Building more informative climate layers for species distribution modelling

The Worldclim data set is a fantastic resource for species distribution modelling. Not only does it include quality controlled monthly temperatures (minimum and maximum) and precipitation data but it also provides 16 derived bioclimatic layers that are designed to be universally applicable and interpretable. These layers are quite simple functions of the original data and…

Importing Modis fire pixels into PostGIS

Modis data are “big data” in every respect. Both the temporal and spatial extent of the information obtained from Modis makes data processing rather challenging. A quick overview of the Modis QuickFire data can be obtained by running the following code in R. A complete archive of all pixels recorded as having possible fire activity…

PostGIS en la “nube”

Los que asitieron en el curso de bases de datos especiales en Ecosur vieron unos ejemplos de analisis con capas espaciales que estan basicamente libre y en el dominio publico (con la sola restricción de registrarte como usuario con el Conabio y el GBIF. HAY QUE HACERLO ANTES DE USAR EL VINCULO A LOS DATOS…

Comparing WorldClim with local climate data

Species distribution models now tend to use Worldclim layers by default, especially in tropical areas where historical climate datat is either sparse or unreliable. However in Mexico the CNA does provide a fairly good archive of data that can be used to derive the worldclim layers. How do the two compare? Looking just at precipitation…

Reformateando datos de Clicom con AWK

El comisión nacional de agua (CNA) de Mexico tradionalmente mantuvo los datos climatalogicos en un herramienta informatica llamado “CLicom”. Todavia se encuentran datos en este formato anticuado. La exportación de Clicom produce tablas de esta forma. ¡Este no es facil de entrar en PostGIS! Pero el formato es consistente. Siempre cuando se trata de datos…

Building utility functions in PostGIS

We want the data that we place in our PostGIS database to be easily extracted by students and technical staff with limited knowledge of spatial SQL. Some queries, particularly those involving raster data can be very daunting. We could try to use a mapserver or build queries for each user. However we would like to…