Entity

Time filter

Source Type


Chen Y.,Guangxi Meteorological Disaster Mitigation Institute Remote Sensing Application and Validation Base of NSMC | Chen Y.,Joint Laboratory for GIS Application | Chen Y.,China Agricultural University | Mo W.,Guangxi Meteorological Disaster Mitigation Institute Remote Sensing Application and Validation Base of NSMC | And 9 more authors.
Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering | Year: 2015

In this paper, taking the vegetation in Karst rocky area as the research subject, MODIS enhanced vegetation index (EVI) series and climatic information during 2001-2010 are used to analyze the relationship between vegetation and climate factors. Vapor pressure, precipitation, relative humidity, maximum temperature, minimum temperature, mean temperature, dew point temperature, wind speed and sunshine hours are taken as climatic variables to explore their relationships with EVI series in different stages using correlation analysis method and path analysis method. Then, climatic factors are selected to establish EVI simulation models of Karst vegetation by stepwise regression analysis method. The results show that: There are significant positive correlations between EVI of Karst vegetation and most climatic factors. The correlation coefficients between EVI and the climatic factors including vapor pressure, mean temperature, dew point temperature, minimum and maximum temperature are higher and show better consistency than other factors, and all the values are over 0.8. The response of EVI to climatic factors has obvious hysteresis nature except sunshine hours and wind speed. The lag time is about 16 days for most climatic factors. Minimum and maximum temperature and mean temperature play a most significant direct effect on vegetation EVI; vapor pressure, precipitation and relative humidity play a significant indirect effect on EVI although their direct effect are not obvious. According to the correlations between EVI and climatic factors, 2 EVI simulation models are established including the same-time model and mixed-time model. The same-time model means the stages of the climatic factor series used in the model are the same to the EVI series. But, in the mixed-time model, climatic factors and EVI series in different stages are used. Vapor pressure, sunshine hours and dew point temperature are used to build the same-time model, and vapor pressure (one stage before), maximum temperature (one stage before), precipitation (one stage before), dew point temperature (one stage before) and sunshine hours (same stage) are used to build the mixed-time model. Two models' efficiencies in total Guangxi Karst area and single station are tested using data series from 2000 to 2010 and data in 2011. The simulation precisions for total Guangxi Karst area are higher than each single station for both models. From 2000 to 2010, the R2 of the same-time model and the mixed-time model are 0.843 and 0.892, respectively, while 0.765±0.033, 0.801±0.021, respectively for single station. Meanwhile, in the year of 2011, the R2 of the same-time model and the mixed-time model are 0.797 and 0.873 while 0.716±0.073, 0.746±0.064 for single station respectively. For most stations, the efficiency of mixed-time model is higher than the same-time model. As the climatic factors used in the model are different and the relationships between climatic factors and vegetation vary among the stations, the efficiency of the same-time model for some stations is higher than the mixed-time model's. ©, 2015, Chinese Society of Agricultural Engineering. All right reserved. Source

Discover hidden collaborations