2021_SpatialModel_Vector_AedesAlbopictus

Abstract:

An ensembled spatial models were produced for the Dengue and Chikungunya Vector  Aedes albopictus ( albovenmalertensrfbrtvar19m1rclpa.zip) by combining Random Forest and Boosted Regression Trees spatial modelling outputs, implemented using the VECMAP modelling suite, using a standard set of covariates including Fourier Processed Remotely Sensed environmental variables, land use proportions, human population, and elevation. The training data offered to the model process include point location and polygon data from the VectorNet project (https://www.ecdc.europa.eu/en/about-us/partnerships-and-networks/disease-and-laboratory-networks/vector-net), from the Global Biodiversity Information Facility (www.gbif.org) and a series of national databases from the UK, Spain and Finland,  and the Citizen Science project Mosquito Alert (https://mosquitoalert.com).  This output has been converted from the original predicted probability of presence to a simple binary presence/absence)

File naming scheme: 

Model output: albovenmalertensrfbrtvar19m1rclpa. TIF 

Projection + EPSG code:Latitude-Longitude/WGS84 (EPSG: 4326)

Spatial extent:

    Extent   -32.0000000000000000,10.0000000000000000 : 69.0000000000000000,82.0000000000000000

Spatial resolution:0.0083333 deg (approx. 1000 m)  

Pixel values:Unit: Presence=1, absence=0

Source: 

The VectorNet project (https://www.ecdc.europa.eu/en/about-us/partnerships-and-networks/disease-and-laboratory-networks/vector-net) ,from the Global Biodiversity Information Facility (www.gbif.org) and a series of national databases from the UK, Spain and Finland,  and the Citizen Science project Mosquito Alert (https://mosquitoalert.com)

Software used:VECMAP

License: CC-BY-SA 4.0

Processed by:ERGO (Environmental Research Group Oxford) https://ergoonline.co.uk/ for the H2020 MOOD project