SHEN Bin, FANG Shibo, YU Weiguo. Different correlations between NDVI and meteorological factors at temporal-time scales. [J]. Journal of Remote Sensing 20(3):481-490(2016)
SHEN Bin, FANG Shibo, YU Weiguo. Different correlations between NDVI and meteorological factors at temporal-time scales. [J]. Journal of Remote Sensing 20(3):481-490(2016) DOI: 10.11834/jrs.20165004.
Different correlations between NDVI and meteorological factors at temporal-time scales
Vegetation index is an important parameter that reflects the status of vegetation in an area. Analyzing the relationship between climatic factors and the vegetation index is helpful to fully understand the impact of climate change on vegetation. However
some conclusions on the relationship between the vegetation index and climatic factors are inconsistent across various time scales. Thus
this issue is addressed in the present study to enhance our understanding of the relationship between vegetation and climatic factors. With the use of the Normalized Difference Vegetation Index(NDVI) data of moderate resolution imaging spectroradiometer(MODIS)during the growing seasons from 2000 to 2009
the monthly climatic factors(i.e.
mean air temperature
accumulated temperature above0 °C
and monthly precipitation) of three observations in the northern Tibetan Naqu were combined
and the within-growing-season and cross-growing-season correlations between the NDVI and the climatic factors were analyzed. First
we preprocessed the data. To eliminate the interference of human factors
especially the urban buildings in the near site
we obtained the NDVI values outside the radius of 25 km around the meteorological station. Second
we calculated the correlation coefficient between the NDVI and the monthly mean air temperature. Similarly
the correlation coefficient between the mean air temperature for the month ahead and NDVI was also calculated using the NDVI(4–9 months) and the monthly mean temperature series(3–8 months). The same process is applied to the two months ahead and the other factors. Third
we calculated the correlation coefficient between the NDVI and the mean air temperature of the month. Similarly
the correlation coefficient of the mean air temperature for the month ahead and the NDVI for April was calculated using the NDVI for April and the mean air temperature for March. The same process is applied to the two months ahead and the other factors. The within-growing-season correlations between the NDVI and the temperature and precipitation factors were highly and positively significant
and the lag effects of the climatic factors on NDVI were most obvious for the one-month lag. By contrast
the inter-growing-season correlation between NDVI and precipitation was not significant
and the lag effect was much weaker than the within-growing-season lag effect. Therefore
the correlations between the NDVI and climatic factors vary between the within-growing-season and the inter-growing-season. Such a variation can be attributed to two aspects: the within-growing-season correlation fully considered the synchronization of the rainfall and temperature
whereas the inter-growing-season did not; the difference in sample sizes resulted in different results. In this paper
the relationship between NDVI and climatic factors is discussed at different time scales. Results show differences in some aspects. At present
most of the studies are based on the relationship between vegetation changes and climate factors in the growing season.The analysis of the relationship between vegetation development and climatic factors are more scientific and persuasive. In conclusion
much more attention should be paid to the different approaches to obtain the various correlations between NDVI and climatic factors. spects: the within-growing-season correlation fully considered the synchronization of the rainfall and temperature
whereas the inter-growing-season did not; the difference in sample sizes resulted in different results.