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Statements

Subject Item
n2:RIV%2F62156489%3A43210%2F13%3A00213248%21RIV14-MSM-43210___
rdf:type
skos:Concept n22:Vysledek
rdfs:seeAlso
http://www.cbks.cz/SbornikSkalice2013/pdf/Semer%C3%A1dov%C3%A1.pdf
dcterms: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.
dcterms: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
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
skos:notation
RIV/62156489:43210/13:00213248!RIV14-MSM-43210___
n22:predkladatel
n23:orjk%3A43210
n3:aktivita
n17:P
n3:aktivity
P(EE2.4.31.0213), P(LD11041)
n3:dodaniDat
n7:2014
n3:domaciTvurceVysledku
n13:5539498 n13:1352482 n13:9619674 n13:4394372 n13:5796288
n3:druhVysledku
n21:D
n3:duvernostUdaju
n8:S
n3:entitaPredkladatele
n10:predkladatel
n3:idSjednocenehoVysledku
102335
n3:idVysledku
RIV/62156489:43210/13:00213248
n3:jazykVysledku
n19:eng
n3:klicovaSlova
remote sensing; drought stress
n3:klicoveSlovo
n18:remote%20sensing n18:drought%20stress
n3:kontrolniKodProRIV
[462C93B8B0DF]
n3:mistoKonaniAkce
Skalica
n3:mistoVydani
Nitra
n3:nazevZdroje
Environmental Changes And Adaptation Strategies
n3:obor
n15:DG
n3:pocetDomacichTvurcuVysledku
5
n3:pocetTvurcuVysledku
9
n3:projekt
n20:LD11041 n20:EE2.4.31.0213
n3:rokUplatneniVysledku
n7:2013
n3:tvurceVysledku
Bohovic, Roman Žalud, Zdeněk Hlavinka, Petr Wardlow, Brian Hayes, Michael Tadesse, Tsegaye Semerádová, Daniela Trnka, Miroslav Lukas, Vojtěch
n3:typAkce
n9:EUR
n3:zahajeniAkce
2013-01-01+01:00
s:numberOfPages
3
n16:hasPublisher
Slovenská poľnohospodárska univerzita v Nitre
n12:isbn
978-80-552-1066-7
n11:organizacniJednotka
43210