Vegetation height and cover fraction between 60A° S and 60A° N from ICESat GLAS data
Vegetation height and cover fraction between 60A° S and 60A° N from ICESat GLAS data
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DOI：
10.5194/gmd-5-413-2012
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发表时间：
2012-01-01
影响因子：
5.1
通讯作者：
Berni, J. A. J.
中科院分区：
文献类型：
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作者：
Los, S. O.;Rosette, J. A. B.;Berni, J. A. J.
我们提出了新的粗分辨率（0.5A度× 0.5A度）植被高度和植被覆盖率数据集之间的60 A度S和60 A度N用于气候模型和生态模型。这些数据集来自2003-2009年地球科学激光高度计系统（GLAS）在冰、云和陆地高程卫星（ICESat）上收集的测量数据，ICESat是唯一提供接近全球覆盖的激光雷达仪器。初始植被高度是使用Rosette等人（2008年）开发的模型从GLAS数据中计算出来的，并在沙漠地点进行了进一步校准。过滤器的开发是为了识别和消除GLAS数据中的虚假观测，例如受云、大气和地形影响的数据，从而导致对植被高度或植被覆盖的错误估计。过滤后的GLAS植被高度估计值汇总在直方图中，从0到70米，每隔0.5米，每0.5A度x 0.5A度。GLAS植被高度产品的评估有四种方式。首先，植被高度数据和数据过滤器使用飞机激光雷达测量在美洲，欧洲和澳大利亚的10个站点进行评估。对GLAS植被高度估算应用滤波器可将与飞机数据的相关性从r = 0.33提高到r = 0.78，将均方根误差降低3倍，降至约6 m（RMSE）或4.5 m（68%误差分布），并将偏差从5.7 m降低到-1.3 m。其次，全球汇总GLAS植被高度产品的敏感性进行了测试，对数据质量过滤器的选择，频繁的云层覆盖和陡峭的地形地区是最敏感的过滤器的阈值的选择。通过应用不同的过滤器的高度估计的变化，主要是小于4.5-6米，从现场测量建立的整体不确定性。第三，GLAS全球植被高度产品与全球植被高度产品通常用于气候模型，最近的全球树高产品，和植被绿化产品进行比较，并显示出产生现实的估计植被高度。最后，GLAS裸土覆盖率进行了全球比较与MODIS裸土覆盖率（r = 0.65）和裸土覆盖率估计来自AVHRR NDVI数据（r = 0.67）; GLAS树木覆盖率进行了比较与MODIS树木覆盖率（r = 0.79）。评估表明，过滤器应用于GLAS数据是保守的，并消除了很大一部分的虚假数据，而只有在少数情况下，在删除可靠的data. New GLAS植被高度产品的成本出现更现实的比以前的数据集在气候模式和生态模式，因此应显着改善模拟，涉及陆面。
We present new coarse resolution (0.5A degrees x 0.5A degrees) vegetation height and vegetation-cover fraction data sets between 60A degrees S and 60A degrees N for use in climate models and ecological models. The data sets are derived from 2003-2009 measurements collected by the Geoscience Laser Altimeter System (GLAS) on the Ice, Cloud and land Elevation Satellite (ICESat), the only LiDAR instrument that provides close to global coverage. Initial vegetation height is calculated from GLAS data using a development of the model of Rosette et al. (2008) with with further calibration on desert sites. Filters are developed to identify and eliminate spurious observations in the GLAS data, e.g. data that are affected by clouds, atmosphere and terrain and as such result in erroneous estimates of vegetation height or vegetation cover. Filtered GLAS vegetation height estimates are aggregated in histograms from 0 to 70 m in 0.5 m intervals for each 0.5A degrees x 0.5A degrees. The GLAS vegetation height product is evaluated in four ways. Firstly, the Vegetation height data and data filters are evaluated using aircraft LiDAR measurements of the same for ten sites in the Americas, Europe, and Australia. Application of filters to the GLAS vegetation height estimates increases the correlation with aircraft data from r = 0.33 to r = 0.78, decreases the root-mean-square error by a factor 3 to about 6 m (RMSE) or 4.5 m (68% error distribution) and decreases the bias from 5.7 m to -1.3 m. Secondly, the global aggregated GLAS vegetation height product is tested for sensitivity towards the choice of data quality filters; areas with frequent cloud cover and areas with steep terrain are the most sensitive to the choice of thresholds for the filters. The changes in height estimates by applying different filters are, for the main part, smaller than the overall uncertainty of 4.5-6 m established from the site measurements. Thirdly, the GLAS global vegetation height product is compared with a global vegetation height product typically used in a climate model, a recent global tree height product, and a vegetation greenness product and is shown to produce realistic estimates of vegetation height. Finally, the GLAS bare soil cover fraction is compared globally with the MODIS bare soil fraction (r = 0.65) and with bare soil cover fraction estimates derived from AVHRR NDVI data (r = 0.67); the GLAS tree-cover fraction is compared with the MODIS tree-cover fraction (r = 0.79). The evaluation indicates that filters applied to the GLAS data are conservative and eliminate a large proportion of spurious data, while only in a minority of cases at the cost of removing reliable data as well.The new GLAS vegetation height product appears more realistic than previous data sets used in climate models and ecological models and hence should significantly improve simulations that involve the land surface.