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首页> 外文期刊>Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of >Inter-Comparison and Validation of the FY-3A/MERSI LAI Product Over Mainland China
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Inter-Comparison and Validation of the FY-3A/MERSI LAI Product Over Mainland China

机译：FY-3A / MERSI LAI产品在中国大陆的比较和验证

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摘要

Leaf area index (LAI) is a key surface parameter that describes the structure of vegetation and plays an important role in Earth system process modeling. In this paper, a new set of LAI products (MERSI GLOBCARBON LAI) has been developed based on the GLOBCARBON LAI algorithm and one year of FY-3A/MERSI land surface reflectance data. MERSI GLOBCARBON LAI has been inter-compared and validated over mainland China against MODIS land surface reflectance (LSR) derived LAI (using the same algorithm) and field LAI measurements. MERSI GLOBCARBON LAI and MODIS GLOBCARBON LAI show continuous and smooth LAI distributions at the start and end of the growing season. For most areas in China, the two LAI products agree well. The temporal variation in MERSI GLOBCARBON LAI and MODIS GLOBCARBON LAI consistently follows the growing season. The largest LAI difference occurs during July, when MERSI shows a much higher frequency of retrievals than does MODIS. Through validation of LAI retrievals with field measurements, our study demonstrates that LAI derived from MERSI and MODIS land surface reflectance products have comparable accuracy. MODIS top-of-atmosphere simple ratio (MODIS TOA SR) is related to MERSI TOA SR with linear correlation coefficients greater than 0.6. After atmospheric correction, the correlation coefficient increases from 0.69 to 0.75 over cropland and from 0.82 to 0.93 over grassland. However, atmospheric correction can still give rise to substantial differences in the reflectance data between the two sensors. Furthermore, different land cover types and different terrain relief have contrasting influences on the atmospheric correction, and these influences reduce the agreement between the two LAI products. This study shows the great potential of FY-3A/MERSI data for global LAI retrieval.
机译：叶面积指数（LAI）是描述植被结构的关键表面参数，在地球系统过程建模中起着重要作用。本文基于GLOBCARBON LAI算法和一年的FY-3A / MERSI地表反射率数据，开发了一套新的LAI产品（MERSI GLOBCARBON LAI）。 MERSI GLOBCARBON LAI已在中国大陆针对MODIS陆面反射率（LSR）得出的LAI（使用相同算法）和现场LAI测量进行了比较和验证。 MERSI GLOBCARBON LAI和MODIS GLOBCARBON LAI在生长季节开始和结束时显示出连续且平稳的LAI分布。对于中国大多数地区，这两种LAI产品非常吻合。 MERSI GLOBCARBON LAI和MODIS GLOBCARBON LAI的时间变化始终遵循生长季节。最大的LAI差异发生在7月份，当时MERSI的检索频率比MODIS高得多。通过现场测量对LAI检索的验证，我们的研究表明，源自MERSI和MODIS陆地表面反射率产品的LAI具有相当的精度。 MODIS最高大气简单比率（MODIS TOA SR）与MERSI TOA SR有关，线性相关系数大于0.6。大气校正后，耕地的相关系数从0.69增加到0.75，草原上的相关系数从0.82增加到0.93。但是，大气校正仍然会导致两个传感器之间的反射率数据存在很大差异。此外，不同的土地覆盖类型和不同的地形起伏对大气校正有相反的影响，这些影响降低了两个LAI产品之间的一致性。这项研究表明FY-3A / MERSI数据对于全球LAI检索具有巨大潜力。

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