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CIE L*a*b* Color Space Based Vegetation Indices Derived from Unmanned Aerial Vehicle Captured Images for Chlorophyll and Nitrogen Content Estimation of Tea (Camellia sinensis L. Kuntze) Leaves

Wahono Wahono(1*), Didik Indradewa(2), Bambang Hendro Sunarminto(3), Eko Haryono(4), Djoko Prajitno(5)

(1) Faculty of Agriculture Universitas Gadjah Mada, Yogyakarta
(2) Faculty of Agriculture Universitas Gadjah Mada, Yogyakarta
(3) Faculty of Agriculture Universitas Gadjah Mada, Yogyakarta
(4) Faculty of Geography University of Gadjah Mada, Yogyakarta
(5) Faculty of Agriculture Universitas Gadjah Mada, Yogyakarta
(*) Corresponding Author


A lot of digital image techniques to assess crop agronomic character have been developed.  Most of those techniques are based on non-visible light equiped cameras, such as infared wavelengths. This research was aimed to examine the use of commercial digital camera with sensor range in visible light spectrum using CIE L*a*b* color space to estimate chlorophyll and nitrogen content of tea leaf.  Data was collected from an experiment of nitrogen dossage levels on 3 years after prunning tea crops.  The result shows that Lb* Difference Simple Index (LI), a*b* Difference Simple Index (AI), and  a* Vegetation Index (VIA) can be used to estimate tea leaf chlorophyll and nitrogen content.  The relationship between VIA and tea leaf nitrogen content was defined on linear equation y = 1.8382x2 - 0.3099x + 3.0658 with determinant coefficient R² = 0.71.


Nitrogen fertilizing; unmanned aerial vehicle; visible light spectrum

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Anderson, H.B., Nilsen, L., Tømmervik, H., Karlsen, S. R., Nagai, S., and Cooper, E. J., 2016. Using ordinary digital cameras in place of near-infrared sensors to derive vegetation indices for phenology studies of High Arctic vegetation. Remote Sensing, 8(10).

Bora, D.J., Gupta, A.K. and Khan, F.A., 2015. Comparing the Performance of L*A*B* and HSV Color Spaces with Respect to Color Image Segmentation. International Journal of Emerging Technology and Advanced Engineering, 5(2), pp.192–203. Available at:

Buschmann, C., Lenk, S. and Lichtenthaler, H.K., 2012. Reflectance Spectra and Images of Green Leaves with Different Tissue Structure and Chlorophyll Content. Israel Journal of Plant Sciences, 60(1), pp.49–64. Available at: [Accessed May 24, 2013].

Effendi, D.S., Syakir, M., Yusron, M., and Wiratno., 2011. Budidaya dan Pasca Panen Teh Jusniarti & A. Budiharto, eds., Bogor, Indonesia: Pusat Penelitian dan Pengembangan Perkebunan.

Graeff, S., Pfenning, J., Claupein, W., and Liebig, H., 2008. Evaluation of Image Analysis to Determine the N-Fertilizer Demand of Broccoli Plants (Brassica oleracea convar. botrytis var. italica). Advances in Optical Technologies, 2008, pp.1–8. Available at:

Hamid, F.S., Ahmad, T., Waheed, A., Ahmad, N., and Aslam, S., 2014. Effect of different levels of nitrogen on the chemical composition of tea (C. Sinensis L) grown at higher altitude. Journal of Materials and Environmental Science, 5(1), pp.72–80.

Knipling, E.B., 1970. Physical and Physiological Basis for the Reflectance of Visible and Near-Infrared Radiation from Vegetation. Remote Sensing of Environment, 1(3), pp.155–159. Available at: S0034425770800219.

Lamb, D.W., Steyn-Ross, M., Schaare, P., Hanna, M. M., Silvester, W., and Steyn-Ross, A., 2002. Estimating leaf nitrogen concentration in ryegrass ( Lolium spp.) pasture using the chlorophyll red-edge: Theoretical modelling and experimental observations. International Journal of Remote Sensing, 23(18), pp.3619–3648. Available at: 01431160110114529.

Li, C., Li, F., Liu, Y., Li, X., Liu, P., and Xiao, B., 2012. Study on the Feasibility of RGB Substitute CIR for Automatic Removal Vegetation Occlusion Based on Ground Close-Range Building Images. ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XXXIX-B3(September), pp.227–230.

Owuor, O.P., Kamau, D.M., and Jondiko, E.O., 2010. The influence of geographical area of production and nitrogenous fertiliser on yields and quality parameters of clonal tea. Journal of Food, Agriculture & Environment, 8(2), pp.682–690.

Pearse, G.D., Dash, J. P., Dungey, H. S., Watt, M. S., and Heaphy, M., 2017. Assessing very high resolution UAV imagery for monitoring forest health during a simulated disease outbreak. ISPRS Journal of Photogrammetry and Remote Sensing, 131, pp.1–14. Available at:

Sarwar, S., Ahmad, F. and Hamid, F.S., 2011. Effect of Nitrogenous Fertilizer on The Growth And Yield of Tea (Camellia sinensis L.) Pruned In Curved Vs Flat Shape. J. Agric. Res., 49(6), pp.477–482.

Woolley, J.T., 1971. Reflectance and Transmittance of Light by Leaves. Plant physiology, 47(5), pp.656–62. Available at: articlerender.fcgi?artid=396745&tool=pmcentrez&rendertype=abstract.

Xue, J. and Su, B., 2017. Significant remote sensing vegetation indices: a review of developments and applications. Journal of sensors, Vol.2017, p.17p.

Zhang, Y., Heipke, C., Butenuth, M., and Hu, X., 2006. Automatic extraction of wind erosion obstacles by integration of GIS data, DSM and stereo images. International Journal of Remote Sensing, 27(8), pp.1677–1690.


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