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闵钰魁，柯樱海，韩月，尹小岚，周德民.2023.融合Sentinel-2和GF-1时序影像的入侵植物互花米草清除动态监测.遥感学报，27（6）： 1467-1479
Min Y K，Ke Y H，Han Y，Yin X L and Zhou D M. 2023. Dynamic monitoring of invasive Spartina alterniflora clearance via fusion of Sentinel-2 and GF-1 time series images. National Remote Sensing Bulletin， 27（6）：1467-1479
互花米草入侵对中国滨海湿地生物多样性和生态系统健康造成严重威胁。近两年，中国沿海多省陆续启动互花米草清除治理工程。及时准确地了解互花米草清除动态对于滨海湿地管理决策具有重要意义。本文以黄河口湿地为研究区，针对2021年互花米草大规模治理工程，提出一种基于密集时间序列遥感影像的互花米草清除动态监测方法。首先融合Sentinel-2 MSI、GF-1 PMS和GF-1 WFV影像，构建高时空分辨率的归一化植被差异指数（NDVI）数据集。充分考虑NDVI的时序变化和潮间带潮汐淹没动态，通过潜在清除时段提取和潮汐淹没监测，识别互花米草清除日期，获取了10 m分辨率下黄河口互花米草清除时间分布图，清除日期总体精度达到88.24%，Kappa系数为0.87。实验表明，相较仅使用Sentinel-2单一数据源，融合Sentinel-2和GF-1数据可以有效提升清除日期识别精度。2021年9月—12月，研究区互花米草清除面积为4816.35 ha，占总面积的92.81%。本研究提出的入侵植物清除监测方法对于全国滨海湿地互花米草治理和湿地修复工程监测评估具有重要的参考意义。
Invasion of
Spartina alterniflora
poses a serious threat to the biodiversity and ecosystem health of coastal wetlands in China. Many coastal provinces in China have initiated projects for clearance and treatment of
S. alterniflora
in recent years. The timely and accurate understanding of
S. alterniflora
clearance dynamics is crucial in coastal wetland management and decision making. The objective of this study was to propose a new method for monitoring
S. alterniflora
clearance dynamics on the basis of dense time series remote sensing images.
The Yellow River Estuary wetland was taken as the study area in this work. First
Sentinel-2 MSI
GF-1 PMS
and GF-1 WFV images were fused to construct time-series Normalized Difference Vegetation Index (NDVI) dataset. Second
temporal variations of NDVI were analyzed
and the potential clearance periods were detected. Finally
tidal inundation was examined and
S. alterniflora
clearance date was identified by eliminating the influence of tidal inundation on NDVI time series. The map of
S. alterniflora
clearance dates with a spatial resolution of 10 m was obtained for the Yellow River Estuary.
The overall accuracy of clearance dates was 88.24%
and the Kappa coefficient was 0.87. Results showed that the fusion of Sentinel-2 and GF-1 data can effectively improve the identification accuracy of clearance dates compared with the single Sentinel-2 date source. The cleared area of
S. alterniflora
from September to December 2021 was 4816.35 ha
which accounts for 92.81% of the total
S. alterniflora
region in the study area. Uncleared areas are mainly distributed in the coastal areas of the north shore with complex hydrology and interlaced tidal creeks. The project was completed in two stages because of the early October flood peak in the lower reaches of the Yellow River. The first stage was finished between early September and early October
and the second stage was concluded between mid-October and mid-December
with the majority of
S. alterniflora
being cleared in early December.
The rapid and accurate observation of the dynamics of
S. alterniflora
clearance through the proposed method is crucial in the monitoring and evaluation of
S. alterniflora
treatment and wetland restoration projects in coastal wetlands across the country. This method is expected to be applied to the dynamic monitoring and comprehensive evaluation of the effectiveness of large-scale treatment projects.
Sentinel-2GF-1入侵物种互花米草治理滨海湿地时间序列
Sentinel-2GF-1invasive speciesspartina alterniflora managementcoastal wetlandtime series
Chen J, Wang S Y and Mao Z P. 2011. Monitoring wetland changes in Yellow River Delta by remote sensing during 1976-2008. Progress in Geography, 30(5): 585-592
陈建, 王世岩, 毛战坡. 2011. 1976-2008年黄河三角洲湿地变化的遥感监测. 地理科学进展, 30(5): 585-592 [DOI: 10.11820/dlkxjz.2011.05.010http://dx.doi.org/10.11820/dlkxjz.2011.05.010]
Chen Y N, Gao S, Jia J J and Wang A J. 2005. Tidalflat ecological changes by transplanting Spartina anglica and Spartina alterniflorea, northern Jiangsu coast. Oceanologia Et Limnologia Sinica, 36(5): 394-403
陈一宁, 高抒, 贾建军, 王爱军. 2005. 米草属植物Spartina angilica和Spartina alterniflora引种后江苏海岸湿地生态演化的初步探讨. 海洋与湖沼, 36(5): 394-403 [DOI: 10.3321/j.issn:0029-814X.2005.05.002http://dx.doi.org/10.3321/j.issn:0029-814X.2005.05.002]
China Ministry of Water Resources. 2021. The Yellow River flood no. 3 in 2021, the Ministry of Water Resources maintained level III emergency response for flood and drought disaster prevention[Z/OL]. http://www.gov.cn/xinwen/2021-10/06/content_5641121.htmhttp://www.gov.cn/xinwen/2021-10/06/content_5641121.htm
中国水利部. 2021. 黄河发生2021年第3号洪水 水利部维持水旱灾害防御Ⅲ级应急响应[Z/OL]. http://www.gov.cn/xinwen/2021-10/06/content_5641121.htmhttp://www.gov.cn/xinwen/2021-10/06/content_5641121.htm
Chung C H. 2006. Forty years of ecological engineering with Spartina plantations in China. Ecological Engineering, 27(1): 49-57 [DOI: 10.1016/j.ecoleng.2005.09.012http://dx.doi.org/10.1016/j.ecoleng.2005.09.012]
Fernández-Guisuraga J M, Calvo L and Suárez-Seoane S. 2020. Comparison of pixel unmixing models in the evaluation of post-fire forest resilience based on temporal series of satellite imagery at moderate and very high spatial resolution. ISPRS Journal of Photogrammetry and Remote Sensing, 164: 217-228 [DOI: 10.1016/j.isprsjprs.2020.05.004http://dx.doi.org/10.1016/j.isprsjprs.2020.05.004]
Gao F, Anderson M C, Zhang X Y, Yang Z W, Alfieri J G, Kustas W P, Mueller R, Johnson D M and Prueger J H. 2017. Toward mapping crop progress at field scales through fusion of Landsat and MODIS imagery. Remote Sensing of Environment, 188: 9-25 [DOI: 10.1016/j.rse.2016.11.004http://dx.doi.org/10.1016/j.rse.2016.11.004]
Han Y, Ke Y H, Zhu L J, Feng H, Zhang Q, Sun Z and Zhu L. 2021. Tracking vegetation degradation and recovery in multiple mining areas in Beijing, China, based on time-series Landsat imagery. GIScience and Remote Sensing, 58(8): 1477-1496 [DOI: 10.1080/15481603.2021.1996319http://dx.doi.org/10.1080/15481603.2021.1996319]
Lei K and Zhang M X. 2005. The wetland resources in china and the conservation advices. Wetland Science, 3(2): 81-86
雷昆, 张明祥. 2005. 中国的湿地资源及其保护建议. 湿地科学, 3(2): 81-86 [DOI: 10.13248/j.cnki.wetlandsci.2005.02.001http://dx.doi.org/10.13248/j.cnki.wetlandsci.2005.02.001]
Li F F. 2021-12-24. Ecological management of Spartina alterniflora. Farmers' Daily
李飞飞. 2021-12-24. 互花米草的生态治理. 农民日报
Li Y R, Wu H T, Zhang S, Lu X and Lu K L. 2021. Morphological characteristics and changes of tidal creeks in coastal wetlands of the Yellow River Delta under Spartina alterniflora invasion and continuous expansion. Wetland Science, 19(1): 88-97
李昱蓉, 武海涛, 张森, 卢霞, 芦康乐. 2021. 互花米草入侵和持续扩张下黄河三角洲滨海湿地潮沟的形态特征及其变化. 湿地科学, 19(1): 88-97 [DOI: 10.13248/j.cnki.wetlandsci.2021.01.009http://dx.doi.org/10.13248/j.cnki.wetlandsci.2021.01.009]
López-Amoedo A, Álvarez X, Lorenzo H and Rodríguez J L. 2021. Multi-temporal Sentinel-2 data analysis for smallholding forest cut control. Remote Sensing, 13(15): 2983 [DOI: 10.3390/rs13152983http://dx.doi.org/10.3390/rs13152983]
Lu J, Huang J L, Wang L H, Ye C J and Pei Y Y. 2018. Monitoring harvesting process of winter wheat using high spatial-temporal data. Remote Sensing Information, 33(4): 22-27
陆俊, 黄进良, 王立辉, 叶春姣, 裴艳艳. 2018. 利用高时空融合数据监测冬小麦收割过程. 遥感信息, 33(4): 22-27 [DOI: 10.3969/j.issn.1000-3177.2018.04.004http://dx.doi.org/10.3969/j.issn.1000-3177.2018.04.004]
Lymburner L, Bunting P, Lucas R, Scarth P, Alam I, Phillips C, Ticehurst C and Held A. 2020. Mapping the multi-decadal mangrove dynamics of the Australian coastline. Remote Sensing of Environment, 238: 111185 [DOI: 10.1016/j.rse.2019.05.004http://dx.doi.org/10.1016/j.rse.2019.05.004]
National Development and Reform Commission, Ministry of Natural Resources, People’s Republic of China. 2022. Issued by the Ministry of Natural Resources of the National Development and Reform Commission A notice on the Master Plan for Major Projects to Protect and Restore Important Ecosystems in China (2021-2035)[Z/OL]. [2022-07-09]. https://www.ndrc.gov.cn/xxgk/zcfb/tz/202006/t20200611_1231112.html?code=&state=123https://www.ndrc.gov.cn/xxgk/zcfb/tz/202006/t20200611_1231112.html?code=&state=123
中华人民共和国国家发展和改革委员会, 中华人民共和国自然资源部. 2022. 国家发展改革委 自然资源部关于印发《全国重要生态系统保护和修复重大工程总体规划(2021-2035年)》的通知[Z/OL]. [2022-07-09]. https://www.ndrc.gov.cn/xxgk/zcfb/tz/202006/t20200611_1231112.html?code=&state=123https://www.ndrc.gov.cn/xxgk/zcfb/tz/202006/t20200611_1231112.html?code=&state=123
Ren G B, Wang J J, Wang A D, Wang J B, Zhu Y L, Wu P Q, Ma Y and Zhang J. 2019. Monitoring the invasion of smooth cordgrass Spartina alterniflora within the modern Yellow River Delta using remote sensing. Journal of Coastal Research, 90(SI): 135-145 [DOI: 10.2112/SI90-017.1http://dx.doi.org/10.2112/SI90-017.1]
Ren W Y, Wang C, Liu H Y, Li Y F, Zhou Y, Xu J Y and Chen H. 2019. Diversity of vegetation coverage based on birds’ habitat demands in the coastal wetland of Yancheng, Jiangsu Province. Chinese Journal of Ecology, 38(12): 3870-3877
任武阳, 王成, 刘红玉, 李玉凤, 周奕, 徐嘉仪, 陈浩. 2019. 基于鸟类生境需求的植被景观覆盖度多样性——以江苏盐城滨海湿地为例. 生态学杂志, 38(12): 3870-3877 [DOI: 10.13292/j.1000-4890.201912.004http://dx.doi.org/10.13292/j.1000-4890.201912.004]
Schwieder M, Wesemeyer M, Frantz D, Pfoch K, Erasmi S, Pickert J, Nendel C and Hostert P. 2022. Mapping grassland mowing events across Germany based on combined Sentinel-2 and Landsat 8 time series. Remote Sensing of Environment, 269: 112795 [DOI: 10.1016/j.rse.2021.112795http://dx.doi.org/10.1016/j.rse.2021.112795]
Shandong Provincial Department of Natural Resources. 2020. Implementation plan of Spartina alterniflora control in Shandong province was published[Z/OL]. [2022-05-02]. https://www.forestry.gov.cn/main/394/20200819/163006883633293.htmlhttps://www.forestry.gov.cn/main/394/20200819/163006883633293.html.
山东省自然资源厅. 2020. 山东省互花米草防治实施方案印发[Z/OL]. [2022-05-02]. https://www.forestry.gov.cn/main/394/20200819/163006883633293.htmlhttps://www.forestry.gov.cn/main/394/20200819/163006883633293.html
Shang J L, Liu J G, Poncos V, Geng X Y, Qian B D, Chen Q H, Dong T F, Macdonald D, Martin T, Kovacs J and Walters D. 2020. Detection of crop seeding and harvest through analysis of time-series Sentinel-1 interferometric SAR data. Remote Sensing, 12(10): 1551 [DOI: 10.3390/rs12101551http://dx.doi.org/10.3390/rs12101551]
Shi D L, Tian J Y and Chen Y P. 2009. Biological and ecological characteristics of an invasive alien species Spartina in Yellow River Delta. Journal of Binzhou University, 25(3): 27-32
石东里, 田家怡, 陈印平. 2009. 黄河三角洲外来入侵物种米草的生物学与生态学特性. 滨州学院学报, 25(3): 27-32 [DOI: 10.3969/j.issn.1673-2618.2009.03.007http://dx.doi.org/10.3969/j.issn.1673-2618.2009.03.007]
Tang C D. 2016. Ecological control of Spartina alternilfora and improvement of birds habitats in Chongming Dongtan Wetland, Shanghai. Wetland Science and Management, 12(3): 4-8
汤臣栋. 2016. 上海崇明东滩互花米草生态控制与鸟类栖息地优化工程. 湿地科学与管理, 12(3): 4-8 [DOI: 10.3969/j.issn.1673-3290.2016.03.01http://dx.doi.org/10.3969/j.issn.1673-3290.2016.03.01.]
Wang X X, Xiao X M, Xu X, Zou Z H, Chen B Q, Qin Y W, Zhang X, Dong J W, Liu D Y, Pan L H and Li B. 2021. Rebound in China’s coastal wetlands following conservation and restoration. Nature Sustainability, 4(12): 1076-1083 [DOI: 10.1038/s41893-021-00793-5http://dx.doi.org/10.1038/s41893-021-00793-5]
Wen Q K, Zhang Z X, Xu J Y, Zuo L J, Wang X, Liu B, Zhao X L and Yi L. 2011. Spatial and temporal change of wetlands in Bohai rim during 2000—2008: an analysis based on satellite images. Journal of Remote Sensing, 15(1): 183-200
温庆可, 张增祥, 徐进勇, 左丽君, 汪潇, 刘斌, 赵晓丽, 易玲. 2011. 环渤海滨海湿地时空格局变化遥感监测与分析. 遥感学报, 15(1): 183-200 [DOI: 10.11834/jrs.20110115http://dx.doi.org/10.11834/jrs.20110115]
Xu Y D, Yu L, Zhao F R, Cai X L, Zhao J Y, Lu H and Gong P. 2018. Tracking annual cropland changes from 1984 to 2016 using time-series Landsat images with a change-detection and post-classification approach: experiments from three sites in Africa. Remote Sensing of Environment, 218: 13-31 [DOI: 10.1016/j.rse.2018.09.008http://dx.doi.org/10.1016/j.rse.2018.09.008]
Yu D X, Han G X, Wang X J and Zhang B H. 2022. Effects of Spartina alterniflora invasion on morphological characteristics of tidal creeks and plant community distribution in the Yellow River Estuary. Chinese Journal of Ecology, 41(1): 42-49
于冬雪, 韩广轩, 王晓杰, 张保华. 2022. 互花米草入侵对黄河口潮沟形态特征和植物群落分布的影响. 生态学杂志, 41(1): 42-49 [DOI: 10.13292/j.1000-4890.202201.003http://dx.doi.org/10.13292/j.1000-4890.202201.003]
Zhang F, Wu B F, Liu C L, Luo Z M, Zhang S W and Zhang G L. 2004. A method to extract regional crop growth profile with time series of NDVI data. Journal of Remote Sensing, 8(6): 515-528
张峰, 吴炳方, 刘成林, 罗治敏, 张树文, 张广录. 2004. 区域作物生长过程的遥感提取方法. 遥感学报, 8(6): 515-528 [DOI: 10.11834/jrs.20040603http://dx.doi.org/10.11834/jrs.20040603]
Zhang X, Xiao X M, Wang X X, Xu X, Chen B Q, Wang J, Ma J, Zhao B and Li B. 2020. Quantifying expansion and removal of Spartina alterniflora on Chongming island, China, using time series Landsat images during 1995-2018. Remote Sensing of Environment, 247: 111916 [DOI: 10.1016/j.rse.2020.111916http://dx.doi.org/10.1016/j.rse.2020.111916]
Zhang X Y, Zhou M Q, Wang W H and Li X J. 2015. Progress of global satellite remote sensing of atmospheric compositions and its’ applications. Science and Technology Review, 33(17): 13-22.
张兴赢, 周敏强, 王维和, 李晓静. 2015. 全球卫星大气成分遥感探测应用进展及其展望. 科技导报, 33(17): 13-22 [DOI: 10.3981/j.issn.1000-7857.2015.17.001http://dx.doi.org/10.3981/j.issn.1000-7857.2015.17.001]
Zhao F, Sun R, Zhong L H, Meng R, Huang C Q, Zeng X X, Wang M Y, Li Y X and Wang Z Y. 2022. Monthly mapping of forest harvesting using dense time series Sentinel-1 SAR imagery and deep learning. Remote Sensing of Environment, 269: 112822 [DOI: 10.1016/j.rse.2021.112822http://dx.doi.org/10.1016/j.rse.2021.112822]
Zhou D. 2020-08-03. Governance Spartina alterniflora wetland ecology gradually restored in Minjiang Estuary. Fuzhou Daily
周冬. 2020-08-03. 治理互花米草 闽江口湿地生态逐渐恢复. 福州日报
Zuo P, Zhao S H, Liu C, Wang C H and Liang Y B. 2012. Distribution of Spartina spp. along China's coast. Ecological Engineering, 40: 160-166 [DOI: 10.1016/j.ecoleng.2011.12.014http://dx.doi.org/10.1016/j.ecoleng.2011.12.014]
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