. . "CZ - \u010Cesk\u00E1 republika" . "Timely identification of agricultural crops in the Temel\u00EDn NPP vicinity using satellite data in the event of radiation contamination" . "Timely identification of agricultural crops in the Temel\u00EDn NPP vicinity using satellite data in the event of radiation contamination"@en . . . . . "Proch\u00E1zka, Jan" . . "RIV/60076658:12220/10:00012574" . . . "3"^^ . . "1803-4403" . . "2" . "11"^^ . . "Vincikov\u00E1, Hana" . . . "Timely identification of agricultural crops in the Temel\u00EDn NPP vicinity using satellite data in the event of radiation contamination" . . "3"^^ . "12220" . "Brom, Jakub" . . "292930" . "RIV/60076658:12220/10:00012574!RIV11-MSM-12220___" . . "P(JC_ 1/2008), Z(MSM6007665806)" . "Timely identification of agricultural crops in the Temel\u00EDn NPP vicinity using satellite data in the event of radiation contamination"@en . "The study established the possibility of rapid evaluation of land cover structure and situation using as an example the Temel\u00EDn NPP (Nuclear Power Plant) emergency zone. The composition, surface representation and spatial distribution of crop species in the area of interest were assessed on the basis of satellite data analysis (Landsat 5 TM). The supervised classification method of Landsat data yielded 92% accuracy of classification into the land cover classes. A comparison of satellite data classification and field investigation (farmers? and LPIS data) showed that the combination of both methods appears to be ideal for the classification of land cover. Analysis of the assessment of Landsat satellite data showed it was possible to process data in a few days. However, obtaining data was problematic; in our case it was 44 days. The results of the classification as well as other outputs (biomass growth model, expense-to-revenue ratio of measures, route network, LPIS database parcel structure,"@en . . . . "remote sensing; land cover; Landsat 5 TM; vegetation"@en . "[DB5AD7CE6646]" . "The study established the possibility of rapid evaluation of land cover structure and situation using as an example the Temel\u00EDn NPP (Nuclear Power Plant) emergency zone. The composition, surface representation and spatial distribution of crop species in the area of interest were assessed on the basis of satellite data analysis (Landsat 5 TM). The supervised classification method of Landsat data yielded 92% accuracy of classification into the land cover classes. A comparison of satellite data classification and field investigation (farmers? and LPIS data) showed that the combination of both methods appears to be ideal for the classification of land cover. Analysis of the assessment of Landsat satellite data showed it was possible to process data in a few days. However, obtaining data was problematic; in our case it was 44 days. The results of the classification as well as other outputs (biomass growth model, expense-to-revenue ratio of measures, route network, LPIS database parcel structure," . "Journal of Agrobiology" . "27" .