Road extraction is a topical research because of complexity due to his large topological variability. Increasing the spatial resolution generates noise which makes extraction difficult, especially in case of major disaster in an urban context. This problem increases false alarm rates and generally affects the performance of road extraction algorithm. Our aim is to improve the quality of roads extraction after adaptation of the Lowe's SIFT descriptors (scale-invariant feature transform) jointly with spectral angle algorithm. The characterization is performed on two image at various resolution images, respectively representing a rural and urban disaster area, captured by Quickbird satellite. Our approach significantly reduces the amount of false detection and shows an overall accuracy of up to nearly 30% in some cases.
Purpose The purpose of this study is to frame digital transformation (DT) within municipalities to improve the life cycles of urban infrastructure.Design/methodology/approach The study provides the results from a systematic review of the literature on concepts of DT and its implications for municipalities, barriers and challenges to DT, as well existing DT frameworks for municipalities and their built assets. This literature review leads to the development of a DT framework to help cities conduct a planned and federated DT beforehand. Then, workshops are conducted with two major Canadian municipalities.Findings The results of these studies point to the need for a dedicated DT framework for municipalities because of their particular context and their role and proximity to citizens. The theoretical framework develops 22 elements, which are divided among 6 categories. Through its application, the framework helps to identify and target the predominant issues hindering the DT of municipalities, specifically “legacy practices” and “data management.”Research limitations/implications Limitations include limited experimental conditions and small sample size. Further work is needed to validate the framework. Other approaches are advocated to complement the data collection and analysis to generate more convincing results.Practical implications The theoretical framework was validated through two case studies on two large Canadian municipalities.Social implications Municipalities maximize the value they provide to citizens and to be at the forefront of resilience and sustainability concerns. The use of technology, digital processes and initiatives helps cities to improve planning, optimize works and provide better services to citizens.Originality/value The framework is original in that it specifically aligns assets management with DT in a municipal context.
Purpose
This paper aims to create a new searchable 3D city model to help managers improve their decision-making.
Design/methodology/approach
This paper identifies data management basics and the key elements used in the new model design; it further analyzes five-city models, presents its findings and proposes analytical trends for the new model. It discusses the concepts underlying existing models, explains the benefit brought by the proposed model and demonstrates its robustness.
Findings
City systems can be interconnected, thanks to data digitization and the integration of new technologies into different management processes. Although there are several 3D city models available, none of those identified in this research can be queried for several sectors.
Research limitations/implications
This model design can only be successfully realized in the presence of a public mandate. Potential limitations include information security risks and political non-acceptance.
Originality/value
The present work proposes a searchable and high performance model having the distinctive capacity to bring together city systems and perform real-time data analysis in order to extract important information needed to guide the city, and in the context of a global vision.
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