Monitoring riverine traffic from space: The untapped potential of remote sensing for measuring human footprint on inland waterways.
Monitoring riverine traffic from space: The untapped potential of remote sensing for measuring human footprint on inland waterways.
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从太空监测河流交通：遥感测量内陆水道人类足迹的未开发潜力。
DOI：
10.1016/j.scitotenv.2022.160363
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发表时间：
2023
期刊：
影响因子：
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通讯作者：
Smigaj M
中科院分区：
文献类型：
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作者：
Smigaj M
河流三角洲的大规模城市化和密集型农业发展推动了生态系统退化，影响了三角洲的社会生态系统，降低了它们对气候变化的适应能力。到目前为止，对这些变化的驱动因素的评估主要集中在陆上三角洲平原上的人类活动。然而，三角洲生态系统的脆弱性和在全球范围内保护生物多样性的需要，需要更准确地量化三角洲水道上人类活动的足迹。为了满足这一需求，我们研究了深度学习和高时空分辨率卫星图像识别内河船舶的潜力，并将越南湄公河三角洲（VMD）作为重点区域。我们训练了Faster R-CNN Resnet101模型来检测两类对象：（i）血管和（ii）血管簇，并实现了两类对象的高检测精度（f-score = 0.84 - 0.85）。该模型随后被应用于2018 - 2021年期间可用的PlanetScope图像;由此产生的检测结果被用于生成每月，季节和年度的产品，绘制河流活动，在这里称为人类水道足迹（HWF），我们用它来展示VMD中的水上活动是如何增加的（从大约2018年到2021年）。2018年的1650艘活跃船只到2021年的2070艘-增长25%）。虽然HWF值与人口密度估计值相关性很好（R2 = 0.59 - 0.61，p <0.001），但许多河流活动热点位于远离人口中心的地方，并且在调查期间的空间变化，强调需要更详细的信息来全面评估人类足迹的范围和类型。高时空分辨率卫星图像与深度学习方法相结合，为此类监测提供了巨大的前景，从而能够对人类活动对地球仪周围三角洲生态系统的环境影响进行地方和区域评估。
Mass urbanisation and intensive agricultural development across river deltas have driven ecosystem degradation, impacting deltaic socio-ecological systems and reducing their resilience to climate change. Assessments of the drivers of these changes have so far been focused on human activity on the subaerial delta plains. However, the fragile nature of deltaic ecosystems and the need for biodiversity conservation on a global scale require more accurate quantification of the footprint of anthropogenic activity across delta waterways. To address this need, we investigated the potential of deep learning and high spatiotemporal resolution satellite imagery to identify river vessels, using the Vietnamese Mekong Delta (VMD) as a focus area. We trained the Faster R-CNN Resnet101 model to detect two classes of objects: (i) vessels and (ii) clusters of vessels, and achieved high detection accuracies for both classes (f-score = 0.84–0.85). The model was subsequently applied to available PlanetScope imagery across 2018–2021; the resultant detections were used to generate monthly, seasonal and annual products mapping the riverine activity, termed here the Human Waterway Footprint (HWF), with which we showed how waterborne activity has increased in the VMD (from approx. 1650 active vessels in 2018 to 2070 in 2021 - a 25 % increase). Whilst HWF values correlated well with population density estimates (R2= 0.59–0.61,p< 0.001), many riverine activity hotspots were located away from population centres and varied spatially across the investigated period, highlighting that more detailed information is needed to fully evaluate the extent, and type, of human footprint on waterways. High spatiotemporal resolution satellite imagery in combination with deep learning methods offers great promise for such monitoring, which can subsequently enable local and regional assessment of environmental impacts of anthropogenic activities on delta ecosystems around the globe.