The glacier environment in the Namcha Barwa–Gyala Peri (NBGP) massif is regarded as one of the most sensitive areas to climate change, yet the change estimates remain inadequate due to the limited knowledge of the complex debris-covered glacier environment and the lack of available remote sensing data caused by continuously cloudy weather. To examine the changes of the complex glacial environment, a multiple hierarchical object- and rule-based classification (MHORC) scheme is proposed by combining Landsat time series images and topographic data. Object-based image analysis (OBIA) is introduced due to its capabilities of handling data contextually and hierarchically and using multi-source data jointly so that multiple hierarchical rule-based classification can be developed to distinguish the objects with similar spectrum such as debris-covered glaciers and their surrounding terrain. All the available Landsat images from 1987 to 2019 are filtered by the cloud cover condition (less than 10%) and accordingly used in the MHORC to obtain spatial and temporal information of the glacier and snow over the NBGP massif. The images collected in the snow-free season are used to estimate the glacier extent state and the historical changes, and those in the snow-covered are used to estimate the snow cover fluctuation using harmonic analysis. The results show that the NBGP contains 65 glaciers (≥0.1 km²) with a total area of 462.7 km², among which valley glaciers account for 21.5% in number but cover an area of 354.2 km², more than 76% of the total area. An accelerating reduction trend of the glacier area is confirmed as the area change velocity is −0.62 km² yr⁻¹ between 1999 and 2003 and reach −2.95 km² yr⁻¹ between 2003 and 2015. The seasonal snow cover area shows a reduction in the secular trend and an increase in fluctuation amplitude. Both glacier and seasonal snow display heterogeneity in the spatial and temporal patterns. Such heterogeneous dynamics might be related to the trade-off between water vapor supply and regional thermal conditions. This MHORC developed in this study demonstrates its effectiveness in delineating the debris-covered glacier environment and the potential of using Landsat time series to track glacial environment evolution. Besides, the analysis of seasonal snow fluctuations provides a novel perspective to re-recognize the glacial environment dynamics, and the knowledge of glacier extent changes and season snow fluctuations over the NBGP massif can improve the understanding of environmental effects from climate change.

Namcha Barwa-Gyala Peri（NBGP）地块的冰川环境被认为是对气候变化最敏感的地区之一，但是由于对复杂的碎屑覆盖的冰川环境了解有限，缺乏对冰川变化的估计，因此仍然不足由持续多云的天气引起的可用遥感数据。为了研究复杂冰川环境的变化，通过结合Landsat时间序列图像和地形数据，提出了一种基于对象和规则的多层次分类法（MHORC）。引入了基于对象的图像分析（OBIA），因为它具有上下文和分层处理数据以及联合使用多源数据的功能，因此可以开发基于规则的多个分层分类，以区分具有类似光谱的对象，例如碎片覆盖冰川及其周围的地形。从1987年到2019年，所有可用的Landsat影像都被云量覆盖条件（小于10％）过滤，并相应地在MHORC中用于获取NBGP地块上冰川和积雪的时空信息。在无雪季节收集的图像用于估计冰川范围状态和历史变化，在积雪覆盖的图像用于进行谐波分析来估计积雪的波动。结果表明，NBGP包含65个冰川（≥0.1km）。在无雪季节收集的图像用于估计冰川范围状态和历史变化，在积雪覆盖的图像用于进行谐波分析来估计积雪的波动。结果表明，NBGP包含65个冰川（≥0.1km）。在无雪季节收集的图像用于估计冰川范围状态和历史变化，在积雪覆盖的图像用于进行谐波分析来估计积雪的波动。结果表明，NBGP包含65个冰川（≥0.1km）。²）总面积为462.7 km ²，其中河谷冰川占21.5％，但面积为354.2 km ²，占总面积的76％以上。随着面积变化速度在1999年至2003年间为-0.62 km ² yr ^-1并达到-2.95 km ² yr ^-1，冰川区域的加速减少趋势得以确认。在2003年至2015年之间。季节性积雪面积显示了长期趋势的减少和波动幅度的增加。冰川和季节性降雪在时空上均表现出异质性。这种非均质动力学可能与水蒸气供应与区域热条件之间的权衡有关。在这项研究中开发的MHORC证明了其在描述碎屑覆盖的冰川环境方面的有效性以及使用Landsat时间序列追踪冰川环境演变的潜力。此外，季节雪波动的分析为重新认识冰川环境动力学提供了一个新颖的观点，而对NBGP地块的冰川范围变化和季节雪波动的了解可以增进对气候变化对环境影响的认识。