The phrase "accessibility over time" is correct and usable in written English.
It can be used when discussing how accessibility may change or evolve throughout a certain period.
Example: "The study examines the impact of technology on accessibility over time, highlighting improvements and ongoing challenges."
Alternatives: "accessibility throughout the years" or "accessibility across time".
So, as it does with everything it touches, Apple continually iterates and refines on iOS's accessibility features over time.
However, the spatial distribution of activities is surely not static, and in fact adjusts to changing accessibility levels over time [10, 11, 12].
Historical data on population and transport infrastructure enables the analysis of accessibility change over time, while the computation of its separate infrastructure and land use components offers a much richer explanation concerning the drivers of accessibility improvements.
Reductions in annual presentations to PAS and in the percentages of clients assigned to the 'uncertain' category (see Figure 1) are reflective of service, assessment, and data accessibility changes over time, and not an underlying change in the relevant regional population.
"People change over time.
The time difference from publication to our assessment of accessibility was greatest for studies from 1991, nevertheless this seems unlikely to explain the decline in accessibility within PubMed over time, as by 2006 studies published in 2000 should have been indexed and available.
To facilitate local and regional index utility we pursue several strategies, including adopting a positive orientation to well-being, integrating subjective and objective measures, employing a sub-county geographic scale of analysis and display, and designing the maps and indices to facilitate their accessibility and use over time.
As transportation planning turns toward strategies associated with maximizing accessibility over minimizing travel time, this epistemological gap is problematic for practitioners tasked with reducing structural inequalities in access to opportunity across society.
A "flattening" or convergence of levels of accessibility across locations was observed over time, with faster-growing suburban locations gaining the most in terms of employment accessibility.
The multivariable linear mixed-effects models developed for the primary aim will be extended to include center and system characteristics and accessibility factors that are fixed over time (i.e. Canada vs. US), as well as time-varying center, system, and accessibility variables (i.e. insurance status, perceived accessibility).
