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Land surface phenologies and seasonalities using cool earthlight in mid-latitude croplands
Phenology deals with timing of biotic phenomena and seasonality concerns temporal patterns of abiotic variables. Studies of land surface phenology (LSP) and land surface seasonality (LSS) have long been limited to visible to near infrared (VNIR) wavelengths, despite degradation by atmospheric effects and solar illumination constraints. Enhanced land surface parameters derived from passive microwave data enable improved temporal monitoring of agricultural land surface dynamics compared to the vegetation index data available from VNIR data. LSPs and LSSs in grain growing regions of the Volga River Basin of Russia and the spring wheat belts of the USA and Canada were characterized using AMSR-E enhanced land surface parameters for the period from April through October for 2003 through 2010. Growing degree-days (GDDs) were calculated from AMSR-E air temperature retrievals using both ascending and descending passes with a base of 0 ° C and then accumulated (AGDD) with an annual restart each 1 April. Tracking the AMSR-E parameters as a function of AGDD revealed the expected seasonal pattern of thermal limitation in mid-latitude croplands. Vegetation optical depth (VOD), a microwave analog of a vegetation index, was modeled as a function of AGDD with the resulting fitted convex quadratic models yielding both high coefficients of determination ( r ^2 > 0.90) and phenometrics that could characterize cropland differences between the Russian and North American sites. The AMSR-E data were also able to capture the effects of the 2010 heat wave that devastated grain production in European Russia. These results showed the potential of AMSR-E in monitoring and modeling cropland dynamics.
Land surface phenologies and seasonalities using cool earthlight in mid-latitude croplands
Phenology deals with timing of biotic phenomena and seasonality concerns temporal patterns of abiotic variables. Studies of land surface phenology (LSP) and land surface seasonality (LSS) have long been limited to visible to near infrared (VNIR) wavelengths, despite degradation by atmospheric effects and solar illumination constraints. Enhanced land surface parameters derived from passive microwave data enable improved temporal monitoring of agricultural land surface dynamics compared to the vegetation index data available from VNIR data. LSPs and LSSs in grain growing regions of the Volga River Basin of Russia and the spring wheat belts of the USA and Canada were characterized using AMSR-E enhanced land surface parameters for the period from April through October for 2003 through 2010. Growing degree-days (GDDs) were calculated from AMSR-E air temperature retrievals using both ascending and descending passes with a base of 0 ° C and then accumulated (AGDD) with an annual restart each 1 April. Tracking the AMSR-E parameters as a function of AGDD revealed the expected seasonal pattern of thermal limitation in mid-latitude croplands. Vegetation optical depth (VOD), a microwave analog of a vegetation index, was modeled as a function of AGDD with the resulting fitted convex quadratic models yielding both high coefficients of determination ( r ^2 > 0.90) and phenometrics that could characterize cropland differences between the Russian and North American sites. The AMSR-E data were also able to capture the effects of the 2010 heat wave that devastated grain production in European Russia. These results showed the potential of AMSR-E in monitoring and modeling cropland dynamics.
Land surface phenologies and seasonalities using cool earthlight in mid-latitude croplands
W G Alemu (Autor:in) / G M Henebry (Autor:in)
2013
Aufsatz (Zeitschrift)
Elektronische Ressource
Unbekannt
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Land surface phenologies and seasonalities using cool earthlight in mid-latitude croplands
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