Search this site
Embedded Files
Agumba Oluoch
  • Home
  • Research
  • Favourite packages
  • Videos
  • Courses
    • Species Distribution Modeling
    • Geospatial AI
  • CV/Resume
  • Photos
  • Blogs
  • Contact
Agumba Oluoch
  • Home
  • Research
  • Favourite packages
  • Videos
  • Courses
    • Species Distribution Modeling
    • Geospatial AI
  • CV/Resume
  • Photos
  • Blogs
  • Contact
  • More
    • Home
    • Research
    • Favourite packages
    • Videos
    • Courses
      • Species Distribution Modeling
      • Geospatial AI
    • CV/Resume
    • Photos
    • Blogs
    • Contact

  

torchgeo

Stewart et al., (2022)

This is the smoothest dive into Geospatial AI for Remote Sensing experts without Deep Learning expertise. It is my number one tool for image segmentation tasks especially for cropland mapping which I am deeply passionate about. No more worries about CRS, Resolution, Insufficient labels, and patch creation plus augmentations. All done on the fly!!

sdm

Naimi & Araujo, (2016)

I rely on this package to build extensible species distribution models. I highly recommend this to anyone getting their feet in species distribution modelling. 

ENMeval

Kass J. M. et al (2021)

This is my go-to package when I want to take control of maxent tuning parameters to pick optimal models and partitioning training data spatially. It is also good for building null models.

geodata

Hijmans et al., (2024)

Most geospatial data sit in this package. I use it a lot to obtain both species occurrence records and climate data both at current and projected future scenarios

terra

Hijmans (2024)

Functions in this package allow me to handle most of the vector and spatial data I use in building species distribution models. Awesome replacement for raster package.

woluoch(at)uni-bonn(dot)de
Google Sites
Report abuse
Page details
Page updated
Google Sites
Report abuse