About: Remotely sensed NDVI as an indicator of drought stress on the vegetation

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About: Remotely sensed NDVI as an indicator of drought stress on the vegetation Goto Sponge NotDistinct Permalink

An Entity of Type : http://linked.opendata.cz/ontology/domain/vavai/Vysledek, within Data Space : linked.opendata.cz associated with source document(s)

Attributes	Values
rdf:type	skos:Concept http://linked.opendata.cz/ontology/domain/vavai/Vysledek
rdfs:seeAlso	http://www.cbks.cz/SbornikSkalice2013/pdf/Semer%C3%A1dov%C3%A1.pdf
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)
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)
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)
skos:notation	RIV/62156489:43210/13:00213248!RIV14-MSM-43210___
http://linked.open...avai/predkladatel	Agronomická fakulta
http://linked.open...avai/riv/aktivita	P
http://linked.open...avai/riv/aktivity	P(EE2.4.31.0213), P(LD11041)
http://linked.open...vai/riv/dodaniDat	2014
http://linked.open...aciTvurceVysledku	Lukas, Vojtěch Žalud, Zdeněk Trnka, Miroslav Semerádová, Daniela Hlavinka, Petr
http://linked.open.../riv/druhVysledku	D - Článek ve sborníku
http://linked.open...iv/duvernostUdaju	S - Úplné a pravdivé údaje nepodléhající ochraně podle zvláštních právních předpisů
http://linked.open...titaPredkladatele	Mendelova univerzita v Brně / Agronomická fakulta
http://linked.open...dnocenehoVysledku	102335
http://linked.open...ai/riv/idVysledku	RIV/62156489:43210/13:00213248
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	remote sensing; drought stress (en)
http://linked.open.../riv/klicoveSlovo	drought stress remote sensing
http://linked.open...ontrolniKodProRIV	[462C93B8B0DF]
http://linked.open...v/mistoKonaniAkce	Skalica
http://linked.open...i/riv/mistoVydani	Nitra
http://linked.open...i/riv/nazevZdroje	Environmental Changes And Adaptation Strategies
http://linked.open...in/vavai/riv/obor	DG
http://linked.open...ichTvurcuVysledku	5 (xsd:int)
http://linked.open...cetTvurcuVysledku	9 (xsd:int)
http://linked.open...vavai/riv/projekt	New remote sensing technologies in research, education and application to support regional development Monitoring biophysical parameters and flux measurements of the International Phenological Garden in Doksany
http://linked.open...UplatneniVysledku	2013
http://linked.open...iv/tvurceVysledku	Hlavinka, Petr Lukas, Vojtěch Semerádová, Daniela Trnka, Miroslav Žalud, Zdeněk Hayes, Michael Bohovic, Roman Wardlow, Brian Tadesse, Tsegaye
http://linked.open...vavai/riv/typAkce	EUR - Evropská
http://linked.open.../riv/zahajeniAkce	2013-01-01 (xsd:date)
number of pages	3 (xsd:int)
http://purl.org/ne...btex#hasPublisher	Slovenská poľnohospodárska univerzita v Nitre
https://schema.org/isbn	978-80-552-1066-7
http://localhost/t...ganizacniJednotka	43210

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