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机构地区:[1]中国科学院寒区旱区环境与工程研究所,甘肃兰州730000 [2]中国科学院寒区旱区环境与工程研究所冻土工程国家重点实验室,甘肃兰州730000
出 处:《冰川冻土》2013年第1期74-83,共10页Journal of Glaciology and Geocryology
基 金:冻土工程国家重点实验室开放基金项目(SKLFSE201009);科技基础性工作专项(2008FY110200)资助
摘 要:0cm土壤温度是冻土模型的上边界条件,连续的、高质量的青藏高原0cm土壤温度数据是进行准确冻土模拟的必要条件.然而受复杂下垫面的影响,遥感手段无法获取可靠的0cm土壤温度.利用自适应网络模糊推理系统(ANFIS)结合青藏高原实测资料建立遥感地表温度产品(LST)与0cm土壤温度的关系,以实现通过LST估算青藏高原逐日0cm土壤温度.研究了ANFIS的各种参数组合,发现筛选合适的小波函数、小波窗口、小波层数建立起来的Wavelet-ANFIS模型能较准确实现估算0cm土壤温度的目的.验证表明,估算结果与气象站点实测0cm土壤温度绝对误差在2K以下,相关系数0.98以上.考虑到原始MODIS LST误差在0~2K之间,该方法可以获取较为理想的0cm土壤温度,为冻土模型提供准确的上边界输入.0-cm soil temperature is the upper boundary condition of many permafrost models.Continuous,high-quality 0-cm soil temperature data are necessary inputs to simulate permafrost distribution.However,owing to the influence of complex underlying surface,remote sensing approaches cannot provide reliable 0-cm soil temperature.In this study,in order to estimate 0-cm soil temperature,adaptive network-fuzzy inference system(ANFIS) combining with the data measured in the Tibetan Plateau is used to establish the relations between remote sensing land surface temperature(LST) and 0-cm soil temperature.In this paper,different parameter combinations of ANFIS are examined,and a Wavelet-ANFIS model established by optimized wavelet functions,wavelet windows and wavelet layers is found able to estimate the 0-cm soil temperature more accurately.A comparison analysis of the estimated results and the 0-cm soil temperatures measured at the meteorological sites shows that the approach can achieve desirable estimation with an absolute error less than 2 K and a correlation coefficient greater than 0.98.In view of the original MODIS LST error range from 0 to 2 K,the proposed method may provide more accurate 0-m soil temperature inputs to permafrost models.
关 键 词:小波分析 自适应网络模糊推理系统 MODIS地表温度产品 青藏高原 0cm土壤温度
分 类 号:P407.8[天文地球—大气科学及气象学]
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