کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
81810 158352 2013 4 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Estimation of olive grove canopy temperature from MODIS thermal imagery is more accurate than interpolation from meteorological stations
موضوعات مرتبط
مهندسی و علوم پایه علوم زمین و سیارات علم هواشناسی
پیش نمایش صفحه اول مقاله
Estimation of olive grove canopy temperature from MODIS thermal imagery is more accurate than interpolation from meteorological stations
چکیده انگلیسی


• A method to estimate olive canopy temperature from satellite data was developed.
• A correction function for satellite Land Surface Temperature was set.
• NDVI is used to set the parameters of the correction function.
• The satellite based estimation of canopy temperature was found more accurate than standard meteorological data.

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.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Agricultural and Forest Meteorology - Volume 176, 15 July 2013, Pages 90–93
نویسندگان
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