This paper reports the phenological response of forest vegetation to climate change(changes in temperature and precipitation)based on Moderate Resolution Imaging Spectroradiometer(MODIS)Enhanced Vegetation Index(EVI)t...This paper reports the phenological response of forest vegetation to climate change(changes in temperature and precipitation)based on Moderate Resolution Imaging Spectroradiometer(MODIS)Enhanced Vegetation Index(EVI)time-series images from 2000 to 2015.The phenological parameters of forest vegetation in the Funiu Mountains during this period were determined from the temperature and precipitation data using the Savitzky-Golay filter method,dynamic threshold method,Mann-Kendall trend test,the Theil-Sen estimator,ANUSPLIN interpolation and correlation analyses.The results are summarized as follows:(1)The start of the growing season(SOS)of the forest vegetation mainly concentrated in day of year(DOY)105-120,the end of the growing season(EOS)concentrated in DOY 285-315,and the growing season length(GSL)ranged between 165 and 195 days.There is an evident t,correlation between forest phenology and altitude.With increasing altitude,the SOS;EOS and GSL presented a significant delayed,advanced and shortening trend,respectively.(2)Both SOS and EOS of the forest vegetation displayed the delayed trend,the delayed pixels accounted for 76.57% and 83.81% of the total,respectively.The GSL of the forest vegetation was lengthened,and the lengthened pixels accounted for 61.21% of the total.The change in GSL was mainly caused by the decrease in spring temperature in the region.(3)The SOS of the forest vegetation was significantly partially correlated with the monthly average temperature in March,with most correlations being negative;that is,the delay in SOS was mainly attributed to the temperature decrease in March.The EOS was significantly partially correlated with precipitation in September,with most correlations being positive;that is,the EOS was clearly delayed with increasing precipitation in September.The GSL of the forest vegetation was influenced by both temperature and precipitation throughout the growing season.For most regions,GSL was most closely related to the monthly average temperature and precipitation in August.展开更多
基于四川省区域范围内144个气象站点的实测降水数据,在综合考虑空间位置、地形等影响因素的基础上,采用改进的回归克里格模型,即混合地理加权回归克里格模型(MGWRK)对四川省年降水量的空间分布进行空间插值,并与普通克里格(OK)、全...基于四川省区域范围内144个气象站点的实测降水数据,在综合考虑空间位置、地形等影响因素的基础上,采用改进的回归克里格模型,即混合地理加权回归克里格模型(MGWRK)对四川省年降水量的空间分布进行空间插值,并与普通克里格(OK)、全局回归克里格(GRK)和地理加权回归克里格(GWRK)等模型的插值效果进行对比分析。结果表明:(1)应用逐步回归法筛选确定的用于回归分析的影响因子组合为经度、纬度和坡度,可有效消除解释变量间的多重共线性,为后续的空间插值奠定基础;(2)同一回归变量在地理加权回归(GWR)与全局回归(GR)两种回归模型中的AICc(修正的赤池信息量准则,Corrected Akaike Information Criterion)值之差(ΔAICc)可用于定量判定各回归变量的空间非平稳性类型,据此将变量坡度设为全局变量,经度和纬度设为局部变量进行处理。在此基础上,通过MGWRK模型对四川省年降水量进行空间插值;(3)MGWRK插值模型综合考虑了空间位置、地形等多个影响因素及其与降水相互关系的空间非平稳性特征,相对于传统的OK和GRK法具有更高的插值精度。展开更多
Based on the daily precipitation data between 1965 and 2009 from 18 rainfall stations in Guangdong Beijiang River basin and the definitions of Precipitation Concentration Degree(PCD) and Precipitation Concentration Pe...Based on the daily precipitation data between 1965 and 2009 from 18 rainfall stations in Guangdong Beijiang River basin and the definitions of Precipitation Concentration Degree(PCD) and Precipitation Concentration Period(PCP),the inhomogeneous distribution characteristics of interannual precipitation were analyzed by introducing the spatial distribution of annual mean values,variable coefficients,correlation coefficients between annual precipitation,change trends and composite analysis. The results showed that(1) PCD mainly decreased from south to north in spatial distribution; PCP was earlier in most of north-central basin,but relatively later in southern basin.(2) Annual precipitation would increase if PCD decreased in most of river basin,and annual precipitation would decrease as PCP lagged in southern basin,but the change trend was the opposite in northern basin.(3) PCD and PCP mainly showed insignificant upward trend in the entire basin by Mann-Kendall test.展开更多
基金National Natural Science Foundation of China,No.41671090National Basic Research Program(973 Program),No.2015CB452702
文摘This paper reports the phenological response of forest vegetation to climate change(changes in temperature and precipitation)based on Moderate Resolution Imaging Spectroradiometer(MODIS)Enhanced Vegetation Index(EVI)time-series images from 2000 to 2015.The phenological parameters of forest vegetation in the Funiu Mountains during this period were determined from the temperature and precipitation data using the Savitzky-Golay filter method,dynamic threshold method,Mann-Kendall trend test,the Theil-Sen estimator,ANUSPLIN interpolation and correlation analyses.The results are summarized as follows:(1)The start of the growing season(SOS)of the forest vegetation mainly concentrated in day of year(DOY)105-120,the end of the growing season(EOS)concentrated in DOY 285-315,and the growing season length(GSL)ranged between 165 and 195 days.There is an evident t,correlation between forest phenology and altitude.With increasing altitude,the SOS;EOS and GSL presented a significant delayed,advanced and shortening trend,respectively.(2)Both SOS and EOS of the forest vegetation displayed the delayed trend,the delayed pixels accounted for 76.57% and 83.81% of the total,respectively.The GSL of the forest vegetation was lengthened,and the lengthened pixels accounted for 61.21% of the total.The change in GSL was mainly caused by the decrease in spring temperature in the region.(3)The SOS of the forest vegetation was significantly partially correlated with the monthly average temperature in March,with most correlations being negative;that is,the delay in SOS was mainly attributed to the temperature decrease in March.The EOS was significantly partially correlated with precipitation in September,with most correlations being positive;that is,the EOS was clearly delayed with increasing precipitation in September.The GSL of the forest vegetation was influenced by both temperature and precipitation throughout the growing season.For most regions,GSL was most closely related to the monthly average temperature and precipitation in August.
基金Project(17D02) supported by the Open Fund of State Laboratory of Information Engineering in Surveying,Mapping and Remote Sensing,Wuhan University,ChinaProject supported by the State Key Laboratory of Satellite Navigation System and Equipment Technology,China.
文摘基于四川省区域范围内144个气象站点的实测降水数据,在综合考虑空间位置、地形等影响因素的基础上,采用改进的回归克里格模型,即混合地理加权回归克里格模型(MGWRK)对四川省年降水量的空间分布进行空间插值,并与普通克里格(OK)、全局回归克里格(GRK)和地理加权回归克里格(GWRK)等模型的插值效果进行对比分析。结果表明:(1)应用逐步回归法筛选确定的用于回归分析的影响因子组合为经度、纬度和坡度,可有效消除解释变量间的多重共线性,为后续的空间插值奠定基础;(2)同一回归变量在地理加权回归(GWR)与全局回归(GR)两种回归模型中的AICc(修正的赤池信息量准则,Corrected Akaike Information Criterion)值之差(ΔAICc)可用于定量判定各回归变量的空间非平稳性类型,据此将变量坡度设为全局变量,经度和纬度设为局部变量进行处理。在此基础上,通过MGWRK模型对四川省年降水量进行空间插值;(3)MGWRK插值模型综合考虑了空间位置、地形等多个影响因素及其与降水相互关系的空间非平稳性特征,相对于传统的OK和GRK法具有更高的插值精度。
基金the National Natural Science Fund of China(41571091)the"13^th Five-year"Planning Item of Guangdong Philosophy and Social Sciences(GD16CGL10).
文摘Based on the daily precipitation data between 1965 and 2009 from 18 rainfall stations in Guangdong Beijiang River basin and the definitions of Precipitation Concentration Degree(PCD) and Precipitation Concentration Period(PCP),the inhomogeneous distribution characteristics of interannual precipitation were analyzed by introducing the spatial distribution of annual mean values,variable coefficients,correlation coefficients between annual precipitation,change trends and composite analysis. The results showed that(1) PCD mainly decreased from south to north in spatial distribution; PCP was earlier in most of north-central basin,but relatively later in southern basin.(2) Annual precipitation would increase if PCD decreased in most of river basin,and annual precipitation would decrease as PCP lagged in southern basin,but the change trend was the opposite in northern basin.(3) PCD and PCP mainly showed insignificant upward trend in the entire basin by Mann-Kendall test.