| Plant phenology is a science of studying the plants appear the annual cycle natural phenomenon because of subjecting to the influence of biological factors and abiotic factors such as climate, hydrology, soil. Autumn leaf plants discolored in autumn is a phenological stage of the change of plant phenological. With the development of science and technology, the observational study of phenology is no longer confined to traditional means of observation, the new observation technology such as digital cameras automatically take pictures and data network transmission were applied to the phenological observations. Using digital cameras repeat shooting means to observe the process of autumn leaf plants discolored in autumn, and using GIS technology to do some relating statistical analysis, not only save the human resources but also reduce the difficulty of the data processing.This paper analysis the process of autumn leaf plants discolored in autumn in macro level firstly, used the record of red leaves index of27red leaves scenic in Sichuan released by Sichuan Forestry Department and Cokriging interpolation method based on ArcGIS statistical analysis module, analysis the change process of Sichuan Basin leaves index spatial distribution during the autumn leaves discolored. The results of the analysis are as follows:1. Use the the semivariogram and orthogonal covariance to analysis the first phase of red leaves index released in19, Oct.2011and the average weekly temperature during this period, the result is that the spatial autocorrelation of temperature is stronger, the autocorrelation of the red leaves index is weaker.2. Use SPSS17.0to do the correlation analysis of temperature and red leaves index and latitude, longitude, altitude and other impact factors, temperature and altitude was a significant negative relationship, and the correlation index is above-0.8; the correlation index between longitude and temperature also above0.4. Because of the autocorrelation of red leaves index is weaker, the correlation analysis of four terms leaves index and temperature, latitude, longitude and altitude show that the correlation coefficient is small and the correlation relationship was not significant.3. Using ordinary Co-kriging method, and introduce latitude, longitude and altitude information as a covariate. Interpolation of the scenic temperature data and leaves index. and we can obtained the spatial distribution of Sichuan Basin temperature and red leaves index. From the Interpolation results we can see that the temperature trend of the Sichuan Basin is that the southeast higher and northwest lower, and the temperature inside the basin is higher than outside the basin. And where the temperature is high, the leaves index is low, where the temperature is low, the leaves index is high.Secondly, this paper select typical Autumn leaf species Ginkgo, Metasequoia in Dujiangyan campus of Sichuan Agricultural University which is located in the western margin of the Sichuan Basin, as the precise object of study. Specific analys is the color change of Autumn leaf trees, Using digital camera repeat shooting means, At a continuous collection of Ginkgo biloba, Metasequoia landscape photographs during the entire autumn leaf discolored, and Record the temperature data during the leaves change color, With GIS extract the RGB values of digital photos of Analysis the color change of Ginkgo biloba, Metasequoia in the western margin of the basin. The results of the analysis are as follows:1. Using ArcGIS extract RGB of the digital photos values of Ginkgo, Metasequoia leaves and establish the corresponding attribute table, in combination with the temperature data during the leaves change, make the chromatography of leaf color changes with temperature. Chromatography clear show that as the temperature decreases, the color of Ginkgo biloba, Metasequoia leaves are from green to yellow and reddish-brown respectively.2. In the specific analysis of the RGB valuesof the Ginkgo, Metasequoia leaf discoloration, introduce of2G-RBi, the green vegetation compensation index, drawing the change process chart of temperature and2G-RBi. The chart shows that as the color of Ginkgo. Metasequoia leaves change, the value of2G-RBi is gradually reduced, and after into the autumn, the first significantly lower of the2G-RBi value represents the beginning of the leaf color change, Indicate that use2G-RBi predict the plant phenological phases is feasible.3. Using SPSS17.0on the temperature and the2G-RBi correlation analysis:Ginkgo1,4and temperature were significantly correlated, and correlation coefficient was above0.5; Ginkgo2,3and the temperature were low correlated; Ginkgo5and temperature almost have no correlation. The Metasequoia1.3,4didn’t have obvious correlation with temperature; Metasequoia2had a low correlation with temperature, the correlation coefficient was0.412; the correlation coefficient of the Metasequoia5and temperature was0.518. The results showed that temperature is the main factor affecting plant leaf discolored. |
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