Temporal and Spatial Characteristics of EVI and Its Response to Climatic Factors in Recent 16 years Based on Grey Relational Analysis in Inner Mongolia Autonomous Region, China
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Area
2.2. Data Sources
2.3. Data Processing
2.3.1. EVI Data Processing
2.3.2. Spatial Interpolation of Meteorological Data
2.4. Methods
2.4.1. Trend Analytical Method
2.4.2. Grey Relational Analysis
2.4.3. Time Lag Analysis
3. Results
3.1. Inter-Annual Change of EVI in the Growing Season and Spatial Distribution Pattern
3.1.1. Inter-Annual Change of EVI in the Growing Season
3.1.2. Features of Spatial Distribution of Multi-Year Mean EVI
3.2. Temporal and Spatial Variation of EVI in the Growing Season
3.3. Time Lag Analysis of EVI in the Growing Season to Climatic Factors
3.4. GRAs between EVI and Climatic Factors
3.4.1. Features of Inter-Annual Change of Climatic Factors
3.4.2. GRAs between the Growing Season EVI and the Climatic Factors
3.5. Zoning of EVI for Climatic Driving Forces
4. Discussion
5. Conclusions
- (1)
- The mean EVI value in the growing season in IMAR from 2000 to 2015 was 0.274. The spatial distribution was significantly different. The EVI value generally showed a spatial distribution of increase from west to east and from south to north. The rate of change from west to east was 0.22/10°E, and that from south to north is 0.28/10°N.
- (2)
- During 2000–2015, the overall EVI in the growing season in IMAR showed a slight increasing trend, with a growth rate of 0.021/10a. The areas with slight and significant improvement during the study period accounted for 21.1% and 7.5% of the total study area. The areas with slight and significant degradation accounted for 24.6% and 4.3% of the total study area.
- (3)
- The results of time lag analysis show that the response time of EVI in IMAR to the three climatic factors (air temperature, relative humidity and precipitation) was different. The EVI lagged behind air temperature by 1–2 months, relative humidity by 1–2 months, and precipitation by one month.
- (4)
- The precipitation driving areas (21.8%) in IMAR were much larger than air temperature driving ones (8%) and the relative humidity driving ones (11.6%). The EVI in the study area had the closest relationship with precipitation, followed by the relative humidity, and then air temperature. However, the growth of vegetation did not depend on the change of a single climate factor, but was the result of the collective effect of multiple climatic factors and human activities.
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
- Guo, L.; Wu, S.; Zhao, D.; Yin, Y.; Leng, G.; Zhang, Q. NDVI-Based vegetation change in Inner Mongolia from 1982 to 2006 and its relationship to climate at the biome scale. Adv. Meteorol. 2014, 4, 79–92. [Google Scholar] [CrossRef]
- Xu, G.; Zhang, H.; Chen, B.; Zhang, H.; Innes, J.; Wang, G.; Yan, J.; Zheng, Y.; Zhu, Z.; Mvneni, R. Changes in Vegetation Growth Dynamics and Relations with Climate over China’s Landmass from 1982 to 2011. Remote Sens. 2014, 6, 3263–3283. [Google Scholar] [CrossRef] [Green Version]
- Hantson, S.; Knorr, W.; Schurgers, G.; Pugh, T.A.M.; Arneth, A. Global isoprene and monoterpene emissions under changing climate, vegetation, CO2, and land use. Atmos. Environ. 2017, 155, 35–45. [Google Scholar] [CrossRef]
- ** using time-series MODIS 250m NDVI data: An assessment for the U.S. Central Great Plains. Remote Sens. Environ. 2008, 112, 1096–1116. [Google Scholar] [CrossRef]
- Piao, S.; Wang, X.; Ciais, P.; Zhu, B.; Wang, T.; Liu, J. Changes in satellite-derived vegetation growth trend in temperate and boreal Eurasia from 1982 to 2006. Glob. Chang. Biol. 2011, 17, 3228–3239. [Google Scholar] [CrossRef]
- Karlsen, S.R.; Tolvanen, A.; Kubin, E.; Poikolainen, J.; Hogda, K.A.; Johansen, B.; Danks, F.S.; Aspholm, P.; Wielgolaski, F.E.; Makarova, O. MODIS-NDVI-based map** of the length of the growing season in northern Fennoscandia. Int. J. Appl. Earth Obs. 2008, 10, 253–266. [Google Scholar] [CrossRef]
- Raynolds, M.K.; Comiso, J.C.; Waiker, D.A.; Verbyla, D. Relationship between satellite-derived land surface temperatures, arctic vegetation types, and NDVI. Remote Sens. Environ. 2008, 112, 1884–1894. [Google Scholar] [CrossRef]
- Wang, X.; Piao, S.; Ciais, P.; Li, J.; Friedlingstein, P.; Koven, C.; Chen, A. Spring temperature change and its implication in the change of vegetation growth in North America from 1982 to 2006. Proc. Natl. Acad. Sci. USA 2011, 108, 1240–1245. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Zhao, X.; Tan, K.; Zhao, S.; Fang, J. Changing climate affects vegetation growth in the arid region of the northwestern China. J. Arid Environ. 2011, 75, 946–952. [Google Scholar] [CrossRef]
- Dan, S.; Li, H.; **, L.; De, X. Effects of Climate Change on Vegetation in Desert Steppe Inner Mongolia. Nat. Resour. 2013, 4, 319–322. [Google Scholar] [CrossRef]
- Qu, H.; Wang, C.J.; Zhang, Z.X. Planning priority conservation areas under climate change for six plant species with extremely small populations in China. Nat. Conserv. 2018, 25, 89–106. [Google Scholar] [CrossRef] [Green Version]
- Hu, M.Q.; Mao, F.; Sun, H.; Hou, Y.Y. Study of normalized difference vegetation index variation and its correlation with climate factors in the three-river-source region. Int. J. Appl. Earth Obs. 2011, 13, 24–33. [Google Scholar] [CrossRef]
- Lin, Y.; **n, X.; Zhang, H.; Wang, X. The implications of serial correlation and time-lag effects for the impact study of climate change on vegetation dynamics—A case study with Hulunber meadow steppe, Inner Mongolia. Int. J. Remote Sens. 2015, 36, 5031–5044. [Google Scholar] [CrossRef]
- Zhang, Y.; Zhou, W. Correlation analysis between vegetation fraction and vegetation indices in reclaimed forest: A case study in **shuo mining area. In Proceedings of the IEEE International Workshop on Earth Observation and Remote Sensing Applications, Guangzhou, China, 4–6 July 2016; pp. 122–126. [Google Scholar]
- Ballantyne, M.; Treby, D.L.; Quarmby, J.; Pickering, C.M. Comparing the impacts of different types of recreational trails on grey box grassy-woodland vegetation: Lessons for conservation and management. Aust. J. Bot. 2016, 64, 246–259. [Google Scholar] [CrossRef]
- Li, J.; Zhang, C.Q.; Zhang, J. The Lag Response of the Growth Dynamics of Dominant Grasses to Meteorological Factors in Typical Steppe of Inner Mongolia. Acta Agrestia Sin. 2017, 25, 267–272. [Google Scholar] [CrossRef]
- Klinge, M.; Dulamsuren, C.; Erasmi, S.; Karger, D.N.; Hauck, M. Climate effects on vegetation vitality at the treeline of boreal forests of Mongolia. Biogeosciences 2018, 15, 1–25. [Google Scholar] [CrossRef]
- **, X.; Xu, X. Rmote sensing of leaf water content for winter wheat using grey relational analysis (GRA), stepwise regression method (SRM) and partial least squares (PLS). In Proceedings of the IEEE First International Conference on Agro-Geoinformatics, Shanghai, China, 2–4 August 2012; pp. 1–5. [Google Scholar]
- Liu, D.; Yue, L.; Wang, T.; Peylin, P.; Macbean, N.; Ciais, P.; Jia, G.S.; Ma, M.G.; Ma, Y.M.; Shen, M.G.; et al. Contrasting responses of grassland water and carbon exchanges to climate change between Tibetan Plateau and Inner Mongolia. Agric. For. Meteorol. 2018, 249, 163–175. [Google Scholar] [CrossRef]
- Dong, Z.Q.; Pan, Z.H.; He, Q.J.; Wang, J.L.; Huang, L.; Pan, Y.Y.; Han, G.L.; Xue, X.P.; Chen, Y.C. Vulnerability assessment of spring wheat production to climate change in the Inner Mongolia region of China. Ecol. Indic. 2018, 85, 67–78. [Google Scholar] [CrossRef]
- Malingreau, J.P. Global vegetation dynamics: Satellite observations over Asia. Int. J. Remote Sens. 1986, 7, 1121–1146. [Google Scholar] [CrossRef]
- Roerink, G.J.; Menenti, M.; Verhoef, W. Reconstructing cloudfree NDVI composites using Fourier analysis of time series. Int. J. Remote Sens. 2000, 21, 1911–1917. [Google Scholar] [CrossRef]
- Xu, Z.X.; Wang, D.J.; Gao, J. Homogeneity Test on Temperature Series in Liaoning Province. J. Anhui Agric. Sci. 2010, 27, 15149–15151. [Google Scholar] [CrossRef]
- Zhang, X.; Shao, J.; Luo, H. Spatial interpolation of air temperature with ANUSPLIN in Three Gorges Reservoir Area. In Proceedings of the IEEE International Conference on Remote Sensing, Environment and Transportation Engineering, Nan**g, China, 24–26 June 2011; pp. 3465–3468. [Google Scholar]
- Yan, L.; Zhou, G.S.; Wang, Y.H.; Hu, T.Y.; Sui, X.H. The spatial and temporal dynamics of carbon budget in the alpine grasslands on the Qinghai-Tibetan Plateau using the Terrestrial Ecosystem Model. J. Clean Prod. 2015, 107, 195–201. [Google Scholar] [CrossRef]
- Way, R.G.; Lewkowicz, A.G.; Bonnaventure, P.P. Development of moderate-resolution gridded monthly air temperature and degree-day maps for the Labrador-Ungava region of northern Canada. Int. J. Climatol. 2017, 37, 493–508. [Google Scholar] [CrossRef]
- Xu, Y.; Yang, J.; Chen, Y. NDVI-based vegetation responses to climate change in an arid area of China. Theor. Appl. Climatol. 2016, 126, 213–222. [Google Scholar] [CrossRef]
- Testa, S.; Soudani, K.; Boschetti, L.; Mondino, E.B. MODIS-derived EVI, NDVI and WDRVI time series to estimate phenological metrics in French deciduous forests. Int. J. Appl. Earth Obs. 2018, 64, 132–144. [Google Scholar] [CrossRef]
- Chan, J.W.K. Product end-of-life options selection: Grey relational analysis approach. Int. J. Prod. Res. 2008, 46, 2889–2912. [Google Scholar] [CrossRef]
- Shen, C.; Wang, Y.; Wei, Y.; Yu, L. A lag analysis of R&D investment driving economic growth using grey relational model. In Proceedings of the IEEE International Conference on Environmental Science and Information Application Technology, Wuhan, China, 17–18 July 2010; pp. 61–64. [Google Scholar]
- Yi, G.H.; Deng, W.; Li, A.N.; Zhang, T.B. Response of Lakes to Climate Change in Xainza Basin Tibetan Plateau Using Multi-Mission Satellite Data from 1976 to 2008. J. Mt. Sci. Engl. 2015, 12, 604–613. [Google Scholar] [CrossRef]
- Yi, G.H.; Zhang, T.B. Delayed Response of Lake Area Change to Climate Change in Siling Co Lake, Tibetan Plateau, from 2003 to 2013. Int. J. Environ. Res. Public Health 2015, 12, 13886–13900. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Lei, J.; Peters, A.J. Assessing vegetation response to drought in the northern Great Plains using vegetation and drought indices. Remote Sens. Environ. 2003, 87, 85–98. [Google Scholar] [CrossRef]
- Nezlin, N.P.; Kostianoy, A.G.; Li, B.L. Inter-annual variability and interaction of remote-sensed vegetation index and atmospheric precipitation in the Aral Sea region. J. Arid Environ. 2005, 62, 677–700. [Google Scholar] [CrossRef]
- Goward, S.N.; Prince, S.D. Transient effects of climate on vegetation dynamics: Satellite observations. J. Biogeogr. 1995, 22, 549–564. [Google Scholar] [CrossRef]
- Liu, C.L.; Fan, R.H.; Wu, J.J.; Yan, F. Temporal lag of grassland vegetation growth reponse to precipitation in xilinguolemeng. Arid Land Geogr. 2009, 32, 512–518. [Google Scholar] [CrossRef]
- Pyankov, V.I.; Black, C.C. C4 plants in the vegetation of Mongolia: Their natural occurrence and geographical distribution in relation to climate. Oecologia 2000, 123, 15–31. [Google Scholar] [CrossRef] [PubMed]
- Xu, L.; Tu, Z.; Zhou, Y.; Yu, G. Profiling Human-Induced Vegetation Change in the Horqin Sandy Land of China Using Time Series Datasets. Sustainability 2018, 10, 1068. [Google Scholar] [CrossRef]
- Greene, R.S.B.; Nettleton, W.D.; Chartres, C.J.; Leys, J. Runoff and micromorphological properties of a grazed haplargid, near Cobar, NSW, Australia. Soil Res. 1998, 36, 87–108. [Google Scholar] [CrossRef]
- Schuman, G.E.; Reeder, J.D.; Manley, J.T.; Hart, R.H.; Manley, W.A. Impact of grazing management on the carbon and nitrogen balance of a mixed-grass rangeland. Ecol Appl. 1999, 9, 65–71. [Google Scholar] [CrossRef]
- John, R.; Chen, J.; Lu, N.; Wilske, B. Land cover/land use change in semi-arid Inner Mongolia: 1992–2004. Environ. Res. Lett. 2009, 4, 4–13. [Google Scholar] [CrossRef]
- Yin, H. Understanding Land Use And Land Cover Change In Inner Mongolia Using Remote Sensing Time Series. Ph.D. Thesis, Humboldt-Universitat zu Berlin, Berlin, Germany, 2014; 145p. [Google Scholar]
- Yin, H.; Pflugmacher, D.; Li, A.; Li, Z.; Hostert, P. Land use and land cover change in Inner Mongolia-understanding the effects of China’s re-vegetation programs. Remote Sens. Environ. 2018, 204, 918–930. [Google Scholar] [CrossRef]
- Bureau of stati of Inner Mongolia Autonomous Region. Available online: http://www.nmgtj.gov.cn/ (accessed on 15 June 2018).
Driving Factors for EVI Change | Rules of Zoning | |||
---|---|---|---|---|
gT 1 | gP 2 | gR 3 | ||
Climatic Factors | T 4 | gT > 0.7 | ||
P 5 | gP > 0.7 | |||
R 6 | gR > 0.7 | |||
[T + P]+ 7 | gT > 0.7 | gP > 0.7 | ||
[T + R]+ 8 | gT > 0.7 | gR > 0.7 | ||
[P + R]+ 9 | gP > 0.7 | gR > 0.7 | ||
[T + R + P]+ 10 | gT > 0.7 | gP > 0.7 | gR > 0.7 |
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He, D.; Yi, G.; Zhang, T.; Miao, J.; Li, J.; Bie, X. Temporal and Spatial Characteristics of EVI and Its Response to Climatic Factors in Recent 16 years Based on Grey Relational Analysis in Inner Mongolia Autonomous Region, China. Remote Sens. 2018, 10, 961. https://doi.org/10.3390/rs10060961
He D, Yi G, Zhang T, Miao J, Li J, Bie X. Temporal and Spatial Characteristics of EVI and Its Response to Climatic Factors in Recent 16 years Based on Grey Relational Analysis in Inner Mongolia Autonomous Region, China. Remote Sensing. 2018; 10(6):961. https://doi.org/10.3390/rs10060961
Chicago/Turabian StyleHe, Dong, Guihua Yi, Tingbin Zhang, Jiaqing Miao, **gji Li, and **aojuan Bie. 2018. "Temporal and Spatial Characteristics of EVI and Its Response to Climatic Factors in Recent 16 years Based on Grey Relational Analysis in Inner Mongolia Autonomous Region, China" Remote Sensing 10, no. 6: 961. https://doi.org/10.3390/rs10060961