Morphology of coastal salt marsh margins: a study using UAV-based Structure-from-Motion photogrammetry
-
摘要: 海岸盐沼前缘作为盐沼和光滩间的过渡带,在垂向剖面上呈现光滑、过渡、陡坎3种地貌类型,在平面岸线上也展现出不同的曲直特征。受到自然过程和人类活动的影响,盐沼前缘这一高度动态的生物地貌系统变化迅速,而高分辨率观测数据的缺乏使得这种变化难以得到充分认识。无人机SfM(Structure from Motion)摄影测量具有高分辨率、非侵入、可重复和低成本的优点,为解决上述问题提供可能。我们在江苏省盐城市大丰区海岸盐沼开展两次无人机调查,获取厘米级分辨率正射影像和地形数据。在高精度数据支持下,成功确定盐沼前缘位置,划分前缘类型,并定量刻画地形变化。研究发现:光滑和陡坎前缘占优势,形态稳定;光滑前缘平面轮廓复杂,后退速率小,过渡和陡坎前缘轮廓平直,后退明显;过渡前缘地形变化剧烈,向陡坎前缘转变。这项工作证明无人机SfM摄影测量适用于高效精准量化盐沼前缘形态,为认识盐沼前缘形态演化过程提供新视角。
-
关键词:
- 无人机SfM摄影测量 /
- 盐沼前缘 /
- 地貌监测 /
- 地貌变化
Abstract: Coastal salt marsh margin, as the transition zone between salt marsh and tidal flat, presents three types of three-dimensional form: smooth, transition and cliff. And it shows different curvilinear features in the planar shape. As a high dynamic bio-geomorphic system, marsh margin changes rapidly due to the influence of natural processes and human activities. But the lack of high-resolution observational data makes further understanding of this change difficult. Here, we address this challenge using UAV-based Structure-from-Motion (UAV-SfM) photogrammetry which has the advantages of high resolution, non-invasive, repeatability, and low cost. We conducted two aerial surveys of salt marsh on Jiangsu coast, to obtain orthophotographs and Digital Surface Model (DSM) with cm-level pixel resolutions. And it supports us to determine the location of marsh margin, classify the type of the margin, and quantitatively describe the topography changes. We found the smooth and cliff margin are stable and dominant. The smooth margin has complex planar shape and retreats slowly. And the transition and cliff margin have regular shape and retreat fast. The transition margin changes drastically and turns to the cliff margin. This work proves that UAV-SfM photogrammetry is suitable for efficient and accurate quantification of the topography of marsh margin, and provides a new perspective for understanding the evolution process of marsh margin. -
图 1 江苏省盐城市大丰区研究区位置(背景为2018年2月3日的Landsat-8卫星影像)(a)、航测调查区域和地面控制点及检查点分布情况(底图为2021年3月航测正射影像)(b)以及人工标志物照片(c,d)
Fig. 1 Location of the study area at Dafeng, Jiangsu, China (satellite imagery from Landsat-8 data, acquired on February 3, 2018) (a), the area of aerial surveys and ground control points (GCPs) and check points (CPs) used for aerial surveys, (background is the orthomosaic from UAV, acquired on March 2021) (b) and examples of ground artificial markers (c, d)
图 3 验证点分布情况(背景为2021年3月正射影像)(a)、RTK地面高程同地表高程模型对比(b−g)和S1–S5短剖面上验证点的详细分布(底图为2020年9月正射影像)(h−l)
由于S1−S5短剖面验证点密集,黄色矩形表示短剖面位置
Fig. 3 Distribution of validation points (background is the March 2021 orthomosaic) (a), RTK elevation is compared with digital surface model (b−g) and the detailed distribution of validation points on the S1–S5 short profiles (background is the September 2020 orthomosaic) (h−l)
Due to the dense distribution of validation points in S1−S5 short profiles, the yellow rectangle corresponds the position of the short profile
图 4 不同类型盐沼前缘分布情况
a. 2020年9月;b. 2021年3月,红色矩形为过渡前缘和陡坎前缘集中的区域,在两次观测期间形态变化剧烈,在图6、图7中详细说明,白色十字形为光滑前缘转变为陡坎前缘的区域,航拍照片见图5;c. 光滑前缘航拍照片;d. 过渡前缘航拍照片;e. 陡坎前缘航拍照片
Fig. 4 Distribution of the marginal classification of the salt marsh area
a. September 2020; b. March 2021, the red rectangular boxes is the area where the transition margin and the cliff margin are concentrated, this area has a dramatic morphological change between the two surveys and is illustrated in detail in Fig. 6 and Fig. 7, the white cross is the area where the smooth margin transforms into the cliff margin, see Fig. 5 for aerial photos; c. photo of smooth margin; d. photo of the transition margin; e. photo of the cliff margin
图 5 发生类型转换的盐沼前缘
a. 2020年9月;b. 2021年3月,两图拍摄位置相同(图4白色十字形位置),分别表现出光滑前缘(a)和陡坎前缘(b)的特征
Fig. 5 The salt marsh margins where the type conversion took place
a. September 2020; b. March 2021, with the same shooting position (the position of white cross in Fig. 4), showed the characteristics of smooth margin (a) and cliff margin (b)
图 6 2021年3月的正射影像(a)、2020年9月和2021年3月间红色矩形区域内前缘侵蚀速率的空间分布(b)和图b蓝色矩形区域的特写(c−e)
红色矩形代表盐沼前缘位置明显后退的区域,红色圆圈颜色越深侵蚀速率越大
Fig. 6 Orthomosaic in March 2021 (a), spatial distribution of erosion rates between September 2020 and March 2021 in the red rectangle area (b) and close-up views of the blue rectangular areas of the figure b (c−e)
The red rectangle represents an area where the salt marsh margin is receding, the darker the color of the red circle, the greater the rate of erosion
图 7 盐沼前缘位置明显后退的区域特写(a);区域1、区域2及区域3在2020年9月的坡度图(b,d,f);区域1、区域2及区域3在2021年3月的坡度图(c,e,g); A–A'、B–B'和C–C' 剖面在2020年9月到2021年3月的DSM高程变化(h−j)
黄色虚线框代表子区域位置,蓝色箭头代表互花米草斑块间通道,绿色矩形代表过渡前缘的位置,灰色矩形代表过渡前缘斜坡的坡脚位置
Fig. 7 The close-up view of an area where the salt marsh margin is receding (a); slope maps for areas 1, 2 and 3 in September 2020 (b, d, f); slope maps for areas 1, 2 and 3 in March 2021 (c, e, g); DSM elevation changes for A–A', B–B' and C–C' profiles between September 2020 and March 2021 (h−j)
The yellow dashed wireframe represents the position of the sub-area, the blue arrow represents the passage between the Spartina alterniflora patches, the green rectangle represents the position of the transition margin and the gray rectangle represents the foot position of the ramp of the transition margin
表 1 SfM摄影测量建模质量及精度
Tab. 1 Quality assessment and geometric accuracy of SfM photogrammetry
航测时间 地面控制点数 点云密度/(pts·m–2) 正射影像分辨率/(cm·pix–1) DSM 分辨率/(cm·pix–1) 水平精度/cm 垂向精度/cm 总体精度/cm 2020年9月 3 336 2.73 5.45 7.58 1.47 7.72 2021年3月 4 330 2.75 5.5 7.68 2.57 8.10 表 2 不同类型盐沼前缘的长度
Tab. 2 Length of different types of salt marsh margins
航测时间 光滑前缘
/m过渡前缘
/m陡坎前缘
/m2020年9月 2 227.86 291.73 419.81 2021年3月 1 997.10 289.00 647.67 表 3 不同类型盐沼前缘的分形维数
Tab. 3 Fractal dimension of different types of salt marsh margins
航测时间 光滑前缘 过渡前缘 陡坎前缘 2020年9月 1.21 1.14 1.14 2021年3月 1.19 1.14 1.15 -
[1] Allen J R L. Morphodynamics of Holocene salt marshes: a review sketch from the Atlantic and southern North Sea coasts of Europe[J]. Quaternary Science Reviews, 2000, 19(12): 1155−1231. doi: 10.1016/S0277-3791(99)00034-7 [2] Möller I, Kudella M, Rupprecht F, et al. Wave attenuation over coastal salt marshes under storm surge conditions[J]. Nature Geoscience, 2014, 7(10): 727−731. doi: 10.1038/ngeo2251 [3] Stark J, Plancke Y, Ides S, et al. Coastal flood protection by a combined nature-based and engineering approach: modeling the effects of marsh geometry and surrounding dikes[J]. Estuarine, Coastal and Shelf Science, 2016, 175: 34−45. doi: 10.1016/j.ecss.2016.03.027 [4] Chmura G L, Anisfeld S C, Cahoon D R, et al. Global carbon sequestration in tidal, saline wetland soils[J]. Global Biogeochemical Cycles, 2003, 17(4): 1111. [5] Haas H L, Rose K A, Fry B, et al. Brown shrimp on the edge: linking habitat to survival using an individual-based simulation model[J]. Ecological Applications, 2004, 14(4): 1232−1247. doi: 10.1890/03-5101 [6] Nelson J L, Zavaleta E S. Salt marsh as a coastal filter for the oceans: changes in function with experimental increases in nitrogen loading and sea-level rise[J]. PLoS ONE, 2012, 7(8): e38558. doi: 10.1371/journal.pone.0038558 [7] Leonardi N, Carnacina I, Donatelli C, et al. Dynamic interactions between coastal storms and salt marshes: a review[J]. Geomorphology, 2018, 301: 92−107. doi: 10.1016/j.geomorph.2017.11.001 [8] Fagherazzi S, Mariotti G, Leonardi N, et al. Salt marsh dynamics in a period of accelerated sea level rise[J]. Journal of Geophysical Research: Earth Surface, 2020, 125(8): e2019JF005200. [9] Mudd S M, Howell S M, Morris J T. Impact of dynamic feedbacks between sedimentation, sea-level rise, and biomass production on near-surface marsh stratigraphy and carbon accumulation[J]. Estuarine, Coastal and Shelf Science, 2009, 82(3): 377−389. doi: 10.1016/j.ecss.2009.01.028 [10] Kirwan M L, Guntenspergen G R. Influence of tidal range on the stability of coastal marshland[J]. Journal of Geophysical Research: Earth Surface, 2010, 115(F2): F02009. [11] Ladd C J T, Duggan-Edwards M F, Bouma T J, et al. Sediment supply explains long-term and large-scale patterns in salt marsh lateral expansion and erosion[J]. Geophysical Research Letters, 2019, 46(20): 11178−11187. doi: 10.1029/2019GL083315 [12] Van de Koppel J, van der Wal D, Bakker J P, et al. Self-organization and vegetation collapse in salt marsh ecosystems[J]. The American Naturalist, 2005, 165(1): E1−E12. doi: 10.1086/426602 [13] Zhao Yangyang, Yu Qian, Wang Dandan, et al. Rapid formation of marsh-edge cliffs, Jiangsu coast, China[J]. Marine Geology, 2017, 385: 260−273. doi: 10.1016/j.margeo.2017.02.001 [14] Leonardi N, Fagherazzi S. How waves shape salt marshes[J]. Geology, 2014, 42(10): 887−890. doi: 10.1130/G35751.1 [15] Leonardi N, Defne Z, Ganju N K, et al. Salt marsh erosion rates and boundary features in a shallow Bay[J]. Journal of Geophysical Research: Earth Surface, 2016, 121(10): 1861−1875. doi: 10.1002/2016JF003975 [16] Evans B R, Möller I, Spencer T, et al. Dynamics of salt marsh margins are related to their three-dimensional functional form[J]. Earth Surface Processes and Landforms, 2019, 44(9): 1816−1827. [17] Xie Weiming, Guo Leicheng, Wang Xianye, et al. Detection of seasonal changes in vegetation and morphology on coastal salt marshes using terrestrial laser scanning[J]. Geomorphology, 2021, 380: 107621. doi: 10.1016/j.geomorph.2021.107621 [18] Ganju N K, Defne Z, Fagherazzi S. Are elevation and open-water conversion of salt marshes connected?[J]. Geophysical Research Letters, 2020, 47(3): e2019GL086703. [19] Anthony E J, Dolique F, Gardel A, et al. Nearshore intertidal topography and topographic-forcing mechanisms of an Amazon-derived mud bank in French Guiana[J]. Continental Shelf Research, 2008, 28(6): 813−822. doi: 10.1016/j.csr.2008.01.003 [20] Brunier G, Michaud E, Fleury J, et al. Assessing the relationship between macro-faunal burrowing activity and mudflat geomorphology from UAV-based Structure-from-Motion photogrammetry[J]. Remote Sensing of Environment, 2020, 241: 111717. doi: 10.1016/j.rse.2020.111717 [21] Anderson K, Westoby M J, James M R. Low-budget topographic surveying comes of age: structure from motion photogrammetry in geography and the geosciences[J]. Progress in Physical Geography: Earth and Environment, 2019, 43(2): 163−173. doi: 10.1177/0309133319837454 [22] Taddia Y, Pellegrinelli A, Corbau C, et al. High-resolution monitoring of tidal systems using UAV: a case study on Poplar Island, MD (USA)[J]. Remote Sensing, 2021, 13(7): 1364. doi: 10.3390/rs13071364 [23] Gómez-Pazo A, Pérez-Alberti A, Trenhaile A. High resolution mapping and analysis of shore platform morphology in Galicia, northwestern Spain[J]. Marine Geology, 2021, 436: 106471. doi: 10.1016/j.margeo.2021.106471 [24] Koukouvelas I Κ, Nikolakopoulos K G, Zygouri V, et al. Post-seismic monitoring of cliff mass wasting using an unmanned aerial vehicle and field data at Egremni, Lefkada Island, Greece[J]. Geomorphology, 2020, 367: 107306. doi: 10.1016/j.geomorph.2020.107306 [25] Leonardi N, Fagherazzi S. Effect of local variability in erosional resistance on large-scale morphodynamic response of salt marshes to wind waves and extreme events[J]. Geophysical Research Letters, 2015, 42(14): 5872−5879. doi: 10.1002/2015GL064730 [26] Fagherazzi S, Kirwan M L, Mudd S M, et al. Numerical models of salt marsh evolution: ecological, geomorphic, and climatic factors[J]. Reviews of Geophysics, 2012, 50(1): RG1002. [27] Zhang Xiaodong, Lu Zhiyong, Jiang Shenghui, et al. The progradation and retrogradation of two newborn Huanghe (Yellow River) Delta lobes and its influencing factors[J]. Marine Geology, 2018, 400: 38−48. doi: 10.1016/j.margeo.2018.03.006 [28] Chen L, Zhou Z, Xu F, et al. Field observation of saltmarsh-edge morphology and associated vegetation characteristics in an open-coast tidal flat[J]. Journal of Coastal Research, 2020, 95(S1): 412−416. [29] 任美锷, 张忍顺, 杨巨海. 江苏王港地区淤泥质潮滩的沉积作用[J]. 海洋通报, 1984(1): 40−54.Ren Mei’e, Zhang Renshun, Yang Juhai. Sedimentation on tidal mud flat in Wanggang Area, Jiangsu Province, China[J]. Marine Science Bulletin, 1984(1): 40−54. [30] 任美锷. 江苏省海岸带与海涂资源综合调查报告[M]. 北京: 海洋出版社, 1986.Ren Mei’e. Comprehensive Investigation of the Coastal Zone and Tidal Flat Resources of Jiangsu Province[M]. Beijing: China Ocean Press, 1986. [31] 张忍顺, 沈永明, 陆丽云, 等. 江苏沿海互花米草(Spartina alterniflora)盐沼的形成过程[J]. 海洋与湖沼, 2005, 36(4): 358−366. doi: 10.3321/j.issn:0029-814X.2005.04.011Zhang Renshun, Shen Yongming, Lu Liyun, et al. Formation of Spartina alterniflora salt marsh on Jiangsu Coast, China[J]. Oceanologia et Limnologia Sinica, 2005, 36(4): 358−366. doi: 10.3321/j.issn:0029-814X.2005.04.011 [32] 赵秧秧, 高抒, 王丹丹, 等. 盐沼前缘陡坎韵律性形态特征及其形成过程与机理[J]. 地理学报, 2014, 69(3): 378−390. doi: 10.11821/dlxb201403009Zhao Yangyang, Gao Shu, Wang Dandan, et al. Characteristics and formation mechanisms of the rhythmicmorphology of salt-marsh edge cliffs[J]. Acta Geographica Sinica, 2014, 69(3): 378−390. doi: 10.11821/dlxb201403009 [33] Nikolakopoulos K G, Soura K, Koukouvelas I K, et al. UAV vs classical aerial photogrammetry for archaeological studies[J]. Journal of Archaeological Science: Reports, 2017, 14: 758−773. doi: 10.1016/j.jasrep.2016.09.004 [34] Peppa M V, Hall J, Goodyear J, et al. Photogrammetric assessment and comparison of Dji Phantom 4 Pro and Phantom 4 Rtk small unmanned aircraft systems[J]. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2019, XLII-2/W13: 503−509. doi: 10.5194/isprs-archives-XLII-2-W13-503-2019 [35] Mian O, Lutes J, Lipa G, et al. Direct georeferencing on small unmanned aerial platforms for improved reliability and accuracy of mapping without the need for ground control points[J]. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2015, XL-1/W4: 397−402. doi: 10.5194/isprsarchives-XL-1-W4-397-2015 [36] Forlani G, Dall’Asta E, Diotri F, et al. Quality assessment of DSMs produced from UAV flights georeferenced with on-board RTK positioning[J]. Remote Sensing, 2018, 10(2): 311. doi: 10.3390/rs10020311 [37] Long N, Millescamps B, Guillot B, et al. Monitoring the topography of a dynamic tidal inlet using UAV imagery[J]. Remote Sensing, 2016, 8(5): 387. doi: 10.3390/rs8050387 [38] Westoby M J, Brasington J, Glasser N F, et al. ‘Structure-from-Motion’ photogrammetry: a low-cost, effective tool for geoscience applications[J]. Geomorphology, 2012, 179: 300−314. doi: 10.1016/j.geomorph.2012.08.021 [39] Jaud M, Grasso F, Le Dantec N, et al. Potential of UAVs for monitoring mudflat morphodynamics (application to the seine estuary, France)[J]. ISPRS International Journal of Geo-Information, 2016, 5(4): 50. doi: 10.3390/ijgi5040050 [40] Chassereau J E, Bell J M, Torres R. A comparison of GPS and lidar salt marsh DEMs[J]. Earth Surface Processes and Landforms, 2011, 36(13): 1770−1775. doi: 10.1002/esp.2199 [41] Goodwin G C H, Mudd S M, Clubb F J. Unsupervised detection of salt marsh platforms: a topographic method[J]. Earth Surface Dynamics, 2018, 6(1): 239−255. doi: 10.5194/esurf-6-239-2018 [42] Farris A S, Defne Z, Ganju N K. Identifying salt marsh shorelines from remotely sensed elevation data and imagery[J]. Remote Sensing, 2019, 11(15): 1795. doi: 10.3390/rs11151795 [43] McLoughlin S M, Wiberg P L, Safak I, et al. Rates and forcing of marsh edge erosion in a shallow coastal bay[J]. Estuaries and Coasts, 2015, 38(2): 620−638. doi: 10.1007/s12237-014-9841-2 [44] Thieler E R, Himmelstoss E A, Zichichi J L, et al. The Digital Shoreline Analysis System (DSAS) version 4.0-an ArcGIS extension for calculating shoreline change[R]. Reston, VA: U. S. Geological Survey, 2009. [45] Allen J R L. Muddy alluvial coasts of Britain: field criteria for shoreline position and movement in the recent past[J]. Proceedings of the Geologists’ Association, 1993, 104(4): 241−262. doi: 10.1016/S0016-7878(08)80044-2 [46] Donadio C, Paliaga G, Radke J D. Tsunamis and rapid coastal remodeling: linking energy and fractal dimension[J]. Progress in Physical Geography: Earth and Environment, 2020, 44(4): 550−571. doi: 10.1177/0309133319893924 [47] Dubuc B, Quiniou J F, Roques-Carmes C, et al. Evaluating the fractal dimension of profiles[J]. Physical Review A, 1989, 39(3): 1500−1512. doi: 10.1103/PhysRevA.39.1500 [48] Temmerman S, Bouma T J, Van de Koppel J, et al. Vegetation causes channel erosion in a tidal landscape[J]. Geology, 2007, 35(7): 631−634. doi: 10.1130/G23502A.1 [49] Lopes C L, Mendes R, Caçador I, et al. Assessing salt marsh extent and condition changes with 35 years of Landsat imagery: Tagus Estuary case study[J]. Remote Sensing of Environment, 2020, 247: 111939. doi: 10.1016/j.rse.2020.111939 [50] Zhang H, Aldana-Jague E, Clapuyt F, et al. Evaluating the potential of post-processing kinematic (PPK) georeferencing for UAV-based structure-from-motion (SfM) photogrammetry and surface change detection[J]. Earth Surface Dynamics, 2019, 7(3): 807−827. doi: 10.5194/esurf-7-807-2019 [51] Tomaštík J, Mokroš M, Surový P, et al. UAV RTK/PPK method—an optimal solution for mapping inaccessible forested areas?[J]. Remote Sensing, 2019, 11(6): 721. doi: 10.3390/rs11060721 [52] Woodget A S, Carbonneau P E, Visser F, et al. Quantifying submerged fluvial topography using hyperspatial resolution UAS imagery and structure from motion photogrammetry[J]. Earth Surface Processes and Landforms, 2015, 40(1): 47−64. doi: 10.1002/esp.3613 [53] Hladik C, Alber M. Accuracy assessment and correction of a LIDAR-derived salt marsh digital elevation model[J]. Remote Sensing of Environment, 2012, 121: 224−235. doi: 10.1016/j.rse.2012.01.018 [54] Kumar L, Sinha P. Mapping salt-marsh land-cover vegetation using high-spatial and hyperspectral satellite data to assist wetland inventory[J]. GIScience & Remote Sensing, 2014, 51(5): 483−497. [55] Tonelli M, Fagherazzi S, Petti M. Modeling wave impact on salt marsh boundaries[J]. Journal of Geophysical Research: Oceans, 2010, 115(C9): C09028. [56] Mariotti G, Fagherazzi S. A numerical model for the coupled long-term evolution of salt marshes and tidal flats[J]. Journal of Geophysical Research: Earth Surface, 2010, 115(F1): F01004. [57] Allen J R L. Evolution of salt-marsh cliffs in muddy and sandy systems: a qualitative comparison of British West-Coast estuaries[J]. Earth Surface Processes and Landforms, 1989, 14(1): 85−92. doi: 10.1002/esp.3290140108