留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

粤港澳大湾区红树林时空分布演变及现存林龄遥感分析

张信 陈建裕 杨清杰

张信,陈建裕,杨清杰. 粤港澳大湾区红树林时空分布演变及现存林龄遥感分析[J]. 海洋学报,2023,45(3):113–124 doi: 10.12284/hyxb2023042
引用本文: 张信,陈建裕,杨清杰. 粤港澳大湾区红树林时空分布演变及现存林龄遥感分析[J]. 海洋学报,2023,45(3):113–124 doi: 10.12284/hyxb2023042
Zhang Xin,Chen Jianyu,Yang Qingjie. Analysis of spatial-temporal distribution evolution and age of existing mangrove forests in Guangdong-Hong Kong-Macao Greater Bay Area using remotely sensed data[J]. Haiyang Xuebao,2023, 45(3):113–124 doi: 10.12284/hyxb2023042
Citation: Zhang Xin,Chen Jianyu,Yang Qingjie. Analysis of spatial-temporal distribution evolution and age of existing mangrove forests in Guangdong-Hong Kong-Macao Greater Bay Area using remotely sensed data[J]. Haiyang Xuebao,2023, 45(3):113–124 doi: 10.12284/hyxb2023042

粤港澳大湾区红树林时空分布演变及现存林龄遥感分析

doi: 10.12284/hyxb2023042
基金项目: 南方海洋科学与工程广东省实验室(广州)人才团队引进重大专项(GML2019ZD0602);卫星海洋环境动力学国家重点实验室资助项目(SOEDZZ2203);国家自然科学基金NSFC—浙江两化融合联合基金重点项目(U1609202);国家自然科学基金(42076216,41376184,40976109)。
详细信息
    作者简介:

    张信(1995-),男,四川省成都市人,主要从事海岸带遥感方面研究。E-mail:mg21270094@smail.nju.edu.cn

    通讯作者:

    陈建裕(1973-),男,浙江省慈溪市人,研究员,主要从事海岸带遥感及近海海洋遥感方面研究。E-mail:chenjianyu@sio.org.cn

  • 中图分类号: TP79;S718.5

Analysis of spatial-temporal distribution evolution and age of existing mangrove forests in Guangdong-Hong Kong-Macao Greater Bay Area using remotely sensed data

  • 摘要: 红树林作为热带、亚热带以红树植物为主体的海岸带生态系统,是重要的海岸湿地类型之一。本文使用多源、多时相遥感数据,形成了1969−2020年粤港澳大湾区岸线、围填海、养殖区、红树林分布数据图集,并利用联合红树林识别指数(CMRI)对大湾区现存红树林进行时序分析得到红树林林龄数据集。结果表明,通过多源遥感数据解译得到现存红树林数据集,结合CMRI时序数据可以建立现存红树林变迁历史,进而有效估算红树林林龄。粤港澳大湾区红树林的时空分布发生了明显变迁,现存红树林面积约为3 316 hm2,大湾区内部各地区存量林龄差异较大,整体林龄均值为20 a。近50年间,岸线整体向海移动,岸线变迁、围填海和养殖区变化显著影响红树林面积、空间分布及林龄大小,人工种植是近20年红树林恢复的主因。
  • 图  1  研究区位置

    Fig.  1  Location of the study area

    图  2  技术路线

    Fig.  2  Technical route

    图  3  不同传感器对红树林及光滩的可分性

    光滩包含淹水及未淹水两种状态

    Fig.  3  Separability of mangrove and tidal flats by different sensors

    The tidal flats include two states: flooded and unflooded

    图  4  3类不同林龄红树林的CMRI时序数据

    Fig.  4  The CMRI time series data of three kinds of mangrove forests with different ages

    图  5  红树林种植林龄分布

    Fig.  5  Distribution of existing mangrove forest planting age

    图  6  现存红树林种植林龄

    离群值表示该地区存在过高/低林龄红树林

    Fig.  6  Existing mangrove forest planting age

    Outliers indicate the presence of mangroves of too high/low stand age in the area

    图  7  红树林景观指数变化

    Fig.  7  Change of mangrove forest landscape index

    图  8  红树林制图结果比较

    Fig.  8  Comparison of mangrove forest mapping results

    图  9  围填海及养殖区年际变化分布

    Fig.  9  Age distribution of reclamation and aquaculture areas

    图  10  围填海、养殖区及现存红树林面积每5年增量变化及存量面积统计

    Fig.  10  Changes in reclamation, aquaculture areas, and existing mangrove areas every 5 years and stock area statistics

    图  11  CMRI提取的林龄(a)和叠加目视解译结果的林龄(b)

    Fig.  11  Forest age extracted from CMRI (a) and forest age with visual interpretation results (b)

    表  1  卫星遥感数据信息

    Tab.  1  Remotely sensed data information

    卫星年份分辨率/m数量/景
    KH-4A19642.741
    KH-4B1967−19691.8335
    KH-919736~92
    KH-919750.61~1.2223
    Landsat-31979604
    Landsat-51986−20103052
    HJ2008−20173016
    Landsat-82013−20193015
    ZY-320202.114
    GF-120202.17
    下载: 导出CSV

    表  2  红树林解译参考资料

    Tab.  2  Mangrove forests intetpretation references

    地区参考资料红树林主要分布位置
    江门市文献[28]
    文献[29]
    广海湾、镇海湾及银湖湾
    珠海市文献[30]淇澳岛、横琴岛滨海湿地公园及二井湾湿地公园
    中山市文献[30]横门水道、磨刀门水道
    广州市文献[30]
    文献[31]
    洪奇沥水道、南沙湿地公园、蕉门水道、新龙特大桥16涌至17涌段
    惠州市文献[32]考州洋、稔山镇三连洲、大亚湾渡头河、
    巽寮
    深圳市文献[33]
    文献[29]
    福田自然保护区和龙岗区东涌、鹿咀、
    坝光
    东莞市文献[30]
    文献[34]
    交椅湾苗涌及龙涌
    香港特别行政区文献[29]米埔自然保护区
    澳门特别行政区文献[35]路氹城生态保护区
    下载: 导出CSV
  • [1] McKee K L, Cahoon D R, Feller I C. Caribbean mangroves adjust to rising sea level through biotic controls on change in soil elevation[J]. Global Ecology and Biogeography, 2007, 16(5): 545−556. doi: 10.1111/j.1466-8238.2007.00317.x
    [2] Bouillon S, Borges A V, Castañeda-Moya E, et al. Mangrove production and carbon sinks: a revision of global budget estimates[J]. Global Biogeochemical Cycles, 2008, 22(2): GB2013.
    [3] Dittmar T, Hertkorn N, Kattner G, et al. Mangroves, a major source of dissolved organic carbon to the oceans[J]. Global Biogeochemical Cycles, 2006, 20(1): GB1012.
    [4] Feller I C, Friess D A, Krauss K W, et al. The state of the world’s mangroves in the 21st century under climate change[J]. Hydrobiologia, 2017, 803(1): 1−12. doi: 10.1007/s10750-017-3331-z
    [5] Bradford J B, Birdsey R A, Joyce L A, et al. Tree age, disturbance history, and carbon stocks and fluxes in subalpine Rocky Mountain forests[J]. Global Change Biology, 2008, 14(12): 2882−2897. doi: 10.1111/j.1365-2486.2008.01686.x
    [6] Song Conghe, Woodcock C E. A regional forest ecosystem carbon budget model: impacts of forest age structure and landuse history[J]. Ecological Modelling, 2003, 164(1): 33−47. doi: 10.1016/S0304-3800(03)00013-9
    [7] Chen Guangcheng, Gao Min, Pang Bopeng, et al. Top-meter soil organic carbon stocks and sources in restored mangrove forests of different ages[J]. Forest Ecology and Management, 2018, 422: 87−94. doi: 10.1016/j.foreco.2018.03.044
    [8] Pregitzer K S, Euskirchen E S. Carbon cycling and storage in world forests: biome patterns related to forest age[J]. Global Change Biology, 2004, 10(12): 2052−2077. doi: 10.1111/j.1365-2486.2004.00866.x
    [9] 李森, 蔡厚才, 陈万东, 等. 海岸带生态恢复区不同林龄红树林对CH4和CO2排放通量的影响[J]. 生态环境学报, 2020, 29(12): 2414−2422.

    Li Sen, Cai Houcai, Chen Wandong, et al. Analysis on CH4 and CO2 fluxes of mangroves with different ages in the coastal ecological restoration zone[J]. Ecology and Environmental Sciences, 2020, 29(12): 2414−2422.
    [10] Giri C, Ochieng E, Tieszen L L, et al. Status and distribution of mangrove forests of the world using earth observation satellite data[J]. Global Ecology and Biogeography, 2011, 20(1): 154−159. doi: 10.1111/j.1466-8238.2010.00584.x
    [11] Bunting P, Rosenqvist A, Lucas R M, et al. The global mangrove watch—a new 2010 global baseline of mangrove extent[J]. Remote Sensing, 2018, 10(10): 1669. doi: 10.3390/rs10101669
    [12] Lu Ying, Wang Le. How to automate timely large-scale mangrove mapping with remote sensing[J]. Remote Sensing of Environment, 2021, 264: 112584. doi: 10.1016/j.rse.2021.112584
    [13] 王子予, 刘凯, 彭力恒, 等. 基于Google Earth Engine的1986−2018年广东红树林年际变化遥感分析[J]. 热带地理, 2020, 40(5): 881−892.

    Wang Ziyu, Liu Kai, Peng Liheng, et al. Analysis of mangrove annual changes in Guangdong Province during 1986−2018 based on Google Earth Engine[J]. Tropical Geography, 2020, 40(5): 881−892.
    [14] 吴培强, 马毅, 李晓敏, 等. 广东省红树林资源变化遥感监测[J]. 海洋学研究, 2011, 29(4): 16−24. doi: 10.3969/j.issn.1001-909X.2011.04.003

    Wu Peiqiang, Ma Yi, Li Xiaomin, et al. Remote sensing monitoring of the mangrove forests resources of Guangdong Province[J]. Journal of Marine Sciences, 2011, 29(4): 16−24. doi: 10.3969/j.issn.1001-909X.2011.04.003
    [15] Jia Mingming, Wang Zongming, Wang Chao, et al. A new vegetation index to detect periodically submerged mangrove forest using single-tide sentinel-2 imagery[J]. Remote Sensing, 2019, 11(17): 2043. doi: 10.3390/rs11172043
    [16] Zhang Tao, Hu Shanshan, He Yun, et al. A fine-scale mangrove map of china derived from 2-meter resolution satellite observations and field data[J]. ISPRS International Journal of Geo-Information, 2021, 10(2): 92. doi: 10.3390/ijgi10020092
    [17] George-Chacón S P, Mas J F, Dupuy J M, et al. Mapping the spatial distribution of stand age and aboveground biomass from Landsat time series analyses of forest cover loss in tropical dry forests[J]. Remote Sensing in Ecology and Conservation, 2022, 8(3): 347−361. doi: 10.1002/rse2.247
    [18] Zhang Quanfa, Pavlic G, Chen Wenjun, et al. Deriving stand age distribution in boreal forests using SPOT VEGETATION and NOAA AVHRR imagery[J]. Remote Sensing of Environment, 2004, 91(3/4): 405−418.
    [19] Razak J A B A, Shariff A R B M, Ahmad N B, et al. Mapping rubber trees based on phenological analysis of Landsat time series data-sets[J]. Geocarto International, 2018, 33(6): 627−650.
    [20] 张文秋, 房磊, 杨健, 等. 基于Landsat时间序列的湖南省会同县杉木人工林干扰历史重建与林龄估算[J]. 生态学杂志, 2018, 37(11): 3467−3479. doi: 10.13292/j.1000-4890.201811.033

    Zhang Wenqiu, Fang Lei, Yang Jian, et al. Reconstruction of stand-replacement disturbance and stand age of Chinese fir plantation based on a Landsat time series in Huitong County, Hunan[J]. Chinese Journal of Ecology, 2018, 37(11): 3467−3479. doi: 10.13292/j.1000-4890.201811.033
    [21] Gupta K, Mukhopadhyay A, Giri S, et al. An index for discrimination of mangroves from non-mangroves using LANDSAT 8 OLI imagery[J]. MethodsX, 2018, 5: 1129−1139. doi: 10.1016/j.mex.2018.09.011
    [22] 林玉英, 胡喜生, 邱荣祖, 等. 基于Landsat影像的NDVI对植被与影响因子交互耦合的响应[J]. 农业机械学报, 2018, 49(10): 212−219. doi: 10.6041/j.issn.1000-1298.2018.10.024

    Lin Yuying, Hu Xisheng, Qiu Rongzu, et al. Responses of landsat-based NDVI to interaction of vegetation and influencing factors[J]. Transactions of the Chinese Society for Agricultural Machinery, 2018, 49(10): 212−219. doi: 10.6041/j.issn.1000-1298.2018.10.024
    [23] 唐少飞. 中国东北典型针叶林林龄信息提取及其对树种分类的影响研究[D]. 南京: 南京大学, 2020.

    Tang Shaofei. Study on extraction of stand age information of typical coniferous forests in Northeast China and its impact on tree species classification[D]. Nanjing: Nanjing University, 2020.
    [24] 国家海洋局908专项办公室. 我国近海海洋综合调查与评价专项: 海岛海岸带卫星遥感调查技术规程[M]. 北京: 海洋出版社, 2005.

    State Oceanic 908 of the State Oceanic Administration. the Investigation and the Evaluation of the State’s Coastal Sea: Technical Specification for Coastal Zone Investigation[M]. Beijing: China Ocean Press, 2005.
    [25] 浙江省质量技术监督局. 海岸线调查统计技术规范: DB33/T 2106−2018[S]. 杭州: 浙江省标准化研究院, 2018.

    Quality and Technology Supervision of Zhejiang Province. Specification for coastline survey statistics: DB33/T 2106−2018[S]. Hangzhou: Zhejiang Institute of Standardization, 2018.
    [26] 侯西勇, 毋亭, 侯婉, 等. 20世纪40年代初以来中国大陆海岸线变化特征[J]. 中国科学: 地球科学, 2016, 59(8): 1791−1802.

    Hou Xiyong, Wu Ting, Hou Wan, et al. Characteristics of coastline changes in mainland China since the early 1940s[J]. Science China: Earth Sciences, 2016, 59(8): 1791−1802.
    [27] 高志强, 刘向阳, 宁吉才, 等. 基于遥感的近30 a中国海岸线和围填海面积变化及成因分析[J]. 农业工程学报, 2014, 30(12): 140−147. doi: 10.3969/j.issn.1002-6819.2014.12.017

    Gao Zhiqiang, Liu Xiangyang, Ning Jicai, et al. Analysis on changes in coastline and reclamation area and its causes based on 30-year satellite data in China[J]. Transactions of the Chinese Society of Agricultural Engineering, 2014, 30(12): 140−147. doi: 10.3969/j.issn.1002-6819.2014.12.017
    [28] 李矿明, 邓小飞, 韩维栋. 广东江门沿海红树林及其它湿地植被[J]. 中南林业调查规划, 2006, 25(1): 35−38. doi: 10.3969/j.issn.1003-6075.2006.01.010

    Li Kuangming, Deng Xiaofei, Han Weidong. Guangdong Jiangmen coastal mangrove and other wetland vegetation[J]. Central South Forest Inventory and Planning, 2006, 25(1): 35−38. doi: 10.3969/j.issn.1003-6075.2006.01.010
    [29] 于凌云, 林绅辉, 焦学尧, 等. 粤港澳大湾区红树林湿地面临的生态问题与保护对策[J]. 北京大学学报(自然科学版), 2019, 55(4): 782−790. doi: 10.13209/j.0479-8023.2019.051

    Yu Lingyun, Lin Shenhui, Jiao Xueyao, et al. Ecological problems and protection countermeasures of mangrove wetland in Guangdong-Hong Kong-Macao greater bay area[J]. Acta Scientiarum Naturalium Universitatis Pekinensis, 2019, 55(4): 782−790. doi: 10.13209/j.0479-8023.2019.051
    [30] 战国强. 珠江口红树林湿地保护与修复的基本思路[J]. 林业与环境科学, 2008, 24(6): 70−74. doi: 10.3969/j.issn.1006-4427.2008.06.015

    Zhan Guoqiang. Basic thought on mangrove wetland conservation planning in Pearl River Estuary[J]. Forestry and Environmental Science, 2008, 24(6): 70−74. doi: 10.3969/j.issn.1006-4427.2008.06.015
    [31] 李海生, 吴灿雄, 欧阳美霞, 等. 广州市南沙区红树林资源现状与保护[J]. 湿地科学, 2020, 18(2): 158−165. doi: 10.13248/j.cnki.wetlandsci.2020.02.004

    Li Haisheng, Wu Canxiong, Ouyang Meixia, et al. The current status and conservation of mangrove resources in Nansha District of Guangzhou[J]. Wetland Science, 2020, 18(2): 158−165. doi: 10.13248/j.cnki.wetlandsci.2020.02.004
    [32] 陈一萌, 杨阳. 惠州市红树林湿地资源及其保护[J]. 热带地理, 2010, 30(1): 34−39. doi: 10.3969/j.issn.1001-5221.2010.01.007

    Chen Yimeng, Yang Yang. Mangrove wetland resources and their protection scheme in Huizhou City[J]. Tropical Geography, 2010, 30(1): 34−39. doi: 10.3969/j.issn.1001-5221.2010.01.007
    [33] 李海生. 深圳龙岗的红树林[J]. 广东教育学院学报, 2006, 26(3): 67−69.

    Li Haisheng. The mangrove of Longgang, Shenzhen[J]. Journal of Guangdong Education Institute, 2006, 26(3): 67−69.
    [34] 王金华, 温钊鹏. 粤港澳大湾区河口海岸生态修复策略研究——以东莞市滨海湾新区为例[J]. 海洋开发与管理, 2020, 37(6): 34−39. doi: 10.3969/j.issn.1005-9857.2020.06.007

    Wang Jinhua, Weng Zhaopeng. The ecological restoration strategy of estuary coastal zone in Guangdong-Hong Kong-Macao Greater Bay Area: take Dongguan Marina Bay New Area as an example[J]. Ocean Development and Management, 2020, 37(6): 34−39. doi: 10.3969/j.issn.1005-9857.2020.06.007
    [35] 何锐荣. 澳门红树林及其保护研究[D]. 广州: 暨南大学, 2009.

    He Ruirong. Study on mangrove and its conservational strategy in Macao, China[D]. Guangzhou: Jinan University, 2009.
    [36] Brown M E, Pinzon J E, Didan K, et al. Evaluation of the consistency of long-term NDVI time series derived from AVHRR, SPOT-vegetation, SeaWiFS, MODIS, and Landsat ETM+ sensors[J]. IEEE Transactions on Geoscience and Remote Sensing, 2006, 44(7): 1787−1793. doi: 10.1109/TGRS.2005.860205
    [37] 吴庭天, 丁山, 陈宗铸, 等. 基于LUCC和景观格局变化的海南东寨港红树林湿地动态研究[J]. 林业科学研究, 2020, 33(5): 154−162.

    Wu Tingtian, Ding Shan, Chen Zongzhu, et al. Dynamic analysis of mangrove wetlands based on LUCC and landscape pattern change in Dongzhai Port[J]. Forest Research, 2020, 33(5): 154−162.
  • 加载中
图(11) / 表(2)
计量
  • 文章访问数:  613
  • HTML全文浏览量:  147
  • PDF下载量:  119
  • 被引次数: 0
出版历程
  • 收稿日期:  2022-04-01
  • 修回日期:  2022-10-10
  • 网络出版日期:  2022-10-24
  • 刊出日期:  2023-02-01

目录

    /

    返回文章
    返回