Detecting and assessing Spartina invasion in coastal region of China: A case study in the Xiangshan Bay

ZHU Changming ZHANG Xin QI Jiaguo

朱长明, 张新, QIJiaguo. 象山港滨海湿地互花米草入侵过程遥感监测与评估[J]. 海洋学报英文版, 2016, 35(4): 35-43. doi: 10.1007/s13131-016-0836-7
引用本文: 朱长明, 张新, QIJiaguo. 象山港滨海湿地互花米草入侵过程遥感监测与评估[J]. 海洋学报英文版, 2016, 35(4): 35-43. doi: 10.1007/s13131-016-0836-7
ZHU Changming, ZHANG Xin, QI Jiaguo. Detecting and assessing Spartina invasion in coastal region of China: A case study in the Xiangshan Bay[J]. Acta Oceanologica Sinica, 2016, 35(4): 35-43. doi: 10.1007/s13131-016-0836-7
Citation: ZHU Changming, ZHANG Xin, QI Jiaguo. Detecting and assessing Spartina invasion in coastal region of China: A case study in the Xiangshan Bay[J]. Acta Oceanologica Sinica, 2016, 35(4): 35-43. doi: 10.1007/s13131-016-0836-7

象山港滨海湿地互花米草入侵过程遥感监测与评估

doi: 10.1007/s13131-016-0836-7
基金项目: The National Natural Science Foundation of China under contract Nos 41201460, 61375002 and 61473286; the Special Research Project for the Commonwealth of the Ministry of Water Resources of the People's Republic of China under contract No.201201092; the National Science and Technology Pillar Program under contract No.2015BAJ02B01.

Detecting and assessing Spartina invasion in coastal region of China: A case study in the Xiangshan Bay

  • 摘要: 互花米草在20世纪70年代后期作为海岸带生态防护工程物种引入我国,由于其超强的繁殖能力,目前已经对我国的滨海湿地生态环境健康与安全造成了严重的威胁,成为生长在中国沿海的一种典型生态入侵植物,引起了相关部门的高度重视。文章选择浙江象山港为重点研究区,通过遥感技术手段,基于2003年,2009年和2014年中分辨率Landsat系列遥感卫星数据,采用空间与光谱特征相结合的综合判读,提出了生境空间环境支持下的植物群落遥感自动识别方法,动态监测了互花米草在象山港的繁衍和入侵过程已经空间格局变化。研究结果表明:过去10年余年,互花米草在象山港呈现指数模型的爆炸性增长。2003年,整个象山港互花米草的分布面积约为590 hm2;2009年其分布面积达到1745 hm2;2014年互花米草在象山港的分布面积超过5715 hm2。2003-1014年10年间互花米草在该区域分布面积翻了近10倍,几乎占据了海岸带所有的泥质海滩,成为象山港滨海湿地区的主导型盐生植被和区域优势种,对附近农田,尤其是淡水水域构成巨大的威胁。而在快速扩张的驱动要素方面,研究认为强劲的自我繁殖性能是互米花草在区域能够快速扩张的主要原因;人类围垦活动促进了这一快速扩张进程。以上研究结论可为区域互花米草的综合治理提供数据支持和遥感监测提供技术参考。
  • Adams J B, Sabol D E, Kapos V, et al. 1995. Classification of multis-pectral images based on fractions of endmembers:application to land-cover change in the Brazilian Amazon. Remote Sensing of Environment, 52(2):137-154
    Aguiar A P D, Shimabukuro Y E, Mascarenhas N D A. 1999. Use of synthetic bands derived from mixing models in the multispec-tral classification of remote sensing images. International Journal of Remote Sensing, 20(4):647-657
    Ayres D R, Strong D R. 2002. The Spartina invasion of San Francisco Bay. Aquatic Nuisance Species Digest, 4(4):37-39
    Boardman J W, Kruse F A. 1994. Automated spectral analysis:a geolo-gical example using AVIRIS data, north Grapevine Mountains, Nevada. In:Proceedings of the ERIM 10th Thematic Confer-ence on Geologic Remote Sensing. Ann Arbor, Michigan:Envir-onmental Research Institute of Michigan, 1:1-407
    Chander G, Markham B L, Helder D L. 2009. Summary of current ra-diometric calibration coefficients for Landsat MSS, TM, ETM+, and EO-1 ALI sensors. Remote Sensing of Environment, 113(5):893-903
    Chen Zhongyi, Li Bo, Chen Jiakuan. 2005. Study of the impact of soil salty and intetidal leveal to Spartinas' growth in island Chongmng. Journal of Yangtze University(Nature Science Edi-tion)(in Chinese), 2(2):6-9
    Chung C H. 2006. Forty years of ecological engineering with Spartina plantations in China. Ecological Engineering, 27(1):49-57
    Cochrane M A. 1998. Linear mixture model classification of burned forests in the eastern Amazon. International Journal of Remote Sensing, 19(17):3433-3440
    Congalton R G. 1991. A review of assessing the accuracy of classifica-tions of remotely sensed data. Remote Sensing of Environment, 37(1):35-46
    Cracknell A P. 1998. Review article Synergy in remote sensing-what's in a pixel. International Journal of Remote Sensing, 19(11):2025-2047
    Daehler C C, Strong D R. 1996. Status, prediction and prevention of introduced cordgrass Spartina spp invasions in Pacific estuar-ies, USA. Biological Conservation, 78(1-2):51-58
    Defries R S, Hansen M C, Townshend J R G. 2000. Global continuous fields of vegetation characteristics:a linear mixture model ap-plied to multi-year 8 km AVHRR data. International Journal of Remote Sensing, 21(6-7):1389-1414
    Deng Zifa, An Shuqing, Zhi Yingbiao, et al. 2006. Preliminary studies on invasive model and outbreak mechanism of exotic species, Spartina alterniflora Loisel. Acta Ecologica Sinica(in Chinese), 26(8):2678-2686
    Dennison P E, Roberts D A. 2003. The effects of vegetation phenology on endmember selection and species mapping in southern California chaparral. Remote Sensing of Environment, 87(2-3):295-309
    Donoghue D N M, Thomas D C R, Zong Y. 1995. Mapping and monit-oring the intertidal zone of the east coast of England using re-mote sensing techniques and a coastal monitoring GIS. Ocean-ographic Literature Review, 42(5):410
    Fisher P. 1997. The pixel:a snare and a delusion. International Journ-al of Remote Sensing, 18(3):679-685
    Foody G M. 2002. Status of land cover classification accuracy assess-ment. Remote Sensing of Environment, 80(1):185-201
    Frazier P S, Page K J. 2000. Water body detection and delineation with Landsat TM data. Photogrammetric Engineering and Remote Sensing, 66(12):1461-1468
    Gade M, Alpers W, Melsheimer C, et al. 2008. Classification of sedi-ments on exposed tidal flats in the German Bight using multi-frequency radar data. Remote Sensing of Environment, 112(4):1603-1613
    García-Haro F J, Gilabert M A, Meliá J. 1996. Linear spectral mixture modelling to estimate vegetation amount from optical spectral data. International Journal of Remote Sensing, 17(17):3373-3400
    Green A A, Berman M, Switzer P, et al. 1988. A transformation for or-dering multispectral data in terms of image quality with implic-ations for noise removal. IEEE Transactions on Geoscience and Remote Sensing, 26(1):65-74
    Green E P, Mumby P J, Edwards A J, et al. 1996. A review of remote sensing for the assessment and management of tropical coastal resources. Coastal Management, 24(1):1-40
    Li Jialin, Yang Xiaoping, Tong Yiqin, et al. 2005. Influences of Spar-tina alterniflora invasion on ecosystem services of coastal wet-land and its countermeasures. Marine Science Bulletin(in Chinese), 24(5):33-38
    Liu Haisong, Jezek K C. 2004. Automated extraction of coastline from satellite imagery by integrating Canny edge detection and loc-ally adaptive thresholding methods. International Journal of Remote Sensing, 25(5):937-958
    Liu Jin'e, Zhou Hongxia, Qin Pei, et al. 2007. Effects of Spartina al-terniflora salt marshes on organic carbon acquisition in inter-tidal zones of Jiangsu Province, China. Ecological Engineering, 30(3):240-249
    Lu Dengsheng, Moran E, Batistella M. 2003. Linear mixture model applied to Amazonian vegetation classification. Remote Sens-ing of Environment, 87(4):456-469
    Lu Dengsheng, Weng Qihao. 2006. Use of impervious surface in urb-an land-use classification. Remote Sensing of Environment, 102(1-2):146-160
    Luo Jiancheng, Sheng Yongwei, Shen Zhanfeng, et al. 2009. Automat-ic and high-precise extraction for water information from multispectral images with the step-by-step iterative transform-ation mechanism. Journal of Remote Sensing(in Chinese), 13(4):610-615
    McFeeters S K. 1996. The use of the Normalized Difference Water In-dex(NDWI) in the delineation of open water features. Interna-tional Journal of Remote Sensing, 17(7):1425-1432
    Min L, Lu S, Wang B, et al. 1997. Spartinas' Observation, Test and It's Enginnering Application(in Chinese). Hangzhou:Reclamation Bureau of Zhejiang Province
    Murray N J, Phinn S R, Clemens R S, et al. 2012. Continental scale mapping of tidal flats across East Asia using the Landsat archive. Remote Sensing, 4(11):3417-3426
    Mustard J F, Sunshine J M. 1999. Spectral analysis for earth science:investigations using remote sensing data. In:Andrew N, ed. Re-mote Sensing for the Earth Sciences:Manual of Remote Sens-ing. 3rd ed. Vol. 3. New York:John Wiley & Sons, Inc, 251-306
    Ouma Y O, Tateishi R. 2006. A water index for rapid mapping of shoreline changes of five East African Rift Valley lakes:an em-pirical analysis using Landsat TM and ETM+ data. Internation-al Journal of Remote Sensing, 27(15):3153-3181
    Ridd M K. 1995. Exploring a V-I-S(vegetation-impervious surface-soil) model for urban ecosystem analysis through remote sens-ing:comparative anatomy for cities. International Journal of Remote Sensing, 16(12):2165-2185
    Rosso P H, Ustin S L, Hastings A. 2006. Use of lidar to study changes associated with Spartina invasion in San Francisco Bay marshes. Remote Sensing of Environment, 100(3):295-306
    Ryu J H, Kim C H, Lee Y K, et al. 2008. Detecting the intertidal mor-phologic change using satellite data. Estuarine, Coastal and Shelf Science, 78(4):623-632
    Ryu J H, Won J S, Min K D. 2002. Waterline extraction from Landsat TM data in a tidal flat:a case study in Gomso Bay, Korea. Re-mote Sensing of Environment, 83(3):442-456
    Smith M O, Ustin S L, Adams J B, et al. 1990. Vegetation in deserts:I. A regional measure of abundance from multispectral images. Re-mote Sensing of Environment, 31(1):1-26
    Theseira M A, Thomas G, Taylor J C, et al. 2003. Sensitivity of mixture modelling to end-member selection. International Journal of Remote Sensing, 24(7):1559-1575
    Van Der Meer F, De Jong S M. 2000. Improving the results of spectral unmixing of Landsat Thematic Mapper imagery by enhancing the orthogonality of end-members. International Journal of Re-mote Sensing, 21(15):2781-2797
    Vinther N, Christiansen C, Bartholdy J. 2001. Colonisation of Spar-tina on a tidal water divide, Danish Wadden Sea. Geografisk Tidsskrift-Danish Journal of Geography, 101(1):11-19
    Wan Huawei, Wang Qiao, Jiang Dong, et al. 2014. Monitoring the in-vasion of Spartina alterniflora using very high resolution un-manned aerial vehicle imagery in Beihai, Guangxi(China). The Scientific World Journal, 2014:638296
    Woodcock C E, Macomber S A, Pax-Lenney M, et al. 2001. Monitor-ing large areas for forest change using Landsat:Generalization across space, time and Landsat sensors. Remote Sensing of En-vironment, 78(1-2):194-203
    Xu Guowan, Zhuo Rongzong. 1985. Preliminary studies of intro-duced of Spartina alterniflora Losiel in China. Journal of Nanjing University(in Chinese), 40(2):212-225
    Yuan Hongwei, Li Shouzhong, Zheng Huaizhou, et al. 2009. Evalu-ation of the influences of foreign Spartina alterniflora on eco-system of Chinese coastal wetland and its countermeasures. Marine Science Bulletin(in Chinese), 28(6):122-128
    Zhang Ying. 2010. The spatial distribution and bioenergy estimation of an invasive plant Spartina alterniflora in China(in Chinese)[dissertation]. Hangzhou:Zhejiang University
    Zhang R S, Shen Y M, Lu L Y, et al. 2004. Formation of Spartina al-terniflora salt marshes on the coast of Jiangsu Province, China. Ecological Engineering, 23(2):95-105
    Zhang M, Ustin S L, Rejmankova E, et al. 1997. Monitoring Pacific coast salt marshes using remote sensing. Ecological Applica-tions, 7(3):1039-1053
    Zhang Yinlong, Lu Dengsheng, Yang Bo, et al. 2011. Coastal wetland vegetation classification with a Landsat Thematic Mapper im-age. International Journal of Remote Sensing, 32(2):545-561
    Zhao Bin, Guo Haiqiang, Yan Yaner, et al. 2008. A simple waterline approach for tidelands using multi-temporal satellite images:a case study in the Yangtze Delta. Estuarine, Coastal and Shelf Science, 77(1):134-142
    Zhu Changming, Luo Jiancheng, Shen Zhanfeng, et al. 2011. A spatial adaptive algorithm for endmember extraction on multispectral remote sensing image. Spectroscopy and Spectral Analysis(in Chinese), 31(10):2814-2818
    Zuo Ping, Liu Chang'an, Zhao Shuhe, et al. 2009. Distribution of Spar-tina plantations along the China's coast. Acta Oceanologica Sinica, 31(5):101-111
    Zuo Ping, Zhao Shuhe, Liu Chang'an, et al. 2012. Distribution of Spartina spp. along China's coast. Ecological Engineering, 40:160-166
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  • 收稿日期:  2014-12-02
  • 修回日期:  2015-10-19

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