The accumulation of thermal time usually represents the local heat resources to drive crop growth.Maps of temperature-based agro-meteorological indices are commonly generated by the spatial interpolation of data colle...The accumulation of thermal time usually represents the local heat resources to drive crop growth.Maps of temperature-based agro-meteorological indices are commonly generated by the spatial interpolation of data collected from meteorological stations with coarse geographic continuity.To solve the critical problems of estimating air temperature(T a) and filling in missing pixels due to cloudy and low-quality images in growing degree days(GDDs) calculation from remotely sensed data,a novel spatio-temporal algorithm for T a estimation from Terra and Aqua moderate resolution imaging spectroradiometer(MODIS) data was proposed.This is a preliminary study to calculate heat accumulation,expressed in accumulative growing degree days(AGDDs) above 10 ℃,from reconstructed T a based on MODIS land surface temperature(LST) data.The verification results of maximum T a,minimum T a,GDD,and AGDD from MODIS-derived data to meteorological calculation were all satisfied with high correlations over 0.01 significant levels.Overall,MODIS-derived AGDD was slightly underestimated with almost 10% relative error.However,the feasibility of employing AGDD anomaly maps to characterize the 2001-2010 spatio-temporal variability of heat accumulation and estimating the 2011 heat accumulation distribution using only MODIS data was finally demonstrated in the current paper.Our study may supply a novel way to calculate AGDD in heat-related study concerning crop growth monitoring,agricultural climatic regionalization,and agro-meteorological disaster detection at the regional scale.展开更多
Aims The study of deciduous phenology over boreal forest is important for understanding forest ecology and better management.In this paper,our objective was to determine the phenological stages of deciduous leaf out(D...Aims The study of deciduous phenology over boreal forest is important for understanding forest ecology and better management.In this paper,our objective was to determine the phenological stages of deciduous leaf out(DLO)over the deciduous-dominant[i.e.trembling aspen(Populus tremuloides)]stands in the Canadian Province of Alberta.Methods During the period 2006–08,we used Moderate Resolution Imaging Spectroradiometer(MODIS)-based 8-day surface temperature(TS)images to calculate accumulated growing degree days(AGDD:a favourable temperature regime for plant growth).The temporal dynamics of AGDD in conjunction with in situ DLO observations were then analysed in determining the optimal threshold for DLO in 2006(i.e.80 degree days).Important Findings The implementation of the above-mentioned optimal threshold revealed reasonable agreements(i.e.on an average 91.9%of the DLO cases within ±2 periods or ±16 days of deviations during 2007–08)in comparison to the in situ observed data.The developments could be useful in various forestry-related applications,e.g.plant growth and its ability of exchanging atmospheric carbon dioxide,forest ecohydrology,risk of insect infestation,forest fire and impact of climate change,among others.展开更多
基金Project supported by the National Key Technology R&D Program of China (No. 2012BAH29B02)the PhD Programs Foundation of Ministry of Education of China (No. 200100101110035)
文摘The accumulation of thermal time usually represents the local heat resources to drive crop growth.Maps of temperature-based agro-meteorological indices are commonly generated by the spatial interpolation of data collected from meteorological stations with coarse geographic continuity.To solve the critical problems of estimating air temperature(T a) and filling in missing pixels due to cloudy and low-quality images in growing degree days(GDDs) calculation from remotely sensed data,a novel spatio-temporal algorithm for T a estimation from Terra and Aqua moderate resolution imaging spectroradiometer(MODIS) data was proposed.This is a preliminary study to calculate heat accumulation,expressed in accumulative growing degree days(AGDDs) above 10 ℃,from reconstructed T a based on MODIS land surface temperature(LST) data.The verification results of maximum T a,minimum T a,GDD,and AGDD from MODIS-derived data to meteorological calculation were all satisfied with high correlations over 0.01 significant levels.Overall,MODIS-derived AGDD was slightly underestimated with almost 10% relative error.However,the feasibility of employing AGDD anomaly maps to characterize the 2001-2010 spatio-temporal variability of heat accumulation and estimating the 2011 heat accumulation distribution using only MODIS data was finally demonstrated in the current paper.Our study may supply a novel way to calculate AGDD in heat-related study concerning crop growth monitoring,agricultural climatic regionalization,and agro-meteorological disaster detection at the regional scale.
文摘Aims The study of deciduous phenology over boreal forest is important for understanding forest ecology and better management.In this paper,our objective was to determine the phenological stages of deciduous leaf out(DLO)over the deciduous-dominant[i.e.trembling aspen(Populus tremuloides)]stands in the Canadian Province of Alberta.Methods During the period 2006–08,we used Moderate Resolution Imaging Spectroradiometer(MODIS)-based 8-day surface temperature(TS)images to calculate accumulated growing degree days(AGDD:a favourable temperature regime for plant growth).The temporal dynamics of AGDD in conjunction with in situ DLO observations were then analysed in determining the optimal threshold for DLO in 2006(i.e.80 degree days).Important Findings The implementation of the above-mentioned optimal threshold revealed reasonable agreements(i.e.on an average 91.9%of the DLO cases within ±2 periods or ±16 days of deviations during 2007–08)in comparison to the in situ observed data.The developments could be useful in various forestry-related applications,e.g.plant growth and its ability of exchanging atmospheric carbon dioxide,forest ecohydrology,risk of insect infestation,forest fire and impact of climate change,among others.
