2011
DOI: 10.3390/rs3122663
|View full text |Cite
|
Sign up to set email alerts
|

Remote Sensing and Modeling of Mosquito Abundance and Habitats in Coastal Virginia, USA

Abstract: Abstract:The increase in mosquito populations following extreme weather

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
1
1

Citation Types

1
27
0
1

Year Published

2013
2013
2023
2023

Publication Types

Select...
8
1

Relationship

0
9

Authors

Journals

citations
Cited by 31 publications
(29 citation statements)
references
References 20 publications
1
27
0
1
Order By: Relevance
“…tarsalis associated with coalbed methane development with a 72.1% success rate [15]. Cleckner et al employed Landsat ETM+ data from 2002, along with historical data of mosquito trap counts and climatic data for 2003, within a GIS to develop a spatial model that would identify mosquito habitats, and also predict mosquito abundance in coastal Virginia, USA [16]. The R 2 values for the models ranged from 0.270 to 0.405, but the authors noted that, among other considerations, the distribution of the traps could have been better, and that improving their distribution in future work may increase the effectiveness of their models.…”
Section: Introductionmentioning
confidence: 99%
“…tarsalis associated with coalbed methane development with a 72.1% success rate [15]. Cleckner et al employed Landsat ETM+ data from 2002, along with historical data of mosquito trap counts and climatic data for 2003, within a GIS to develop a spatial model that would identify mosquito habitats, and also predict mosquito abundance in coastal Virginia, USA [16]. The R 2 values for the models ranged from 0.270 to 0.405, but the authors noted that, among other considerations, the distribution of the traps could have been better, and that improving their distribution in future work may increase the effectiveness of their models.…”
Section: Introductionmentioning
confidence: 99%
“…Vector abundance maps were available by statistical estimation from multiple regressions of trap data on environmental factors and habitat suitability and are published in prior works [3,4]. The vulnerability index was overlaid onto predicted mosquito abundance grids to calculate a monthly exposure potential index for both groups of species per pixel, with mosquito abundance and human vulnerability input indices weighted equally in the risk formulas.…”
Section: Mapping Exposure To Mosquito Vectorsmentioning
confidence: 99%
“…In addition, the risk of exposure to mosquito-borne disease vectors may be estimated using mosquito abundance values and the broad physiological factors of human vulnerability to disease infection. Mosquito abundance values for this project were derived from a previously published study measuring the abundance of competent mosquito vector species Culiseta melanura as well as the combined abundance of Aedes vexans and Psorophora columbiae [4,5]. A. vexans and P. columbiae share a habitat preference for ephemeral pools and therefore are referred to as the "ephemeral species" throughout this paper.…”
Section: Introductionmentioning
confidence: 99%
“…Correlative species distribution models (SDMs) relate species distribution data at known locations with information on the environmental and/or spatial characteristics of these locations [6]; these models differ from the mechanistic ones that mathematically describe the biological processes underpinning population performance [7]. In addition, Remote Sensing (RS) and Geographic Information Systems (GIS) are helpful tools for predicting and mapping species distribution [8,9].…”
Section: Introductionmentioning
confidence: 99%