Extensive studies have focused on instantaneous and time‐lag impacts of climatic factors on vegetation growth; however, the chronical and accumulative indirect impacts of antecedent climatic factors carrying over for a period of time on vegetation growth, defined as cumulative effects, are less investigated. Here we aimed to disentangle the cumulative effects of climatic factors on vegetation growth by using vegetation indexes and accumulated meteorological data. First, we investigated the explanation and fit of climate changes on vegetation variations by applying stepwise multiple linear regression with Akaike information criterion. Then, we obtained the correlation coefficients and lagged time of climatic factors on vegetation growth whereby partial correlation and time‐lag effect analyses. Results showed that (i) consideration of cumulative climate effects increased the explanation and fit of climate changes on vegetation dynamics for more than 77% of vegetated surface with an average global explanation of 68.33%, which was approximately 3.35% higher than the scenario when only time‐lag effects were considered; (ii) big differences exhibited in the correlation coefficients and lagged times under the scenarios with cumulative climate effects considered or not; and (iii) positive accumulated temperature (accumulated solar radiation) effects with zero (three‐month) time lag dominates most mid‐high latitude ecosystems, and negative accumulated temperature effects with three‐month delay dominates the temperate arid and semiarid regions and tropical dry ecosystems. By comparison, accumulated precipitation had relatively complex cumulative effects on vegetation growth. We concluded that climatic factors had significant cumulative effects on vegetation growth; consideration of the cumulative effects helps us better understand the climate‐vegetation interactions.

Land use and land cover change is a major issue in global environment change,and is especially significant in rapidly developing regions in the world. With its economicdevelopment, population growth, and urbanization, Guangzhou, a major metropolitan inSouth China, have experienced a dramatic land use and land cover (LULC) change over thepast 30 years. Fast LULC change have resulted in degradation of its ecosystems andaffected adversely the environment. It is urgently needed to monitor its LULC changes andto analyses the consequences of these changes in order to provide information for policy-makers to support sustainable development. This study employed two Landsat TM/ETM images in the dry season to detect LULC patterns in 1998 and 2003, and to examine LULCchanges during the period from 1998 to 2003. The type, rate, and pattern of the changesamong five counties of Guangzhou Municipality were analyzed in details by post-classification method. LULC conversion matrix was produced for each county in order toexplore and explain the urban expansion and cropland loss, the most significant types ofLULC change. Land use conversion matrixes of five counties were discussed respectivelyin order to explore and explain the inherence of land use change. The results showed thaturban expansion in these five counties kept an even rate of increase, while substantialamount of cropland vanished during the period. It is also noted that the conversion between cropland and orchard land was intensive. Forest land became the main source of new croplands.