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References
Architectural and Transportation Barriers Compliance Board (2023). Accessibility Guidelines for Pedestrian Facilities in the Public Right-of-Way: A Rule by the Architectural and Transportation Barriers Compliance Board. Available at: |
|
Adams MA, Phillips CB, Patel A, Middel A (2022). Training computers to see the built environment related to physical activity: Detection of microscale walkability features using computer vision. International Journal of Environmental Research and Public Health 19(8):4548. |
|
Ai CB, Tsai YC (2016). Automated sidewalk assessment method for Americans with Disabilities Act compliance using three-dimensional mobile lidar. Transportation Research Record 2542:25-32. |
|
Al-Ahmadi FS, Hames AS (2009). Comparison of four classification methods to extract land use and land cover from raw satellite images for some remote arid areas, Kingdom of Saudi Arabia. Journal of King Abdulaziz University, Earth Sciences 20(1):167-191. |
|
Brown SE (1999). The curb ramps of Kalamazoo: discovering our unrecorded history. Disability Studies Quarterly 19(3):203-205. |
|
Brumbaugh S (2018). Travel patterns of American adults with disabilities. Bureau Of Transportation Statistics, Washington DC, WA, USA, US Department of Transportation. Available at: |
|
Chun Y (2008). Modeling network autocorrelation within migration flows by eigenvector spatial filtering. Journal of Geographical Systems 10(4):317-344. |
|
Eisenberg Y, Heider A, Gould R, Jones R (2020). Are communities in the United States planning for pedestrians with disabilities? Findings from a systematic evaluation of local government barrier removal plans. Cities 102:102720. |
|
Griffith DA (2003). Spatial autocorrelation and spatial filtering: Gaining understanding through theory and spatial vizualization. Springer. |
|
Griffith DA, Chun Y, Li B (2019). Spatial regression analysis using eigenvector spatial filtering. Academic Press. |
|
Hara K, Sun J, Moore R, Jacobs D, Froehlich J (2014). Tohme: detecting curb ramps in Google Street View using crowdsourcing, computer vision, and machine learning Proceedings of the 27th annual ACM symposium on User interface software and technology, Honolulu, Hawaii, USA. |
|
Hillsborough County (2022). Hillsborough approves an additional $20 million in sidewalk repair funding. Hillsborough County. Available at: |
|
Hu Z, Hu H, Huang Y (2018). Association between nighttime artificial light pollution and sea turtle nest density along Florida coast: A geospatial study using VIIRS remote sensing data. Environmental Pollution 239:30-42. |
|
Jacob BG, Izureta R, Bell J, Parikh J, Loum D, Casanova J, Gates T, Murray K, White L, Aceng JR (2023). Approximating Non-Asymptoticalness, Skew Heteroscedascity and Geo-spatiotemporal Multicollinearity in Posterior Probabilities in Bayesian Eigenvector Eigen-Geospace for Optimizing Hierarchical Diffusion-Oriented COVID-19 Random Effect Specifications Geo-sampled in Uganda. American Journal of Math and Statistics 13(1):1-43. |
|
Jacob BG, Novak RJ (2014). Integrating a Trimble Recon X 400 MHz Intel PXA255 Xscale CPU mobile field data collection system using differentially corrected global positioning system technology and a real-time bidirectional platform within an ArcGIS cyberenvironment for implementing mosquito control. Advances in Remote Sensing, 3(3):141-196. |
|
Kraemer JD, Benton CS (2015). Disparities in road crash mortality among pedestrians using wheelchairs in the USA: Results of a capture-recapture analysis. BMJ Open 5(11):e008396. |
|
Maselli F, Conese C, Petkov L, Resti R (1992). Inclusion of prior probabilities derived from a nonparametric process into the maximum likelihood classifier. Photogrammetric Engineering and Remote Sensing 58(2):201-207. |
|
Meldon P (2019). Disability history: The disability rights movement. National Parks Service. Available at: |
|
Meyers AR, Anderson JJ, Miller DR, Shipp K, Hoenig H (2002). Barriers, facilitators, and access for wheelchair users: Substantive and methodologic lessons from a pilot study of environmental effects. Social Science and Medicine 55(8):1435-1446. |
|
Mingguo Z, Qianguo C, Mingzhou Q (2009). The effect of prior probabilities in the maximum likelihood classification on individual classes: A theoretical reasoning and empirical testing. Photogrammetric Engineering and Remote Sensing 75(9):1109-1117. |
|
Murakami D, Yoshida T, Seya H, Griffith DA, Yamagata Y (2017). A Moran coefficient-based mixed effects approach to investigate spatially varying relationships. Spatial Statistics 19:68-89. |
|
Park YM, Kim Y (2014). A spatially filtered multilevel model to account for spatial dependency: application to self-rated health status in South Korea. International Journal of Health Geographics 13:6. |
|
Smart Growth America (2022). Dangerous by Design 2022. Smart Growth America. Available at: View |
|
Stahler AH (1980). The use of prior probabilities in maximum likelihood classification of remotely sensed data. Remote Sensing of Environment 10(2):135-163. |
|
State of Idaho (2023). ADA curb ramp program. Idaho Transportation Department. Available at: View |
|
U.S. Census Bureau (2021). Disability characteristics. American Community Survey, ACS 5-Year Estimates Subject Tables, Table S1810. Available at: |
|
U.S. Department of Justice (2020). The ADA and city governments: Common problems. ADA.gov. Available at: |
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