首页> 外文期刊>Agricultural and Forest Meteorology >Estimation of olive grove canopy temperature from MODIS thermal imagery is more accurate than interpolation from meteorological stations.
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Estimation of olive grove canopy temperature from MODIS thermal imagery is more accurate than interpolation from meteorological stations.

机译:从MODIS热成像仪估算橄榄树冠层温度要比从气象站进行插值更准确。

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摘要

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.
机译:开发了一种根据卫星数据估算橄榄冠层温度的方法。使用中分辨率成像光谱仪(MODIS)地表温度(LST,1 km)和归一化植被指数(NDVI,250 m)产品。 LST与东地中海不同地区和橄榄园环境中由数据记录仪收集的冠层温度测量值的偏差表现出季节性行为(即夏季偏差较大,冬季偏差较小)。我们为LST建立了一个校正函数,该函数表示LST与原地冠层温度的偏差的季节性行为。 NDVI用于设置校正功能的参数。我们计算了以下数据的平均绝对误差:(a)基于卫星的冠层温度估算;(b)LST和(c)最近的气象站相对于原地冠层温度的气温。发现基于卫星的冠层温度估计比使用LST或气象站的气温更准确,这是生态建模中常用的方法。因此,可以预期的是,这项研究中开发的校正功能将提高建模橄榄园有害生物种群趋势以及其他农艺性状的能力,从而增强果园的时空管理能力。

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