ACCOUNTING THE EFFECT OF ATMOSPHERIC AEROSOL WHEN VALIDATING THE RESULTS OF REMOTE SENSING OF PLANT STRESS SEVERITY
https://doi.org/10.25587/SVFU.2021.21.1.003
Abstract
An increased level of illness stress on plants leads to a changed color of their leaves and therefore, there appears some uncertainty in the result of remote diagnostics of vegetation condition. Because of that, the spectral indices utilized in practice were composed mainly at the basis of spectral narrow band measurements held in the red edge zone. The article reviews the issue of accounting the effect of atmospheric aerosol when validating the results of remotely sensing of plant stress severity. The aim of the paper was to modify the known rule of validation by increasing noise immunity of this operation. The effect of aerosol contamination of on earth atmosphere on results of validation procedures is considered. The validation of results of remote sensing of plant stress severity is usually done by carrying out ground checking up using portable spectroradiometers. Measurements of reflection spectrums of typical vegetation, infected or stressed in different levels are carried out. We analyzed the effect of atmospheric aerosol on the result of a carried out validation in relation to the known direct and suggested intersect spectral coefficientsm physically determining the dynamic band of the ratio of used spectral reflection signals in he NIR and RED bands. The comparison of the atmospheric aerosol effect on the possibility of carrying out remote sensing of plant stress severity shows that upon utilization of the suggested intersect spectral coefficientsm, the validation of results of remote sensing of plant stress severity can be carried out at a greater amount of aerosol noise signal than upon utilization of the known direct spectral ratio coefficients.
References
1. Zhang J., Pu R., Huang W., Yuan L., Luo J., Wang J. Using in-situ hyperspectral data for detecting and discriminating yellow rust disease from nutrient stress // Field Crops Research. - 2012. - Vol. 134. - P. 165-174.
2. Hillnhutter C., Mahlein A. K., Sikora R. A., Oerke E.C. Remote sensing to detect plant stress induced by Heterodera schachtii and Rhizoctonia solani in sugar beet fileds // Field Crops Research. - 2011. - Vol. 122. - P. 70-77.
3. Moshou D., Bravo C., West J., Wahlen S., McCartney A., Ramon H. Automatic detection of “yellow rust” inn wheat using reflectance measurements and neural network’s// Computers and Electronics in Agriculture. - 2004. - Vol. 44. - P. 173-188.
4. Mehlein A.K., Rumpf T., Welke P., Dehne H.W., Plumer L., Steiner U., Oerke E.C. Development of spectral indices for detecting and identifying plant diseases// Remote Sensing of Environment. - 2013. - Vol. 128. - P. 21-30.
5. Muhammed H.H. Using hyperspectral reflectance data for discrimination between healthy and diseased plants and determination of damage-level in diseased plants// In proceedings of the 31st Applied Imagery Pattern Recognition Workshop. - Washington, DC, USA, 2002. - P. 49-54.
6. Ashourloo D., Mobasheri M.R., Huete A. Developing two spectral disease indices for detection of wheat leaf rust (Pucciniatriticina)// Remote Sensing of Environment. - 2014. - Vol. 6. - P. 4723-4740. doi: 10.3390/rs6064723.
7. Mahlein A.K., Steiner U., Dehne H.W., Oerke E.C. Spectral signatures of sugar beet leaves for the detection and differentiation of diseases// Precision Agriculture. - 2010. -Vol. 11. - P. 413-431.
8. Rumpf T., Mahlein A.K., Steiner U., Oerke E.C., Dehne H.W., Plumer L. Early detection and classification of plant diseases with support vector machines based on hyperspectral reflectance// Computers and Electronics in Agriculture. - 2010. - Vol. 74. - P. 91-99.
9. Mahlein A.K., Steiner U., Hillnhutter C., Oerke E.C., Dehne H.W. Hyperspectral imaging for small - scale analysis of symptoms caused by different sugar beet diseases// Plant Methods. - 2012. - Vol. 8. doi: 10.1186/1746-4811-8-3.
10. Huang L., Zhang H., Ding W., Huang W., Hu T., Zhao J. Monitoring of wheat scab using the specific spectral index from ASD hyperspectral dataset// Hidawi Journal od Spectroscopy. - 2019. - ID 9153195. - P. 9. https://doi.org/10.115/2019/9153195.
Review
For citations:
Abaszadeh F.G. ACCOUNTING THE EFFECT OF ATMOSPHERIC AEROSOL WHEN VALIDATING THE RESULTS OF REMOTE SENSING OF PLANT STRESS SEVERITY. Vestnik of North-Eastern Federal University Series "Earth Sciences". 2021;(1):28-34. (In Russ.) https://doi.org/10.25587/SVFU.2021.21.1.003
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