全球植被叶倾角与天顶方向叶片投影函数产品

叶倾角（Leaf Inclination Angle, LIA）是叶片表面法线与天顶方向之间的夹角。LIA是辐射传输、降雨截获、蒸散发、光合作用以及水文过程的关键参数。在辐射传输过程中，LIA常通过叶片投影函数（G(θ)）来表示。该函数定义为在光照或观测方向θ上单位叶面积的平均投影比例。
本数据集（CAS-GLA）首次提供了全球平均叶倾角（MLA）及天底方向叶片投影函数（G(0)）产品。本产品包含两种空间分辨率：500米与0.05度。产品以GeoTIFF格式存储，采用WGS-84地理坐标系。全球500米MLA产品通过对LIA测量数据进行空间扩展、升尺度和样本筛选等预处理后，采用随机森林回归模型生成。交叉验证表明，预测MLA与验证样本间具有中等一致性（r = 0.75，RMSE = 7.15°）。此外，0.05度MLA产品由500米MLA产品根据MODIS 500米叶面积指数加权升尺度得到。G(0)产品则通过假设叶倾角符合单参数椭球形分布，由MLA推导得出。G(0)产品与高分辨率参考数据呈现中等吻合度（r = 0.62，RMSE = 0.15）。需注意，全球MLA和G(0)产品主要反映2001-2022年生长季的典型状态。本产品将深化我们对全球叶倾角分布的理解，并为遥感反演和陆面模式研究提供重要数据支撑。
在此V1.1版本中，500米MLA产品新增了两个质量层：输入数据质量层和预测模型质量层。输入数据质量由每个像元内高质量BRDF反演结果的比例表征；预测模型质量则根据MLA预测值是否超出训练样本范围进行定性评估（插值或外推）。在500米MLA产品中，三个波段一次表示：MLA值、输入数据质量（缩放系数=0.01）和预测模型质量（1：样本范围内预测；0：样本范围外预测）。发表在ESSD上的数据论文“Mapping global leaf inclination angle (LIA) based on field measurement data”对本数据集做了更详细的介绍，可访问 https://doi.org/10.5194/essd-17-1347-2025 了解。

Leaf Inclination Angle (LIA) is defined as the angle between the normal vector of a leaf surface and the zenith direction. LIA is a critical parameter for radiation transfer, rainfall interception, evapotranspiration, photosynthesis, and hydrological processes. In radiation transfer studies, LIA is often represented by the leaf projection function G(θ), which is defined as the average projected fraction of unit leaf area in the illumination or observation direction θ.

This dataset (CAS-GLA) provides, for the first time, global mean leaf inclination angle (MLA) and nadir-direction leaf projection function (G(0)) products. The products are available in two spatial resolutions: 500 m and 0.05 degrees. Stored in GeoTIFF format, they adopt the WGS-84 geographic coordinate system.

The global 500 m MLA product was generated using a random forest regression model after preprocessing steps including spatial expansion, upscaling, and sample screening of LIA measurement data. Cross-validation results show moderate agreement between the predicted MLA and validation samples (r = 0.75, RMSE = 7.15°).

Additionally, the 0.05° MLA product was derived by weighted upscaling of the 500 m MLA product using the MODIS 500 m leaf area index.

The G(0) product was derived from MLA based on the assumption that leaf inclination angles follow a single-parameter ellipsoidal distribution. The G(0) product exhibits moderate consistency with high-resolution reference data (r = 0.62, RMSE = 0.15).

It should be noted that the global MLA and G(0) products primarily reflect the typical conditions of the growing seasons from 2001 to 2022. This product will deepen our understanding of global leaf inclination angle distribution and provide important data support for remote sensing inversion and land surface model research.

In this V1.1 version, the 500 m MLA product adds two quality layers: the input data quality layer and the prediction model quality layer. The input data quality is characterized by the proportion of high-quality BRDF inversion results within each pixel. The prediction model quality is qualitatively evaluated based on whether the MLA prediction value falls within the range of training samples (1 for prediction within the training sample range, 0 for prediction outside the training sample range).

In the 500 m MLA product, three bands are presented in sequence: MLA value, input data quality (scaling factor = 0.01), and prediction model quality (1: prediction within the training sample range; 0: prediction outside the training sample range).

The data paper "Mapping global leaf inclination angle (LIA) based on field measurement data" published in ESSD provides a more detailed introduction to this dataset, which can be accessed at https://doi.org/10.5194/essd-17-1347-2025.

搜集汇总

背景与挑战

背景概述

该数据集为全球植被叶倾角与叶片投影函数产品，包含两种空间分辨率（500米和0.05度），数据覆盖2001-2022年生长季，适用于遥感反演和陆面模式研究。