Computer vision for environmental and social sustainability policy
Abstract/Contents
- Abstract
- Computer vision (CV) has succeeded in many benchmark datasets but has yet to be widely applied to large-scale spatial and temporal correlated image datasets to address environmental or social issues. This thesis demonstrates the challenge, solutions, and policy implications of using computer vision for satellite, aerial, and street view images at scale with four empirical studies: 1) Mapping Vegetation and Classifying the driver of deforestation in Indonesia; 2) Detecting and characterizing high-emission oil and gas facilities in the U.S.; 3) Estimating the prevalence and placement of surveillance cameras in 16 major cities; 4) Mapping the Trend of Crosswalks Visibility Enhancements in the U.S. Transit-Oriented Development (TOD) areas. We conclude with a systematic review of the opportunities and challenges of using computer vision in facility urban and environmental policy research.
Description
| Type of resource | text |
|---|---|
| Form | electronic resource; remote; computer; online resource |
| Extent | 1 online resource. |
| Place | California |
| Place | [Stanford, California] |
| Publisher | [Stanford University] |
| Copyright date | 2021; ©2021 |
| Publication date | 2021; 2021 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Author | Sheng, Hao, (Researcher in computational mathematics) |
|---|---|
| Degree supervisor | Jackson, Rob, 1961- |
| Thesis advisor | Jackson, Rob, 1961- |
| Thesis advisor | Hwang, Jackelyn |
| Thesis advisor | Ng, Andrew Y, 1976- |
| Thesis advisor | Rajagopal, Ram |
| Degree committee member | Hwang, Jackelyn |
| Degree committee member | Ng, Andrew Y, 1976- |
| Degree committee member | Rajagopal, Ram |
| Associated with | Stanford University, Institute for Computational and Mathematical Engineering |
Subjects
| Genre | Theses |
|---|---|
| Genre | Text |
Bibliographic information
| Statement of responsibility | Hao Sheng. |
|---|---|
| Note | Submitted to the Institute for Computational and Mathematical Engineering. |
| Thesis | Thesis Ph.D. Stanford University 2021. |
| Location | https://purl.stanford.edu/sn393gd4411 |
Access conditions
- Copyright
- © 2021 by Hao Sheng
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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