The degradation of subarctic peatland ecosystems under climate change impacts surrounding landscapes, carbon balance, and biogeochemical cycles. To assess these ecosystems' responses to climate change, it is essential to consider not only the active-layer thickness but also its thermo-hydraulic conditions. Ground-penetrating radar is one of the leading methods for studying the active layer, and this paper proposes systematically investigating its potential to determine the thermal properties of the active layer. Collected experimental data confirm temperature hysteresis in peat linked to changes in water and ice content, which GPR may detect. Using palsa mires of the Kola Peninsula (NW Russia) as a case study, we analyze relationships between peat parameters in the active layer and search for thermal gradient responses in GPR signal attributes. The results reveal that frequency-dependent GPR attributes can delineate thermal intervals of +/- 1 degrees C through disperse waveguides. However, further verification is needed to clarify the conditions under which GPR can reliably detect temperature variations in peat, considering factors such as moisture content and peat structure. In conclusion, our study discusses the potential of GPR for remotely monitoring freeze-thaw processes and moisture distribution in frozen peatlands and its role as a valuable tool for studying peat thermal properties in terms of permafrost stability prediction.

冰川识别对于周边地区水资源与气候变化监测具有重要意义。全极化SAR影像包含地物表面散射、偶次散射、体散射、统计特性等丰富的特征，而深度学习能够充分挖掘影像信息，因此使用全极化SAR影像结合深度学习能够得到精确的冰川识别效果。本文基于喜马拉雅山脉西端ALOS2-PALSAR全极化影像，使用VGG16特征提取网络与全卷积神经网络模型U-net相结合的VGG16-unet对冰川进行识别。采用的特征包括极化相干矩阵对角线元素、Freeman-Durden、H/A/α、Pauli、VanZyl、Yamaguchi这5种极化分解参数共计19种特征。为了充分利用影像信息，对这些特征进行分析与组合，并比较它们之间的冰川识别精度，以选取最佳特征。由于冰川与非冰川的地形具有明显差异，因此将DEM、坡度、局部入射角等作为辅助特征与极化特征结合。通过对比不同极化特征分类精度得出，基于物理特性的Pauli、Freeman-Durden、VanZyl、Yamaguchi特征分类的精度较高，其中Pauli特征分类的精度最高，整体精度(OA)达到92.54%，平均用户交并比(mIoU)达到78.78%。加入地形数据后...

冰川识别对于周边地区水资源与气候变化监测具有重要意义。全极化SAR影像包含地物表面散射、偶次散射、体散射、统计特性等丰富的特征，而深度学习能够充分挖掘影像信息，因此使用全极化SAR影像结合深度学习能够得到精确的冰川识别效果。本文基于喜马拉雅山脉西端ALOS2-PALSAR全极化影像，使用VGG16特征提取网络与全卷积神经网络模型U-net相结合的VGG16-unet对冰川进行识别。采用的特征包括极化相干矩阵对角线元素、Freeman-Durden、H/A/α、Pauli、VanZyl、Yamaguchi这5种极化分解参数共计19种特征。为了充分利用影像信息，对这些特征进行分析与组合，并比较它们之间的冰川识别精度，以选取最佳特征。由于冰川与非冰川的地形具有明显差异，因此将DEM、坡度、局部入射角等作为辅助特征与极化特征结合。通过对比不同极化特征分类精度得出，基于物理特性的Pauli、Freeman-Durden、VanZyl、Yamaguchi特征分类的精度较高，其中Pauli特征分类的精度最高，整体精度(OA)达到92.54%，平均用户交并比(mIoU)达到78.78%。加入地形数据后...

慕士塔格峰位于帕米尔高原西部，是我国西部山地冰川的集中分布区之一，长期监测该地区冰川不仅有益于评估水资源状况，也有助于气候变化方面的研究。本文基于日本ALOS/PALSAR卫星分别于2009年1月14日和3月1日获取覆盖慕士塔格峰地区（37°48′18″N～38°35′14″N,74°42′45″E～75°41′50″E）的SAR数据，借助改进的像素跟踪算法，通过精确去除卫星轨道和传感器姿态差异带来的全局性位移和地形起伏导致的地形效应误差，得到了该地区山地冰川表面高精度运动分布场（GeoTIFF格式，32位浮点型）。其空间分辨率约为20 m。非冰川区残余运动的统计分析表明其总体精度约为0.5 m/46 day。冰川运动分布表明，该地区冰川运动主要呈现为积累区速度快，消融区和末端运动速度慢的特点，冰川运动整体上与地形存在一定的相关性，其中个别中小型冰川呈现出较强的活动性。本数据集可以作为该地区山地冰川运动的本底调查资料，为慕士塔格峰地区山地冰川运动研究提供基础数据支撑。另外，山地冰川运动高精度监测将有助于研究其动力学特征和预测冰川运动导致的地质灾害，同时也为我国冰川资源普查提供了一种有效...

本数据集是基于2011～2014年多时相Landsat光学影像、2009～2010年的L波段PALSAR雷达影像和改正的SRTM数字高程模型（DEM）得到的最新藏东南冰川目录。大致空间范围在28°N～31°N、93°E～97°E内，包括念青唐古拉山中部和东部，以及横断山西部，覆盖面积达11.5万平方公里。数据集内包括三个文件：1）定义研究区范围的矢量文件；2）冰川目录矢量文件；3）统计每条冰川特征的文档，参数包括GLIMS编号、冰川面积、最大和最小高程、平均高程、平均坡度、平均朝向、有无冰碛覆盖，以及冰碛覆盖面积等。为克服藏东南地区多云雨对光学影像的影响，对无冰碛覆盖冰川的提取采用了一种基于自动识别云和冰雪覆盖的方法，实现多景影像信息半自动融合；并将从光学影像中提取的地面信息和PALSAR雷达影像得到的相干图以及坡度结合起来，实现了冰碛冰川的半自动化单独提取。在后处理阶段，采用人工编辑提高数据精度：比如控制无冰碛覆盖冰川与其冰碛覆盖部分的连接，调整单条冰川界限，以及改正部分阴影、水体的影响。与人工数字化提取的冰川边界相比较，本数据集的冰川面积精度总体在3%以内。此编目为目前最新的冰川编...

本数据集是基于2011～2014年多时相Landsat光学影像、2009～2010年的L波段PALSAR雷达影像和改正的SRTM数字高程模型（DEM）得到的最新藏东南冰川目录。大致空间范围在28°N～31°N、93°E～97°E内，包括念青唐古拉山中部和东部，以及横断山西部，覆盖面积达11.5万平方公里。数据集内包括三个文件：1）定义研究区范围的矢量文件；2）冰川目录矢量文件；3）统计每条冰川特征的文档，参数包括GLIMS编号、冰川面积、最大和最小高程、平均高程、平均坡度、平均朝向、有无冰碛覆盖，以及冰碛覆盖面积等。为克服藏东南地区多云雨对光学影像的影响，对无冰碛覆盖冰川的提取采用了一种基于自动识别云和冰雪覆盖的方法，实现多景影像信息半自动融合；并将从光学影像中提取的地面信息和PALSAR雷达影像得到的相干图以及坡度结合起来，实现了冰碛冰川的半自动化单独提取。在后处理阶段，采用人工编辑提高数据精度：比如控制无冰碛覆盖冰川与其冰碛覆盖部分的连接，调整单条冰川界限，以及改正部分阴影、水体的影响。与人工数字化提取的冰川边界相比较，本数据集的冰川面积精度总体在3%以内。此编目为目前最新的冰川编...

慕士塔格峰位于帕米尔高原西部，是我国西部山地冰川的集中分布区之一，长期监测该地区冰川不仅有益于评估水资源状况，也有助于气候变化方面的研究。本文基于日本ALOS/PALSAR卫星分别于2009年1月14日和3月1日获取覆盖慕士塔格峰地区（37°48′18″N～38°35′14″N,74°42′45″E～75°41′50″E）的SAR数据，借助改进的像素跟踪算法，通过精确去除卫星轨道和传感器姿态差异带来的全局性位移和地形起伏导致的地形效应误差，得到了该地区山地冰川表面高精度运动分布场（GeoTIFF格式，32位浮点型）。其空间分辨率约为20 m。非冰川区残余运动的统计分析表明其总体精度约为0.5 m/46 day。冰川运动分布表明，该地区冰川运动主要呈现为积累区速度快，消融区和末端运动速度慢的特点，冰川运动整体上与地形存在一定的相关性，其中个别中小型冰川呈现出较强的活动性。本数据集可以作为该地区山地冰川运动的本底调查资料，为慕士塔格峰地区山地冰川运动研究提供基础数据支撑。另外，山地冰川运动高精度监测将有助于研究其动力学特征和预测冰川运动导致的地质灾害，同时也为我国冰川资源普查提供了一种有效...

Snow cover distribution has a profound impact on ground temperature, on thickness of the active layer, and on permafrost. The purpose of this study was to evaluate the effects of snow cover on soil thermal regimes in West Siberia and to characterize the meso- and micro-scale spatial variation of winter ground surface temperature (GST). Maximum snow cover thickness (> 80 cm) and duration (similar to 8 months) were recorded for the lower elevation areas and in the forest site (using a vertical array of Muttons). Shallow snow cover and a late snow formation characterized open raised areas with shallow permafrost. Our results indicate that 20 cm snow cover thickness is the minimum for generating a significant insulating effect. Date of snow cover formation with thickness > 20 cm had the strongest influence on soil temperature regimes. We found a significant negative correlation between winter GST and elevation. This relationship is indirectly controlled by snow cover redistribution. We additionally have shown that elevation, n-factor and winter GST are the variables most significantly affecting thaw depth in permafrost-affected soils. This research dictates the need for taking into account snowfall, and its redistribution due to the variability of local factors, in predicting the effects of climate change on soil temperatures and active layer depth. According to long-term meteorological data for West Siberia, a temporal trend in snowfall is not observed. Nevertheless, considerable interannual fluctuations in snow cover thickness can lead to interannual variations in the soil thermal regimes.

Peatlands in the Hudson Bay Lowlands (HBL) extend from the sporadic to the continuous permafrost zones. They store similar to 30 Pg of soil carbon, similar to 10% of which is sequestered in permafrost. Palsa fields and peat plateaus are dominant features in the HBL of northern Ontario, but pronounced warming trends in the area are associated with accelerated degradation of these features. This research investigated greenhouse gas production potential (CO2 and CH4) from HBL peatlands near Peawanuck, ON, in the context of rapid palsa degradation. Active layer and permafrost samples from palsas, and samples from fens adjacent to the palsas were collected at sites exhibiting different degradation rates and patterns, identified via the sequential analysis of historical aerial photographs and recent satellite imagery. The samples were incubated anaerobically at 4 degrees C and 14 degrees C to assess CO2 and CH4. In general, CO2 production potential was higher than CH4, however the production of CH4 was extremely sensitive to increased temperatures. Between 4 degrees C and 14 degrees C CH4 production increased by factors ranging from 6 to 90, whereas CO2 production consistently increased by a factor of similar to 2. The production of both gases was higher from fen peat then from permafrost and active layer peat at either temperature when incubated in anaerobic conditions for 225 days. This suggests that higher production rates of CO2 and CH4 from thermokarst features compared to intact permafrost landscapes are not only the result of environmental conditions such as wetness and increased temperatures, but also likely a result of organic matter chemistry and bioavailability associated with increased sedge growth following permafrost degradation.

Increased mineralization of the organic matter (OM) stored in permafrost is expected to constitute the largest additional global warming potential from terrestrial ecosystems exposed to a warmer climate. Chemical composition of permafrost OM is thought to be a key factor controlling the sensitivity of decomposition to warming. Our objective was to characterise OM from permafrost soils of the European Arctic: two mineral soils-Adventdalen, Svalbard, Norway and Vorkuta, northwest Russia-and a palsa (ice-cored peat mound patterning in heterogeneous permafrost landscapes) soil in Neiden, northern Norway, in terms of molecular composition and state of decomposition. At all sites, the OM stored in the permafrost was at an advanced stage of decomposition, although somewhat less so in the palsa peat. By comparing permafrost and active layers, we found no consistent effect of depth or permafrost on soil organic matter (SOM) chemistry across sites. The permafrost-affected palsa peat displayed better preservation of plant material in the deeper layer, as indicated by increasing contribution of lignin carbon to total carbon with depth, associated to decreasing acid (Ac) to aldehyde (Al) ratio of the syringyl (S) and vanillyl (V) units, and increasing S/V and contribution of plant-derived sugars. By contrast, in Adventdalen, the Ac/Al ratio of lignin and the Alkyl C to O-alkyl C ratio in the NMR spectra increased with depth, which suggests less oxidized SOM in the active layer compared to the permafrost layer. In Vorkuta, SOM characteristics in the permafrost profile did not change substantially with depth, probably due to mixing of soil layers by cryoturbation. The composition and state of decomposition of SOM appeared to be site-specific, in particular bound to the prevailing organic or mineral nature of soil when attempting to predict the SOM proneness to degradation. The occurrence of processes such as palsa formation in organic soils and cryoturbation should be considered when up-scaling and predicting the responses of OM to climate change in arctic soils.