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Estimating daily gross primary production of maize based only on MODIS WDRVI and shortwave radiation data

机译:仅基于MODIS WDRVI和短波辐射数据估算玉米的每日总初级生产量

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Accurate assessment of temporal changes in gross primary production (GPP) is important for carbon budget assessments and evaluating the impact of climate change on crop productivity. The objective of this study was to devise a simple remote sensing-based GPP model to quantify daily GPP of maize. In the model, (1) daily shortwave radiation (SW), derived from the reanalysis data (North American Land Data Assimilation System; NLDAS-2) and (2) smoothed Wide Dynamic Range Vegetation Index (WDRVI) data, derived from Moderate Resolution Imaging Spectroradiometer (MODIS) 250-m observations were used as proxy variables of the incident photosynthetically active radiation (PAR) and the total canopy chlorophyll content, respectively. The model was calibrated and validated by using tower-based CO_2 flux observations over an 8-year period (2001 to 2008) for one rainfed and two irrigated sites planted to maize as part of the Carbon Sequestration Program at the University of Nebraska-Lincoln. The results showed the temporal features of the product SW WDRVI closely related to the temporal GPP variations in terms of both daily variations and seasonal patterns. The simple GPP model was able to predict the daily GPP values and accumulated GPP values of maize with high accuracy.
机译:准确评估初级生产总值(GPP)的时间变化对于碳预算评估和评估气候变化对作物生产力的影响至关重要。这项研究的目的是设计一个简单的基于遥感的GPP模型来量化玉米的每日GPP。在该模型中,(1)从重新分析数据(北美土地数据同化系统; NLDAS-2)得出的每日短波辐射(SW)和(2)从中等分辨率得到的平滑的宽动态范围植被指数(WDRVI)数据成像光谱仪(MODIS)的250米观测值分别用作入射光合有效辐射(PAR)和总冠层叶绿素含量的替代变量。作为内布拉斯加州林肯大学碳固存计划的一部分,通过使用塔基的CO_2通量观测值,在8年期间(​​2001年至2008年)对一个雨养和两个灌溉玉米种植地点进行了校准和验证,对模型进行了验证。结果表明,在每日变化和季节性模式方面,产品SW WDRVI的时间特征都与时间GPP变化密切相关。简单的GPP模型能够高精度地预测玉米的每日GPP值和累积的GPP值。

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