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Technical Note

Spatial and Seasonal Patterns in Vegetation Growth-Limiting Factors over Europe

The Remote Sensing Laboratory, the Jacob Blaustein Institutes for Desert Research, Ben-Gurion University, Sede Boker Campus, Sede Boker 84990, Israel
Department of Soil, Water and Environmental Sciences, Agricultural Research Organization, Gilat Research Center, Midreshet Ben-Gurion 85280, Israel
Department of Sensing, Information, and Mechanization Engineering, Institute of Agriculture Engineering, Agriculture Research Organization, Volcani Center, Ben Shemen 7505101, Israel
Remote Sensing Lab, Institute of Applied and Computational Mathematics, FORTH, Vassilika Vouton, 70013 Heraklion, Greece
Institute of Geosciences and Earth Resources, National Research Council, 56124 Pisa, Italy
Author to whom correspondence should be addressed.
Remote Sens. 2019, 11(20), 2406;
Received: 19 August 2019 / Revised: 8 October 2019 / Accepted: 14 October 2019 / Published: 17 October 2019
(This article belongs to the Special Issue Remote Sensing in Ecosystem Modelling)
Water and energy are recognized as the most influential climatic vegetation growth-limiting factors. These factors are usually measured from ground meteorological stations. However, since both vary in space, time, and scale, they can be assessed by satellite-derived biophysical indicators. Energy, represented by land surface temperature (LST), is assumed to resemble air temperature; and water availability, related to precipitation, is represented by the normalized difference vegetation index (NDVI). It is hypothesized that positive correlations between LST and NDVI indicate energy-limited conditions, while negative correlations indicate water-limited conditions. The current project aimed to quantify the spatial and seasonal (spring and summer) distributions of LST–NDVI relations over Europe, using long-term (2000–2017) MODIS images. Overlaying the LST–NDVI relations on the European biome map revealed that relations between LST and NDVI were highly diverse among the various biomes and throughout the entire study period (March–August). During the spring season (March–May), 80% of the European domain, across all biomes, showed the dominance of significant positive relations. However, during the summer season (June–August), most of the biomes—except the northern ones—turned to negative correlation. This study demonstrates that the drought/vegetation/stress spectral indices, based on the prevalent hypothesis of an inverse LST–NDVI correlation, are spatially and temporally dependent. These negative correlations are not valid in regions where energy is the limiting factor (e.g., in the drier regions in the southern and eastern extents of the domain) or during specific periods of the year (e.g., the spring season). Consequently, it is essential to re-examine this assumption and restrict applications of such an approach only to areas and periods in which negative correlations are observed. Predicted climate change will lead to an increase in temperature in the coming decades (i.e., increased LST), as well as a complex pattern of precipitation changes (i.e., changes of NDVI). Thus shifts in plant species locations are expected to cause a redistribution of biomes. View Full-Text
Keywords: vegetation growth-limiting factors; NDVI; LST; MODIS; Europe vegetation growth-limiting factors; NDVI; LST; MODIS; Europe
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MDPI and ACS Style

Karnieli, A.; Ohana-Levi, N.; Silver, M.; Paz-Kagan, T.; Panov, N.; Varghese, D.; Chrysoulakis, N.; Provenzale, A. Spatial and Seasonal Patterns in Vegetation Growth-Limiting Factors over Europe. Remote Sens. 2019, 11, 2406.

AMA Style

Karnieli A, Ohana-Levi N, Silver M, Paz-Kagan T, Panov N, Varghese D, Chrysoulakis N, Provenzale A. Spatial and Seasonal Patterns in Vegetation Growth-Limiting Factors over Europe. Remote Sensing. 2019; 11(20):2406.

Chicago/Turabian Style

Karnieli, Arnon, Noa Ohana-Levi, Micha Silver, Tarin Paz-Kagan, Natalya Panov, Dani Varghese, Nektarios Chrysoulakis, and Antonello Provenzale. 2019. "Spatial and Seasonal Patterns in Vegetation Growth-Limiting Factors over Europe" Remote Sensing 11, no. 20: 2406.

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