Précédent|Prochain

Dynamic monitoring of invasive Spartina alterniflora clearance via fusion of Sentinel-2 and GF-1 time series images

  • role： First author第一作者
  • Affiliation：

    State Key Laboratory Cultivation Base of Urban Environment Process and Simulation, Beijing 100048, China

    Beijing Laboratory of Water Resources Security, Beijing 100048, China

    College of Resource Environment and Tourism, Capital Normal University, Beijing 100048, China

  • Email：2210902155@cnu.edu.cn
  • Introduction：闵钰魁，研究方向为多源遥感数据融合，生态水文遥感应用。E-mail： 2210902155@cnu.edu.cn
MIN Yukui,  
  • role： Corresponding author通信作者
  • Affiliation：

    State Key Laboratory Cultivation Base of Urban Environment Process and Simulation, Beijing 100048, China

    Beijing Laboratory of Water Resources Security, Beijing 100048, China

    College of Resource Environment and Tourism, Capital Normal University, Beijing 100048, China

  • Email：yke@cnu.edu.cn
  • Introduction：柯樱海，研究方向为多源遥感数据融合，人工智能及数据挖掘方法，生态水文遥感应用。E-mail： yke@cnu.edu.cn
KE Yinghai*,  
  • Affiliation：

    State Key Laboratory Cultivation Base of Urban Environment Process and Simulation, Beijing 100048, China

    Beijing Laboratory of Water Resources Security, Beijing 100048, China

    College of Resource Environment and Tourism, Capital Normal University, Beijing 100048, China

HAN Yue,  
  • Affiliation：

    State Key Laboratory Cultivation Base of Urban Environment Process and Simulation, Beijing 100048, China

    Beijing Laboratory of Water Resources Security, Beijing 100048, China

    College of Resource Environment and Tourism, Capital Normal University, Beijing 100048, China

YIN Xiaolan,  
  • Affiliation：

    State Key Laboratory Cultivation Base of Urban Environment Process and Simulation, Beijing 100048, China

    Beijing Laboratory of Water Resources Security, Beijing 100048, China

    College of Resource Environment and Tourism, Capital Normal University, Beijing 100048, China

ZHOU Demin

résumé

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.

mots-clés

Sentinel-2;GF-1;Invasive species;Spartina alterniflora management;coastal wetland;time series

References

  1. 1.
    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
  2. 2.
    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
  3. 3.
    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].
  4. 4.
    Chung C H. 2006. Forty years of ecological engineering with Spartina plantations in China. Ecological Engineering, 27(1): 49-57
  5. 5.
    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
  6. 6.
    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
  7. 7.
    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
  8. 8.
    Lei K and Zhang M X. 2005. The wetland resources in china and the conservation advices. Wetland Science, 3(2): 81-86
  9. 9.
    Li F F. 2021-12-24. Ecological management of Spartina alterniflora. Farmers' Daily
  10. 10.
    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
  11. 11.
    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
  12. 12.
    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
  13. 13.
    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
  14. 14.
    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].
  15. 15.
    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
  16. 16.
    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
  17. 17.
    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
  18. 18.
    Shandong Provincial Department of Natural Resources. 2020. Implementation plan of Spartina alterniflora control in Shandong province was published[Z/OL]. [2022-05-02]. .
  19. 19.
    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
  20. 20.
    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
  21. 21.
    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
  22. 22.
    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
  23. 23.
    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
  24. 24.
    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
  25. 25.
    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
  26. 26.
    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
  27. 27.
    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
  28. 28.
    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.
  29. 29.
    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
  30. 30.
    Zhou D. 2020-08-03. Governance Spartina alterniflora wetland ecology gradually restored in Minjiang Estuary. Fuzhou Daily
  31. 31.
    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

Lire l'article complet

The above content is generated by Large Model Translation. The translated content is for reference only. We do not assume any commercial or legal responsibilty for any consequences arising from the use of our website