Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2019, Vol. 16, No. 3, pp. 61-68
Experimental basis for remote sensing of phytosanitary condition of agroecosystems in the North-West of the Russian Federation
1 Agrophysical Research Institute, Saint Petersburg, Россия
Accepted: 20.03.2019
DOI: 10.21046/2070-7401-2019-16-3-61-68
Phytosanitary monitoring as a key element of integrated plant protection system requires modernization of available approaches and methods for better match with the current level of the high technologies and its application in agriculture. The development of remote sensing assessment of phytosanitary condition of agroecosystems has promising prospects to identify within-field spatial distribution pattern of harmful objects and carry out the protective measures. Long-term field and short-term detailed experiments on plant protection have being conducted since 2012 at the Menkovo experimental station of Agrophysical Research Institute (Leningrad region, Gatchina district). The detailed description of the experiments is considered including the tools used: unmanned aerial vehicles and hand-portable sensors for spectral characteristic and vegetation indexes estimation of different phytosanitary conditions. The analysis of the phytosanitary situation formed in the crop canopies under harmful objects infestation is presented. At the same time, the list of harmful organisms economically significant for the region is distinguished for effective remote sensing application. Weed plants, particularly dominant types ― Capsella bursa-pastoris, Viola arvensis, Matricaria inodora, Chenopodium album are specific for the most crops in agrocenoses. Among cereal diseases are distinguished Microdochium nivale, Septoria spp., Helminthosporium spp., potato diseases ― Phytophthora infestans, spring rapeseed diseases ― Alternaria brassicae. Among cereal pests are distinguished Rhopalosiphum padi, potato ― Leptinotarsa decemlineata, Agriotes spp., spring rape ― Phyllotreta spp., Plutella xylostella, Meligethes aeneus.
Keywords: experimental basis, phytosanitary condition, remote sensing, unmanned aerial vehicles, spectral characteristics, vegetation index
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