We developed a sophisticated method to depict the spatial and seasonal characterization of net primary productivity (NPP) and climate variables. The role of climate variability in the seasonal variation of NPP exerts delayed and continuous effects. This study expands on this by mapping the seasonal characterization of NPP and climate variables from space using geographic information system (GIS) technology at the pixel level. Our approach was developed in southeastern China using moderate-resolution imaging spectroradiometer (MODIS) data. The results showed that air temperature,precipitation and sunshine percentage contributed significantly to seasonal variation of NPP. In the northern portion of the study area,a significant positive 32-d lagged correlation was observed between seasonal variation of NPP and climate (P<0.01),and the influences of changing climate on NPP lasted for 48 d or 64 d. In central southeastern China,NPP showed 16-d,48-d,and 96-d lagged correlation with air temperature,precipitation,and sunshine percentage,respectively (P<0.01); the influences of air temperature and precipitation on NPP lasted for 48 d or 64 d,while sunshine influence on NPP only persisted for 16 d. Due to complex topography and vegetation distribution in the southern part of the study region,the spatial patterns of vegetation-climate relationship became complicated and diversiform,especially for precipitation influences on NPP. In the northern part of the study area,all vegetation NPP had an almost similar response to seasonal variation of air temperature except for broad crops. The impacts of seasonal variation of precipitation and sunshine on broad and cereal crop NPP were slightly different from other vegetation NPP.
Dai-liang PENGJing-feng HUANGAlfredo R. HUETETai-ming YANGPing GAOYan-chun CHENHui CHENJun LIZhan-yu LIU
Combined with remote sensing data and meteorological data, cold damage risk was assessed for planting area of double cropping rice （DCR） in Hunan Province, China. A new methodology of cold damage risk assessment was built that apply to grid and have clear hazard-affected body. Each station cold damage annual frequency and average annual intensity of cold damage was calculated by using 1951-2010 station daily mean temperature and simple cold damage identification index. On this basis, average annual cold damage risk index was obtained by their product. The spatial analysis models of cold damage risk index about double-season early rice （DSER） and double-season later rice （DSLR） were established respectively by the relation of average annual cold damage risk index and its geographic factors. Critical threshold of level of average annual cold damage risk index for DSER and DSLR were respectively divided by the correlative equation of cold damage annual frequency and average annual intensity of cold damage. 2001-2010 planting area of DCR, acquired by time series analysis of MOD09AI 8-d composite land surface reflectance product, was as target of assessment. The results show average annual intensity of cold damage is exponential function of cold damage annual frequency, average annual cold damage risk index is directly proportional to cold damage cumulant and cold damage annual frequency, and is inversely proportional to happen times of cold damage and the square of statistical time sequence length. Cold damage risk of DSER is higher than DSLR in Hunan Province. In the 10-yr stacking map, DCR planting in low risk area accounted for 11.92% of total extraction area, in moderate risk area accounted for 69.62%, in high risk area accounted for 18.46%. According to the cold damage risk assessment result, DCR production can be guided to reduce cold damage losses.
