Name: Juan Escamilla Molgora
Type: User
Company: Lancaster University
Bio: I'm a mathematical biologist that works with spatial statistics.
I work with environmental and ecological problems.
I do Environmental Data Science
Location: Lancaster, Uk
Blog: https://ecomorphisms.holobio.me
Juan Escamilla Molgora's Projects
Ansible role to provision KVM/QEMU virtual machines
Biodiversity
Spatial tools for biodiversity analysis based on Python and using GBIF!
A spatial graph-based computing engine for ecological big data
Tools for initialising a Postgis database for use with Biospytial. The Biospytial Postgis container includes this repository
A wrapper to communicate biospytial with R
Spatial Generalised Linear Mixed Models for Areal Unit Data
WebServices to your garden with Raspberry Pi!
The Web framework for perfectionists with deadlines.
A Django implementation for handling the Forest Inventory and Analysis Program
Docker Cheat Sheet
A Sandbox for developing a Double CAR SDM model.
:package: :snake: Python package to model and forecast the risk of deforestation
Python tools for geographic data
SOme basic GIS tools written in python.
Basic GIS Algorithms revisited in the Lars Harrie lectures in Lund University.
Some code and files by the Meta-Analysis Group (iDiv Summer School 2017).
Introducción a la estadística bayesiana y procesos gausianos
a Joint Species Distribution Model for Presence-Only Data
A LaTeX / XeLaTeX / LuaLaTeX PhD thesis template for Lancaster University
A beamer template for Lancaster University
Latex template for postgraduate lancaster university thesis
Repository for Geospatial Learning Group
Power CLI and Workflow manager for LLMs (core package)
Curos en línea de modelado de nicho ecológico impartido por: Jorge Soberón, Peter Townsend, Ángela Cuervo y colaboradores
Config files for my GitHub profile.
Altimeter, Barometer and Temperature Sensor
A modern LaTeX Beamer theme
Gremlin for Neo4jServer 2.x
Open Location Codes are short, generated codes that can be used like street addresses, for places where street addresses don't exist.