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Quantification Of Leaf Emissivities Of Forest Species: Effects On Modelled Energy And Matter Fluxes In Forest Ecosystems

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Climate  change  has distinct regional and local differences in its impacts on the land sur face. One of the important parameters determining the climate change signal is the emissivity (ε) of the sur face. In forest-climate interactions, the leaf sur face emissivity plays a decisive   role.  The accurate  determination  of leaf emissivities  is crucial for  the appropriate  interpretation  of measured  energy and matter fluxes between the forest and the atmosphere. In this study, we quantified the emissivity of the five broadleaf tree species Acer pseudoplatanus, Fagus sylvatica, Fraxinus excelsior, Populus simonii and Populus candicans. Measurements of leaf sur face temperatures were conducted under laboratory conditions in a controlled-climate chamber within the temperature range of +8 °C and +32°C. Based on these measurements, broadband  leaf emissivities ε (ε for the spectral range of 8-14 µm) were calculated. Average ε8-14 µm was 0.958±0.002 for all species with very little variation among species. In a second step, the soil-vegetation-atmosphere  transfer model ‘MixFor-SVAT ’ was applied to examine the effects of ε changes on radiative, sensible and latent energy  fluxes of the Hainich  forest in Central Germany.  Model experiments  were driven by meteorological data measured at the Hainich  site. The simulations  were  forced with the calculated ε value as well as with minimum and maximum values obtained from the literature.  Significant  effects  of ε changes were detected.  The strongest  effect was identified for the sensible heat flux with a sensitivity of 20.7 % per 1 % ε change. Thus, the variability of ε should be considered in climate change studies.

About the Authors

Nina Tiralla
University of Goettingen



Oleg Panferov
University of Applied Sciences Bingen

Dept. of Life Sciences and Engineering.


Heinrich Kreilein
University of Goettingen



Alexander Olchev
Moscow State University; Russian Academy of Sciences
Russian Federation

Faculty of Geography, MSU; Severtsov Institute of Ecology and Evolution, RAS.


Ashehad A. Ali
University of Goettingen



Alexander Knohl
University of Goettingen




1. Alkama R. and Cescatti A. (2016). Biophysical climate impacts of recent changes in global forest cover. Science, 351, pp. 600-604.

2. Anthoni P.M., Knohl A., Rebmann C., Freibauer A., Mund M., ziegler W., Kolle O. and Schulze E.D. (2004). Forest and agricultural land-use-dependent CO2 exchange in Thuringia, Germany. Global Change Biology, 10, pp. 2005-2019. doi: 10.1111/j.1365-2486.2004.00863.x.

3. Bonan G.B. (2008). Forests and Climate Change: Forcings, Feedbacks, and the Climate Benefits of Forests. Science, 320 (5882), pp. 1444-1449. doi: 10.1126/science.1155121.

4. Chen C. (2015). Determining the leaf emissivity of three crops by infrared thermometry. Sensors, 15(5), pp. 11387-11401. doi:10.3390/s150511387.

5. Da Luz B.R. and Crowley J.K. (2007). Spectral reflectance and emissivity features of broad leaf plants: Prospects for remote sensing in the thermal infrared (8.0 –14.0 μm). Remote Sensing of Environment, 109(4), pp. 393-405.

6. Falge E., Reth S., Brüggemann N, Butterbach-Bahl K., Goldberg V., Oltchev A., Schaaf S., Spindler G., Stiller B., Queck R., Köstner B. and Bernhofer C. (2005). Comparison of surface energy exchange models with eddy flux data in forest and grassland ecosystems of Germany. Ecological Modelling, 188, pp. 174-216.

7. Fuchs M. and Tanner C.B. (1966). Infrared thermometry of vegetation. Agronomy Journal, 58, pp. 597-601.

8. Horton K.A., Johnson J.R. and Lucey P.G. (1998). Infrared measurements of pristine and disturbed soils 2. Environmental effects and field data reduction. Remote Sensing of Environment, 64(1), pp. 47-52.

9. Idso S.B., Jackson R.D., Ehrler W.L. and Mitchell S.T. (1969). A Method for Determination of Infrared Emittance of Leaves. Ecology, 50, pp. 899-902. doi:10.2307/1933705.

10. Jin, M. and Liang S. (2006). An improved land surface emissivity parameter for land surface models using global remote sensing observations. Journal of Climate, 19(12), pp. 2867-2881.

11. Knohl A., Schulze E.D., Kolle O. and Buchmann N. (2003). Large carbon uptake by an unmanaged 250-year-old deciduous forest in Central Germany. Agricultural and Forest Meteorology, 118, pp. 151-167.

12. Lopez A., Molina-Aiz F.D., Valera D.L. and Peña A. (2012). Determining the emissivity of the leaves of nine horticultural crops by means of infrared thermography. Scientia Horticulturae, 137, pp. 49-58.

13. Oltchev A., Cermak J., Nadezhdina N., Tatarinov F., Tishenko A., Ibrom A. and Gravenhorst G. (2002). Transpiration of a mixed forest stand: field measurements and simulation using SVAT models. Boreal Environmental Research, 7(4), pp. 389-397.

14. Olchev A., Ibrom A., Ross T., Falk U., Rakkibu G., Radler K., Grote S., Kreilein H. and Gravenhorst G. (2008). A modelling approach for simulation of water and carbon dioxide exchange between multi species tropical rain forest and the atmosphere. Ecological Modelling, 212, 122-130.

15. Olchev A., Ibrom A., Panferov O., Gushchina D., Kreilein H., Popov V., Propastin P., June T., Rauf A., Gravenhorst G., Knohl A. (2015). Response of CO2 and H2O fluxes in a mountainous tropical rainforest in equatorial Indonesia to El Niño events. Biogeosciences, 12, pp. 6655-6667.

16. Pielke R.A., Pitman A., Niyogi D., Mahmood R., McAlpine C., Hossain F., Goldewijk K.K., Nair U., Betts R., Fall S., Reichstein M., Kabat P., Noblet N. (2011). Land use/land cover changes and climate: modeling analysis and observational evidence. WIREs Climate Change, 2, pp. 828-850. doi:10.1002/wcc.144.

17. Rahkonen J. and Jokela H. (2003). Infrared radiometry for measuring plant leaf temperature during thermal weed control treatment. Biosystems Engineering, 86, pp. 257-266.

18. Sabajo C.R., le Maire G., June T., Meijide A., Roupsard O. and Knohl A. (2017). Expansion of oil palm and other cash crops causes an increase of the land surface temperature in the Jambi province in Indonesia. Biogeosciences, 14, pp. 4619-4635.

19. Snyder P.K., Delire C. and Foley J. (2004). Evaluating the influence of different vegetation biomes on the global climate. Climate Dynamics, 23, pp. 279-302.

20. Valor E. and Caselles V. (1996). Mapping Land Surface Emissivity from NDVI: Application to European, African, and South American Areas. Remote Sensing of Environment, 57, pp. 167-184.

21. Wolfe W.L. and zissis G.J. (1978). The Infrared Handbook. Washington DC, Environmental Research Institute of Michigan.

22. Zhou L., Dickinson R., Dirmeyer P., Chen, H., Dai D. and Tian Y. (2008). Asymmetric response of maximum and minimum temperatures to soil emissivity change over the Northern African Sahel in a GCM. Geophysical Research Letters, 35, L05402. doi:10.1029/2007GL032953.

For citation:

Tiralla N., Panferov O., Kreilein H., Olchev A., Ali A.A., Knohl A. Quantification Of Leaf Emissivities Of Forest Species: Effects On Modelled Energy And Matter Fluxes In Forest Ecosystems. GEOGRAPHY, ENVIRONMENT, SUSTAINABILITY. 2019;12(2):245-258.

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