in the first section we will explore the entire area of the Dolomities, pointing out their location with respect to the Italian regions and municipalities, calculating some basics statistics; we will study their morphology visualizing and investigating the lakes and the glaciers that are present; last point of this first section concern a first exploration of the alpine huts retrieved from the official website of CAI and geo-coded through Nominatim service.

In the second section we will explore all the alpine huts, not only the ones from CAI website, and the peaks. We will retrieve the data from the OverPass API that allow to extract information from OpenStreetMap graph, focusing on the data geo-located in the North-east area of Italy. We will perform some analyses pointing out the major characteristics as the elevation, Dolomities group/province of belonging, the distance between the alpine huts and peaks greater than 3000m and highlighting the cost of the alpine huts (only for those from CAI).

In the third section we will focus on the trails, first starting from the SAT trails then using all the possible trails extracted with OpenStreetMap in the interested area. Doing this we will be able to generate real trails to reach each of the hut in the Dolomities. Moreover while doing this operation we will also add the elevation to each node in the graph allowing us to predict a travel time for complete the trails, this time is directly dependent of the difference in height of each piece of the trail. We will explore better the relation between peaks and huts exploring where it actually exists a path that bind them. Then we connect the trails and street graph calculating the optimal trail for each hut to the street taking in count, exploring the actual difference in height between the starting point-alpine huts and generating insightful details such as the expected walking time and level of difficulty of each trail.

In the fourth section we have performed a simple spatial regression in order to understand if there is some kind of correlation in the prices of the hut's half board, we will also explore other possible explanatory variables such as the elevation of the hut and the capacity of the sleeping accommodations.

Summary report containing a discursive introduction to the project as well with some results and data licenses.