  One billion people live in informal settlements worldwide. The complex and
multilayered spaces that characterize this unplanned form of urbanization pose
a challenge to traditional approaches to mapping and morphological analysis.
This study proposes a methodology to study the morphological properties of
informal settlements based on terrestrial LiDAR (Light Detection and Ranging)
data collected in Rocinha, the largest favela in Rio de Janeiro, Brazil. Our
analysis operates at two resolutions, including a \emph{global} analysis
focused on comparing different streets of the favela to one another, and a
\emph{local} analysis unpacking the variation of morphological metrics within
streets. We show that our methodology reveals meaningful differences and
commonalities both in terms of the global morphological characteristics across
streets and their local distributions. Finally, we create morphological maps at
high spatial resolution from LiDAR data, which can inform urban planning
assessments of concerns related to crowding, structural safety, air quality,
and accessibility in the favela. The methods for this study are automated and
can be easily scaled to analyze entire informal settlements, leveraging the
increasing availability of inexpensive LiDAR scanners on portable devices such
as cellphones.
