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An integrated remote sensing-machine learning framework for assessing plant air pollution tolerance using satellite-derived air quality and reanalysis meteorological data
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| Published in: | Environmental Systems Research |
|---|---|
| Format: | Online Article RSS Article |
| Published: |
2026
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| _version_ | 1868553050553057281 |
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| collection | WordPress RSS FRELIP Feed Integration |
| container_title | Environmental Systems Research |
| description | |
| discipline_display | Environmental Studies |
| discipline_facet | Environmental Studies |
| format | Online Article RSS Article |
| genre | Journal Article |
| id | rss_article:72562 |
| institution | FRELIP |
| journal_source_facet | Environmental Systems Research |
| last_indexed | 2026-06-20T21:30:51.459Z |
| publishDate | 2026 |
| publishDateSort | 2026 |
| record_format | rss_article |
| spellingShingle | An integrated remote sensing-machine learning framework for assessing plant air pollution tolerance using satellite-derived air quality and reanalysis meteorological data Environmental Studies General Environmental Studies |
| sub_discipline_display | General |
| sub_discipline_facet | General |
| subject_display | Environmental Studies General Environmental Studies |
| subject_facet | Environmental Studies General Environmental Studies |
| title | An integrated remote sensing-machine learning framework for assessing plant air pollution tolerance using satellite-derived air quality and reanalysis meteorological data |
| title_alt | Un marco integrado de teledetección y aprendizaje automático para evaluar la tolerancia de las plantas a la contaminación del aire utilizando calidad del aire derivada de satélites y datos meteorológicos de reanálisis Un cadre intégré de télédétection et d'apprentissage automatique pour évaluer la tolérance des plantes à la pollution atmosphérique à l'aide de données satellitaires sur la qualité de l'air et de données météorologiques de réanalyse Uma estrutura integrada de sensoriamento remoto e aprendizado de máquina para avaliar a tolerância de plantas à poluição do ar usando qualidade do ar derivada de satélite e dados meteorológicos de reanálise |
| title_auth | An integrated remote sensing-machine learning framework for assessing plant air pollution tolerance using satellite-derived air quality and reanalysis meteorological data |
| title_es_txt | Un marco integrado de teledetección y aprendizaje automático para evaluar la tolerancia de las plantas a la contaminación del aire utilizando calidad del aire derivada de satélites y datos meteorológicos de reanálisis |
| title_fr_txt | Un cadre intégré de télédétection et d'apprentissage automatique pour évaluer la tolérance des plantes à la pollution atmosphérique à l'aide de données satellitaires sur la qualité de l'air et de données météorologiques de réanalyse |
| title_full | An integrated remote sensing-machine learning framework for assessing plant air pollution tolerance using satellite-derived air quality and reanalysis meteorological data |
| title_fullStr | An integrated remote sensing-machine learning framework for assessing plant air pollution tolerance using satellite-derived air quality and reanalysis meteorological data |
| title_full_unstemmed | An integrated remote sensing-machine learning framework for assessing plant air pollution tolerance using satellite-derived air quality and reanalysis meteorological data |
| title_pt_txt | Uma estrutura integrada de sensoriamento remoto e aprendizado de máquina para avaliar a tolerância de plantas à poluição do ar usando qualidade do ar derivada de satélite e dados meteorológicos de reanálise |
| title_short | An integrated remote sensing-machine learning framework for assessing plant air pollution tolerance using satellite-derived air quality and reanalysis meteorological data |
| title_sort | an integrated remote sensing-machine learning framework for assessing plant air pollution tolerance using satellite-derived air quality and reanalysis meteorological data |
| topic | Environmental Studies General Environmental Studies |
| url | https://link.springer.com/article/10.1186/s40068-026-00477-z |