基于多源RS数据的多尺度青藏高原冻土监测

Multi-scale Monitoring of Permafrost in Qinghai-Tibet Plateau Using Multi-source RS Images

青藏高原作为世界上中低纬度海拔最高、面积最大的多年冻土区域,其冻土环境变化会对中国东部乃至东亚气候的形成、变化和发展造成重大影响。RS技术对于冻土环境动态监测具有特别优势。针对青藏高原冻土的特点,提出一种基于多源RS监测数据的融合技术反演地表温度,实现不同空间尺度条件下冻土分类的自动提取方法。该技术方法先利用MODIS全年温度产品数据集,结合地表覆盖类型数据,使用TTOP模型反演得到1 km空间分辨率的冻土分布;然后对Landsat数据源采取PSC反演算法获得30 m空间分辨率的地表温度数据;最后利用多项式拟合技术,将Landsat反演地表温度与MODIS温度数据相互融合,以提高Landsat反演地表温度的准确度,并据此数据利用TTOP模型提取30 m空间分辨率的冻土分布,实现了小尺度精细化的冻土分类与制图。结果验证分析表明:本文的技术方法具有较好的可信度。

As the permafrost region with the highest altitude and the largest area at middle-low latitude in the world,the permafrost environment change of Qinghai-Tibet Plateau will have a significant impact on the formation,change and development of climate in East China and even East Asia.RS technology has special advantages for dynamic monitoring of permafrost environment.This paper proposes a fusion technique based on multi-source RS image data to retrieve the surface temperature and realize the automatic extraction of permafrost classification under different spatial scales.The main technical methods are as follows:(1)Using the MODIS annual temperature product data set,combined with the soil cover type data and using the TTOP model,the distribution of permafrost with a spatial resolution of 1 km can be retrieved;(2)The PSC inversion algorithm is adopted for Landsat data sources to obtain surface temperature data with a spatial resolution of 30 m.By using polynomial fitting technology,Landsat ground temperature inversion and MODIS temperature data are combined to improve the accuracy of Landsat ground temperature inversion.Based on the data,TTOP model is used to extract the distribution of permafrost with a spatial resolution of 30 m,which realizes the classification and mapping of permafrost small-scale fine.The results show that the technical method has good reliability.