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首页> 外文期刊>Remote Sensing of Environment: An Interdisciplinary Journal >A regional phenology model for detecting onset of greenness in temperate mixed forests, Korea: an application of MODIS leaf area index
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A regional phenology model for detecting onset of greenness in temperate mixed forests, Korea: an application of MODIS leaf area index

机译:韩国温带混交林中检测绿色开始的区域物候模型:MODIS叶面积指数的应用

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A regional phenology model for detecting onset of vegetation greenness was developed using year 2001MODIS land products in temperate mixed forests in Korea. The model incorporates a digital elevation model (DEM), moderate resolution imaging spectroradiometer (MODIS) landcover and leaf area index (LAI) products, and climate data from weather-monitoring stations. MODIS-based onset of greenness varied spatially and showed significant correlation with air temperature (r = -0.70, p < 0.001). Our modeling methodology is to relate thermal summation calculated using the MODIS-based timing of onset with 30-year mean air temperature. Onset of greenness is expected to occur at values above the critical thermal summation threshold and is predicted to vary spatially. An algorithm for downscaling 8-day composite MODIS LAI product to a daily unit was introduced, and its predictability was validated using ground-measured onset of greenness. Two unknown parameters and the best regression were determined by iterative cross-validation. Minimal cross-validation errors between the predicted and MODIS-based timings of onset were found at a mean absolute error (MAE = 3.0 days) and bias (+ 1.6 days). The predicted onsets show good agreement with ground-measured onset of greenness (MAE = 2.5 days and bias = +2.5 days). This study demonstrates the utility of MODIS land products as tools for detecting spatial variability in phenology across climate gradients. (C) 2003 Elsevier Science Inc. All rights reserved. [References: 56]
机译:在韩国温带混交林中,使用2001MODIS年的土地产品,开发了一种用于检测植被绿色开始的区域物候模型。该模型结合了数字高程模型(DEM),中分辨率成像光谱仪(MODIS)地被植物和叶面积指数(LAI)产品以及气象台的气候数据。基于MODIS的绿色发源在空间上发生变化,并与气温显着相关(r = -0.70,p <0.001)。我们的建模方法是将使用基于MODIS的发病时间与30年平均气温计算的热量总和联系起来。预计绿色开始会在高于临界热总和阈值的值处发生,并且预计会在空间上变化。引入了将8天复合MODIS LAI产品缩减为每日单位的算法,并通过地面测量的绿色开始验证了其可预测性。通过迭代交叉验证确定两个未知参数和最佳回归。在平均绝对误差(MAE = 3.0天)和偏差(+ 1.6天)处发现了预测的发作时间和基于MODIS的发作时间之间的最小交叉验证误差。预测的发作与地面测得的绿色发作有很好的一致性(MAE = 2.5天,偏差= +2.5天)。这项研究证明了MODIS土地产品作为检测跨气候梯度的物候学中空间变异性的工具的实用性。 (C)2003 Elsevier Science Inc.保留所有权利。 [参考:56]

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