Pixel-by-pixel rectification of urban perspective thermography

Miño, Jairo Acuña Paz y; Duport, Nicolas; Beckers, Benoît

doi:10.1016/j.rse.2021.112689

Cited by 8 publications

(5 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Thermal images captured by terrestrial thermal cameras require adjustments for perspective correction [1] and compensation for reflected longwave radiation from the Sun [2]. Despite their low resolution, thermal images can be processed using SfM (Structure from Motion) techniques [3].…”

Section: Fig 2 -Flat Roof Leak Samplementioning

confidence: 99%

Flat roof classification and leaks detections by Deep Learning

Zahradník,

Roučka,

Karlovská

2024

CEJ

View full text Add to dashboard Cite

This paper presents an efficient and accurate method for detecting flat roof leaks using a combination of unmanned aerial vehicles (UAVs) and deep learning. The proposed method utilizes a DJI M300 drone equipped with RGB and thermal cameras to capture high-resolution images of the roof. These images are then processed to create orthomosaics and digital elevation models (DEMs). A deep learning model based on the U-NET architecture is then used to segment the roof into different classes, such as PVC foil, windows, and sidewalks. Finally, the damaged insulation is identified by analyzing the temperature distribution within the PVC foil segments. The proposed method has several advantages over traditional inspection methods. It is much faster and more efficient. A UAV can collect images of a large roof in a matter of minutes, while traditional methods can take several days or weeks. The orthomosaics and temperature maps generated by the UAV are much more detailed than the images that can be collected by a human inspector. Third, the UAV-based system is safer. The UAV can collect images of the roof without the need for a human inspector to climb onto the roof, which can be dangerous. The results of this study show that the proposed method is an effective and accurate way to detect flat roof leaks. The deep learning model was able to achieve an overall accuracy of 95% in segmenting the roof into different classes. The method was also able to identify damaged insulation with a high degree of accuracy.

show abstract

Section: Fig 2 -Flat Roof Leak Samplementioning

confidence: 99%

Flat roof classification and leaks detections by Deep Learning

Zahradník,

Roučka,

Karlovská

2024

CEJ

View full text Add to dashboard Cite

show abstract

“…However, due to the complex mechanisms between solar radiation and urban development [18], there remains a significant research gap. Firstly, previous studies on urban solar radiation have focused on measurements in special or key areas [19], with little attention given to the imbalances in development within and outside cities. Secondly, discussions and observations of the characteristic distribution of solar radiation in urban streets are often limited to the same temporal cross-section [20].…”

Section: Introductionmentioning

confidence: 99%

Analysing the Spatio-Temporal Variations of Urban Street Summer Solar Radiation through Historical Street View Images: A Case Study of Shanghai, China

Wang,

Zhang,

2024

IJGI

View full text Add to dashboard Cite

Understanding solar radiation in urban street spaces is crucial for comprehending residents’ environmental experiences and enhancing their quality of life. However, existing studies rarely focus on the patterns of urban street solar radiation over time and across different urban and suburban areas. In this study, street view images from the summers of 2013 and 2019 in Shanghai were used to calculate solar radiation in urban street spaces. The results show a general decrease in street solar radiation in 2019 compared to 2013, with an average drop of 12.34%. The decrease was most significant in October (13.47%) and least in May (11.71%). In terms of solar radiation data gathered from street view sampling points, 76.57% showed a decrease, while 23.43% showed an increase. Spatially, solar radiation decreased by 79.66% for every additional 1.5 km from the city centre. In summary, solar radiation generally shows a decreasing trend, with significant variations between different areas. These findings are vitally important for guiding urban planning, optimising green infrastructure, and enhancing the urban ecological environment, further promoting sustainable urban development and improving residents’ quality of life.

show abstract

“…Maybe it would be even better if the towers were dark, like the very first skyscrapers in the city, with their brick façades pierced by small windows. In this case, however, the walls would absorb more radiation, which would be re-emitted in infrared, and it is not sure that the radiation balance would be better for the people passing by [3].…”

Section: Introductionmentioning

confidence: 99%

Taking a step back from glass towers facades to make them compatible with the 2050 targets

Paule,

Aguacil Moreno,

Beckers

2023

J. Phys.: Conf. Ser.

View full text Add to dashboard Cite

Skyscrapers or glass towers are an extremely common model throughout the world. In the current context of climate change and resource depletion, we need to develop new postures towards these objects, especially for existing buildings that are becoming obsolete. This article begins by showing how the nature of the facades of these buildings influences the urban climate. It continues with the analysis of an emblematic building from the 1970s, the Tour Areva in Paris-La Défense (France). Through this typical example, we show how it is possible to improve the quality of use and the energy performance by exploring various scenarios. The main theme is the transformation of the façade and how it is possible, through different actions, to simultaneously improve daylighting performance, visual and thermal comfort and overall energy performance. New approaches to geometry and photometry are explored and show, through daylighting and thermal simulations, that it is possible to give these objects a new start. This work concludes with a life cycle analysis that quantifies the valorization of the intrinsic energy stock associated with the building and which elements can be conserved or reused. In this project, we demonstrate that with good design, it is possible to convert these office buildings into pleasant and generous flats and to achieve a high level of energy efficiency and comfort, without forgetting the environmental objectives for the 2050 horizon.

show abstract

Pixel-by-pixel rectification of urban perspective thermography

Cited by 8 publications

References 31 publications

Flat roof classification and leaks detections by Deep Learning

Flat roof classification and leaks detections by Deep Learning

Analysing the Spatio-Temporal Variations of Urban Street Summer Solar Radiation through Historical Street View Images: A Case Study of Shanghai, China

Taking a step back from glass towers facades to make them compatible with the 2050 targets

Contact Info

Product

Resources

About