Monitoring of mangrove growth using HY-1C Satellite CZI data based on remote sensing

ZOU Yarong; LIU Jianqiang; LIANG Chao; ZHU Haitian

doi:10.3969/j.issn.1001-909X.2020.01.008

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Journal of Marine Sciences ›› 2020, Vol. 38 ›› Issue (1) : 68-76. DOI: 10.3969/j.issn.1001-909X.2020.01.008

Monitoring of mangrove growth using HY-1C Satellite CZI data based on remote sensing

ZOU Yarong^1,2, LIU Jianqiang^1,2, LIANG Chao^1,2, ZHU Haitian^1,2

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Abstract

Mangrove is a kind of biological coast composed of salt tolerant mangrove plant communities. Its growth status is of great significance to the coastal zone. Remote sensing technology has become one of the main means for mangrove monitoring. In this study, taking the mangrove in Shankou, Beihai of Guangxi as an example, using the coastal zone imager data of HY-1C satellite, combined with its texture parameters, the mangrove information was extracted, and the mangrove vegetation indexes were analyzed. The results showed that from October to November 2018, the RVI value of mangroves was greater than 1, and this in some areas was greater than 5; the NDVI value of mangroves varied from 0 to 0.01, and the average value was greater than 0.5; the EVI value of mangroves was mainly concentrated between 0.2 and 0.7. The results of different vegetation indexes showed that mangrove in Shankou grew well.

Key words

HY-1C CZI / mangrove / vegetation index / remote sensing monitoring

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ZOU Yarong, LIU Jianqiang, LIANG Chao, ZHU Haitian. Monitoring of mangrove growth using HY-1C Satellite CZI data based on remote sensing[J]. Journal of Marine Sciences. 2020, 38(1): 68-76 https://doi.org/10.3969/j.issn.1001-909X.2020.01.008

References

[1] 范航清. 红树林——海岸环保卫士[M]. 南宁:广西科学技术出版社,2000.
FAN Hangqing. Mangrove: Environmental protection guard of the coast[M].Nanning: Guangxi Science and Technology Press, 2000.
[2] LUCAS R, LULE A V, RODRíGUEZ M T, et al. Spatial ecology of mangrove forests: A remote sensing perspective[M]//RIVERA-MONROY V, LEE S, KRISTENSEN E, et al. Mangrove ecosystems: A global biogeographic perspective. Springer, Cham, 2017: 87-112.
[3] 郑艺,林懿琼,周建,等. 基于资源三号的雷州半岛红树林种间分类研究[J]. 国土资源遥感,2019,31(3):201-208.
ZHENG Yi, LIN Yiqiong, ZHOU Jian, et al. Mangrove inter-species classification based on ZY-3 image in Leizhou Peninsula, Guangdong Province[J]. Remote Sensing for Land & Resources, 2019, 31(3): 201-208.
[4] 周振超,李贺,黄翀,等. 红树林遥感动态监测研究进展[J]. 地球信息科学学报,2018,20(11):1631-1643.
ZHOU Zhenchao, LI He, HUANG Chong, et al. Review on dynamic monitoring of mangrove forestry using remote sensing[J].Journal of Geo-Information Science, 2018, 20(11): 1631-1643.
[5] HOSKING E J, BACH C S, APPLEGATE R J, et al. Mangrove monitoring using sequences of Landsat imagery in the Mary River wetlands[C]//IEEE International Geoscience and Remote Sensing Symposium, IGARSS, 9-13 July 2001: 2241-2243.
[6] SULONG I, MOHD-LOKMAN H, MOHD-TARMIZI K, et al. Mangrove mapping using Landsat imagery and Aerial Photographs: Kemaman District, Terengganu, Malaysia[J]. Environment Development & Sustainability, 2002, 4(2): 135-152.
[7] 李想,刘凯,朱远辉,等. 基于资源三号影像的红树林物种分类研究[J]. 遥感技术与应用,2018,33(2):360-369.
LI Xiang, LIU Kai, ZHU Yuanhui, et al. Study on mangrove species classification based on ZY-3 image[J]. Remote Sensing Technology and Application, 2018, 33(2): 360-369.
[8] PEREZ A C, DAMEN M C J, GENELETTI D, et al. Monitoring a recent delta formation in a tropical coastal wetland using remote sensing and GIS. Case study: Guapo River Delta, Laguna De Tacarigua, Venezuela[J]. Environment Development & Sustainability, 2002, 4(2): 201-219.
[9] LUCAS R M, MITCHELL A, DONNELLY B, et al. Characterising and mapping mangroves in Northern Australia using stereo aerial photography and hyperspectral CASI data[C]//IEEE International Geoscience & Remote Sensing Symposium. IEEE, 2003.
[10] 林鹏. 中国红树林研究进展[J]. 厦门大学学报(自然科学版), 2001,40(2):592-603.
LIN Peng. A Review on the mangrove research in China[J].Journal of Xiamen University(Natural Science), 2001, 40(2): 592-603.
[11] 恽才兴,蒋兴伟. 海岸带可持续发展与综合管理[M].北京:海洋出版社,2002.
YUN Caixing, JIANG Xingwei. Sustainable development and comprehensive management of coastal zone[M]. Beijing: China Ocean Press, 2002.
[12] 苏岫,耿杰,马晓瑞,等. 基于多种植被指数信息与联合稀疏表示的红树林种类识别[J]. 海洋环境科学,2017,36(1):117-123.
SU Xiu, GENG Jie, MA Xiaorui. Mangrove species classification based on multiple vegetation index extraction and joint sparse representation[J].Marine Environmental Science, 2017, 36(1): 117-123.
[13] 陶艳成,葛文标,刘文爱,等. 基于高分辨率卫星影像的广西红树林面积监测与群落调查[J]. 自然资源学报,2017,32(9):1602-1614.
TAO Yancheng, GE Wenbiao, LIU Wen'ai, et al. A survey on the spatial distribution and community types of mangroves in Guangxi based on high-resolution satellite imageries[J].Journal of Natural Resources, 2017, 32(9): 1602-1614.
[14] VALDERRAMA-LANDEROS L, FLORES-DE-SANTIAGO F, KOVACS J M. An assessment of commonly employed satellite-based remote sensors for mapping mangrove species in Mexico using an NDVI-based classification scheme[J]. Environmental Monitoring & Assessment, 2018, 190(1): 23.
[15] 阚丽萍,邹亚荣,胡卓玮. 多光谱与纹理特征结合的Worldview-2影像海岸线提取方法研究[J].海洋学研究,2018,36(4):43-52.
KAN Liping, ZOU Yarong, HU Zhuowei. Research on coastline extraction method of WorldView-2 image combined with multi-spectral and texture features: Take the Cotton Island of Malaysia as an example[J].Journal of Marine Sciences, 2018, 36(4): 43-52.