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rdf:type
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rdfs:seeAlso
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Description
| - The ability of remotely sensed Normalized Difference Vegetation Index (NDVI) in form of seasonal greenness (SG) was tested to explain water balance and drought occurrence through various vegetation covers. For this purpose data from 6 districts (Olomouc, Přerov, Znojmo, Břeclav, Žďár nad Sázavou and Havlíčkův Brod) within the Czech Republic were analysed. Namely , data mining technique was used, which was originally developed for machine learning community, but is increasingly used for a variety of applications. Relative form of Palmer Drought Severity Index (rPDSI) was used as dependent variable to indicate drought occurrence. Standardized Precipitation Index (SPI),Percent of Average SG (PASG), Start of Season Anomaly (SOSA) and district identification were used as independent variables. MODIS (Moderate Resolution Imaging Spectroradiometer) observations from Terra satellite were used as a source of NDVI and Cubist software v 2.07 (RuleQuest Research, Australia) for data mining. The comparison of results for field crops, forests and permanent grasslands from 2000 to 2012 was carried out.
- The ability of remotely sensed Normalized Difference Vegetation Index (NDVI) in form of seasonal greenness (SG) was tested to explain water balance and drought occurrence through various vegetation covers. For this purpose data from 6 districts (Olomouc, Přerov, Znojmo, Břeclav, Žďár nad Sázavou and Havlíčkův Brod) within the Czech Republic were analysed. Namely , data mining technique was used, which was originally developed for machine learning community, but is increasingly used for a variety of applications. Relative form of Palmer Drought Severity Index (rPDSI) was used as dependent variable to indicate drought occurrence. Standardized Precipitation Index (SPI),Percent of Average SG (PASG), Start of Season Anomaly (SOSA) and district identification were used as independent variables. MODIS (Moderate Resolution Imaging Spectroradiometer) observations from Terra satellite were used as a source of NDVI and Cubist software v 2.07 (RuleQuest Research, Australia) for data mining. The comparison of results for field crops, forests and permanent grasslands from 2000 to 2012 was carried out. (en)
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Title
| - Remotely sensed NDVI as an indicator of drought stress on the vegetation
- Remotely sensed NDVI as an indicator of drought stress on the vegetation (en)
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skos:prefLabel
| - Remotely sensed NDVI as an indicator of drought stress on the vegetation
- Remotely sensed NDVI as an indicator of drought stress on the vegetation (en)
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skos:notation
| - RIV/62156489:43210/13:00213248!RIV14-MSM-43210___
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http://linked.open...avai/riv/aktivita
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http://linked.open...avai/riv/aktivity
| - P(EE2.4.31.0213), P(LD11041)
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http://linked.open...vai/riv/dodaniDat
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http://linked.open...aciTvurceVysledku
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http://linked.open.../riv/druhVysledku
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http://linked.open...iv/duvernostUdaju
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http://linked.open...titaPredkladatele
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http://linked.open...dnocenehoVysledku
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http://linked.open...ai/riv/idVysledku
| - RIV/62156489:43210/13:00213248
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http://linked.open...riv/jazykVysledku
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http://linked.open.../riv/klicovaSlova
| - remote sensing; drought stress (en)
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http://linked.open.../riv/klicoveSlovo
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http://linked.open...ontrolniKodProRIV
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http://linked.open...v/mistoKonaniAkce
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http://linked.open...i/riv/mistoVydani
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http://linked.open...i/riv/nazevZdroje
| - Environmental Changes And Adaptation Strategies
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http://linked.open...in/vavai/riv/obor
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http://linked.open...ichTvurcuVysledku
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http://linked.open...cetTvurcuVysledku
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http://linked.open...vavai/riv/projekt
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http://linked.open...UplatneniVysledku
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http://linked.open...iv/tvurceVysledku
| - Hlavinka, Petr
- Lukas, Vojtěch
- Semerádová, Daniela
- Trnka, Miroslav
- Žalud, Zdeněk
- Hayes, Michael
- Bohovic, Roman
- Wardlow, Brian
- Tadesse, Tsegaye
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http://linked.open...vavai/riv/typAkce
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http://linked.open.../riv/zahajeniAkce
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number of pages
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http://purl.org/ne...btex#hasPublisher
| - Slovenská poľnohospodárska univerzita v Nitre
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https://schema.org/isbn
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http://localhost/t...ganizacniJednotka
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