Spatio-temporal predictions of the abundance of biting midges (Culicoides) in the western part of Europe: A large scale machine learning approach based on surveillance data, remote sensing and climate predictors

Ana Carolina Cuellar

Spatio-temporal predictions of the abundance of biting midges (Culicoides) in the western part of Europe: A large scale machine learning approach based on surveillance data, remote sensing and climate predictors

Ana Carolina Cuellar

Research output: Book/Report › Ph.D. thesis

140 Downloads (Pure)

Original language	English

Place of Publication	Kgs. Lyngby, Denmark
Publisher	Technical University of Denmark
Number of pages	219
Publication status	Published - 2018

Access to Document

Cuellar PhD thesis Corrected version 2 Final published version, 42.3 MB

OpenUrl availability

Full text

Novel methods for applied spatio-temporal risk assessment models of endemic and emerging vector borne diseases
Cuellar, A. C., Bødker, R., Kjær, L. J., Toft, N., Christiansen, L. E., Konradsen, F. & Purse, B.
Technical University of Denmark
15/02/2015 → 15/01/2019
Project: PhD

Cite this

@phdthesis{03f256f53109438382299a24b457ad95,

title = "Spatio-temporal predictions of the abundance of biting midges (Culicoides) in the western part of Europe: A large scale machine learning approach based on surveillance data, remote sensing and climate predictors",

author = "Cuellar, {Ana Carolina}",

year = "2018",

language = "English",

publisher = "Technical University of Denmark",

}

TY - BOOK

T1 - Spatio-temporal predictions of the abundance of biting midges (Culicoides) in the western part of Europe: A large scale machine learning approach based on surveillance data, remote sensing and climate predictors

AU - Cuellar, Ana Carolina

PY - 2018

Y1 - 2018

M3 - Ph.D. thesis

BT - Spatio-temporal predictions of the abundance of biting midges (Culicoides) in the western part of Europe: A large scale machine learning approach based on surveillance data, remote sensing and climate predictors

PB - Technical University of Denmark

CY - Kgs. Lyngby, Denmark

ER -

Spatio-temporal predictions of the abundance of biting midges (Culicoides) in the western part of Europe: A large scale machine learning approach based on surveillance data, remote sensing and climate predictors

Access to Document

OpenUrl availability

Projects

Novel methods for applied spatio-temporal risk assessment models of endemic and emerging vector borne diseases

Cite this