Spacetime maps visualize travel time by distorting geographical maps. Instead of showing distances, these maps warp space so that the distance to any point represents the time it takes to travel there from a chosen origin. Faster travel methods result in less distortion, while slower methods exaggerate distances. The map demonstrates how travel time, rather than physical distance, shapes our perception and accessibility of different locations. It allows users to select various transportation modes (car, walking, public transit) and adjust the starting point to explore how travel time changes the perceived world.
TheretoWhere.com lets you visualize ideal housing locations in a city based on your personalized criteria. By inputting preferences like price range, commute time, proximity to amenities (parks, groceries, etc.), and preferred neighborhood vibes, the site generates a heatmap highlighting areas that best match your needs. This allows users to quickly identify promising neighborhoods and explore potential living areas based on their individualized priorities, making the often daunting process of apartment hunting or relocation more efficient and targeted.
HN users generally found the "theretowhere" website concept interesting, but criticized its execution. Several commenters pointed out the limited and US-centric data, making it less useful for those outside major American cities. The reliance on Zillow data was also questioned, with some noting Zillow's known inaccuracies and biases. Others criticized the UI/UX, citing slow load times and a cumbersome interface. Despite the flaws, some saw potential in the idea, suggesting improvements like incorporating more data sources, expanding geographic coverage, and allowing users to adjust weighting for different preferences. A few commenters questioned the overall utility of the heatmap approach, arguing that it oversimplifies a complex decision-making process.
Summary of Comments ( 3 )
https://news.ycombinator.com/item?id=43040986
HN users generally praised the map's concept and execution. Several appreciated its ability to visualize travel time in a novel way, highlighting the dominance of air travel over geographical distance in modern times. Some pointed out interesting details revealed by the map, such as the relative isolation of Australia and New Zealand. A few users suggested potential improvements, like the inclusion of high-speed rail lines, ferry routes, and more granular city-level data. There was also discussion of the projection used and its potential distortion effects. Finally, some comments offered alternative methods for visualizing similar data, referencing existing tools or suggesting different approaches.
The Hacker News post "Spacetime maps: A map that warps to show travel time," linking to maps.vvolhejn.com, generated a modest amount of discussion, with a handful of comments exploring different facets of the concept and its implementation.
Several commenters appreciated the visualization and its novelty. One user described it as "pretty neat," highlighting how it effectively illustrates the impact of geographical features and transportation infrastructure on travel time. Another commenter praised the interactive nature of the map, noting the ability to drag the destination point and observe the resulting distortions in real-time. This interactivity, they suggested, makes the concept more engaging and understandable.
The discussion also touched upon the practical implications and potential applications of such maps. One user pondered the usefulness of incorporating this kind of visualization into standard mapping applications, suggesting it could be valuable for urban planning and logistics. Another commenter pointed out the existing use of similar concepts in isochrone maps, which depict areas reachable within a given time frame. This prompted a brief comparison of the spacetime map to isochrone maps, with some users noting the spacetime map's more visually striking presentation of the same underlying data.
A few commenters delved into the technical aspects of the map. One user questioned the specific algorithm employed to calculate travel times and suggested an alternative method. They speculated on the use of Dijkstra's algorithm or A* search, highlighting the complexities of accurately modeling real-world travel conditions. Another user inquired about the data source used for the map, recognizing the importance of accurate and up-to-date information for generating meaningful visualizations.
While generally positive, the comments also acknowledged limitations. One user pointed out the current focus on driving times, suggesting the inclusion of other modes of transportation like public transit would enhance the map's utility.
Overall, the comments on the Hacker News post reflect a general appreciation for the innovative approach to visualizing travel time, coupled with a pragmatic discussion of its practical applications, technical underpinnings, and potential areas for improvement.