Development of Nationwide Road Quality Map: Remote Sensing Meets Field Sensing

Karimzadeh, Sadra; Matsuoka, M.

doi:10.3390/s21062251

Cited by 6 publications

(5 citation statements)

References 25 publications

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Section: Synthetic Aperture Radarmentioning

confidence: 99%

“…The use of SAR technology for evaluating pavement roughness has been the focus of multiple studies [24,[129][130][131][132][133][134][135]. SAR data from X-band [132][133][134][135], L-band [24,131], and C-band [130] was investigated for pavement roughness estimation. The data were collected using various satellites such as Sentinel-1 [24,130], Sentinel-2 [132], Cosmo-SkyMed [129], and Advanced Land Observing Satellite (ALOS) [131].…”

Section: Synthetic Aperture Radarmentioning

confidence: 99%

“…SAR data from X-band [132][133][134][135], L-band [24,131], and C-band [130] was investigated for pavement roughness estimation. The data were collected using various satellites such as Sentinel-1 [24,130], Sentinel-2 [132], Cosmo-SkyMed [129], and Advanced Land Observing Satellite (ALOS) [131]. Moreover, different ML algorithms were utilized to evaluate pavement roughness.…”

Section: Synthetic Aperture Radarmentioning

confidence: 99%

“…However, multiple studies developed models to classify the roads based on their roughness. Karimzadeh and Matsuoka [132] suggested a qualitative assessment instead of quantifying pavement roughness due to insufficient image resolution. Karimzadeh and Matsuoka [132], Suanpaga et al [131], and Meyer et al [129] classified roads into two classes; roads with good and bad roughness.…”

Section: Synthetic Aperture Radarmentioning

confidence: 99%

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Industry- and Academic-Based Trends in Pavement Roughness Inspection Technologies over the Past Five Decades: A Critical Review

Fares

Zayed

2023

Remote Sensing

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Roughness is widely used as a primary measure of pavement condition. It is also the key indicator of the riding quality and serviceability of roads. The high demand for roughness data has bolstered the evolution of roughness measurement techniques. This study systematically investigated the various trends in pavement roughness measurement techniques within the industry and research community in the past five decades. In this study, the Scopus and TRID databases were utilized. In industry, it was revealed that laser inertial profilers prevailed over response-type methods that were popular until the 1990s. Three-dimensional triangulation is increasingly used in the automated systems developed and used by major vendors in the USA, Canada, and Australia. Among the research community, a boom of research focusing on roughness measurement has been evident in the past few years. The increasing interest in exploring new measurement methods has been fueled by crowdsourcing, the effort to develop cheaper techniques, and the growing demand for collecting roughness data by new industries. The use of crowdsourcing tools, unmanned aerial vehicles (UAVs), and synthetic aperture radar (SAR) images is expected to receive increasing attention from the research community. However, the use of 3D systems is likely to continue gaining momentum in the industry.

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Section: Synthetic Aperture Radarmentioning

confidence: 99%

Section: Synthetic Aperture Radarmentioning

confidence: 99%

Section: Synthetic Aperture Radarmentioning

confidence: 99%

Section: Synthetic Aperture Radarmentioning

confidence: 99%

See 2 more Smart Citations

Industry- and Academic-Based Trends in Pavement Roughness Inspection Technologies over the Past Five Decades: A Critical Review

Fares

Zayed

2023

Remote Sensing

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“…Therefore, identification and zoning of areas sensitive to light pollution in order to assess the environment of these areas seems necessary. Recently, advances in data collection and sharing in many aspects of urban life have provided us with better clues about the characteristics of cities [1][2][3]. In this regard, the effectiveness of remote sensing techniques and data in detecting changes, whether physical or optical changes, has been more than other methods.…”

Section: Introductionmentioning

confidence: 99%

Investigation and modeling of physical development of urban areas and its effects on light pollution using night light data

BAGHERİ

Karimzadeh

Feizizadeh

2023

International Journal of Engineering and Geosciences

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The expansion of urbanization and unbalanced urban growth has attracted the attention of many urban planners and decision makers to the issues and consequences of urban population growth. In general, monitoring how urban areas are developed on a large scale is very important in order to plan urban development. However, in most cases, the lack of basic information in this area, especially in developing countries is one of the main obstacles to achieve this. With the development of human civilization and urbanization, the demand for artificial light has increased and this growth will continue. Found. Due to its lack of direct impact on daily life, light pollution has remained largely unknown and has rarely been studied. In this regard, the role of remote sensing techniques and data in identifying changes in the physical development of cities and changes in the amount of light is clearer than other methods. Using VIIRS satellite imagery, other satellite, digital and GIS data can measure and measure the physical growth of cities as well as the spatial and temporal distribution and extent of this type of pollution, and can even manage the risk of this pollution and Reach zoning. High-risk and dangerous areas. In this study, NPP images, travel time layer of Landsat 7 and 8 images have been used, which have been analyzed with the help of remote sensing and GIS techniques. The time frame considered in this study is 2012 to 2020.

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