کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6347030 1621260 2014 11 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Comparison between SMOS Vegetation Optical Depth products and MODIS vegetation indices over crop zones of the USA
موضوعات مرتبط
مهندسی و علوم پایه علوم زمین و سیارات کامپیوتر در علوم زمین
پیش نمایش صفحه اول مقاله
Comparison between SMOS Vegetation Optical Depth products and MODIS vegetation indices over crop zones of the USA
چکیده انگلیسی
The Soil Moisture and Ocean Salinity (SMOS) mission provides multi-angular, dual-polarised brightness temperatures at 1.4 GHz, from which global soil moisture and vegetation optical depth (τ) products are retrieved. This paper presents a study of SMOS' τ product in 2010 and 2011 for crop zones of the USA. Retrieved τ values for 504 crop nodes were compared to optical/IR vegetation indices from the MODIS (Moderate Resolution Imaging Spectroradiometer) satellite sensor, including the Normalised Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Leaf Area Index (LAI), and a Normalised Difference Water Index (NDWI) product. τ values were observed to increase during the growing season and decrease during senescence in these areas, as did MODIS vegetation indices. SMOS' τ values generally peaked later than MODIS LAI values, with an estimated time difference of about 19 days. A linear regression between τ and the MODIS products was carried out for each node and values of the determination coefficient, R2, slope, b′ and intercept, b″ were found. The average R2 value varied from 0.32 to 0.35 for the different vegetation indices. The linear regression between LAI and τ produced an average slope of b′ = 0.06, and an average intercept of b″ = 0.14. The effects of crop fraction and dominant crop type were investigated and crop fraction was found to have a low effect on R2 values. R2values appeared to be lower for wheat and hay and higher for corn. b′ and b″ values had higher standard deviations for wheat but were generally close to the mean values for corn, soybean and hay.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Remote Sensing of Environment - Volume 140, January 2014, Pages 396-406
نویسندگان
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