Remote and field level quantification of vegetation covariates for malaria mapping in three rice agro-village complexes in Central Kenya.
about
Modelling malaria incidence with environmental dependency in a locality of Sudanese savannah area, MaliA heteroskedastic error covariance matrix estimator using a first-order conditional autoregressive Markov simulation for deriving asympotical efficient estimates from ecological sampled Anopheles arabiensis aquatic habitat covariates.Satellite-derived NDVI, LST, and climatic factors driving the distribution and abundance of Anopheles mosquitoes in a former malarious area in northwest Argentina.Spatial modelling of rheumatoid arthritis in Turkey by geographic information systems (GIS).Evaluating Efficacy of Landsat-Derived Environmental Covariates for Predicting Malaria Distribution in Rural Villages of Vhembe District, South Africa.A Cartographic Analysis Using Spatial Filter Logistic Model Specifications for Implementing Mosquito Control in Kenya
P2860
Remote and field level quantification of vegetation covariates for malaria mapping in three rice agro-village complexes in Central Kenya.
description
2007 nî lūn-bûn
@nan
2007年の論文
@ja
2007年論文
@yue
2007年論文
@zh-hant
2007年論文
@zh-hk
2007年論文
@zh-mo
2007年論文
@zh-tw
2007年论文
@wuu
2007年论文
@zh
2007年论文
@zh-cn
name
Remote and field level quantif ...... ge complexes in Central Kenya.
@ast
Remote and field level quantif ...... ge complexes in Central Kenya.
@en
type
label
Remote and field level quantif ...... ge complexes in Central Kenya.
@ast
Remote and field level quantif ...... ge complexes in Central Kenya.
@en
prefLabel
Remote and field level quantif ...... ge complexes in Central Kenya.
@ast
Remote and field level quantif ...... ge complexes in Central Kenya.
@en
P2093
P2860
P50
P921
P356
P1476
Remote and field level quantif ...... ge complexes in Central Kenya.
@en
P2093
Benjamin G Jacob
Erick X Caamano
Jose Funes
Robert J Novak
Simon Muriu
P2860
P2888
P356
10.1186/1476-072X-6-21
P577
2007-06-05T00:00:00Z
P5875
P6179
1033705499