For this module, I continued to use Cambodia. The first step was to download all of the data from both sites. The GAMD database was not working the first few tries I tried to download the data, but after a couple days of checking every few hours the data finally downloaded sucessfully and completely. There were no other problems getting data from Worldpop, and I was able to get a population raster for both 2019 and 2020, but I ended up using the raster from 2019 in the end. From the data in class, here are some figures I was able to create.
This includes layers the first two administrative levels inside Cambodia. Only the first administration has levels though for optimal readability.
Code:
pop19_fit %>% collect_metrics()
# A tibble: 2 x 4
.metric .estimator .estimate .config
<chr> <chr> <dbl> <fct>
1 rmse standard 20812. Preprocessor1_Model1
2 rsq standard 0.0667 Preprocessor1_Model1
Variable Importance Chart: