利用历史多光谱卫星图像开发珊瑚和竞争性藻类相关指数,以评估珊瑚礁的生态状况

Rongyong Huang , Zhiwei He , Kefu Yu , Zuofang Yao , Bin Zou , Junyou Xiao
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引用次数: 0

摘要

了解活珊瑚和竞争性藻类(包括草皮藻和大型藻类)生长区的特征对于评估珊瑚礁生态系统的退化情况至关重要。然而,在多光谱卫星图像中识别活珊瑚和竞争性藻类具有挑战性,因为不同的物体可能具有相似的光谱。为了解决这个问题,我们使用了在不同时间获取的两幅卫星图像(大地遥感卫星专题成像仪(TM)、大地遥感卫星业务陆地成像仪(OLI)或哨兵-2 多光谱仪器(MSI))来评估活珊瑚和竞争性藻类的生长区特征。该评估利用了竞争性藻类的季节性枯死和活珊瑚生长区在短时间内的相对稳定性。具体来说,我们开发了一种归一化红-绿差异指数(NRGI)来分割卫星图像中的活珊瑚或竞争藻类生长区。通过比较一张竞争藻类较少时期拍摄的图像和另一张竞争藻类茂盛时期拍摄的图像的分割结果,我们估算出了活珊瑚和竞争藻类的生长区面积。最后,我们计算了竞争藻生长区面积与活珊瑚生长区面积的比率(RCL)。1995 年至 2022 年在中国南海(SCS)8 个典型珊瑚岛和珊瑚礁上进行的实验表明(1) 在竞争藻较少的时期(1 月至 3 月)和竞争藻较多的时期(4 月至 10 月),活珊瑚生长区或竞争藻生长区的识别准确率分别达到 80.3% 和 92.6%;(2) RCL 与珊瑚-巨藻相遇率(表示竞争藻对活珊瑚压力的生态指数)具有良好的相关性(r = 0.79,P<0.05);(3)竞争藻类和活珊瑚的生长区以及 RCL 的变化趋势与南中国海的重大生态事件(如珊瑚白化、钝头栉水母爆发和黑带病)相一致。(4) 此外,还观察到热应力与 RCL 之间存在时滞相关性。总之,建议的方法简单、有效、可行。RCL 是反映珊瑚礁生态系统状况的一个重要指标,可突出显示竞争性藻类对活珊瑚的压力和珊瑚礁生态系统的退化。该方法引入了多光谱卫星图像在珊瑚礁生态系统评估中的新应用,在未来珊瑚礁生态系统监测中具有巨大潜力。
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Development of a coral and competitive alga-related index using historical multi-spectral satellite imagery to assess ecological status of coral reefs
Understanding the characteristics of the growth zones of live corals and competitive algae, including turf algae and macroalgae, is crucial for assessing the degradation of coral reef ecosystems. However, identifying live corals and competitive algae in multispectral satellite images is challenging because different objects can have similar spectra. To address this, we used two satellite images acquired at different times (Landsat thematic mapper (TM), Landsat operational land imager (OLI), or Sentinel-2 multi-spectral instrument (MSI)) to assess the growth zone characteristics of live corals and competitive algae. This assessment leveraged the seasonal dieback of competitive algae and the relative stability of live-coral growth zones over a short period. Specifically, we developed a normalized red–green difference index (NRGI) to segment live-coral-or-competitive-alga growth zones in satellite images. By comparing the segmentation results from an image captured during a period with few competitive algae and another image captured during a period with lush competitive algae, we estimated the growth zone areas of the live corals and competitive algae. Finally, we calculated the ratio of the competitive-alga growth zone area to the live-coral growth zone area (RCL). Experiments on eight typical coral islands and reefs in the South China Sea (SCS) from 1995 to 2022 revealed that: (1) the identification accuracies of live-coral-or-competitive-alga growth zones reached 80.3 % and 92.6 % during periods with few competitive algae (January to March) and lush competitive algae (April to October), respectively; (2) the RCL was well correlated with the coral-macroalgae encounter rate (an ecological index indicating the pressure of the competitive algae on the live corals) (r = 0.79, P<0.05); and (3) the trends in the growth zones of competitive algae and live corals, along with the RCL, were consistent with major ecological events in the SCS, such as coral bleaching, outbreak of Acanthaster planci, and black band disease. (4) Moreover, a time-lagged correlation was observed between heat stress and the RCL. In summary, the proposed approach is simple, effective, and feasible. The RCL is a valuable indicator of the status of coral reef ecosystems, highlighting the pressure of competitive algae on live corals and the degradation of coral reef ecosystems. This method introduces a novel application of multispectral satellite images for assessing coral reef ecosystems and has significant potential for future coral reef ecosystem monitoring.
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来源期刊
International journal of applied earth observation and geoinformation : ITC journal
International journal of applied earth observation and geoinformation : ITC journal Global and Planetary Change, Management, Monitoring, Policy and Law, Earth-Surface Processes, Computers in Earth Sciences
CiteScore
12.00
自引率
0.00%
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0
审稿时长
77 days
期刊介绍: The International Journal of Applied Earth Observation and Geoinformation publishes original papers that utilize earth observation data for natural resource and environmental inventory and management. These data primarily originate from remote sensing platforms, including satellites and aircraft, supplemented by surface and subsurface measurements. Addressing natural resources such as forests, agricultural land, soils, and water, as well as environmental concerns like biodiversity, land degradation, and hazards, the journal explores conceptual and data-driven approaches. It covers geoinformation themes like capturing, databasing, visualization, interpretation, data quality, and spatial uncertainty.
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