An Aedes aegypti dataset from the urban area of the metropolitan zone of Mexico City

ae_aegypti_cdmx

Format

A sf object with 214 rows and 43 variables

class

is the binary response variable of presence and pseudo-absence

bio1

Annual mean temperature

bio2

Mean diurnal range

bio3

Isothermality

bio4

Temperature seasonality

bio5

Max temperature of the warmest month

bio6

Min temperature of the coldest month

bio7

Annual temperature range

bio8

Mean temperature of wettest quarter

bio9

Mean temperature of driest quarter

bio10

Mean temperature of warmest quarter

bio11

Mean temperature of coldest quarter

bio12

Annual precipitation

bio13

Precipitation of wettest month

bio14

Precipitation of driest month

bio15

Precipitation seasonality

bio16

Precipitation of wettest quarter

bio17

Precipitation of driest quarter

bio18

Precipitation of warmest quarter

bio19

Precipitation of coldest quarter

dhi

Dinamyc Habitat Indices

hfp

Human Foot Print

ia

Accessibility index

ice

Enviromental quality index

im

Marginalization index

irs

Social lag index

pop

Population

indexp

IndexP 2022

suit

Dengue temperature suitability

temp

Temperature mean

built

Estimated probability of complete coverage by built

tree

Estimated probability of complete coverage by trees

ndvi

Normalized Difference Vegetation Index

psdi

Palmer Drought Severity Index

prcp

Precipitation mean

tmin

average minimum temperature

tmax

average maximum temperature

eddi

Evaporative Demand Drought Index

hr

Relative humidity

elevation

Elevation

suhi

Standardized Urban Heat Island

uhi

Urban Heat Island

geometry

simple feature.

...

Details

The Ae. aegypti database was used to model the probability of presence in the urban area of the Mexico City metropolitan area using machine learning algorithms XGBoost and LightGBM.