Song, R; Gao, X; Nan, H; Zeng, S and Tam, V W Y (2024) Ecological restoration for mega-infrastructure projects: a study based on multi-source heterogeneous data. Engineering, Construction and Architectural Management, 31(9), pp. 3653-3678. ISSN 0969-9988
Abstract
Purpose: This research aims to propose a model for the complex decision-making involved in the ecological restoration of mega-infrastructure (e.g. railway engineering). This model is based on multi-source heterogeneous data and will enable stakeholders to solve practical problems in decision-making processes and prevent delayed responses to the demand for ecological restoration. Design/methodology/approach: Based on the principle of complexity degradation, this research collects and brings together multi-source heterogeneous data, including meteorological station data, remote sensing image data, railway engineering ecological risk text data and ecological restoration text data. Further, this research establishes an ecological restoration plan library to form input feature vectors. Random forest is used for classification decisions. The ecological restoration technologies and restoration plant species suitable for different regions are generated. Findings: This research can effectively assist managers of mega-infrastructure projects in making ecological restoration decisions. The accuracy of the model reaches 0.83. Based on the natural environment and construction disturbances in different regions, this model can determine suitable types of trees, shrubs and herbs for planting, as well as the corresponding ecological restoration technologies needed. Practical implications: Managers should pay attention to the multiple types of data generated in different stages of megaproject and identify the internal relationships between these multi-source heterogeneous data, which provides a decision-making basis for complex management decisions. The coupling between ecological restoration technologies and restoration plant species is also an important factor in improving the efficiency of ecological compensation. Originality/value: Unlike previous studies, which have selected a typical section of a railway for specialized analysis, the complex decision-making model for ecological restoration proposed in this research has wider geographical applicability and can better meet the diverse ecological restoration needs of railway projects that span large regions.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | complexity degradation; ecological restoration; machine learning; multi-source heterogeneous data; railway engineering |
| Index terms: | degradation, railway engineering, decision-making process, coupling, efficiency, infrastructure project, compensation, remote sensing, accuracy, forest, manager, restoration, machine learning, megaproject, complexity, decision-making, methodology, management decision |
| Subjects: | decision-making and reasoning, research methods, civil engineering, performance management, renovation and retrofit, professional development, decision analysis, systems engineering, infrastructure and transport systems, dispute resolution, practitioner, research products and data, strategic project management, material degradation and durability, artificial intelligence, environmental science |
| Topics: | Quality Management, Legal Issues, Digital Applications, Project Management, Research Practice, Construction Materials, Engineering Principles, Information Management, Sustainability, Roles and Professions, Risk Management |
| Descriptive scope: | 3 PCT |
N.B. Descriptive scope is a count of how many of the five facets of empirical research are indicated by the words used in title, abstract and keywords. It is not intended as a judgement on the research; merely a count of the kind of word we would expect to indicate Phenomenon, Concepts, Theoretical framing, Empirical techniques, Analytical techniques. If all five are present, then a code of “5 PCTEA” will indicate this. If you feel the coding for this record is questionable, we welcome discussion around the terms we matched or the way we categorized them. The facet you would expect may not be coded, or a facet may be coded inappropriately. This can also bear on a larger question, of which facets should be treated as defining in construction management research. Please get in touch, and we will look at it. More details here