Tracing Hidden Mineral Deposits: How Hyperspectral Imaging Makes Rocks "Speak"

在甘肅柳園的戈壁深處，一支地質勘探隊正面臨著挑戰：如何在綿延數百平方公里的裸露巖層中，精準鎖定銅礦的蛛絲馬跡？十年前，這樣的任務需要地質隊員背著地質錘和羅盤，頂著烈日徒步數月，用肉眼辨識巖石顏色的微妙差異。而今天，他們只需放飛一架搭載高光譜成像儀的無人機——隨著鏡頭掃過蒼茫大地，巖石的“光譜指紋"在屏幕上躍動，隱藏的銅礦脈絡如同被施了魔法般浮現。

這雙穿透地表的“光譜之眼"，正是高光譜成像技術。它不僅能看清人眼無法捕捉的礦物光譜特征，甚至能通過巖石的細微反光差異，破解地球億萬年的地質密碼。

Deep in the Gobi Desert of Liuyuan, Gansu, a geological exploration team faces an unprecedented challenge: how can they accurately pinpoint traces of copper ore across hundreds of square kilometers of exposed rock formations? A decade ago, such a task would have required geologists to carry rock hammers and compasses, trekking for months under the scorching sun, relying on the naked eye to detect subtle variations in rock coloration. Today, they simply launch a drone equipped with a hyperspectral imager. As the sensor scans the vast terrain, the "spectral fingerprints" of the rocks flicker across the screen, and hidden copper veins emerge as if by magic.

This "spectral eye" that penetrates the Earth's surface is hyperspectral imaging technology. It not only captures mineral spectral characteristics invisible to the human eye but also deciphers billions of years of geological history through subtle differences in rock reflectance.

對現場采集的36個樣品（左一）在實驗室進行了高光譜和傳統方法的分析和表征。根據常見的地球化學數據對樣品進行聚類，并自動識別樣本（左二）。光譜圖利用聚類材料的反射率建立（右一）

A total of 36 field-collected samples (left) were analyzed and characterized in the laboratory using both hyperspectral and traditional methods. Samples were clustered based on common geochemical data, with automated sample identification performed (second from left). Spectral graphs were constructed using the reflectance of clustered materials (right).  

高光譜成像儀的核心能力，源于它驚人的“視覺靈敏度"。以愛博能提供的HY-1710系列為例，其光譜范圍覆蓋400-2500nm，相當于同時捕捉可見光、近紅外和短波紅外的共460個波段。這就像給相機裝上了460層濾光片，每一層都能捕獲特定礦物的獨特“光波密碼"——比如高嶺石在2200nm附近的吸收峰。

The core capability of hyperspectral imaging lies in its remarkable "visual sensitivity." Take the HY-1710 series as an example: its spectral range covers 400–2500 nm, capturing 460 bands across visible, near-infrared, and short-wave infrared wavelengths. It is as if the camera is equipped with 460 layers of filters, each capable of detecting the unique "light-wave signature" of specific minerals—such as the absorption peak of kaolinite near 2200 nm.

矽卡巖礦床中常見蝕變礦物光譜曲線 / Spectral Curves of Common Alteration Minerals in Skarn Deposits

在甘肅華牛山多金屬礦區，某團隊使用高光譜成像儀對裸露巖層進行遙感檢測，旨在尋找新的礦藏資源。通過高光譜技術，他們對巖石進行分類和映射，在廣闊的區域內快速識別出鉛礦、鋅礦等礦物。此外，團隊運用了高效的圖像處理方法，提升了礦數據信息的提取精度，尤其是在鉛鋅礦體方面獲得了81%的礦物識別率。這使得他們成功繪制出礦物分類圖，并識別出了該地區的重要礦藏。

華牛山礦區經歷了多次地質演變，形成了復雜的構造特征和多樣的礦藏類型，通過高光譜技術，團隊不僅為資源的探索提供了科學依據，也為今后的礦藏開發和地質研究奠定了堅實的基礎。這種“從地表透視地殼運動"的能力，讓高光譜成像成為新一輪找礦突破戰略行動的核心技術。

In the Huaniushan polymetallic mining area of Gansu, a team used hyperspectral imaging to conduct remote sensing detection of exposed rock formations, aiming to discover new mineral resources. Through hyperspectral technology, they classified and mapped rocks, rapidly identifying minerals such as lead and zinc ores across extensive areas. Moreover, the team employed efficient image processing methods to enhance the accuracy of mineral data extraction, achieving an 81% mineral recognition rate for lead-zinc ore bodies. This enabled them to successfully generate mineral classification maps and identify significant deposits in the region.

The Huaniushan mining area has undergone multiple phases of geological evolution, resulting in complex structural features and diverse mineral deposit types. By applying hyperspectral technology, the team not only provided a scientific basis for resource exploration but also laid a solid foundation for future mineral development and geological research. This ability to "see through surface features to interpret crustal movements" has made hyperspectral imaging a core technology in the new strategic action for mineral exploration breakthroughs.

研究團隊繪制的華牛山礦物分布圖 / Mineral Distribution Map of Huaniushan Produced by the Research Team

2024年，中國地質調查局西安礦產中心聯合航空物探遙感中心和資源所，共同申報的基于國產高光譜數據找礦遠景區快速圈定技術，已成功入選中國地質調查局正式印發的《新一輪找礦突破戰略行動先進適用勘查技術清單（第一批）》。更值得一提的是，我國高分五號衛星的高光譜載荷，已實現90%以上的礦物識別準確率，該團隊更獲得了2024年度中國科學院杰出科學成就獎。

In 2024, the Xi’an Mineral Resources Center under the China Geological Survey, in collaboration with the Aerogeophysical Survey and Remote Sensing Center and the Institute of Mineral Resources, successfully developed a rapid prospect delineation technology based on domestically produced hyperspectral data. This achievement was included in the *List of Advanced and Applicable Exploration Technologies for the New Strategic Action for Mineral Exploration Breakthroughs (First Batch)* officially issued by the China Geological Survey. It is also worth highlighting that the hyperspectral payload onboard China’s Gaofen-5 satellite has achieved over 90% accuracy in mineral identification. The team behind this effort was awarded the 2024 Outstanding Scientific Achievement Prize by the Chinese Academy of Sciences.

由西安礦產中心發布的東天山-北山成礦帶高光譜遙感礦物分布圖

Hyperspectral Remote Sensing Mineral Distribution Map of the East Tianshan-Beishan Metallogenic Belt (Released by the Xi’an Mineral Resources Center)

從戈壁荒漠到深海礦藏，高光譜成像正在重寫人類探索地球的方式。它不僅是技術的革新，更是一種認知的革命——當我們學會傾聽巖石的光譜語言，那些沉睡億萬年的礦藏終將揭開面紗，為文明續寫新的能源篇章。

From desert wilderness to deep-sea mineral resources, hyperspectral imaging is reshaping how humanity explores the Earth. It is not only a technological revolution but also a cognitive one—by learning to interpret the spectral language of rocks, we are unveiling mineral deposits that have slumbered for billions of years, paving the way for a new chapter in energy resources and civilizational progress.

案例來源 / Sources：

1. 葉彬,王加昇,李金龍,付浩.高光譜遙感技術在地質勘查中的應用現狀及展望[J].化工礦物與加工,2024,53(11):77-88

2. Wan, Yq., Fan, Yh. & Jin, Ms. Application of hyperspectral remote sensing for supplementary investigation of polymetallic deposits in Huaniushan ore region, northwestern China. Sci Rep 11, 440 (2021)

3. 李士杰，何海洋，秦昊洋，孫旭，王思琪，劉小玉. 中國地質調查局西安礦產資源調查中心. 東天山-北山成礦帶高光譜礦物填圖數據集. 2024,09

4. 基于國產高光譜數據找礦遠景區快速圈定技術入選《新一輪找礦突破戰略行動先進適用勘查技術清單（第一批）》

5. 董新豐,甘甫平,李娜,閆柏琨,張磊,趙佳琪,于峻川,劉镕源,馬燕妮.2020.高分五號高光譜影像礦物精細識別.遙感學報,24(4): 454-464