NDVI dynamics as reflected in climatic variables: spatial and temporal trends – a case study of Hungary

References

• Arora, V. K. 2002. “The Use of the Aridity Index to Assess Climate Change Effect on Annual Runoff.” Journal of Hydrology 265 (1–4): 164–177. doi:10.1016/S0022-1694(02)00101-4.
   Web of Science ®Google Scholar
• Barger, G. L., and H. C. S. Thom. 1949. “Evaluation of Drought Hazard.” Agronomy Journal 41 (11): 519–526. doi:10.2134/agronj1949.00021962004100110004x.
   Web of Science ®Google Scholar
• Bartholy, J., R. Pongrácz, and A. Kis. 2015. “Projected Changes of Extreme Precipitation Using Multi-Model Approach.” Quarterly Journal of the Royal Meteorological Society 119 (2): 129–142.
   Google Scholar
• Bartholy, J., R. Pongrácz, C. Torma, I. Pieczka, P. Kardos, and A. Hunyady. 2009. “Analysis of Regional Climate Change Modelling Experiments for the Carpathian Basin.” International Journal of Global Warming 1 (1–3): 238–252. doi:10.1504/IJGW.2009.027092.
   Web of Science ®Google Scholar
• Basto, M., and J. M. Pereira. 2012. “An SPSS R-Menu for Ordinal Factor Analysis.” Journal of Statistical Software 46 (4): 1–29. doi:10.18637/jss.v046.i04.
   PubMed Web of Science ®Google Scholar
• Bhuiyan, C., A. K. Saha, N. Bandyopadhyay, and F. N. Kogan. 2017. “Analyzing the Impact of Thermal Stress on Vegetation Health and Agricultural Drought – A Case Study from Gujarat, India.” GIScience & Remote Sensing 54 (5): 678–699. doi:10.1080/15481603.2017.1309737.
   Web of Science ®Google Scholar
• Bihari, Z., and T. Szentimrey. 2013. “Final Version of Metadata per Country of All National Gridded Datasets Created within Module 2. Annex 3 – Description of MASH and MISH Algorithms, Deliverable D2.10.” CarpatClim. Accessed September 2018. http://www.carpatclim-eu.org/docs/mashmish/mashmish.pdf
   Google Scholar
• Blanka, V., G. Mezősi, and B. Meyer. 2013. “Projected Changes in the Drought Hazard in Hungary Due to Climate Change.” Időjárás 117 (2): 219–237.
   Web of Science ®Google Scholar
• Bradford, R. B. 2000. “Drought Events in Europe.” In Drought and Drought Mitigation in Europe, edited by J. V. Vogt and F. Somma, 7–20. Netherlands: Springer.
   Google Scholar
• CLC. 2012. “Corine Land Cover 2012 V18 — Copernicus Land Monitoring Service.” Land item. European Environmental Agency. https://land.copernicus.eu/pan-european/corine-land-cover/clc-2012
   Google Scholar
• R Core Team. 2017. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing. Vienna. https://www.R-project.org/
   Google Scholar
• Deák, B., O. Valkó, P. Török, Z. Végvári, T. Hartel, A. Schmotzer, I. Kapocsi, and B. Tóthmérész. 2014. “Grassland Fires in Hungary – A Problem or a Potential Alternative Management Tool.” Applied Ecology and Environmental Research 12 (1): 267–283. doi:10.15666/aeer/1201_267283.
   Google Scholar
• Didan, K. 2015. “MOD13Q1 MODIS/Terra Vegetation Indices 16-Day L3 Global 250m SIN Grid V006.” NASA EOSDIS Land Processes DAAC. doi:10.5067/MODIS/MOD13Q1.006.
   Google Scholar
• Dövényi, Z., ed. 2010. Inventory of Natural Micro-Regions of Hungary. Budapest: Hungarian Academy of Sciences Geographical Institute.
   Google Scholar
• “European Phenological Data Platform for Climatological Applications.” External Data Spec. European Environment Agency. https://www.eea.europa.eu/data-and-maps/data/external/european-phenological-data-platform-for
   Google Scholar
• Farkas, J. Z., E. Hoyk, and J. Rakonczai. 2017. “Geographical Analysis of Climate Vulnerability at a Regional Scale: The Case of the Southern Great Plain in Hungary.” Hungarian Geographical Bulletin 66 (2): 129–144. doi:10.15201/hungeobull.66.2.3.
   Google Scholar
• Gong, D. Y., and P. J. Shi. 2003. “Northern Hemispheric NDVI Variations Associated with Large-Scale Climate Indices in Spring.” International Journal of Remote Sensing 24 (12): 2559–2566. doi:10.1080/0143116031000075107.
   Web of Science ®Google Scholar
• Guttman, N. B. 1998. “Comparing the Palmer Drought Index and the Standardized Precipitation Index 1.” JAWRA Journal of the American Water Resources Association 34 (1): 113–121. doi:10.1111/j.1752-1688.1998.tb05964.x.
   Web of Science ®Google Scholar
• Hao, F. :., X. Zhang, W. Ouyang, A. K. Skidmore, and A. G. Toxopeus. 2012. “Vegetation NDVI Linked to Temperature and Precipitation in the Upper Catchments of Yellow River.” Environmental Modeling & Assessment 17 (4): 389–398. doi:10.1007/s10666-011-9297-8.
   Web of Science ®Google Scholar
• Haylock, M. R., N. Hofstra, A. M. G. Klein Tank, E. J. Klok, P. D. Jones, and M. New. 2008. “A European Daily High Resolution Gridded Data Set of Surface Temperature and Precipitation for 1950–2006.” Journal of Geophysical Research: Atmospheres 113 (D20): 1–12. doi:10.1029/2008JD010201.
   Web of Science ®Google Scholar
• Hellmann, J. J., J. E. Byers, B. G. Bierwagen, and J. S. Dukes. 2008. “Five Potential Consequences of Climate Change for Invasive Species.” Conservation Biology 22 (3): 534–543. doi:10.1111/j.1523-1739.2008.00951.x.
   PubMed Web of Science ®Google Scholar
• Horváth, L., N. Solymosi, and M. Gaál. 2009. “Use of the Spatial Analogy to Understand the Effects of Climate Change.” In Environmental, Health And Humanity Issues In The Down Danubian Region: Multidisciplinary Approaches edited by D. Mihailovic and M. V. Miloradov, 215–222. Singapore: World Scientific Publishing. https://www.worldscientific.com/doi/pdf/10.1142/9789812834409_fmatter
   Google Scholar
• Hothorn, T., F. Bretz, and P. Westfall. 2008. “Simultaneous Inference in General Parametric Models.” Biometrical Journal 50 (3): 346–363. doi:10.1002/bimj.200810425.
   PubMed Web of Science ®Google Scholar
• Husson, F., S. Le, and J. Pagès. 2010. Exploratory Multivariate Analysis by Example Using R. Vol. 30. Boca Raton: CRC Press.
   Google Scholar
• Jarvis, A., H. I. Reuter, A. Nelson, and E. Guevara. 2008. “Hole-Filled SRTM for the Globe Version 4.” CGIAR-CSI SRTM 90 m Database. http://srtm.csi.cgiar.org
   Google Scholar
• Justice, C. O., E. Vermote, J. R. G. Townshend, R. Defries, D. P. Roy, D. K. Hall, V. V. Salomonson, et al. 1998. “The Moderate Resolution Imaging Spectroradiometer (MODIS): Land Remote Sensing for Global Change Research.” IEEE Transactions on Geoscience and Remote Sensing 36 (4): 1228–1249. doi:10.1109/36.701075.
   Web of Science ®Google Scholar
• Kern, A., H. Marjanović, and Z. Barcza. 2016. “Evaluation of the Quality of NDVI3g Dataset against Collection 6 MODIS NDVI in Central Europe between 2000 and 2013.” Remote Sensing 8 (11): 955. doi:10.3390/rs8110955.
   Web of Science ®Google Scholar
• Kertész, Á. 2016. “Is Desertification a Problem in Hungary?” Acta Geographica Debrecina. Landscape & Environment 10 (3–4): 242–247. doi:10.21120/LE/10/3-4/18.
   Google Scholar
• Kertész, Á., and J. Mika. 1999. “Aridification — Climate Change in South-Eastern Europe.” Physics and Chemistry of the Earth, Part A: Solid Earth and Geodesy 24 (10): 913–920. doi:10.1016/S1464-1895(99)00135-0.
   Web of Science ®Google Scholar
• Kis, A., R. Pongrácz, and J. Bartholy. 2018. “Multi-Model Analysis of Regional Dry and Wet Conditions for the Carpathian Region.” International Journal of Climatology 37 (13): 4543–4560. doi:10.1002/joc.5104.
   Web of Science ®Google Scholar
• Lakatos, M., T. Szentimrey, Z. Bihari, and S. Szalai. 2013. “Creation of a Homogenized Climate Database for the Carpathian Region by Applying the MASH Procedure and the Preliminary Analysis of the Data.” Quarterly Journal of the Royal Meteorological Society 117 (1): 143–158.
   Google Scholar
• Lhermitte, S., J. Verbesselt, W. W. Verstraeten, and P. Coppin. 2011. “A Comparison of Time Series Similarity Measures for Classification and Change Detection of Ecosystem Dynamics.” Remote Sensing of Environment 115 (12): 3129–3152. doi:10.1016/j.rse.2011.06.020.
   Web of Science ®Google Scholar
• Loukas, A., L. Vasiliades, and J. Tzabiras. 2008. “Climate Change Effects on Drought Severity.” Advanced Geosciences 17 (June): 23–29. doi:10.5194/adgeo-17-23-2008.
   Google Scholar
• Love, J., and P. Mair. 2017. “Walrus: Robust Statistical Methods.” version R package version 1.0.1. https://cran.r-project.org/package=walrus
   Google Scholar
• Menzel, A., T. H. Sparks, N. Estrella, E. Koch, A. Aasa, R. Ahas, K. Alm-Kübler, P. Bissolli, O. Braslavská, and A. Briede. 2006. “European Phenological Response to Climate Change Matches the Warming Pattern.” Global Change Biology 12 (10): 1969–1976. doi:10.1111/j.1365-2486.2006.01193.x.
   Web of Science ®Google Scholar
• Mezősi, G., V. Blanka, Z. Ladányi, T. Bata, P. Urdea, A. Frank, and B. C. Meyer. 2016. “Expected Mid-And Long-Term Changes in Drought Hazard for the South-Eastern Carpathian Basin.” Carpathian Journal of Earth and Environmental Sciences 11 (2): 355–366.
   Web of Science ®Google Scholar
• Mika, J. 2009. “Changes in Means and Extremities of Temperature and Precipitation in Hungary: One Empirical and Two Dynamical Model Approaches with Special Reference to Northeast Hungary.” Thaiszia Journal of Botany 19 (SUPPL. 1): 443–457.
   Google Scholar
• Mika, J. 2013. “Changes in Weather and Climate Extremes: Phenomenology and Empirical Approaches.” Climatic Change 121 (1): 15–26. doi:10.1007/s10584-013-0914-1.
   Web of Science ®Google Scholar
• Molnár, K., and J. Mika. 1997. “Climate as a Changing Component of Landscape: Recent Evidence and Projections for Hungary.” Zeitschrift Fur Geomorphologie, Supplementband 110: 185–195.
   Google Scholar
• Móring, A. 2011. “Weather of 2010.” Légkör 56 (1): 38–42.
   Google Scholar
• Pálfai, I., and Á. Herceg. 2011. “Droughtness of Hungary and Balkan Peninsula.” Riscuri Si Catastrofe 9 (2): 145–154.
   Google Scholar
• Parmesan, C., and G. Yohe. 2003. “A Globally Coherent Fingerprint of Climate Change Impacts across Natural Systems.” Nature 421 (6918): 37–42. doi:10.1038/nature01286.
   PubMed Web of Science ®Google Scholar
• Pettorelli, N., J. O. Vik, A. Mysterud, J. M. Gaillard, C. J. Tucker, and N. C. Stenseth. 2005. “Using the Satellite-Derived NDVI to Assess Ecological Responses to Environmental Change.” Trends 20 (9): 503–510. doi:10.1016/j.tree.2005.05.011.
   Google Scholar
• Pongrácz, R., J. Bartholy, G. Gelybó, and P. Szabó. 2009. “Detected and Expected Trends of Extreme Climate Indices for the Carpathian Basin.” In Bioclimatology and Natural Hazards, edited by K. Strelcová, C. Mátyás, A. Kleidon, M. Lapin, F. Matejka, M. Blaženec, J. Škvarenina, and J. Holécy, 15–28. Dordrecht: Springer. doi:10.1007/978-1-4020-8876-6_2.
   Google Scholar
• Pongrácz, R., J. Bartholy, and A. Kis. 2014. “Estimation of Future Precipitation Conditions for Hungary with Special Focus on Dry Periods.” Quarterly Journal of the Royal Meteorological Society 118 (4): 305–321.
   Google Scholar
• Rao, M., Z. Silber-Coats, S. Powers, L. Fox III, and A. Ghulam. 2017. “Mapping Drought-Impacted Vegetation Stress in California Using Remote Sensing.” GIScience & Remote Sensing 54 (2): 185–201. doi:10.1080/15481603.2017.1287397.
   Web of Science ®Google Scholar
• Ray, D. K., J. S. Gerber, G. K. MacDonald, and P. C. West. 2015. “Climate Variation Explains a Third of Global Crop Yield Variability.” Nature Communications 6 (1): 5989. doi:10.1038/ncomms6989.
   PubMedGoogle Scholar
• Revelle, W. 2017. Psych: Procedures for Psychological, Psychometric, and Personality Research (Version 1.8.4). Evanston, IL: Northwestern University. https://CRAN.R-project.org/package=psych
   Google Scholar
• Rouse, J. W., R. H. Haas, D. W. Deering, J. A. Schell, and J. C. Harlan. 1974. “Monitoring the Vernal Advancement and Retrogradation (Green Wave Effect) of Natural Vegetation.” NASA/GSFC Type III Final Report. Greenbelt, MD. https://ntrs.nasa.gov/search.jsp?R=19740022555
   Google Scholar
• Schultz, P. A., and M. S. Halpert. 1993. “Global Correlation of Temperature, NDVI and Precipitation.” Advances in Space Research 13 (5): 277–280. doi:10.1016/0273-1177(93)90559-T.
   Web of Science ®Google Scholar
• Sellers, P. J., J. A. Berry, G. J. Collatz, C. B. Field, and F. G. Hall. 1992. “Canopy Reflectance, Photosynthesis, and Transpiration. III. A Reanalysis Using Improved Leaf Models and A New Canopy Integration Scheme.” Remote Sensing of Environment 42 (3): 187–216. doi:10.1016/0034-4257(92)90102-P.
   Web of Science ®Google Scholar
• Solano, R., K. Didan, A. Jacobson, and A. Huete. 2010. “MODIS VI (MOD13) C5 User’s Guide.” Terrestrial Biophysics and Remote Sensing Lab, The University of Arizona. http://www.ctahr.hawaii.edu/grem/modis-ug.pdf
   Google Scholar
• Spinoni, J., M. Lakatos, T. Szentimrey, Z. Bihari, S. Szalai, J. Vogt, and T. Antofie. 2015b. “Heat and Cold Waves Trends in the Carpathian Region from 1961 to 2010.” International Journal of Climatology 35 (14): 4197–4209. doi:10.1002/joc.4279.
   Web of Science ®Google Scholar
• Spinoni, J., S. Szalai, T. Szentimrey, M. Lakatos, Z. Bihari, A. Nagy, Á. Németh, et al. 2015a. “Climate of the Carpathian Region in the Period 1961-2010: Climatologies and Trends of 10 Variables: Climate Change in the Carpathian Region.” International Journal of Climatology 35 (7): 1322–1341. doi:10.1002/joc.4059.
   Web of Science ®Google Scholar
• Szalai, S., I. Auer, J. Hiebl, J. Milkovich, T. Radim, P. Stepanek, P. Zahradnicek, Z. Bihari, M. Lakatos, and T. Szentimrey. 2013. “Climate of the Greater Carpathian Region.” Final Technical Report.  http://www.carpatclim-eu.org
   Google Scholar
• Szalai, S., J. Mika, P. Németh, Z. Tóth, L. Bozó, J. Bartholy, and Z. Konkolyné Bihari. 2004. Atlas of Hungarian Climatology (Magyarország éghajlati atlasza). Edited by Ambrózy, P., Dunkel, Z., Hunkár, M., Práger, T., Mersich, I. Budapest: Hungarian Meteorological Service.
   Google Scholar
• Szalai, S., C. S. Szinell, and J. Zoboki. 2000. “Drought Monitoring in Hungary.” In Early Warning Systems for Drought Preparedness and Drought Management, Vol. 57. edited by D. A. Wilhite, M. V. K. Sivakumar, and D. A. Wood, 182–199. Lisbon, Portugal. 5–7 September 2000. Geneva: World Meteorological Organization.
   Google Scholar
• Szentimrey, T. 2011. “Manual of Homogenization Software MASHv3. 03.” Budapest: Hungarian Meteorological Service. http://www.dmcsee.org/uploads/file/331_2_mashmanual.pdf
   Google Scholar
• Szentimrey, T., and Z. Bihari. 2007. “Mathematical Background of Spatial Interpolation, Meteorological Interpolation Based on Surface Homogenized Data Bases (MISH).” In edited by S. Szalai, Z. Bihari, T. Szentimrey, and M. Lakatos, COST Action, 719:17–27. Budapest: COST Office.
   Google Scholar
• Szentimrey, T., M. Lakatos, Z. Bihari, T. Kovács, A. Németh, S. Szalai, I. Auer, J. Hiebl, J. Milkovic, and P. Zahradnicek. 2012b. “Final Report on the Creation of National Gridded Datasets, per Country. 9.” CARPATCLIM Project Deliverable D2. http://www.CARPATCLIM-eu.org/docs/deliverables/D2_9.pdf
   Google Scholar
• Szentimrey, T., M. Lakatos, Z. Bihari, T. Kovacs, S. Szalai, I. Auer, J. Hiebl, J. Milkovic, P. Stepanek, and P. Zahradnicek. 2012a. “Final Report on Quality Control and Data Homogenization Measures Applied per Country, Including QC Protocols and Measures to Determine the Achieved Increase in Data Quality. 12.” CARPATCLIM Project Deliverable D1. http://www.CARPATCLIM-eu.org/docs/deliverables/D1_12.pdf
   Google Scholar
• Tadesse, T., C. Champagne, B. D. Wardlow, T. A. Hadwen, J. F. Brown, G. B. Demisse, Y. A. Bayissa, and A. M. Davidson. 2017. “Building the Vegetation Drought Response Index for Canada (Vegdri-Canada) to Monitor Agricultural Drought: First Results.” GIScience & Remote Sensing 54 (2): 230–257. doi:10.1080/15481603.2017.1286728.
   Web of Science ®Google Scholar
• Tang, Y., M. Horikoshi, and W. Li. 2016. “Ggfortify: Unified Interface to Visualize Statistical Result of Popular R Packages.” The R Journal 8 (2): 474–485.
   Google Scholar
• Török, P., A. Helm, K. Kiehl, E. Buisson, and O. Valkó. 2018. “Beyond the Species Pool: Modification of Species Dispersal, Establishment, and Assembly by Habitat Restoration: Restoration Modify Dispersal and Establishment.” Restoration Ecology 26: S65–S72. doi:10.1111/rec.12825.
   Web of Science ®Google Scholar
• Tran, H. T., J. B. Campbell, T. D. Tran, and H. T. Tran. 2017. “Monitoring Drought Vulnerability Using Multispectral Indices Observed from Sequential Remote Sensing (Case Study: Tuy Phong, Binh Thuan, Vietnam).” GIScience & Remote Sensing 54 (2): 167–184. doi:10.1080/15481603.2017.1287838.
   Web of Science ®Google Scholar
• United Nations Educational, Scientific and Cultural Organization (UNESCO). 1979. Map of the World Distribution of Arid Regions. Map at Scale 1:25 000 000 with Explanatory Note. 7. MAB Technical Notes. Paris: UNES. http://unesdoc.unesco.org/images/0003/000326/032661eo.pdf
   Google Scholar
• Valkó, O., P. Török, B. Deák, and B. Tóthmérész. 2014. “Review: Prospects and Limitations of Prescribed Burning as a Management Tool in European Grasslands.” Basic and Applied Ecology 15 (1): 26–33. doi:10.1016/j.baae.2013.11.002.
   Web of Science ®Google Scholar
• Vári, A., and Z. Ferencz. 2006. “Flood Research from the Social Perspective: The Case of the Tisza River in Hungary.” In Frontiers in Flood Research, edited by I. Tchiguirinskaia, K. N. N. Thein, and P. Hubert, 155–172. Oxfordshire: IAHS/IHP-UNES.
   Google Scholar
• Verbesselt, J., R. Hyndman, G. Newnham, and D. Culvenor. 2010. “Detecting Trend and Seasonal Changes in Satellite Image Time Series.” Remote Sensing of Environment 114 (1): 106–115. doi:10.1016/j.rse.2009.08.014.
   Web of Science ®Google Scholar
• Vicente-Serrano, S. M., J.-I. Lopez-Moreno, S. Beguería, J. Lorenzo-Lacruz, A. Sanchez-Lorenzo, J. M. García-Ruiz, C. Azorin-Molina, et al. 2014. “Evidence of Increasing Drought Severity Caused by Temperature Rise in Southern Europe.” Environmental Research Letters 9 (4): 044001. doi:10.1088/1748-9326/9/4/044001.
   Web of Science ®Google Scholar
• Wallace, C. S. A., P. Thenkabail, J. R. Rodriguez, and M. K. Brown. 2017. “Fallow-Land Algorithm Based on Neighborhood and Temporal Anomalies (FANTA) to Map Planted versus Fallowed Croplands Using MODIS Data to Assist in Drought Studies Leading to Water and Food Security Assessments.” GIScience & Remote Sensing 54 (2): 258–282. doi:10.1080/15481603.2017.1290913.
   Web of Science ®Google Scholar
• Wang, J., P. M. Rich, and K. P. Price. 2003. “Temporal Responses of NDVI to Precipitation and Temperature in the Central Great Plains, USA.” International Journal of Remote Sensing 24 (11): 2345–2364. doi:10.1080/01431160210154812.
   Web of Science ®Google Scholar
• Wickham, H. 2009. Ggplot2: Elegant Graphics for Data Analysis. Use R! New York: Springer-Verlag. //www.springer.com/us/book/9780387981413
   Google Scholar
• Wilhite, D. A., M. J. Hayes, and M. D. Svoboda. 2000. “Drought Monitoring and Assessment: Status and Trends in the United States.” In Drought and Drought Mitigation in Europe, edited by J. V. Vogt and F. Somma, 149–160. Netherlands: Springer.
   Google Scholar