type L-Band SAR (ALOS PALSAR) to inform the conservation of mangroves:Sundarbans as a case study. Remote Sens., 5(1):224-237.
Gao X M, Han W D, Liu S Q. 2009. The mangrove and its conservation in Leizhou Peninsula, China. J. Fores. Res., 20(2):174-178.
Giri C, Long J, Abbas S et al. 2015. Distribution and dynamics of mangrove forests of South Asia. J. Environ. Manage., 148:101-111.
Giri C, Ochieng E, Tieszen L L et al. 2011. Status and distribution of mangrove forests of the world using earth observation satellite data. Global Ecol. Biogeogr., 20(1):154-159.
Giri C, Pengra B, Zhu Z L et al. 2007. Monitoring mangrove forest dynamics of the Sundarbans in Bangladesh and India using multi-temporal satellite data from 1973 to 2000. Estuarine Coastal Shelf Sci., 73(1-2):91-100.
Glaser M. 2003. Interrelations between mangrove ecosystem, local economy and social sustainability in Caeté Estuary, North Brazil. Wetlands Ecol. Manage., 11(4):265-272.
Han W D, Gao X M. 2009. The Mangrove Ecosystem and Its Conservation Strategy in Leizhou Peninsula. South China University of Technology Press, Guangzhou, China. (in Chinese)
Jones T G, Glass L, Gandhi S et al. 2016. Madagascar's mangroves:quantifying nation-wide and ecosystem specific dynamics, and detailed contemporary mapping of distinct ecosystems. Remote Sens., 8(2):106.
Kanniah K D, Sheikhi A, Cracknell A P et al. 2015. Satellite images for monitoring mangrove cover changes in a fast growing economic region in southern peninsular Malaysia. Remote Sens., 7(11):14 360-14 385.
Kovacs J M, Wang J F, Flores-Verdugo F. 2005. Mapping mangrove leaf area index at the species level using IKONOS and LAI-2000 sensors for the Agua Brava Lagoon, Mexican Pacific. Estuarine Coastal Shelf Sci., 62(1-2):377-384.
Lee T M, Yeh H C. 2009. Applying remote sensing techniques to monitor shifting wetland vegetation:a case study of Danshui River estuary mangrove communities, Taiwan.Ecol. Eng., 35(4):487-496.
Li C G. 2013. Research on Remote Sensing Information Extraction and the Evolution Mechanism of Mangrove.Science Press, Beijing, China. (in Chinese)
Li M S, Mao L J, Shen W J et al. 2013. Change and fragmentation trends of Zhanjiang mangrove forests in southern China using multi-temporal Landsat imagery(1977-2010). Estuarine Coastal Shelf Sci., 130:111-120.
Li T H, Han P, Zhao Z J. 2008. Impact Analysis of coastal engineering projects on mangrove wetland area change with remote sensing. China Ocean Eng., 22(2):347-358.
Nascimento W R Jr, Souza-Filho P W M, Proisy C et al. 2013.Mapping changes in the largest continuous Amazonian mangrove belt using object-based classification of multisensor satellite imagery. Estuarine Coastal Shelf Sci., 117:83-93.
Porwal M C, Padalia H, Roy P S. 2012. Impact of tsunami on the forest and biodiversity richness in Nicobar Islands(Andaman and Nicobar Islands), India. Biodivers.Conserv., 21(5):1 267-1 287.
Proisy C, Couteron P, Fromard F. 2007. Predicting and mapping mangrove biomass from canopy grain analysis using Fourier-based textural ordination of IKONOS images. Remote Sens. Environ., 109(3):379-392.
Satapathy D R, Krupadam R J, Kumar L P et al. 2007. The application of satellite data for the quantification of mangrove loss and coastal management in the Godavari estuary, East Coast of India. Environ. Monit. Assess., 134(1-3):453-469.
Satyanarayana B, Koedam N, De Smet K et al. 2011. Longterm mangrove forest development in Sri Lanka:early predictions evaluated against outcomes using VHR remote sensing and VHR ground-truth data. Mar. Ecol.Prog. Ser., 443:51-63.
Seto K C, Fragkias M. 2007. Mangrove conversion and aquaculture development in Vietnam:a remote sensingbased approach for evaluating the Ramsar Convention on Wetlands. Global Environ. Change, 17(3-4):486-500.
Shapiro A C, Trettin C C, Küchly H, Alavinapanah S, Bandeira S. 2013. The mangroves of the Zambezi delta:increase in extent observed via satellite from 1994 to 2013. Remote Sens., 7(12):16 504-16 518.
Souza Filho P W M, Farias Martins E D S, Da Costa F R. 2006.Using mangroves as a geological indicator of coastal changes in the Bragança macrotidal flat, Brazilian Amazon:a remote sensing data approach. Ocean Coastal Manage., 49(7-8):462-475.
Wang L, Sousa W P, Gong P et al. 2004. Comparison of IKONOS and QuickBird images for mapping mangrove species on the Caribbean coast of Panama. Remote Sens.Environ., 91(3-4):432-440.