Idea After having worked on the exploratory analysis on this dataset, we can try to answer some questions, for example: Which are the countries most affected by landslides? The general idea is make a ranking of all the countries by quantity of landslides and after that shows it using a visualization. Step 1: Creating a ranking We will use the dataset from NASA Landslides after all the process of cleaning. library("dplyr") count_bycountry <- count(df_new, country = df_new$country_name) count_bycountry <- drop_na(count_bycountry) #order count_bycountry <- arrange(count_bycountry,desc(n)) Step 2: Using a treemap

A treemap is an area-based visualization where the size of each rectangle represents a metric. It could be used to show hierarchical data.

In our case we have a ranking with the countries with more and less landslides. We are using the ggplot library to create the visualization, in general terms we need to give an specific format to the data and after create the tree map.

We have already created a table (count_bycountry) we need to add a new column “v_alpha” to decrease the intensity of each rectangle into the three map, but maintain the same color base.

#alpha count_bycountry$v_alpha <- seq(141, 1, by=-1) count_bycountry$v_alpha <- count_bycountry$v_alpha/141

Finally we can create the visualization using a tree map to show in what countries are more landslides. All the code here ggplot2::ggplot(df_t, ggplot2::aes(area = n, label = country)) + geom_treemap(aes(alpha = v_alpha), fill = "#453781FF") + geom_treemap_text(fontface = "italic", colour = "white", place = "centre", grow = TRUE)

Which other visualizations do you want to create?

I would like to explore the relationship between triggers, category and settings of the landslides. Also, I am wondering if some of the countries with most landslides reported has less severe landslides. (For example, countries like USA and UK, with very good system to report landslides where perhaps the there are a lot of reports but the severity of the events is minor.)

Sources

Kirschbaum, D. B., Adler, R., Hong, Y., Hill, S., & Lerner-Lam, A. (2010). A global landslide catalog for hazard applications: method, results, and limitations. Natural Hazards, 52(3), 561–575. doi:10.1007/s11069-009-9401-4. [1] Kirschbaum, D.B., T. Stanley, Y. Zhou (In press, 2015). Spatial and Temporal Analysis of a Global Landslide Catalog. Geomorphology. doi:10.1016/j.geomorph.2015.03.016. [2]