Home.Land.Security Official Project Launch!!

Project:


In the wake of the murder of Trayvon Martin, there is heightened awareness of violent actions against and harassment of folks from marginalized communities by the police or otherwise. While there are existent sites that address traditional notions of safety, particularly in the form of mapping crimes, there are little or no resources available for people from these communities–people of color, queer folks, and undocumented people– to gauge how safe they are in their communities or in the communities that they are visiting. Our site is designed for vulnerable citizens and visitors of San Francisco, who wish to better identify safety risks from their viewpoint, including, but not limited to, officer involved shootings and targeted arrests for what we call “quality of life” crimes.

Home.Land.Security is an interactive learning and planning tool for the vulnerable citizens and tourists of San Francisco, who could potentially be the target of attacks similar to the killings of Oscar Grant and Trayvon Martin. We aim to show how neighborhoods and demographics are disproportionately targeted for intimidation, harassment, and excessive use of force by mapping officer involved shootings, quality of life crimes (which represent crimes in which vulnerable groups are typically targeted with excessive force), and user reported incidents that can expand past traditional notions of safety and crime.

This site highlights spatial patterns of excessive force and aid both citizens and policymakers in preventing future incidents. This site will also give people a forum to map their negative experiences with law enforcement officials or other citizens.

Check out Home.Land.Security.

Diagrams:

Team Metro:
Jordan “Google Earthling” Rosencranz
Jordan was the utility man. In addition to putting nearly 60 officer involved shootings on the map, he was instrumental in adding key functions such as activating the user reported crime form tool and switching toggle tools from checkboxes to radio buttons. He also added a search bar.
Ben “Likes Shiny Things” Palmquist
Ben made our site shine with CSS and bootstrap and took the lead on many of our debugging projects. He also handled the finicky crimespotting data, while taking the lead on coding our custom function, which ranks neighborhoods by non-traditional safety measures.
Pamela “Devil in the Details” Stephens
Pam took the reins on the GIS projects, publishing a myriad of demographic layers with clear/user friendly legends. She was the lead formatter of the initial accordion-style site design and paved the way for final design. Pam also helped format our charts.
Will “Wordsmith” Dominie
Will published all of our written content on the site, allowing the user to better understand the purpose layer and function. Will was also a GIS superstar and put in a great deal of work behind the scenes to ensure that the neighborhood ranking function worked properly. Extremely detail oriented, Will worked with divs and charts to create an intuitive user interface.

Evaluation:
Things that worked great!
o Our styling was super stylin.
o We presented our data really well. It looks good and is easy to read/understand.
• Things that worked less great!
o Forms?
o We have this strange bug in the site where our demographic layers don’t always align with the map itself. It only happens some of the time, usually after loading the map, clicking on a neighborhood to display graphs, and then changing the demographic layer. It is a disturbingly fickle bug, only occurring in some browsers and only at certain window sizes. Our only hypothesis is that it may be due to an overzealous div (a number are rigged to pop up on click ) that changes the window size. Since the map is set to 100%, perhaps the map resizes to meet the new size (we do observe a faint shift on click), but forgets to resize the map server layer? While we are usually very willing to take responsibility for our mistakes, we kinda suspect that their error might be more on google or ESRI’s end.
o It was difficult to connect the searchbar to our user reporting forms.
o Crimespotting was really annoying and difficult to work with. Sometimes they would turn their API off and then back on again randomly.

• The future of Home.Land.Security
Following our successful launch on Yohman, we will be shopping our site around to organizations that might be interested, such as copwatch.

Added functionalities:
a. Expand the project to outside of San Francisco, either by creating national website, or similar sites for other cities and counties.
b. Add a resources page for those reporting harassment that want to take action
c. Integrate more positive indicators of security for our targeted population such as availability of cultural resource centers
d. Add introductory window/awesome video to help capture the narrative of the site akin to Will’s framing in the presentation)

Documentation:
o User interaction: User interaction is a key feature of our site’s design. We attempted to create an interface that encourages exploration, allowing users to explore the data presented in a nonlinear manner. In particular, we wanted users to be able to make comparisons between different neighborhoods and datasets, exploring how race, immigration, location and other factors influence policing and safety. Toward this end, we included a variety of tools for people to interact with the site. These include:
• A search bar: This allows users to easily locate a place or address.
• Forms: We have included a form that allows users to report on incidents that threaten their safety, or the safety of others. These incidents are stored in a database, and can be shown on the map.
• Radio Buttons: We included a number of layers that users can toggle using checkboxes or radio buttons.
Custom function: We authored a function (metro.showRank) that displays the relative ranking of a neighborhood and color codes the display to reflect how a safe a neighborhood is. We think its pretty neat.

o Custom layers: We created oodles of custom layers, including some with some with some really slick legends that Pam created in illustrator. These layers include:
•An Officer Involved Shooting (OIS) KML, which we later converted to an ArcMap mapserver.
•A neighborhood master layer, in which we converted our data layers (census demographics, OIS and crime statistics) to SF neighborhood boundaries using dissolve and some spatial joins. This layer was the base for our demographic layer. It also defines neighborhoods that users can click on to get more data on the safety of a neighborhood, which is shown at the bottom of the map.
•A number of demographic and neighborhood layers to allow users to explore the characteristics of their neighborhoods.

oWe also include Purpose, About Us, and FAQ tabs.

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