Influence of surface water variations on VOD and biomass estimates from passive microwave sensors
Influence of surface water variations on VOD and biomass estimates from passive microwave sensors
复制标题
DOI：
10.1109/igarss47720.2021.9554873
复制
发表时间：
2021-02-21
影响因子：
13.5
通讯作者：
Kerr, Yann H.
中科院分区：
文献类型：
--
作者：
Bousquet, Emma;Mialon, Arnaud;Kerr, Yann H.
植被光学厚度（VOD）是表征植被层对地球微波波长热辐射衰减的遥感指标。在L波段，VOD被用来估计全球生物量，这是地球表面和碳循环的关键组成部分。本研究的重点是L波段VOD（L-VOD）检索算法在季节性淹没地区的行为，因为以前的一些观察表明，在洪水事件VOD意外下降。为了分析这种变化，被动微波模型被用来模拟由土壤和静水组成的混合场景所发射的信号。在此淹没场景的检索导致高估的土壤水分（SM）和低估的L-VOD。这一现象在草原上比在森林上更为明显，因为低矮的植被大多淹没在水下，传感器无法看到;而且传感器可以看到更多的静水。估计的L-VOD通常在洪水淹没的森林上减少10%，在洪水淹没的草原上减少100%。这种影响可能会扭曲基于L-VOD估计的地上生物量（AGB）和地上碳（AGC）动态分析。我们估计，在最大的季节性湿地中，AGB可以被低估15/20 Mg ha（-1），这可以代表这些领域实际AGB的50%以上，在特殊的气象年份可以达到更高的值。因此，为了更好地估计全球生物量，在被动微波反演算法中必须考虑地表水的季节性。
Vegetation optical depth (VOD) is a remotely sensed indicator characterizing the attenuation of the Earth's thermal emission at microwave wavelengths by the vegetation layer. At L-band, VOD is used to estimate the global biomass, a key component of the Earth's surface and of the carbon cycle. This study focuses on the behaviour of L-band VOD (L-VOD) retrieval algorithm over seasonally inundated areas, as some previous observations have shown an unexpected decline in VOD during flooding events. To analyse such variations, a passive microwave model was used to simulate the signal emitted by a mixed scene composed of soil and standing water. The retrieval over this inundated scene led to an overestimation of soil moisture (SM) and an underestimation of L-VOD. The phenomenon is more pronounced over grasslands than over forests, since low vegetation is mostly submerged under water and becomes invisible to the sensor; and since more standing water is visible to the sensor. The estimated L-VOD is typically reduced by similar to 10% over flooded forests and up to 100% over flooded grasslands. Such effects can distort the analysis of aboveground biomass (AGB) and aboveground carbon (AGC) dynamics based on L-VOD estimates. We evaluated that AGB can be underestimated by 15/20 Mg ha(-1) in the largest seasonal wetlands, which can represent more than 50% of the actual AGB of these fields, and up to higher values during exceptional meteorological years. Consequently, to better estimate the global biomass, surface water seasonality has to be taken into account in passive microwave retrieval algorithms.