Sudden and unexpected, landslides and avalanches claim thousands of lives each year and cause billions of dollars in damage. What if we could see them coming?
山体滑坡和雪崩来势汹汹、毫无征兆，每年都夺去成千上万人的生命，造成数十亿美元的损失。如果能够提前预知它们的到来，那该多好啊？
All around the village of Kimtang, in central Nepal, are tell-tale signs that something isn’t right. There are cracks in the concrete steps of houses, trees growing at strange angles – evidence that the ground is shifting beneath the villagers’ feet. The question is, just how much is the ground moving?
在尼泊尔中部的金唐村周围，到处都能看到一些不寻常的迹象，表明这里的情况不太对劲。房屋的混凝土台阶上出现了裂缝，树木也以奇怪的角度生长着——这些都是地面正在移动的证据。问题是，地面的移动程度究竟有多大呢？
“This is not good,” says Antoinette Tordesillas, a mathematician at the University of Melbourne, as she shows me an overhead view of Kimtang via Zoom. There’s a large red spot on the image, which is not any old satellite image but a coloured map created by an artificial intelligence (AI) system.
“情况不太妙，”墨尔本大学的数学家安托瓦内特·托尔德西利亚斯说道。她通过 Zoom 向我展示了金塘的俯视图。图像上有一个巨大的红色斑块。那并非普通的卫星图像，而是一张由人工智能系统生成的彩色地图。
The AI has identified a large unstable area, right beneath the village, colouring it bright red amid the dark blue of the rest of the hillside. It means the village sits right on top of a spot at high risk of a potentially devastating landslide. “Their village, where they live and farm, are actually on the slope,” says Tordesillas. She and her colleagues have visited Nepal, and in some cases interviewed villagers about the slowly developing situation.
人工智能识别出了一块面积很大的不稳定区域，正好位于村庄的正下方。在山坡上其他区域的深蓝色背景中，这块区域被标记为鲜红色。这意味着，该村庄就坐落在极有可能发生毁灭性山体滑坡的危险地带。“他们的村庄和农田其实都位于斜坡上，”托尔德西利亚斯说道。她和她的同事们曾前往尼泊尔，与当地村民进行了交谈，了解这一日益严重的情况。
Landslides, she adds, might seem like sudden catastrophes that are impossible to predict. But satellite images captured using radar can reveal otherwise invisible signs of the ground starting to move days, weeks or even years in advance of a collapse. Granules of earth begin subtly separating from one another. “Dancers, if you like, following some kind of unwritten choreography,” says Tordesillas.
她补充说，山体滑坡看似是突如其来的灾难，根本无法预测。但实际上，利用雷达拍摄的卫星图像能够揭示出那些在山体崩塌前几天、几周甚至几年前就出现的、肉眼无法察觉的迹象。土壤中的颗粒开始逐渐分离开来。“可以说，这些颗粒就像是在遵循某种无形的‘舞蹈节奏’而移动的，”托尔德西利亚斯说道。
In this precarious village in the mountains of Nepal, lives may be at stake. The AI-generated image is a warning. But it’s also a chance.
在尼泊尔山区的这个岌岌可危的村庄里，人们的生命可能处于危险之中。这张由人工智能生成的图片其实是一种警告。但同时，它也代表着一种机会。
Landslides are becoming more common, partly due to climate change, but also more direct human activities such as construction works and mining. In the US, landslides kill 25-50 people each year and cause billions of dollars in damage. Worldwide, they claim thousands of lives annually. Predicting when and where they will happen is incredibly difficult. But developments in AI are making it possible, helping geologists identify thousands of slopes around the world that are at high risk of slipping.
山体滑坡越来越频繁地发生，部分原因是气候变化，但人类活动，如建筑工程和采矿活动，也是重要诱因。在美国，山体滑坡每年导致 25 到 50 人死亡，并造成数十亿美元的损失。在全球范围内，山体滑坡每年都会夺去数千人的生命。预测山体滑坡何时何地会发生极其困难。不过，人工智能技术的进步使得这一任务变得可能，有助于地质学家识别出全球范围内那些具有高滑坡风险的区域。
Nepal is home to some of the highest reaches of the Himalaya and is particularly prone to landslides and avalanches. In October 2025, a spate of landslides killed around 60 people in this mountainous country.
尼泊尔拥有喜马拉雅山脉中一些最高的峰顶，因此极易发生山体滑坡和雪崩。2025 年 10 月，该山区国家因连串的山体滑坡而造成约 60 人死亡。
While it’s possible to monitor such places using satellites, or ground-based sensors, observing large areas in this way generates vast amounts of data. Analysing it manually would be “beyond human capability”, says Tordesillas. Fortunately, well-established forms of AI such as machine learning can do this work.
虽然可以利用卫星或地面传感器来监测这些区域，但以这种方式来观测大片区域会产生海量数据。托尔德西利亚斯表示，人工分析这些数据“远远超出了人类的能力范围”。幸运的是，像机器学习这样的成熟人工智能技术能够胜任这项工作。
“We use our knowledge of the physics of [slope] failure to guide AI,” says Tordesillas. That is to say, this is a much more specialised system. That doesn’t mean it could never make a mistake – but it does mean that scientists can try to ensure that it reflects their own deep knowledge of how landslides unfold.
“我们利用自己对斜坡崩塌物理机制的了解来指导人工智能的运作，”托尔德西利亚斯说道。也就是说，这是一个高度专业化的系统。这并不意味着它永远不会出错——但至少科学家可以确保，该系统的运作方式能够体现他们对滑坡形成机制的深刻理解。
Kimtang’s villagers may be grateful for that. In 2019, they were relocated after a landslide struck a nearby area where they had been farming. “The unfortunate thing is, this area where they’ve been relocated to is the most unstable part in this whole region,” says Tordesillas.
金塘村的村民们或许会为此感到庆幸。2019 年，由于附近地区发生了山体滑坡，他们不得不离开原来的居住地。“不幸的是，他们现在所居住的这个地方，其实是整个地区中最不稳定的区域，”托尔德西利亚斯说道。
Getting the data to reveal this was, in part, a stroke of luck. It came from a European satellite called Sentinel-1, which bounces radar off the ground – at roughly 2,000 flashes per second – to map terrain in fine detail. Sentinel-1 happened to fly over this part of Nepal in just the right way. “The angle of the satellite on this particular village is such that we were able to get good measurements,” says Tordesillas.
能够获取到这些数据，某种程度上算是运气使然。这些数据来自一颗名为“Sentinel-1”的欧洲卫星。该卫星以每秒约 2,000 次的频率向地面发射雷达波，从而精确地绘制出地形图。恰巧，Sentinel-1 卫星以最佳角度飞过了尼泊尔的这一地区。“卫星相对于这个村庄的姿态恰到好处，因此我们才能获得准确的测量数据，”托尔德西利亚斯说道。
The latest imagery dates from January 2025 and, thankfully, no landslide has yet occurred there in the time since. But the information and analysis it allowed the AI to perform has given Tordesillas, and her partners at other institutions, an opportunity to inform villagers of the risk, work with them to develop ways of monitoring the situation at ground-level, and plan evacuation routes or muster points.
最新的影像数据来自 2025 年 1 月。幸运的是，自那以后，该地区并未发生任何山体滑坡。不过，这些数据和分析结果让人工智能能够发挥作用。托尔德西利亚斯及其在其他机构的合作伙伴借此机会向当地村民说明了相关风险，与他们一起探讨了监测当地情况的办法，同时规划了疏散路线和集结点。
Again, the AI map could help with that.
同样，人工智能绘制的地图也能在这方面提供帮助。
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