Abstract The quantification of vegetation height for the circumpolar Arctic tundra biome is of interest for a wide range of applications, including biomass and habitat studies as well as permafrost modelling in the context of climate change. To date, only indices from multispectral data have been used in these environments to address biomass and vegetation changes over time. The retrieval of vegetation height itself has not been attempted so far over larger areas. Synthetic Aperture Radar (SAR) holds promise for canopy modeling over large extents, but the high variability of near-surface soil moisture during the snow-free season is a major challenge for application of SAR in tundra for such a purpose. We hypothesized that tundra vegetation height can be derived from multispectral indices as well as from C-band SAR data acquired in winter (close to zero liquid water content). To test our hypothesis, we used C-band SAR data from Sentinel-1 and multi-spectral data from Sentinel-2. Results show that vegetation height can be derived with an RMSE of 44 cm from Normalized Difference Vegetation Index (NDVI) and 54 cm from Tasseled Cap Wetness index (TC). Retrieval from C-band SAR shows similar performance, but C-VV is more suitable than C-HH to derive vegetation height (RMSEs of 48 and 56 cm respectively). An exponential relationship with in situ height was evident for all tested parameters (NDVI, TC, C-VV and C-HH) suggesting that the C-band SAR and multi-spectral approaches possess similar capabilities including tundra biomass retrieval. Errors might occur in specific settings as a result of high surface roughness, high photosynthetic activity in wetlands or high snow density. We therefore introduce a method for combined use of Sentinel-1 and Sentinel-2 to address the ambiguities related to Arctic wetlands and barren rockfields. Snow-related deviations occur within tundra fire scars in permafrost areas in the case of C-VV use. The impact decreases with age of the fire scar, following permafrost and vegetation recovery. The evaluation of masked C-VV retrievals across different regions, tundra types and sources (in situ and circumpolar vegetation community classification from satellite data) suggests pan-Arctic applicability to map current conditions for heights up to 160 cm. The presented methodology will allow for new applications and provide advanced insight into changing environmental conditions in the Arctic.

中文翻译：

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从 Sentinel-1 和 Sentinel-2 数据中检索苔原植被高度的可行性

摘要 极地北极苔原生物群落植被高度的量化具有广泛的应用价值，包括生物量和栖息地研究以及气候变化背景下的永久冻土模型。迄今为止，在这些环境中仅使用来自多光谱数据的指数来解决生物量和植被随时间的变化。到目前为止，还没有尝试在更大的区域内检索植被高度本身。合成孔径雷达 (SAR) 有望在很大程度上进行冠层建模，但无雪季节近地表土壤水分的高度可变性是 SAR 在苔原中为此目的应用的主要挑战。我们假设苔原植被高度可以从多光谱指数以及冬季获得的 C 波段 SAR 数据（接近零液态水含量）推导出来。为了验证我们的假设，我们使用了来自 Sentinel-1 的 C 波段 SAR 数据和来自 Sentinel-2 的多光谱数据。结果表明，植被高度可以通过归一化差异植被指数 (NDVI) 的 44 厘米和缨帽湿度指数 (TC) 的 54 厘米得出。从 C 波段 SAR 检索显示类似的性能，但 C-VV 比 C-HH 更适合推导植被高度（RMSE 分别为 48 和 56 厘米）。所有测试参数（NDVI、TC、C-VV 和 C-HH）与原位高度呈指数关系，表明 C 波段 SAR 和多光谱方法具有类似的能力，包括苔原生物量反演。由于高表面粗糙度、湿地高光合活动或高雪密度，在特定环境中可能会出现错误。因此，我们引入了一种结合使用 Sentinel-1 和 Sentinel-2 的方法来解决与北极湿地和贫瘠岩场相关的歧义。在使用 C-VV 的情况下，与雪有关的偏差发生在永久冻土区的苔原火灾疤痕内。在永久冻土和植被恢复之后，影响随着火痕的年龄而减小。对不同区域、苔原类型和来源（来自卫星数据的原位和极地植被群落分类）的掩蔽 C-VV 检索的评估表明泛北极适用于绘制高达 160 厘米高度的当前条件。