Linked Life Data

16044675

Source:http://linkedlifedata.com/resource/pubmed/id/16044675

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
1
pubmed:dateCreated
2005-7-27
pubmed:abstractText
Geographical Information Systems (GIS) and Remote Sensing (RS) technologies are being used increasingly to study the spatial and temporal patterns of diseases. They can be used to complement conventional ecological monitoring and modelling techniques, and provide a means to portray complex relationships in the ecology of diseases with strong environmental determinants. In particular, satellite technology has been extraordinarily improved during recent years, providing new parameters useful to understand the epidemiology of parasites, such as vegetation indices, land surface temperatures, soil moisture and rainfall indices. In the present review, Normalized Difference Vegetation Index (NDVI) is primarily considered, since it is the index characterizing vegetation that is most used in epidemiological studies. Multi-temporal study of RS data allows collection of bio-climatic information about risk area distribution, along with predictive studies and anticipatory models of diseases, at different geographic scales ranging from global to local. The main physical and technological basis of a mathematical model, effective at different scales, for identification of landscape pheno-climatic features is described in the current paper.
pubmed:commentsCorrections
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Mar
pubmed:issn
0048-2951
pubmed:author
pubmed:issnType
Print
pubmed:volume
47
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
51-62
pubmed:dateRevised
2008-11-21
pubmed:meshHeading
pubmed:year
2005
pubmed:articleTitle
Advances in satellite remote sensing of pheno-climatic features for epidemiological applications.
pubmed:affiliation
Dipartimento di Patologia e Sanità Animale, Settore di Parassitologia Veterinaria e Malattie Parassitarie, Università degli Studi di Napoli Federico II, CREMOPAR-Regione Campania, Napoli, Italy. cringoli@unina.it
pubmed:publicationType
Journal Article, Review