Remote sensing analysis to map inter-regional spatio-temporal variations of the vegetation in Iceland during 2001–2018


  • Haraldur Olafsson University of Iceland, Department of Physics, Reykjavik, Iceland; University of Iceland, Institute for Atmospheric Sciences-Weather and Climate, Reykjavik, Iceland; Icelandic Meteorological Office (IMO), Reykjavik, Iceland
  • Iman Rousta University of Iceland, Institute for Atmospheric Sciences-Weather and Climate, Reykjavik, Iceland; Icelandic Meteorological Office (IMO), Reykjavik, Iceland; Yazd University, Department of Geography, Yazd, Iran



Iceland, vegetation dynamics, MODIS, NDVI, anomaly analysis


Changes in the vegetation of the Arctic and sub-Arctic regions have been used as indicators of the impact and seriousness of climate change. In this study, 342 MODIS NDVI images were used to monitor and assess the variability and long-term changes in the vegetation in Iceland in the period 2001–2018. An insignificant trend in the changes of the vegetation coverage (R = 0.16, p-value = 0.05) was obtained, however, it also resulted that the area with the low values of the NDVI (< 0.6) is decreasing, whereas the area with higher values of the NDVI (> 0.6, mostly forests) is increasing. The NDVI index during the study period rose for the area of about 3260 km2, while it declined for 1635 km2. The results of this study can be used for organizing the strategies preventing climate change and global warming.


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Alcaraz‐Segura, D., Chuvieco, E., Epstein, H. E., Kasischke, E. S., Trishchenko, A. 2010: Debating the greening vs. browning of the North American boreal forest: Differences between satellite datasets. Global Change Biology 16-2. DOI:

Anderson, R., Bayer, P. E., Edwards, D. 2020: Climate change and the need for agricultural adaptation. Current Opinion in Plant Biology 56. DOI:

Aradóttir, Á. L., Petursdottir, T., Halldorsson, G., Svavarsdottir, K., Arnalds, O. 2013: Drivers of ecological restoration: lessons from a century of restoration in Iceland. Ecology and Society 18-4. DOI:

Arnalds, Ó. 2008: The soils of Iceland. World Soils Book Series. Dortrecht. DOI:

Arnalds, Ó., Ellin Fjola, T., Sigmar, M., Asgeir, J., Arnor, A. 2001: Soil erosion in Iceland. Reykjavík.

Arnalds, O., Hallmark, C. T., Wilding, L. P. 1995: Andisols from four different regions of Iceland. Soil Science Society of America Journal 59-1. DOI:

Arnalds, O., Ólafsson, H., Dagsson-Waldhauserova, P. 2014: Quantification of iron-rich volcanogenic dust emissions and deposition over the ocean from Icelandic dust sources. Biogeosciences 11. DOI:

Atasoy, M. 2018: Monitoring the urban green spaces and landscape fragmentation using remote sensing: A case study in Osmaniye, Turkey. Environmental Monitoring and Assessment 190. DOI:

Bates, R., Erlendsson, E., Eddudóttir, S. D., Möckel, S. C., Tinganelli, L., Gísladóttir, G. 2021: Landnám, land use and landscape change at Kagaðarhóll in Northwest Iceland. Environmental Archaeology 27-2. DOI:

Bhatt, U. S., Walker, D. A., Raynolds, M. K., Bieniek, P. A., Epstein, H. E., Comiso, J. C., Pinzon, J. E., et al. 2013: Recent declines in warming and vegetation greening trends over pan-Arctic tundra. Remote Sensing 5-9. DOI:

Bjerke, J. W., Karlsen, S. R., Høgda, K. A., Malnes, E., Jepsen, J. U., Lovibond, S., Vikhamar-Schuler, D., et al. 2014: Record-low primary productivity and high plant damage in the Nordic Arctic Region in 2012 caused by multiple weather events and pest outbreaks. Environmental Research Letters 9-8. DOI:

Bokhorst, S. F., Bjerke, J. W., Tømmervik, H., Callaghan, T. V., Phoenix, G. K. 2009: Winter warming events damage sub‐Arctic vegetation: consistent evidence from an experimental manipulation and a natural event. Journal of Ecology 97-6. DOI:

Chao, L., Zhang, K., Wang, J., Feng, J., Zhang, M. 2021: A comprehensive evaluation of five evapotranspiration datasets based on ground and GRACE satellite observations: Implications for improvement of evapotranspiration retrieval algorithm. Remote Sensing 13-12. DOI:

Chen, D., Brutsaert, W. 1998: Satellite-sensed distribution and spatial patterns of vegetation parameters over a tallgrass prairie. Journal of the Atmospheric Sciences 55-7. DOI:<1225:SSDASP>2.0.CO;2

Cui, L., Shi, J., Yang, Y., Fan, W. 2009: Ten-day response of vegetation NDVI to the variations of temperature and precipitation in eastern China. Acta Geographica Sinica 64-7. DOI:

Dabiri, Z., Hölbling, D., Abad, L., Prasicek, G., Argentin, A.-L., Tsai, T.-T. 2019: An Object-Based Approach for Monitoring the Evolution of Landslide-Dammed Lakes and Detecting Triggering Landslides in Taiwan. ISPRS-International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences 4238. DOI:

Dabrowska-Zielinska, K., Kogan, F., Ciolkosz, A., Gruszczynska, M., Kowalik, W. 2002: Modelling of crop growth conditions and crop yield in Poland using AVHRR-based indices. International Journal of Remote Sensing 23-6. DOI:

Didan, K. 2015a: MOD13Q1 MODIS/Terra vegetation indices 16-day L3 global 250 m SIN grid V006. NASA EOSDIS Land Processes DAAC. DOI:

Didan, K., Munoz, A. B., Solano, R., Huete, A. 2015: MODIS vegetation index user’s guide (MOD13 series). Internet: (6. 5. 2022).

Dugmore, A. J., Gísladóttir, G., Simpson, I. A., Newton, A. 2009: Conceptual models of 1200 years of Icelandic soil erosion reconstructed using tephrochronology. Journal of the North Atlantic 2-1. DOI:

Dutta, D., Kundu, A., Patel, N. R., Saha, S. K., Siddiqui, A. R. 2015: Assessment of agricultural drought in Rajasthan (India) using remote sensing derived Vegetation Condition Index (VCI) and Standardized Precipitation Index (SPI). The Egyptian Journal of Remote Sensing and Space Science 18-1. DOI:

Dye, D. G., Tucker, C. J. 2003: Seasonality and trends of snow‐cover, vegetation index, and temperature in northern Eurasia. Geophysical Research Letters 30-7. DOI:

Einarsson, M. A., 1984: Climate of iceland. Climates of the Oceans. World Survey of Climatology. Amsterdam.

Elmendorf, S. C., Henry, G. H., Hollister, R. D., Björk, R. G., Boulanger-Lapointe, N., Cooper, E. J., Cornelissen, J. H., et al. 2012: Plot-scale evidence of tundra vegetation change and links to recent summer warming. Nature Climate Change 2. DOI:

Epstein, H. E., Raynolds, M. K., Walker, D. A., Bhatt, U. S., Tucker, C. J., Pinzon, J. E. 2012: Dynamics of aboveground phytomass of the circumpolar Arctic tundra during the past three decades. Environmental Research Letters 7-1. DOI:

Foley, J. A., Levis, S., Costa, M. H., Cramer, W., Pollard, D. 2000: Incorporating dynamic vegetation cover within global climate models. Ecological Applications 10-6. DOI:

Fries, E., 2017: Reforestation in the far north. Umeå.

Gandhi, G. M., Parthiban, S., Thummalu, N., Christy, A. 2015: NDVI: Vegetation change detection using remote sensing and GIS–a case study of Vellore District. Procedia Computer Science 57. DOI:

Gao, B.-C., Goetzt, A. F. H. 1995: Retrieval of equivalent water thickness and information related to biochemical components of vegetation canopies from AVIRIS data. Remote Sensing of Environment 52-3. DOI:

Geerken, R., Zaitchik, B., Evans, J. 2005: Classifying rangeland vegetation type and coverage from NDVI time series using Fourier Filtered Cycle Similarity. International Journal of Remote Sensing 26-24. DOI:

Ghafarian Malamiri, H. R., Zare, H., Rousta, I., Olafsson, H., Izquierdo Verdiguier, E., Zhang, H., Mushore, T. D. 2020: Comparison of Harmonic Analysis of Time Series (HANTS) and Multi-Singular Spectrum Analysis (M-SSA) in reconstruction of long-gap missing data in NDVI time series. Remote Sensing 12-17. DOI:

Gitelson, A. A., Viña, A., Arkebauer, T. J., Rundquist, D. C., Keydan, G., Leavitt, B. 2003: Remote estimation of leaf area index and green leaf biomass in maize canopies. Geophysical Research Letters 30. DOI:

Huang, M., Piao, S., Janssens, I. A., Zhu, Z., Wang, T., Wu, D., Ciais, P., et al. 2017: Velocity of change in vegetation productivity over northern high latitudes. Nature Ecology and Evolution 1. DOI:

James, P., Chester, D., Duncan, A. 2000: Volcanic soils: Their nature and significance for archaeology. Geological Society, London, Special Publications, 171. DOI:

Ji, L., Peters, A. J. 2003: Assessing vegetation response to drought in the northern Great Plains using vegetation and drought indices. Remote Sensing of Environment 87-1. DOI:

Jóhannesdóttir, L., Alves, J. A., Gill, J. A., Gunnarsson, T. G. 2017: Reconciling biodiversity conservation and agricultural expansion in the sub-arctic environment of Iceland. Ecology and Society 22-1. DOI:

Jóhannesson, T. 2010: Agriculture in Iceland: Conditions and characteristics. Internet: (11. 5. 2022).

Jovanović, M. M., Milanović, M. M., Zorn, M. 2018: The use of NDVI and CORINE Land Cover databases for forest management in Serbia. Acta geographica Slovenica 58-1. DOI:

King, M., Altdorff, D., Li, P., Galagedara, L., Holden, J., Unc, A. 2018: Northward shift of the agricultural climate zone under 21st-century global climate change. Scientific Reports 8. DOI:

Kogan, F. 1991: Observations of the 1990 US drought from the NOAA-11 polar-orbiting satellite. Drought Network News 3.

Kogan, F. N. 1995: Droughts of the late 1980s in the United States as derived from NOAA polar-orbiting satellite data. Bulletin of the American Meteorological Society 76-5. DOI:<0655:DOTLIT>2.0.CO;2

Lemenkova, P. 2020a: Hyperspectral vegetation indices calculated by Qgis using Landsat Tm image: A case study of Northern Iceland. Advanced Research in Life Sciences 4. DOI:

Lemenkova, P. 2020b: SAGA GIS for information extraction on presence and conditions of vegetation of northern coast of Iceland based on the Landsat TM. Acta Biologica Marisiensis 3-2. DOI:

Li, J., Charles, L. S., Yang, Z., Du, G., Fu, S. 2022: Differential mechanisms drive species loss under artificial shade and fertilization in the alpine meadow of the Tibetan Plateau. Frontiers in Plant Science 13. DOI:

Li, W., Shi, Y., Zhu, D., Wang, W., Liu, H., Li, J., Shi, N., et al. 2021: Fine root biomass and morphology in a temperate forest are influenced more by the nitrogen treatment approach than the rate. Ecological Indicators 130. DOI:

Liu, Y., Li, Y., Li, S., Motesharrei, S. 2015: Spatial and temporal patterns of global NDVI trends: Correlations with climate and human factors. Remote Sensing 7-10. DOI:

Loveland, T. R., Zhu, Z., Ohlen, D. O., Brown, J. F., Reed, B. C., Yang, L. 1999: An analysis of the IGBP global land-cover characterization process. Photogrammetric Engineering and Remote Sensing 65-9.

MacDicken, K. G. 2015: Global forest resources assessment 2015: what, why and how? Forest Ecology and Management 352. DOI:

Mansourmoghaddam, M., Ghafarian Malamiri, H. R., Rousta, I., Olafsson, H., Zhang, H. 2022: Assessment of Palm Jumeirah Island’s construction effects on the surrounding water quality and surface temperatures during 2001–2020. Water 14-4. DOI:

Mansourmoghaddam, M., Rousta, I., Zamani, M., Mokhtari, M. H., Karimi Firozjaei, M., Alavipanah, S. K. 2021: Study and prediction of land surface temperature changes of Yazd city: Assessing the proximity and changes of land cover. Journal of RS and GIS for Natural Resources 12-4.

Martínez, B., Gilabert, M. A. 2009: Vegetation dynamics from NDVI time series analysis using the wavelet transform. Remote sensing of environment 113-9. DOI:

Masson-Delmotte, V., Zhai, P., Pörtner, H.-O., Roberts, D., Skea, J., Shukla, P. R., Pirani, A., et al. (eds.) 2018: Global Warming of 1.5 °C. An IPCC Special Report on the impacts of global warming of 1.5°C above pre-industrial levels and related global greenhouse gas emission pathways, in the context of strengthening the global response to the threat of climate change, sustainable development, and efforts to eradicate poverty. Internet: (6. 5. 2022).

McVicar, T. R., Bierwirth, P. N. 2001: Rapidly assessing the 1997 drought in Papua New Guinea using composite AVHRR imagery. International Journal of Remote Sensing 22-11. DOI:

Merrington, A. T., 2019: A time series analysis of vegetation succession on lava flow fields at Hekla Volcano: Assessing the utility of Landsat data. M.Sc. thesis, University of Iceland. Reykjavik.

Metternicht, G., Zinck, J. A., Blanco, P. D., del Valle, H. F. 2010: Remote sensing of land degradation: Experiences from Latin America and the Caribbean. Journal of Environmental Quality 39-1. DOI:

Miao, R., Liu, Y., Wu, L., Wang, D., Liu, Y., Miao, Y., Yang, Z., et al. 2022: Effects of long-term grazing exclusion on plant and soil properties vary with position in dune systems in the Horqin Sandy Land. Catena 209-2. DOI:

Miao, R., Qiu, X., Guo, M., Musa, A., Jiang, D. 2018: Accuracy of space-for-time substitution for vegetation state prediction following shrub restoration. Journal of Plant Ecology 11-2. DOI:

Moniruzzaman, M., Thakur, P. K., Kumar, P., Ashraful Alam, M., Garg, V., Rousta, I., Olafsson, H. 2021: Decadal urban land use/land cover changes and its impact on surface runoff potential for the Dhaka city and surroundings using remote sensing. Remote Sensing 13-1. DOI:

Montandon, L. M., Small, E. E. 2008: The impact of soil reflectance on the quantification of the green vegetation fraction from NDVI. Remote Sensing of Environment 112-4. DOI:

Moulin, S., Kergoat, L., Viovy, N., Dedieu, G. 1997: Global-scale assessment of vegetation phenology using NOAA/AVHRR satellite measurements. Journal of Climate 10-6. DOI:<1154:GSAOVP>2.0.CO;2

Myneni, R. B., Keeling, C. D., Tucker, C. J., Asrar, G., Nemani, R. R. 1997: Increased plant growth in the northern high latitudes from 1981 to 1991. Nature 386. DOI:

Nyirenda, H. 2020: Soil carbon status after vegetation restoration in South West Iceland. Heliyon 6-10. DOI:

Olafsson, H., Rousta, I. 2021: Influence of atmospheric patterns and North Atlantic Oscillation (NAO) on vegetation dynamics in Iceland using Remote Sensing. European Journal of Remote Sensing 54-1. DOI:

Ollinger, S. V. 2011: Sources of variability in canopy reflectance and the convergent properties of plants. New Phytologist 189-2. DOI:

Óskarsdóttir, G. 2016: Gróðurvöktun í Kringilsárrana: samanburður á samsetningu og þekju gróðurs árin 2006 og 2015. Internet: (6. 5. 2022).

Óskarsson, H., Arnalds, Ó., Gudmundsson, J., Gudbergsson, G. 2004: Organic carbon in Icelandic Andosols: Geographical variation and impact of erosion. Catena 56-1,2,3. DOI:

Pettorelli, N., Vik, J. O., Mysterud, A., Gaillard, J.-M., Tucker, C. J., Stenseth, N. C. 2005: Using the satellite-derived NDVI to assess ecological responses to environmental change. Trends in ecology and evolution 20-9. DOI:

Polyakov, I. V., Bekryaev, R. V., Alekseev, G. V., Bhatt, U. S., Colony, R. L., Johnson, M. A., Maskshtas, A. P., et al. 2003: Variability and trends of air temperature and pressure in the maritime Arctic, 1875–2000. Journal of Climate 16-12. DOI:<2067:VATOAT>2.0.CO;2

Raynolds, M., Magnússon, B., Metúsalemsson, S., Magnússon, S. H. 2015: Warming, sheep and volcanoes: Land cover changes in Iceland evident in satellite NDVI trends. Remote Sensing 7-8. DOI:

Rouse, J. W., Haas, R. W., Schell, J. A., Deering, D. W., Harlan, J. C. 1974: Monitoring the vernal advancement and retrogradation (green wawe effect) of natural vegetation. NASA/GSFCT Type III Final report.

Rousta, I., Javadizadeh, F., Dargahian, F., Olafsson, H., Shiri-Karimvandi, A., Vahedinejad, S. H., Doostkamian, M., et al. 2018: Investigation of vorticity during prevalent winter precipitation in Iran. Advances in Meteorology 2018. DOI:

Rousta, I., Karampour, M., Doostkamian, M., Olafsson, H., Zhang, H., Mushore, T. D., et al. 2020a: Synoptic-dynamic analysis of extreme precipitation in Karoun River Basin, Iran. Arabian Journal of Geosciences 13. DOI:

Rousta, I., Olafsson, H., Moniruzzaman, M., Ardö, J., Zhang, H., Mushore, T. D., Shahin, S., et al. 2020b: The 2000–2017 drought risk assessment of the western and southwestern basins in Iran. Modeling Earth Systems and Environment 6. DOI:

Rousta, I., Olafsson, H., Moniruzzaman, M., Zhang, H., Liou, Y.-A., Mushore, T. D., Gupta, A. 2020c: Impacts of drought on vegetation assessed by vegetation indices and meteorological factors in Afghanistan. Remote Sensing 12-15. DOI:

Rousta, I., Olafsson, H., Nasserzadeh, M. H., Zhang, H., Krzyszczak, J., Baranowski, P. 2021: Dynamics of daytime land surface temperature (LST) variabilities in the Middle East countries during 2001–2018. Pure and Applied Geophysics 178. DOI:

Running, S. W., Loveland, T. R., Pierce, L. L., Nemani, R. R., Hunt Jr, E. R. 1995: A remote sensing based vegetation classification logic for global land cover analysis. Remote Sensing of Environment 51-1. DOI:

Shen, X., Liu, B., Jiang, M., Lu, X. 2020: Marshland loss warms local land surface temperature in China. Geophysical research letters 47-6. DOI:

Sigurmundsson, F. S., Gísladóttir, G., Óskarsson, H. 2014: Decline of birch woodland cover in Þjórsárdalur Iceland from 1587 to 1938. Human ecology 42. DOI:

Slayback, D. A., Pinzon, J. E., Los, S. O., Tucker, C. J. 2003: Northern hemisphere photosynthetic trends 1982–99. Global Change Biology 9-1. DOI:

Symeonakis, E., Drake, N. 2004: Monitoring desertification and land degradation over sub-Saharan Africa. International Journal of Remote Sensing 25-3. DOI:

Tarpley, J. D., Schneider, S. R., Money, R. L. 1984: Global vegetation indices from the NOAA-7 meteorological satellite. Journal of Climate and Applied Meteorology 23-3.

Thenkabail, P. S., Gamage, M. S. D. N., Smakhtin, V. U. 2004: The use of remote sensing data for drought assessment and monitoring in Southwest Asia. Colombo.

Thorarinsson, S. 1967: Some problems of volcanism in Iceland. Geologische Rundschau 57. DOI:

Thorsteinsson, I., Olafsson, G., Van Dyne, G. M. 1971: Range resources of Iceland. Journal of Range Management 24-2.

Tucker, C. J. 1979: Red and photographic infrared linear combinations for monitoring vegetation. Remote Sensing of Environment 8-2. DOI:

Wan, Z., Wang, P., Li, X. 2004: Using MODIS land surface temperature and normalized difference vegetation index products for monitoring drought in the southern Great Plains, USA. International Journal of Remote Sensing 25-1. DOI:

Wang, P., Wang, L., Leung, H., Zhang, G. 2020: Super-resolution mapping based on spatial–spectral correlation for spectral imagery. IEEE Transactions on Geoscience and Remote Sensing 59-3. DOI:

Yang, L., Wylie, B. K., Tieszen, L. L., Reed, B. C. 1998: An analysis of relationships among climate forcing and time-integrated NDVI of grasslands over the US northern and central Great Plains. Remote Sensing of Environment 65-1. DOI:

Zandbergen, P. 2008: Applications of shuttle radar topography mission elevation data. Geography Compass 2-5. DOI:

Zhang, K., Ali, A., Antonarakis, A., Moghaddam, M., Saatchi, S., Tabatabaeenejad, A., Chen, R., et al. 2019a: The sensitivity of North American terrestrial carbon fluxes to spatial and temporal variation in soil moisture: An analysis using radar‐derived estimates of root‐zone soil moisture. Journal of Geophysical Research: Biogeosciences 124-11. DOI:

Zhang, K., Chao, L.-j., Wang, Q.-q., Huang, Y.-c., Liu, R.-h., Hong, Y., Tu, Y., et al. 2019b: Using multi-satellite microwave remote sensing observations for retrieval of daily surface soil moisture across China. Water Science and Engineering 12-2. DOI:

Zhao, T., Shi, J., Entekhabi, D., Jackson, T. J., Hu, L., Peng, Z., Yao, P., et al. 2021a: Retrievals of soil moisture and vegetation optical depth using a multi-channel collaborative algorithm. Remote Sensing of Environment 257. DOI:

Zhao, T., Shi, J., Lv, L., Xu, H., Chen, D., Cui, Q., Jackson, T. J., et al. 2020: Soil moisture experiment in the Luan River supporting new satellite mission opportunities. Remote Sensing of Environment 240. DOI:

Zhao, X., Xia, H., Pan, L., Song, H., Niu, W., Wang, R., Li, R., et al. 2021b: Drought monitoring over Yellow River basin from 2003–2019 using reconstructed MODIS land surface temperature in Google Earth Engine. Remote Sensing 13-18. DOI:

Zuo, Y., Jiang, S., Wu, S., Xu, W., Zhang, J., Feng, R., Yang, M., et al. 2020: Terrestrial heat flow and lithospheric thermal structure in the Chagan Depression of the Yingen‐Ejinaqi Basin, north central China. Basin Research 32-6. DOI:




How to Cite

Olafsson H, Rousta I. Remote sensing analysis to map inter-regional spatio-temporal variations of the vegetation in Iceland during 2001–2018. AGS [Internet]. 2022 Jun. 21 [cited 2022 Jul. 6];62(1):105-24. Available from: