THE METHOD OF CORRELATION OF ASSESSMENT OF CORRELATION OF THE MAIN INDICATORS OF THE GROWTH OF PLANTS WITH THE HELP OF AIRBORNE REMOTE SENSING WITH REGARD TO AIR POLLUTION
It is shown that the known vegetation index edge of the red zone (REP) can be presented in the form of the sum of two components from increased content of nitrogen in the air and the vegetation under normal conditions of air pollution.The method of study of correlation of the index REP and protein c...
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Online Access: | https://ecodag.elpub.ru/ugro/article/view/128 |
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doaj-bedc8361a0984b0eb889052475ec2d642021-07-28T21:17:29ZrusKamertonÛg Rossii: Èkologiâ, Razvitie1992-10982413-09582014-11-0174899210.18470/1992-1098-2012-4-89-92142THE METHOD OF CORRELATION OF ASSESSMENT OF CORRELATION OF THE MAIN INDICATORS OF THE GROWTH OF PLANTS WITH THE HELP OF AIRBORNE REMOTE SENSING WITH REGARD TO AIR POLLUTIONKh. Sh. Mustafabeili0Национальное Аэрокосмическое АгентствоIt is shown that the known vegetation index edge of the red zone (REP) can be presented in the form of the sum of two components from increased content of nitrogen in the air and the vegetation under normal conditions of air pollution.The method of study of correlation of the index REP and protein content in plants, where the impact of air pollution with nitrogen gas is excluded.https://ecodag.elpub.ru/ugro/article/view/128remote sensingair pollutionvegetation indicesvegetationcorrelation estimate |
collection |
DOAJ |
language |
Russian |
format |
Article |
sources |
DOAJ |
author |
Kh. Sh. Mustafabeili |
spellingShingle |
Kh. Sh. Mustafabeili THE METHOD OF CORRELATION OF ASSESSMENT OF CORRELATION OF THE MAIN INDICATORS OF THE GROWTH OF PLANTS WITH THE HELP OF AIRBORNE REMOTE SENSING WITH REGARD TO AIR POLLUTION Ûg Rossii: Èkologiâ, Razvitie remote sensing air pollution vegetation indices vegetation correlation estimate |
author_facet |
Kh. Sh. Mustafabeili |
author_sort |
Kh. Sh. Mustafabeili |
title |
THE METHOD OF CORRELATION OF ASSESSMENT OF CORRELATION OF THE MAIN INDICATORS OF THE GROWTH OF PLANTS WITH THE HELP OF AIRBORNE REMOTE SENSING WITH REGARD TO AIR POLLUTION |
title_short |
THE METHOD OF CORRELATION OF ASSESSMENT OF CORRELATION OF THE MAIN INDICATORS OF THE GROWTH OF PLANTS WITH THE HELP OF AIRBORNE REMOTE SENSING WITH REGARD TO AIR POLLUTION |
title_full |
THE METHOD OF CORRELATION OF ASSESSMENT OF CORRELATION OF THE MAIN INDICATORS OF THE GROWTH OF PLANTS WITH THE HELP OF AIRBORNE REMOTE SENSING WITH REGARD TO AIR POLLUTION |
title_fullStr |
THE METHOD OF CORRELATION OF ASSESSMENT OF CORRELATION OF THE MAIN INDICATORS OF THE GROWTH OF PLANTS WITH THE HELP OF AIRBORNE REMOTE SENSING WITH REGARD TO AIR POLLUTION |
title_full_unstemmed |
THE METHOD OF CORRELATION OF ASSESSMENT OF CORRELATION OF THE MAIN INDICATORS OF THE GROWTH OF PLANTS WITH THE HELP OF AIRBORNE REMOTE SENSING WITH REGARD TO AIR POLLUTION |
title_sort |
method of correlation of assessment of correlation of the main indicators of the growth of plants with the help of airborne remote sensing with regard to air pollution |
publisher |
Kamerton |
series |
Ûg Rossii: Èkologiâ, Razvitie |
issn |
1992-1098 2413-0958 |
publishDate |
2014-11-01 |
description |
It is shown that the known vegetation index edge of the red zone (REP) can be presented in the form of the sum of two components from increased content of nitrogen in the air and the vegetation under normal conditions of air pollution.The method of study of correlation of the index REP and protein content in plants, where the impact of air pollution with nitrogen gas is excluded. |
topic |
remote sensing air pollution vegetation indices vegetation correlation estimate |
url |
https://ecodag.elpub.ru/ugro/article/view/128 |
work_keys_str_mv |
AT khshmustafabeili themethodofcorrelationofassessmentofcorrelationofthemainindicatorsofthegrowthofplantswiththehelpofairborneremotesensingwithregardtoairpollution AT khshmustafabeili methodofcorrelationofassessmentofcorrelationofthemainindicatorsofthegrowthofplantswiththehelpofairborneremotesensingwithregardtoairpollution |
_version_ |
1721261191773290496 |