ICAR Research Data Repository for Knowledge Management
Active Living Feature Score
Harvard Dataverse (Africa Rice Center, Bioversity International, CCAFS, CIAT, IFPRI, IRRI and WorldFish)
View Archive Info| Field | Value | |
| Title |
Active Living Feature Score
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| Identifier |
https://doi.org/10.7910/DVN/WBQXXZ
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| Creator |
Fuller, Daniel
Alfosool, Ali |
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| Publisher |
Harvard Dataverse
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| Description |
In this research, Ali Alfosool proposes Active Living Feature Score or ALF-Score, a novel approach to measure walkability more accurately and efficiently while addressing existing limitations. ALF-Score incorporates road network structure to derive various features such as network science centralities and network embedding which are crucial in better understanding the road structure. ALF-Score utilizes user opinion to build high-confidence ground-truth that is used to generate models capable of estimating walkability scores based on user opinion. By incorporating machine learning approaches in my pipelines, he was able to achieve a much higher granularity and higher spatial resolution of walkability scores at point level.
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| Subject |
Computer and Information Science
Earth and Environmental Sciences Medicine, Health and Life Sciences walkability, active living |
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| Language |
English
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| Contributor |
Fuller, Daniel
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