# District-scale surface temperatures generated from high-resolution longitudinal thermal infrared images

arXiv: https://arxiv.org/abs/2305.01971 · HTML: https://mlsanity.com/paper/2305.01971/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 2 of its 47 references that are in the map.
- First posted on arXiv 3 May 2023.

## Builds on (most cited first, 2 of 2)

- [InfraRed Investigation in Singapore (IRIS) Observatory: Urban heat island contributors and mitigators analysis using neighborhood-scale thermal imaging](https://mlsanity.com/paper/2210.11663/) (2022)
- [Longitudinal thermal imaging for scalable non-residential HVAC and occupant behaviour characterization](https://mlsanity.com/paper/2211.09288/) (2022)

## Built on by (most cited first, 1 of 1)

- [Semantic segmentation of longitudinal thermal images for identification of hot and cool spots in urban areas](https://mlsanity.com/paper/2310.04247/) (2023)

## Abstract (arXiv)

The paper describes a dataset that was collected by infrared thermography, which is a non-contact, non-intrusive technique to collect data and analyze the built environment in various aspects. While most studies focus on the city and building scales, the rooftop observatory provides high temporal and spatial resolution observations with dynamic interactions on the district scale. The rooftop infrared thermography observatory with a multi-modal platform that is capable of assessing a wide range of dynamic processes in urban systems was deployed in Singapore. It was placed on the top of two buildings that overlook the outdoor context of the campus of the National University of Singapore. The platform collects remote sensing data from tropical areas on a temporal scale, allowing users to determine the temperature trend of individual features such as buildings, roads, and vegetation. The dataset includes 1,365,921 thermal images collected on average at approximately 10 seconds intervals from two locations during ten months.