Core Viewpoint - The integration of drone technology into natural resource supervision is transforming traditional inspection methods, enhancing efficiency and effectiveness in data collection and decision-making processes [3][11]. Group 1: Multi-Dimensional Information Capture - Drones equipped with diverse sensors, including LiDAR and thermal imaging, extend information gathering from visible to multi-dimensional data, enabling precise identification of non-agricultural land disguised as farmland [3][11]. - The ability to capture thermal signals allows for the detection of illegal mining activities even under dense vegetation, enhancing the depth of resource utilization information [5][11]. Group 2: Temporal and Spatial Flexibility - Drones demonstrate strong adaptability to various terrains, enabling comprehensive inspections in challenging environments such as steep mountains and wetlands, achieving "no blind spots" in monitoring [12]. - Small drones can be deployed within 10 minutes for immediate response, while larger drones can cover hundreds of square kilometers for macro-level scanning, facilitating a combination of detailed and broad inspections [12]. Group 3: Enhanced Data Precision - Advances in positioning and surveying technologies have led to centimeter-level accuracy in drone data, meeting high precision requirements for land surveys and mineral extraction monitoring [13]. - In Hebei province, drones have been used to create 3D models that accurately calculate monthly extraction volumes, with discrepancies controlled within 3%, providing a solid basis for resource management [13]. Group 4: Cost-Effectiveness and Efficiency - The cost of a small to medium-sized drone system is significantly lower than traditional surveying equipment, making it feasible for widespread adoption in natural resource departments [14]. - The use of drones has reduced the time required for inspections from five days to two in hard-to-reach areas, optimizing resource allocation and enhancing accuracy in data verification [14]. Group 5: Dynamic Collaborative Capability - Drones serve as a critical node in an integrated natural resource supervision network, collaborating with satellite imagery and ground sensors to create a comprehensive inspection model [15]. - This collaborative approach enhances the speed and efficiency of inspections, transitioning from single technology applications to multi-technology operations, significantly improving response times and operational effectiveness [15].

高光谱相机技术是基于非常多窄波段的影像数据技术，它将成像技术与光谱技术相结合，探测目标的二维几何空间及一维光谱信息，获 取高光谱分辨率的连续、窄波段的图像数据。高光谱相机技术发展迅速，常见的包括光栅分光、声光可调谐滤波分光、棱镜分光、芯片 镀膜等。可以应用在食品安全、医学诊断、航天领域等领域。 中国高光谱相机发展现状及未来趋势 2023 年，中国高光谱相机市场规模达到了 30.59 百万美元，预计 203 1 年将达到 103.77 百万美元，年复合增长率（ CAGR ）为 18.29% 。过去，高端高光谱相机市场主要被国外品牌占据，但近年来国内企业加大了研发投入，技术水平不断提高，国产高光谱相机在性能上 已逐渐接近国际先进水平。同时，国产产品具有价格优势和本地化服务优势，能够更好地满足国内客户的需求，在国内市场的份额有望 逐步提高，实现进口产品的替代。 中国市场核心厂商包括彩谱科技、双利合谱、中达瑞和、 Specim 、 Headwall Photonics 、杭州高谱成像技术有限公司、奥谱天成（厦 门）光电有限公司、 Cubert 、 IMEC 等，按收入计， 2024 年中国市场前三大厂商占有大约 60 ...