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首页> 外文期刊>Water >Evaluation and Inter-Comparison of Satellite Soil Moisture Products Using In Situ Observations over Texas, U.S.
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Evaluation and Inter-Comparison of Satellite Soil Moisture Products Using In Situ Observations over Texas, U.S.

机译：使用美国德克萨斯州的原位观测资料评估和比较卫星土壤水分产品

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The main goal of this study was to evaluate four major remote sensing soil moisture (SM) products over the state of Texas. These remote sensing products are: (i) the Advanced Microwave Scanning Radiometer—Earth Observing System (AMSR-E) (2002–September 2011); (ii) the Soil Moisture Ocean Salinity system (SMOS, 2010–present); (iii) AMSR2 (2012–present); and (iv) the Soil Moisture Active Passive system (SMAP, 2015–present). The quality of the generated SM data is influenced by the accuracy and precision of the sensors and the retrieval algorithms used in processing raw data. Therefore, it is important to evaluate the quality of these satellite SM products using in situ measurements and/or by inter-comparing their data during overlapping periods. In this study, these two approaches were used where we compared each satellite SM product to in situ soil moisture measurements and we also conducted an inter-comparison of the four satellite SM products at 15 different locations in Texas over six major land cover types (cropland, shrub, grassland, forest, pasture and developed) and eight climate zones along with in situ SM data from 15 Mesonet, USCRN and USDA-NRCS Scan stations. Results show that SM data from SMAP had the best correlation coefficients range from 0.37 to 0.92 with in situ measurements among the four tested satellite surface SM products. On the other hand, SM data from SMOS, AMSR2 and AMSR-E had moderate to low correlation coefficients ranges with in situ data, respectively, from 0.24–0.78, 0.07–0.62 and 0.05–0.52. During the overlapping periods, average root mean square errors (RMSEs) of the correlations between in situ and each satellite data were 0.13 (AMSR-E) and 0.13 (SMOS) cm 3 /cm 3 (2010–2011), 0.16 (AMSR2) and 0.14 (SMOS) cm 3 /cm 3 (2012–2016) and 0.13, 0.16, 0.14 (SMAP, AMSR2, SMOS) cm 3 /cm 3 (2015–2016), respectively. Despite the coarser spatial resolution of all four satellite products (25–36 km), their SM measurements are considered reasonable and can be effectively used for different applications, e.g., flood forecasting, and drought prediction; however, further evaluation of each satellite product is recommended prior to its use in practical applications.
机译：这项研究的主要目的是评估德克萨斯州的四种主要遥感土壤水分（SM）产品。这些遥感产品包括：（i）先进的微波扫描辐射计-地球观测系统（AMSR-E）（2002年-2011年9月）; （ii）土壤水分海洋盐度系统（SMOS，2010年至今）; （iii）AMSR2（2012年至今）; （iv）土壤水分主动被动系统（SMAP，2015年至今）。生成的SM数据的质量受传感器的准确性和精度以及用于处理原始数据的检索算法的影响。因此，重要的是使用原位测量和/或在重叠期间相互比较它们的数据来评估这些卫星SM产品的质量。在这项研究中，使用了这两种方法，我们将每种卫星SM产品与原位土壤湿度测量值进行了比较，并且还比较了德克萨斯州15个不同地点的六个卫星土地覆盖类型（作物地）上的四种卫星SM产品的内部比较。 ，灌木，草原，森林，牧场和发达地区）和八个气候区，以及来自15个Mesonet，USCRN和USDA-NRCS扫描站的原位SM数据。结果表明，在四个被测卫星表面SM产品中，来自SMAP的SM数据具有0.37到0.92的最佳相关系数，并且就地测量。另一方面，来自SMOS，AMSR2和AMSR-E的SM数据与原位数据的相关系数范围适中至低，分别为0.24-0.78、0.07-0.62和0.05-0.52。在重叠期间，就地和每个卫星数据之间的相关性的平均均方根误差（RMSE）为0.13（AMSR-E）和0.13（SMOS）cm 3 / cm 3（2010-2011），0.16（AMSR2）和0.14（SMOS）cm 3 / cm 3（2012-2016）和0.13、0.16、0.14（SMAP，AMSR2，SMOS）cm 3 / cm 3（2015-2016）。尽管所有四个卫星产品（25-36 km）的空间分辨率都较差，但它们的SM测量值仍被认为是合理的，可以有效地用于不同的应用，例如洪水预报和干旱预报;但是，建议在实际应用中对每个卫星产品进行进一步评估。

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