Quantifying end of summer season Active Layer Thickness (ALT) of permafrost is critical for understanding the effects of climate warming, disturbance, and hydrologic changes on permafrost. Current research mainly focuses on ALT estimation and mapping at large scales using process-based or statistical-empirical models with biophysical variables as predictors. Here we modeled multi-year ALT field measurements between 2014 and 2019 at a site in Interior Alaska using 1-m hyperspectral imaging data and an object-based ensemble approach at a local scale (1 km²), examined the efficacy of the multispectral sensor WorldView (WV)-2 for ALT estimation, and explored the potential of integrating single-date imaging data with multi-year in-situ measurements for mapping the spatial and temporal variation of ALT. Modeling results showed hyperspectral imaging was accurate for estimating ALT with a correlation coefficient (r) larger than 0.7, while application of WV-2 data produced an r around 0.4. Reasonable ALT patterns were generated, and the spatial and temporal variation of ALT was delineated between the shallowest (2015) and deepest (2019) years using hyperspectral data. This study suggests hyperspectral imaging is a promising tool for predicting field ALT measurements and monitoring ALT change at local scales. We expect this study will stimulate hyperspectral optical sensors for permafrost studies in general, and particularly for ALT upscaling.

量化夏季结束时永久冻土的活动层厚度 (ALT) 对于了解气候变暖、干扰和水文变化对永久冻土的影响至关重要。当前的研究主要集中在使用以生物物理变量作为预测变量的基于过程或统计经验模型的大规模 ALT 估计和映射。在这里，我们使用 1 米高光谱成像数据和局部尺度（1 公里²)，研究了多光谱传感器 WorldView (WV)-2 对 ALT 估计的功效，并探索了将单日成像数据与多年原位测量相结合以绘制 ALT 时空变化图的潜力。建模结果表明，高光谱成像可以准确估计 ALT，相关系数 ( r ) 大于 0.7，而应用 WV-2 数据产生了r0.4左右。生成了合理的ALT模式，并使用高光谱数据在最浅（2015）和最深（2019）年之间描绘了ALT的时空变化。这项研究表明，高光谱成像是预测现场 ALT 测量值和监测局部尺度的 ALT 变化的有前途的工具。我们预计这项研究将刺激用于永久冻土研究的高光谱光学传感器，特别是对于 ALT 升级。