Enhanced Modeling of Annual Temperature Cycles with Temporally Discrete Remotely Sensed Thermal Observations
Enhanced Modeling of Annual Temperature Cycles with Temporally Discrete Remotely Sensed Thermal Observations
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DOI：
10.3390/rs10040650
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发表时间：
2018-04
期刊：
影响因子：
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通讯作者：
Z. Zou;W. Zhan;Zihan Liu;B. Bechtel;Lun Gao;Falu Hong;F. Huang;Jiameng Lai
中科院分区：
文献类型：
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作者：
Z. Zou;W. Zhan;Zihan Liu;B. Bechtel;Lun Gao;Falu Hong;F. Huang;Jiameng Lai
卫星热遥感提供了广泛地区的地表温度（LST），这在各种应用中都是至关重要的，但这种技术受到其采样方式和云的不可穿透性的影响，这经常产生数据空白。年温度循环（ATC）模式可以填补这些空白，并从一些热观测值估计连续的日地表温度动态。然而，标准的ATC模式（称为ATCS）仍然无法量化由天气条件引起的短期LST变化。通过结合地面气温（sat）和卫星导出的归一化植被指数（NDVIs），我们提出了一个增强的ATC模型（ATCE）来描述地表温度的日波动。以Aqua/MODIS LST产品作为验证数据，在中国长三角地区实施并测试了ATCE。结果表明，与ATCS相比，ATCE在白天和夜间的总体均方根误差分别降低了1.0 K和0.8 K。不同土地覆盖类型的精度提高幅度不同，森林、草地和建成区的精度提高幅度大于农田和湿地。不同时间尺度的评估进一步证实，ATCE可以更好地描述地表温度波动。尽管存在局限性，但我们认为该模型及其相关参数在各种应用中具有很大的潜力。
Satellite thermal remote sensing provides land surface temperatures (LST) over extensive areas that are vital in various applications, but this technique suffers from its sampling style and the impenetrability of clouds, which frequently generates data gaps. Annual temperature cycle (ATC) models can fill these gaps and estimate continuous daily LST dynamics from a number of thermal observations. However, the standard ATC model (termed ATCS) remains incapable of quantifying the short-term LST variations caused by synoptic conditions. By incorporating in-situ surface air temperatures (SATs) and satellite-derived normalized difference vegetation indexes (NDVIs), here we proposed an enhanced ATC model (ATCE) to describe the daily LST fluctuations. With Aqua/MODIS LST products as validation data, we implemented and tested the ATCE over the Yangtze River Delta region of China. The results demonstrate that, when compared with the ATCS, the overall root mean square errors of the ATCE decrease by 1.0 and 0.8 K for the day and night, respectively. The accuracy improvements vary with land cover types with greater improvements over the forest, grassland, and built-up areas than over cropland and wetland. The assessments at different time scales further confirm that LST fluctuations can be better described by the ATCE. Though with limitations, we consider this new model and its associated parameters hold great potentials in various applications.