ISSN 2070-7401 (Print), ISSN 2411-0280 (Online)
Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa


Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2016, Vol. 13, No. 3, pp. 72-83

Methods for detection of weeds, pests and diseases of plants from remote sensing data

I.M. Mikhailenko 1 , I.V. Voronkov 2 
1 Agrophysical Research Institute, Saint-Petersburg, Russia
2 JGSC "Engineering Center"GEOMIR", Mytischi, Moscow region, Russia
Accepted: 05.04.2016
DOI: 10.21046/2070-7401-2016-13-3-72-83
A method for a crop state evaluation on the basis of space remote sensing data and vegetation indices is discussed. The method essentially reduces the informativeness of the spectral channels as the vegetation indices represent convolution of signals of individual channels. Besides, both a stochastic character of the problem and an initially high uncertainty do not allow solving the problem of weed detection, as well as detection of plant diseases and pests using vegetation indices. To solve the problem, we propose to use a set of spectral channels with the highest informativeness. The selection of the channels is based on the Shannon theory of information. The problem of weed, plant disease and pest detection can be solved in two steps. The first step includes the use of the information from all the spectral channels and satellite remote sensors to develop a classification for such groups as “weeds”, “diseases” and “pests”. To fulfill the first step a statistical approach is used with an assumption that the reflectance parameters of the sensing channels have normal distribution when the three above mentioned groups are being separated. The second step includes an exact specification for different types or classes within the three selected groups. The Bayesian classification procedure with a subsequent input of information from different sensing channels is used for this purpose. A software and hardware complex was developed to test the proposed method. It uses the information format from Resurs-P Russian spacecraft. The results of testing confirmed the functionality and high reliability of the proposed method. The reasons for hindering the implementation of the method were analyzed. These reasons are considered to be the absence of systematic studies on the reflection spectra of weeds, diseases and pests for individual crops. The developed software and hardware complex can be an effective tool in such studies.
Keywords: remote sensing, weeds, diseases, pests, detection, Bayesian procedures
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