To evaluate and provide an appropriate theoretical direction for research into climate-vegetation interactions using meteorological station data at different time scales, we examined differences between the Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) and their responses to climate factors. We looked for correlations between data extracted from MOD13Q1 remote sensing images and meteorological station data for the two indexes. The results showed that even though NDVI and EVI are derived from the same remote sensing image, their response to climate factors was significantly different. In the same meteorological station, the correlation coefficients for NDVI, EVI and climate factors were different; correlation coefficients between NDVI, EVI and climate factors varied with meteorological station. In addition, there was a lag effect for responses of NDVI to average minimum temperature, average temperature, average vapor pressure, minimum relative humidity, extreme wind speed, maximum wind speed, average wind speed and average station air-pressure. EVI had a lag only for average minimum temperature, average vapor pressure, extreme wind speed, maximum wind speed and average station air-pressure. The lag period was variable, but most were in the -3 period. Different vegetation types had different sensitivities to climate. The correlation between meteorological stations and vegetation requires more attention in future research.
PAN Xia, GAO Yong, WANG Ji
. Response Differences of MODIS-NDVI and MODIS-EVI to Climate Factors[J]. Journal of Resources and Ecology, 2018
, 9(6)
: 673
-680
.
DOI: 10.5814/j.issn.1674-764x.2018.06.010
[1] Ahmed A, Akhtar A, Shamim A,et al. 2013. Correlation of meteorological parameters and remotely sensed normalized difference vegetation index (NDVI) with cotton leaf curl virus (CLCV) in Multan 2044.
[2] Behrenfeld M J, Randerson J T, McClain C R, et al.2001. Biospheric primary production during an ENSO transition.Science, 291(5513): 2594-2597.
[3] Bao Y J, Song G B.2007. Study on the spatial differences and its time lag effect on climatic factors of the vegetation in the Longitudinal Range-Gorge Region.Chinese Science Bulletin, 52(A2): 42-49.
[4] Chen Z H, Chen W J, Leblanc S G, et al.2010. Digital photograph analysis for measuring percent plant cover in the Arctic.Arctic, 63: 315-326.
[5] Chen W, Sakai T, Moriya K,et al.2013. Estimation of Vegetation Coverage in Semi-arid Sandy Land Based on Multivariate Statistical Modeling Using Remote Sensing Data. Environmental Modeling and Assessment, 18(5): 547-558.
[6] Chen Y, Shi P, Li X, et al.2006. A combined approach for estimating vegetation cover in urban/suburban environments from remotely sensed data.Computers and Geosciences, 32(9): 1299-1309.
[7] Gitelson A A, Kaufman Y J, Stark R, et al.2002. Novel algorithms for remote estimation of vegetation fraction.Remote Sensing of Environment, 80(1): 76-87.
[8] Jeffery S B, Masters G J, Hodkinson I D, et al.2002. Herbivory in global climate change research: direct effects of rising temperature on insect herbivores. Global Change Biology, 8(1): 1-16.
[9] Karl T R, Melillo J M, Peterson T C, et al.2009. Global climate change impacts in the United States.Journal of Environmental Quality, 40(4): 279.
[10] Karl T R, Trenberth K E.2003. Modern global climate change.Science, 302(5651): 1719.
[11] Liu B, Yue Y M, Li R,et al.2010. Study on the relation between fraction cover and mixed spectra in karst environment.Spectroscopy and Spectral Analysis, 30: 2470-2474.
[12] Xu L P, Guo P, Liu L, et al.2014. The Sensitivity of Vegetation Index and Climate Factors in North Tianshan Mountain.Hubei Agricultural Sciences, 33(11): 152-158. (in Chinese)
[13] Matsushita B, Yang W, Chen J, et al.2007. Sensitivity of the Enhanced Vegetation Index (EVI) and Normalized Difference Vegetation Index (NDVI) to Topographic Effects: A Case Study in High-Density Cypress Forest.Sensors, 7(11): 2636-2651.
[14] Ni J, Wang G H.2004. Northeast China Transect (NECT): ten-year synthesis and future challenges.Journal of Integrative Plant Biology, 46(4): 379-391.
[15] Nie Q, Xu J, Ji M, et al.2012. The Vegetation Coverage Dynamic Coupling with Climatic Factors in Northeast China Transect.Environmental Management, 50(3): 405-417.
[16] Parmesan C, Yohe G.2003. A globally coherent fingerprint of climate change impacts across natural systems.Nature, 421(6918): 37-42.
[17] Pisek J, Chen J M.2009. Mapping forest background reflectivity over North America with multi-angle imaging spectroradiometer (MISR) data.Remote Sensing of Environment, 113(11): 2412-2423.
[18] Pazpellat F, Bolañosgonzález M, Palaciosvélez E, et al.2008. Optimization of the spectral vegetation index NDVIcp.Agrociencia, 42(8):443-450.
[19] Running S W, Glassy J M, Thornton P E.1999. MODIS daily photosynthesis (PSN) and annual net primary production (NPP) product (MOD17) Algorithm Theoretical Basis Document. version 3.0.
[20] Shaojie M U, Yang H, Jianlong L I, et al.2013. Spatio-temporal dynamics of vegetation coverage and its relationship with climate factors in Inner Mongolia,China. Journal of Geographical Sciences, 23(2): 231-246.
[21] Stojanova D, Panov P, Gjorgjioski V, et al.2010. Estimating vegetation height and canopy cover from remotely sensed data with machine learning.Ecological Informatics, 5(4): 256-266.
[22] Walker B, Steffen W.1997. IGBP Science No.1: A synthesis of GCTE and Related Research. Stockholm: IGBP, 1-24.
[23] Wigley T M L, Raper S C B.2002. Reasons for Larger Warming Projections in the IPCC Third Assessment Report. Journal of Climate, 15(20): 2945-2952.
[24] Wei Y, White R, Hu K, et al.2010. Valuing the environmental externalities of oasis farming in Left Banner, Alxa, China.Ecological Economics, 69(11): 2151-2157.
[25] Wardlow B, Egbert S.2010. A comparison of MODIS 250-m EVI and NDVI data for crop mapping: a case study for southwest Kansas.International Journal of Remote Sensing, 31(3): 805-830.
[26] Yan E, Wang G, Lin H,et al.2015. Phenology-based classification of veg-etation cover types in Northeast China using MODIS NDVI and EVI time series. International Journal of Remote Sensing, 36(2): 489-512.
[27] Ying-Mina H U, Gao Q, Lan Y F, et al.2012. Responses of EVI to Climate and Land-use Variation in Taips County from 2000 to 2008.Journal of Natural Resources, 27(7): 1200-1213. (in Chinese)
[28] Zhang C, Li W, Fan M.2013. Adaptation of herders to droughts and privatization of rangeland-use rights in the arid Alxa Left Banner of Inner Mongolia.Journal of Environmental Management, 126(14): 182-190.
