Estimation of olive grove canopy temperature from MODIS thermal imagery is more accurate than interpolation from meteorological stations
Estimation of olive grove canopy temperature from MODIS thermal imagery is more accurate than interpolation from meteorological stations
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DOI：
10.1016/j.agrformet.2013.03.007
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发表时间：
2013-07-15
影响因子：
6.2
通讯作者：
Nestel, David
中科院分区：
文献类型：
--
作者：
Blum, Moshe;Lensky, Itamar M.;Nestel, David
提出了一种利用卫星数据估算橄榄冠层温度的方法。中分辨率成像光谱仪（MODIS）的土地表面温度（LST，1公里）和归一化植被指数（NDVI，250米）的产品。LST从冠层温度测量与数据记录器收集的东地中海不同地区和橄榄果园环境的偏差表现出季节性行为（即夏季大偏差和冬季小偏差）。我们建立了一个LST的校正函数，代表LST从原位冠层温度的偏差的季节行为。利用归一化植被指数（NDVI）设置校正函数的参数。我们计算了（a）基于卫星的冠层温度估计，（B）LST和（c）空气温度从最近的气象站相对于现场冠层温度的平均绝对误差。基于卫星的冠层温度的估计被发现比使用LST或从气象站的空气温度，通常用于生态模拟更准确。因此，预计本研究中开发的校正函数将提高模拟害虫种群趋势的能力，以及橄榄种植园的其他农艺性状，增强果园的时间和空间管理。(C)2013爱思唯尔有限公司版权所有。
A method to estimate olive canopy temperature from satellite data was developed. Moderate Resolution Imaging Spectrometer (MODIS) Land Surface Temperature (LST, 1 km) and Normalized Difference Vegetation Index (NDVI, 250 m) products were used. The deviation of LST from the canopy temperature measurements collected with data loggers in different regions and olive orchard environments of the East Mediterranean showed seasonal behavior (i.e. large deviations at summer and small at winter). We built a correction function for the LST, representing the seasonal behavior of the deviation of LST from the in situ canopy temperature. NDVI was used to set the parameters for the correction function. We calculated the average absolute errors of (a) the satellite based estimation of the canopy temperature, (b) LST and (c) air temperature from the nearest meteorological station with respect to the in situ canopy temperature. The satellite-based estimation of canopy temperature was found more accurate than using LST or air temperature from meteorological station, as commonly used in ecological modeling. Therefore, it is expected that the correction function developed in this study will improve the capability to model pest population trends, and other agronomic traits of olive plantations, enhancing orchard management in time and space. (C) 2013 Elsevier B.V. All rights reserved.