Advancing Data for Street-Level Flood Vulnerability: Evaluation of Variables Extracted from Google Street View in Quito, Ecuador

Abstract

Data relevant to flood vulnerability is minimal and infrequently collected, if at all, for much of the world. This makes it difficult to highlight areas for humanitarian aid, monitor changes, and support communities in need. It is time consuming and resource intensive to do an exhaustive study for multiple flood relevant vulnerability variables using a field survey. We use a mixed methods approach to develop a survey on variables of interest and utilize an open-source crowdsourcing technique to remotely collect data with a human-machine interface using high-resolution satellite images and Google Street View. Finally, we perform an inter-rater agreement to assess if this technique provides consistent results. This paper focuses on Quito, Ecuador as a case study, but the methodology can be replicated to produce labeled training data in other areas. The overall goal is to advance methods to help build training datasets that allow for assessing and automating the mapping of flood vulnerability for urban areas.

The value of ultra-detailed survey data for an improved flood damage modelling with explicit input data uncertainty treatment: INSYDE 2.0

“…The process for developing these specific datasets, here exemplified for northern Italy (Po River district), but theoretically replicable in any other region/country, mainly involves a combination of traditional methods for data collection, such as desk-based analysis of statistical databases as well as virtual surveys for creating building portfolios; even though such tasks can be time-consuming, especially in consideration of the significant regional spatial variability of the building stock, it is worth noting that emerging technologies, such as remote sensing and automatic image reconnaissance (Velez et al, 2022), can potentially enhance the process in the future, with a more efficient and accurate exposure and vulnerability modelling.…”

“…Unfortunately, the availability and reliability of required data is generally low, especially for large-scale applications (Papathoma-Köhle et al, 2007;Schröter et al, 2018;Bhuyan et al, 2022;Velez et al, 2022).…”

Group-Privacy Threats for Geodata in the Humanitarian Context

“…The use of UAVs and street-view images is nascent in DRRM applications compared to satellites. The main advantage of using RS data is the timeliness of data collection, cost efficiency and the relative ease of scaling up [22][23][24]. This is compared to using in situ datacollection methods like field surveys which can be costly and time-consuming when the area coverage is large.…”

“…For example, Harb et al [32], note that roof types can be used as a proxy to physical vulnerability, as different roof types have differential susceptibility to hazards, while heterogenous building heights in a neighborhood increase physical vulnerability of an area in the case of earthquakes. Similarly, façade building characterization is important for earthquake, tsunami, and flood physical vulnerability assessments [23,26,27,33].…”

Stormwater Sewerage Masterplan for Flood Control Applied to a University Campus

“…Although the material damage present in the area does not reflect a significant severity, inefficient planning can lead to more serious consequences; such as the case of what happened on 31 January 2022 in the city of Quito, Ecuador, in the sector known as La Gasca, where a landslide, which consists of a flow of abundant water that drags with it loose material from a hillside or stream [80], occurred which left a total of 170 people affected, 28 dead, 41 houses affected, and seven houses destroyed. In addition to morphological conditions such as the presence of hillsides and ravines [81], inadequate management of the city's natural drainage, and poor territorial planning coupled with detonating events such as heavy rains or earthquakes, can increase vulnerability to flooding [82,83]. These events, under similar conditions, have also occurred in other areas of the world (e.g., [84][85][86]) affecting infrastructure and the safety of inhabitants.…”