We are all geographers | Mingshu Wang | TEDxUGA
Geography is evolving beyond traditional elements to focus on human-environment relations, which is now fueled by participatory 'Geotech' mapping utilizing everyday apps and social data. The speaker argues that everyday users are already acting as geographers by contributing location-enabled, user-generated content, which has significant potential for advanced scientific research. This potential is exemplified by using cross-state cannabis pricing data to generate a catogram, providing unique insights into health policy and logistics not available from traditional census data.
## Speakers & Context
- A geographer addressing an audience, inviting participation by asking who identifies as a geographer.
- The discussion frames geography as evolving beyond "rocks, rivers and mountains" to study relations between humans and the environment.
- The emergence of "Neo geography" is presented as a descriptive and analytical tool driven by digital mapping technology and social networks.
## Theses & Positions
- Geography is no longer limited to physical features but is increasingly about the complex relationship between humans and their environment.
- The combination of digital mapping technology and social networks enables a new mode of knowledge generation through user-generated content (Geotech).
- Everyday digital interactions (using GPS, reading reviews) demonstrate that the audience already functions as "new geographers," mutually contributing to complex recommendation systems.
- Users have a "golden opportunity" to advance and contribute to the scientific community by actively producing and contributing location-enabled data.
## Concepts & Definitions
- **Neo geography:** An emerging descriptive and analytical tool used by non-academics, catalyzed by digital mapping and social networks.
- **Geotech:** The term used for knowledge generated through location-enabled, user-generated content.
- **Catogram:** A specific type of map used to visualize data where the area of a state on the map is proportional to the total number of cannabis users in that state.
- **Semantic map:** A standard map representation where the darker the color indicates the higher average price of marijuana in that state.
## Mechanisms & Processes
- **Restaurant Selection (Example):** A newcomer uses a favorite app (e.g., Yelp) to look for places to eat, relying on review counts (222 reviews) and star ratings (more than four stars) before deciding on a specific item (e.g., a Cuban sandwich).
- **Traffic Prediction (Example):** Google Maps uses a GPS-enabled user to anonymously send speed data back to a centralized server, allowing Google to calculate average speeds and improve traffic prediction reliability for all users on that route.
- **Data Contribution (Mechanism):** Users are *mutually contributing to a fast routing recommendation system* by using apps like Google Maps while having GPS enabled.
- **Geographic Research Mapping (Process):** Generating knowledge by mapping specific variables (e.g., cannabis price) across states using location data, which reveals patterns otherwise inaccessible (e.g., eastern vs. western coast price differences).
## Timeline & Sequence
- **Prior to the current state:** Usage of apps for basic navigation and consumer information (e.g., going to a restaurant in Athens, GA).
- **Beginning 2009:** Google started using users to help improve traffic prediction accuracy.
- **Present day:** The optimal state for contributing to both daily life efficiency and broader scientific knowledge.
## Named Entities
- **Athens, Georgia:** A specific location used as an example of a newcomer needing guidance.
- **Atlanta airport:** A destination used as an example for GPS routing.
- **China:** Country mentioned where marijuana is illegal.
- **Census Bureau:** Governmental agency mentioned as a source that cannot provide the required data.
## Numbers & Data
- Restaurant review count example: **222 reviews**.
- Star rating example: **more than four stars**.
- Route example: Driving to **Atlanta airport** via **Route 316**.
- Marijuana price in Georgia: **roughly about $270 per ounce**.
- Data source required: **consumer** (the end user who actually purchases and uses).
## Examples & Cases
- **Restaurant Choice:** Choosing a restaurant in Athens, GA, based on the confluence of high review counts and star ratings.
- **Navigation Improvement:** Google Maps providing a "slightly complicated however much faster route" to the Atlanta airport.
- **Marijuana Price Mapping (Case Study):**
- Upper panel map: Shows darker color = *higher* average price of Marijuana in the state.
- Lower panel map (Catogram): Area of states is proportional to the total number of cannabis users in that state.
- Observation: Average price on the eastern coast is *much more expensive* than on the western coast.
- Observation: Georgia's price ($\$270$/oz) is roughly *in the middle* of the general US range.
- **Logistics Insight:** Marijuana price variability can inform strategies about plantation, transportation, and logistics.
## Tools, Tech & Products
- **Google Maps app:** Core technology used for navigation and accessing local business data.
- **GPS:** Required for the traffic data contribution mechanism.
- **Smartphones:** The primary device used by users to run these applications.
## References Cited
- **Environment and Planning:** The journal where the speaker published the article using geo-geography and user-generated content.
## Trade-offs & Alternatives
- **Traditional Data vs. Geotech Data:** Census Bureau cannot reliably provide real-time, consumer-level data like the price of marijuana; user contribution is necessary.
- **Map Visualization:** Trade-off between a simple semantic map (color gradient) and a catogram (area proportional to usage volume).
## Methodology
- **Quantitative Data Collection:** Mapping variable prices (e.g., marijuana) across multiple states.
- **Geo-location Dependency:** Requires users to be present in the location to generate data points.
- **Cross-referencing:** Combining price data with usage data (Catogram) and traditional administrative data (Semantic map).
## Conclusions & Recommendations
- Embrace the identity of the "new geographer" and actively contribute Geotech data.
- The immediate benefit is improved daily life (best food, fastest routes), leading to broader scientific potential.
- The call to action is to "Embrace this new social identity together for a better future."
## Implications & Consequences
- Increased citizen participation leads to faster, more accurate scientific modeling across diverse fields (e.g., public health, logistics).
- User-generated data makes previously inaccessible data sets viable for analyzing population health outcomes (e.g., optimizing tobacco vs. cannabis usage).
## Verbatim Moments
- *"Geography is beyond rocks rivers and mountains it is evolving all the time essentially it deals with relations between humans and the environment"*
- *"Neo geography has emerged as a descriptive and analytical tool for a large number of people outside Academia"*
- *"I open up app my favorite app and look for place to eat then I come across this restaurant"*
- *"Google Maps app can give us a better traffic prediction Because of You beginning 2009 Google turned to you to help improve its traffic prediction accuracy"*
- *"you and I we are mutually contributing to a fast routing recommendation system"*
- *"you have a golden opportunity to advance and contribute to the whole scientific community"*
- *"the upper panel is just a typical semantic map where the darker the color is the higher the average price of Marijuana it is in that state the lower panel is a funing looking map called catogram"*
- *"Let us Embrace this new social identity together for a better future"*