Remote Sensing Based Spatial-Temporal Monitoring of the Changes in Coastline Mangrove Forests in China over the Last 40 Years

As a developing country, China’s mangrove landscape pattern has undergone significant temporal and spatial changes over the last four decades. However, we know little about the changes in the mangrove landscape pattern characteristics other than the area at the national scale. The analysis of mangrove landscape pattern changes from different perspectives on a national scale can provide scientific support for mangrove protection and restoration. In this study, the temporal and spatial changes in the pattern of the mangrove landscape over the last 40 years in China were analyzed based on remote sensing data with high classification accuracy (99.3% of 2018). First, according to the natural geographical conditions of the coastal zone and the distribution of the mangroves, the distribution area of the mangroves in China was divided into 31 natural shores. Then, by selecting representative landscape indexes and constructing an integrated landscape index, the spatial-temporal changes in the landscape pattern of China’s mangroves over the last 40 years were analyzed based on five perspectives: Total area change, shape complexity, connectivity, fragmentation, and the integrated state of the landscape. From a temporal viewpoint, before 2000, the total area of each shore exhibited a downward trend, and the degree of connectivity deteriorated continuously, but the degree of fragmentation was stable at a low level. After 2000, although the total area improved, the degree of fragmentation gradually increased. The spatial changes are mainly reflected by the fact that the shores in Guangdong and Hainan exhibited significant differences within the same province. Based on the above analysis, corresponding scientific suggestions are proposed from temporal and spatial viewpoints to provide guidance for mangrove management and protection in China and to provide a reference for mangrove research in other regions of the world.

[1]  U. Krumme,et al.  Decadal trends in mangrove and pond aquaculture cover on Hainan (China) since 1966: mangrove loss, fragmentation and associated biogeochemical changes , 2020 .

[2]  P. Lin.  A review on the mangrove research in China , 2001 .

[3]  Hae-Sang Park,et al.  A simple and fast algorithm for K-medoids clustering , 2009, Expert Syst. Appl..

[4]  Yuyu Wang,et al.  Mapping the potential of mangrove forest restoration based on species distribution models: A case study in China. , 2020, The Science of the total environment.

[5]  M. Kanninen,et al.  Mangroves among the most carbon-rich forests in the tropics , 2011 .

[6]  G. Lin,et al.  Recent progresses in mangrove conservation, restoration and research in China , 2009 .

[7]  I. Valiela,et al.  Mangrove Forests: One of the World's Threatened Major Tropical Environments , 2001 .

[8]  Catherine Ticehurst,et al.  Mapping the multi-decadal mangrove dynamics of the Australian coastline , 2020, Remote Sensing of Environment.

[9]  Farid Dahdouh-Guebas,et al.  Dynamics in mangroves assessed by high-resolution and multi-temporal satellite data: a case study in Zhanjiang Mangrove National Nature Reserve (ZMNNR), P. R. China , 2013 .

[10]  Nan Xu,et al.  Advancing the Mapping of Mangrove Forests at National-Scale Using Sentinel-1 and Sentinel-2 Time-Series Data with Google Earth Engine: A Case Study in China , 2020, Remote. Sens..

[11]  Run Wang,et al.  Evaluating the Performance of Sentinel-2, Landsat 8 and Pléiades-1 in Mapping Mangrove Extent and Species , 2018, Remote. Sens..

[12]  R. Lucas,et al.  Aberystwyth University Distribution and Drivers of Global Mangrove Forest Change, 1996-2010 , 2017 .

[13]  Masanobu Shimada,et al.  The Global Mangrove Watch - A New 2010 Global Baseline of Mangrove Extent , 2018, Remote. Sens..

[14]  Zhang Qiao,et al.  The mangrove wetland resources and their conservation in China , 2001 .

[15]  Qiu Penghua,et al.  Community distribution and landscape pattern of the mangrove on the Qi'ao Island, Zhuhai. , 2019 .

[16]  Chao Wang,et al.  Monitoring loss and recovery of mangrove forests during 42 years: The achievements of mangrove conservation in China , 2018, Int. J. Appl. Earth Obs. Geoinformation.

[17]  Joost C F de Winter,et al.  Comparing the Pearson and Spearman correlation coefficients across distributions and sample sizes: A tutorial using simulations and empirical data. , 2016, Psychological methods.

[18]  Songsangjinda Putth,et al.  Mangrove Rehabilitation on Highly Eroded Coastal Shorelines at Samut Sakhon, Thailand , 2012 .

[19]  A. C. Ellis,et al.  Remote sensing techniques for mangrove mapping , 1998 .

[20]  D. Murdiyarso,et al.  Effect of land‐use and land‐cover change on mangrove blue carbon: A systematic review , 2019, Global change biology.

[21]  Chandra P. Giri,et al.  Mapping the Philippines’ Mangrove Forests Using Landsat Imagery , 2011, Sensors.

[22]  Ashbindu Singh,et al.  Status and distribution of mangrove forests of the world using earth observation satellite data , 2011 .

[23]  N. Clinton,et al.  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 , 2017 .

[24]  Yuhang Gan,et al.  A Fine-Scale Mangrove Map of China Derived from 2-Meter Resolution Satellite Observations and Field Data , 2021, ISPRS Int. J. Geo Inf..

[25]  D. Alongi.  Mangrove forests: Resilience, protection from tsunamis, and responses to global climate change , 2008 .

[26]  Athanassios I. Sfougaris,et al.  electing landscape metrics as indicators of spatial heterogeneity — A omparison among Greek landscapes , 2013 .

[27]  P. W. M. S. Filho,et al.  Using mangroves as a geological indicator of coastal changes in the Bragança macrotidal flat, Brazilian Amazon: A remote sensing data approach , 2006 .

[28]  Shanze Li,et al.  A comparison of coastal habitat restoration projects in China and the United States , 2019, Scientific Reports.

[29]  K. Seto,et al.  Quantifying Spatiotemporal Patterns of Urban Land-use Change in Four Cities of China with Time Series Landscape Metrics , 2005, Landscape Ecology.

[30]  F. Dahdouh-Guebas.  World Atlas of Mangroves: Mark Spalding, Mami Kainuma and Lorna Collins (eds) , 2011 .

[31]  Jun Zhao,et al.  Change Detection of Mangrove Forests in Coastal Guangdong during the Past Three Decades Based on Remote Sensing Data , 2019, Remote. Sens..

[32]  E. Barbier.  The protective service of mangrove ecosystems: A review of valuation methods. , 2016, Marine pollution bulletin.

[33]  J. Borg,et al.  Influence of wave climate on architecture and landscape characteristics of Posidonia oceanica meadows , 2017 .

[34]  Keqi Zhang,et al.  Remote sensing of seasonal changes and disturbances in mangrove forest: a case study from South Florida , 2016 .

[35]  D. Richards,et al.  Global trends in mangrove forest fragmentation , 2020, Scientific Reports.

[36]  Aliyu Salisu Barau,et al.  Using agent-based modelling and landscape metrics to assess landscape fragmentation in Iskandar Malaysia , 2015, Ecological Processes.

[37]  P. Mayaux,et al.  An object-based method for mapping and change analysis in mangrove ecosystems , 2008 .

[38]  C. Qin,et al.  10-m-resolution mangrove maps of China derived from multi-source and multi-temporal satellite observations , 2020 .

[39]  P. Rousseeuw.  Silhouettes: a graphical aid to the interpretation and validation of cluster analysis , 1987 .

[40]  R. O'Neill,et al.  Landscape patterns in a disturbed environment , 1987 .

[41]  Le Wang,et al.  A review of remote sensing for mangrove forests: 1956–2018 , 2019, Remote Sensing of Environment.

[42]  Li Tian.  Detection and Analysis of Mangrove Changes with Multi-temporal Remotely Sensed Imagery in the Shenzhen River Estuary , 2002 .

[43]  Naoto Yokoya,et al.  Probabilistic Mangrove Species Mapping with Multiple-Source Remote-Sensing Datasets Using Label Distribution Learning in Xuan Thuy National Park, Vietnam , 2020, Remote. Sens..

[44]  Karen C. Seto,et al.  Mangrove conversion and aquaculture development in Vietnam: A remote sensing-based approach for evaluating the Ramsar Convention on Wetlands , 2007 .

[45]  Michael W. Beck,et al.  The role of ecosystems in coastal protection: Adapting to climate change and coastal hazards , 2014 .

[46]  Anne-Sophie Crépin,et al.  Mangroves can provide protection against wind damage during storms , 2013 .

[47]  Yao Guoqing,et al.  Decision tree algorithm of automatically extracting mangrove forests information from Landsat 8 OLI imagery , 2016 .

[48]  Land use Change Impacts on Heavy Metal Sedimentation in Mangrove Wetlands—A Case Study in Dongzhai Harbor of Hainan, China , 2014, Wetlands.

[49]  N. Duke.  Mangrove reforestation in Panama: an evaluation of planting in areas deforested by a large oil spill , 1996 .

[50]  Craig E. Nelson,et al.  The Influence of Landscape Position and Catchment Characteristics on Aquatic Biogeochemistry in High-Elevation Lake-Chains , 2012, Ecosystems.

[51]  D. Eggleston,et al.  Juvenile fish densities in Florida Keys mangroves correlate with landscape characteristics , 2008 .

[52]  T. Albers,et al.  Site-specific and integrated adaptation to climate change in the coastal mangrove zone of Soc Trang Province, Viet Nam , 2013, Journal of Coastal Conservation.

[53]  S. Q. Liu,et al.  Change and fragmentation trends of Zhanjiang mangrove forests in southern China using multi-temporal Landsat imagery (1977–2010) , 2013 .

[54]  Eric Vaz,et al.  Managing urban coastal areas through landscape metrics: An assessment of Mumbai's mangrove system , 2014 .