Biudes Marcelo Sacardi, Machado Nadja Gomes, Danelichen Victor Hugo de Morais, Souza Maísa Caldas, Vourlitis George Louis, Nogueira José de Souza
Programa de Pós-Graduação em Física Ambiental, Instituto de Física, Universidade Federal de Mato Grosso, Cuiabá, Mato Grosso, Brazil,
Int J Biometeorol. 2014 Aug;58(6):1181-93. doi: 10.1007/s00484-013-0713-4. Epub 2013 Aug 14.
Leaf area index (LAI) is a key driver of forest productivity and evapotranspiration; however, it is a difficult and labor-intensive variable to measure, making its measurement impractical for large-scale and long-term studies of tropical forest structure and function. In contrast, satellite estimates of LAI have shown promise for large-scale and long-term studies, but their performance has been equivocal and the biases are not well known. We measured total, overstory, and understory LAI of an Amazon-savanna transitional forest (ASTF) over 3 years and a seasonal flooded forest (SFF) during 4 years using a light extinction method and two remote sensing methods (LAI MODIS product and the Landsat-METRIC method), with the objectives of (1) evaluating the performance of the remote sensing methods, and (2) understanding how total, overstory and understory LAI interact with micrometeorological variables. Total, overstory and understory LAI differed between both sites, with ASTF having higher LAI values than SFF, but neither site exhibited year-to-year variation in LAI despite large differences in meteorological variables. LAI values at the two sites have different patterns of correlation with micrometeorological variables. ASTF exhibited smaller seasonal variations in LAI than SFF. In contrast, SFF exhibited small changes in total LAI; however, dry season declines in overstory LAI were counteracted by understory increases in LAI. MODIS LAI correlated weakly to total LAI for SFF but not for ASTF, while METRIC LAI had no correlation to total LAI. However, MODIS LAI correlated strongly with overstory LAI for both sites, but had no correlation with understory LAI. Furthermore, LAI estimates based on canopy light extinction were correlated positively with seasonal variations in rainfall and soil water content and negatively with vapor pressure deficit and solar radiation; however, in some cases satellite-derived estimates of LAI exhibited no correlation with climate variables (METRIC LAI or MODIS LAI for ASTF). These data indicate that the satellite-derived estimates of LAI are insensitive to the understory variations in LAI that occur in many seasonal tropical forests and the micrometeorological variables that control seasonal variations in leaf phenology. While more ground-based measurements are needed to adequately quantify the performance of these satellite-based LAI products, our data indicate that their output must be interpreted with caution in seasonal tropical forests.
叶面积指数（LAI）是森林生产力和蒸散的关键驱动因素；然而，它是一个难以测量且劳动强度大的变量，这使得对热带森林结构和功能进行大规模和长期研究时，对其进行测量并不实际。相比之下，卫星对LAI的估计在大规模和长期研究中显示出了前景，但其性能并不明确，偏差也不为人所知。我们使用消光法和两种遥感方法（MODIS LAI产品和陆地卫星 - METRIC方法），对一片亚马逊 - 稀树草原过渡森林（ASTF）进行了3年的总LAI、上层LAI和下层LAI测量，并对一片季节性水淹森林（SFF）进行了4年的测量，目的是：（1）评估遥感方法的性能；（2）了解总LAI、上层LAI和下层LAI如何与微气象变量相互作用。两个站点的总LAI、上层LAI和下层LAI存在差异，ASTF的LAI值高于SFF，但尽管气象变量差异很大，两个站点的LAI均未表现出逐年变化。两个站点的LAI值与微气象变量的相关模式不同。ASTF的LAI季节变化比SFF小。相比之下，SFF的总LAI变化较小；然而，上层LAI在旱季的下降被下层LAI的增加所抵消。对于SFF，MODIS LAI与总LAI的相关性较弱，而对于ASTF则不然，而METRIC LAI与总LAI无相关性。然而，MODIS LAI与两个站点的上层LAI都有很强的相关性，但与下层LAI无相关性。此外，基于冠层消光的LAI估计与降雨量和土壤含水量的季节变化呈正相关，与水汽压差和太阳辐射呈负相关；然而，在某些情况下，卫星衍生的LAI估计与气候变量无相关性（ASTF的METRIC LAI或MODIS LAI）。这些数据表明，卫星衍生的LAI估计对许多季节性热带森林中发生的下层LAI变化以及控制叶片物候季节变化的微气象变量不敏感。虽然需要更多的地面测量来充分量化这些基于卫星的LAI产品的性能，但我们的数据表明，在季节性热带森林中，对其输出结果必须谨慎解释。
