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Zoning and Urban Land Use Planning for Drones



Just prior to my last stint of working in Somalia, I purchased a small consumer drone to use as social research tool.  Unfortunately the landscape had changed drastically since my last time in Mogadishu, and it was impossible to use, in particular because I am terrible at flying the damn thing. But I have since invested many hours into piloting the UAV to explore its utility as a research tool for urban planning and design.

Last weekend, a small disaster took place when I lost the signal to the UAV. The drone drifted out of sight and crash landed.  I had no idea where. It took several hours to find (on a building rooftop, I couldn't see it, but I found its WIFI signal), and even longer to recover (24 hours). At some point on TwitterConstantine Samaras, raised a significant point:  Perhaps this situation could have been avoided if I was in a no drone zone. But what does would that look like?



Legal Framework for Drones

In the United States, airspace above 700 feet is Federally restricted.  Airspace below 30 feet is considered part of individual property rights, meaning that when you own a piece of land, you also own the 30 feet of air above it. Ownership of this airspace is occasionally able to be sold for provide through a transfer of development rights. But what about the airspace between 30 and 700 feet?  At present, the FAA has restricted the use of drones for commercial use but amateurs are free to fly.

Some cities have already taken progressive steps concerning the legality of drones. The city of Evanston Illinois has passed a 2 year ban on drone use in the city for use in warrantless surveillance. This is a good thing. Carrol county in Maryland is looking for similar legislation on the use of drones by law enforcement. There was even recently a temporary event ban during golf tournament in North Carolina.  But existing UAV zoning laws are "all or nothing" in design, they do not make use of the opportunity that drones can provide in creating new markets, improved public policy, and better design for communities.

Zoning for Drones
In general, I'm not a big fan of city zoning.  I admire its intention, to make sure that the overall quality of urban life is consistent with high standards of physical and mental health.  We do not want the aluminum factory next to the children's playground or the speedway motor park in the residential neighborhood.  We do need a legal instrument for communities to make decisions about what they want to look like and how they need to function.  Yet overall, I find my city zoning is poorly conceived.  I am highly supportive of health standards, environmental regulation and taxes, but I see zero advantage toward regulating the values of a population (such as zoning concerning bars or adult services) or the economic geography as such zoning only reinforces the values of those who hold power, not the people who constitute the community.  Likewise zoning for residential vs. commercial use tends to put more strain on the landscape, increase traffic, increase pollution, and reduce the distribution of wealth. Zoning should not hinder social mobility, yet it can and does.

Therefore, to approach zoning for drones, it is important to examine the issue from multiple points of view.  After all, the goal is to create a regulatory framework that will maximize the ratio of nuisance to utility in favor of people at large, not a particular social group or economic class.

Areas of Review:

Example UAV Questions to Consider
Is the UAV big or small? 
Loud or quiet? 
Does it have a payload or a camera? 
Is it operating according to a predefined flightpath (using GPS waypoints) or is it freely piloted?
How fast and how high is it?
Is it for commercial or amateur purposes?

Example Site Questions to Consider
Is the site of high or low pedestrian traffic?
Does the site contain socially vulnerable or critical security infrastructure (schools, power plants etc)?
Does the site consist mostly of public or privately owned property?
To what extent is the airspace already cluttered and at what density?
Is this an area of high or low diversity in land use?

Example Population Issues
Is this area a public space or private space?
Is what is the privacy expectation in this space - for example, on a beach?

To recognize the array of drone designs and use designs is to realize that an affective zoning solution is flexible to support the advantages of the UAV but with limited interference upon bystanders. Conversely, it is important to insure that UAV operation is not disruptive to the general activities of the population.  Ideally, UAV operation should be able to operate "in the background" of day-to-day life.


General Guidelines for UAV/Drone Land Use Zoning Laws
While thinking about zoning for drones, one of the first questions that comes to my mind is "what will that look like"?  After all, 2-dimensional arial map is insufficient to capture the particular sense of space that will be used and affected by a UAV.  An advantage of contemporary design and modeling is that we do not need to restrict zoning maps to a 2D surface, but can draw these maps in the air, to model them above cities and within them.  A zoning map for drones should not only take advantage of modeling the airspace, but should take into consideration the variations of time.  For example, an area that might restrict private drone use from 9-5 could lift the ban from 30-400 feet after 5pm and 400-600 feet after 10 pm.

Implementation
It might seem abstract to place an imaginary 3D geometry around a building to restrict flight patterns. But for those who are already flying drones, it is no unimaginable.  Furthermore, providing the information online (such as a downloadable CAD file) for a drone operator to layer onto Google Earth or other GIS software would easily remedy the situation.  GPS and time sequencing can even be programmed into flight patterns.  It might seem abstract and hightech, but 3D mapping of airspace for drone use has few hurdles and requires no new technology.


CASE STUDY/CONCEPT EXPLORATION - CHICAGO
Drone Zoning and Urban Planning Concept Location, Chicago Illinois. Sutika Sipus 2014.
Drone Zoning Concept in Chicago, Illinois. Sutika Sipus 2014.


Case Study: Urban Planning for UAVs in Chicago
To explore this idea, I have rendered a rough concept drawing of drone zoning in the parks bordering downtown Chicago.  Basing the idea off of a traditional traffic light, green areas are free-use, yellow and orange maintain various restrictions according to the time of day and day of week, while red areas are restricted at all times.


Buckingham Fountain, Chicago, Open UAV Zone. Sutika Sipus 2014.

Open Droning
The green zone is near Buckingham fountain.  This area is a wide open space, with zero infrastructure of critical value.  It should be realized that we design areas where free drone use is available so as to offset the general distribution of restrictions.  A greenspace, therefore, should permit the widest amount of flexibility and opportunity.  Likewise, in such spaces we want to reduce the likelihood of losing the drone or disrupting others in the event of an accident.  Accidents will happen, so it is best to permit a space for those accidents to happen with limited consequence.


Side-View, Zoning for Drones/UAVs in Chicago. Sutika Sipus 2014.

Limited and Restricted Drone Use
In the image above the football stadium has been recognized as a "zero public drone" area.  In this space we can imagine private licensing options for droned cameras and advertising initiatives by the stadium and partners.  However, unaffiliated individuals should not have the right to use their drone in this are.

The yellow and orange spaces represent the Field Museum, the Shedd Aquarium, Aviary, and Observatory.  For the sake of the example, I have suggested that these properties contain their own particular rules that change according to the day, season, or event.  This is not a unreasonable regulation, given that it is common place to create zoning in a similar manner for public parking during weekdays, sporting events, and even according to the weather.

Example Drone Zoning in Chicago. Sutika Sipus 2014.
Alternative Perspective of Drone Zoning in Chicago. Sutika Sipus 2014.

Drone Zoning at Human Scale. Sutika Sipus 2014

Drone Zoning at Human Scale II. Sutika Sipus 2014.

The New Digital Divide: Transforming the Global South into Reliable Data

Transforming the world's most hard-to-access and uncertain landscapes into digital data. Sutika Sipus 2014.
Everyday urban professionals, data scientists, economists, and geographers sit in front of a computer screen and create extraordinary visualizations and statistical methods to unravel the world.  Geographic information systems such as QGIS, statistical programs like "R", spreadsheet softwares like Excel and lines of python code have empowered us with the ability to understand economies at scale, measure and predict public health, monitor pollution and deter violence.  Data is good.

Yet what about cities, states, and nations that do not or cannot generate reliable data?  In his recent book, Poor Numbers, author Morten Jerven reveals the faulty statistics collected and published by government agencies throughout Africa.  Over the last three years that I was in Afghanistan, I witnessed nearly every single aid agency or government research contractor rely upon "perception based" data which means researchers confronted too much danger in the field to collect actual information, but could only ask locals their opinion on matters ranging from conflict to education and corruption.  This method is safe but provides zero validity.  It might as well be make-believe.

The result is the global data gap.  Governments and institutions that can transform intangible social dynamics into quantifiable data can conduct sophisticated analysis and move forward at a faster pace. This sensibility was the foundation of my initiative in Mogadishu, to create a comprehensive map of the city that fused business and residential management with geography.  As my operation was too small to go beyond the proof of concept, the vision was eventually passed via the local government and integrated into a longstanding UN initiative to develop a city planning department which is advancing with some success.  Yet while Mogadishu may be on the cusp of a digital governance revolution, problems persist.  Data dies.  Situations change.  More dramatically, very little of the world is generating the data sets commonly enjoyed throughout the west.

The global data gap is economically inhibitive. Imagine if your company sought a new market opportunity because the markets your normally serve are saturated with your product and your competitors.  Most companies would never imagine distribution in an African nation, partly because of misled beliefs on stability of those markets, but that those misconceptions are ultimately founded on a lack of reliable data.  With no local data, there is no global opportunity.

This is also a failure for companies that already working in data-deficient nations.  A few months ago I had a meeting with Afghanistan's largest tele-communications provider, Roshan, and when I asked about coverage, they could only give vague feedback.  When I asked for data on every household using Roshan to access the internet in Kabul, they could not give this information because Kabul doesn't have a postal address system, so all installations are tied to a person's name and neighborhood, but not a specific address.  In this instance I created alternative solution, where after about three weeks of combing selected neighborhoods, I was able to generate a GPS location for every Wi-Fi network and mobile tower in each area which could then be joined with the existing data.  We could filter Roshan networks vs competitor networks and now had sufficient data to improve marketing and coverage strategies.

Location and evaluation of strength of Wi-Fi access in Kabul, Afghanistan. Sutika Sipus 2014.
Having worked throughout Africa and Asia as a researcher since 2007,  I have developed an array of techniques to get past this problem, focusing on the creation and testing of indirect indicators.  In Zimbabwe economic wealth could be measured by counting the number of water jugs in front of each house.  In the Philipines, one could count denim jeans swinging on the clothesline of an apartment.  In a variety of Somali refugee camps I found that metal roofing materials separated the less-poor from the more-poor.  In Afghanistan I have steadily been testing and re-testing the presence of graffiti as a predictor of social protest and conflict with success.  The advantage of these Rapid Rural Appraisal techniques is that they are safe, fast, efficient, and quantifiable.  To determine an RRA indicator requires extensive time on the ground, but once established, we can effectively measure anything, anywhere.  There are of course other methods, standard survey techniques, but my efforts generate GPS location, culturally relative valuation, and easily shared outcomes.  RRA is not new, but my method of fusing RRA with traditional research methods, GIS tools, and mobile technologies does create a new outcome. I produce valid, quantifiable and mappable data that is customized to the problem and the location, but can accommodate different scales.

Digital Data Collection and Mapping.
Cambodia. Sutika Sipus 2014.
To me, the global data gap is a new frontier of untapped opportunity.  Maybe more people will realize this sooner than later and I'll encounter some digital cowboys, wandering deserts with laptops and satellite phones, their backpacks sagging beneath the weight of external hard drives.  I won't be the only one canvasing the worlds most remote locations.

Maybe soon more companies will ask "what about Nigeria?  what about Ghana or Bangladesh?" and they will need answers.  They will look online and see some global statistics that are 5 years old and impossible to trust.  They will need a fresh perspective they can trust and they can see.  Something they can drop into their software and understand.  Good thing I'm easy to find.


Looking for a little humanity in central Dubai U.A.E.


Over the last few years I've had the opportunity to visit Dubai several times, and admittedly, I've never liked it.  The city is beautiful and expensive but it also doesn't have much character.  In many ways, it reflects all the bad things about urban planning.  Everything is designed to be so refined and perfect according to some particular set of values that the wonderful  spontaneity of urbanism is squashed.  But last week I made a series effort to explore the city and try to get to know it better.  I wandered on foot for several hours, relaxed on the beach, stopped by a few cafes and watched a movie at the mall.   In a city famous for glass towers, it was my goal to find a more human side to the city.  I'm not sure if I really found it that day, but I did at least catch a glimpse, and left Dubai a little less skeptical.

I also collected GPS points along the way, and above is a map documenting my walk through the city.   Below are also some photographs taken.  If the gallery doesn't load you can access them here.


Finding #Kabul on a Map - The Challenge of Acquiring #GIS Data in #Afghanistan


Lately I've been working hard to improve my skills with Geographic Information Systems.  As a Planner, GIS is a critical tool for researching, deconstructing, and analyzing human settlements.  I've been using GIS for several years, yet was never confident in my ability to utilize the software packages or the datasets.  I could do the work, but it was never intuitive.  Fortunately that is beginning to change.   Recently, GIS has taken on a new role in my life as I've been using it to determine and model advance indicators of insecurity.  While there are plenty of competing organizations and individuals out there hoping to find ways to asess the probability and locations of conflict  before it happens, the truth is, all these systems are bulky, expensive, slow, and not feasible for an individual user.  Yet there is a demand among individual users and so my goal is to create a  reliable statistical tool for common individuals with basic internet access, not to reinvent the wheel of security and defense.

Image via Spatial Networks
Surprisingly, the biggest obstacle hasn't been acquiring real-time data. Thanks to recent developments in social media, it has been remarkably simple to acquire and filter information on recent events as they happen.  When a problem takes place in Kabul, I have full details on that situation within seconds and after only a matter of minutes am able to fully assess its scale and location.  Knowing when and where things are happening is the easiest part.

Google Maps - Map of Kabul
Instead, the biggest challenge has been the acquisition of a useful base map.  In short, maps of Kabul are terrible.  Take for example this map acquired from Google.  You will notice that the streets outlined in yellow do not remotely correlate to the actual roads in the satellite image.  Someone should be fired for this.

WikiMapia - Map of Kabul
Other typical map options are equally limited.  In the past I've been a solid user of Wikimapia, as it allows individuals to upload information and draw vector-boundaries around areas of interest, so its useful for studying remote geographies.  It has been of great value when studying Somalia, and it is clear from the example that Wikimapia is densely loaded with relevant information in Kabul as well. Clearly this is better than Google, yet it has one majore flaw, it does not allow one to export the maps into any useable format.

Options do exist out there in the world to obtain high quality geographic data on Kabul, such as found through Spatial Networks, but if you are like me and must do the work with a limited budget, options are slim.  Using ESRI's online ArcExplorer, I was able to pull up a collection of maps for comparison.  Although they look suitable in the small examples to the right, once you actually begin to zoom inward, all feasibility of use at street-scale is lost.  Bummer.

Today I made the breakthrough and found the winner to be OpenStreeMap.org.  It functions basically like google earth, allows one to customize the map like wikimaps, but best all, allows the user to export the map as an XML file.  The result is that I can integrate this map with my datasets and an actually useful product is in the making.   I'm excited about the prospects of this new tool and look forward to sharing updates on its development in the near future.   If any other GIS users out there have insight on ways to obtain useful data and maps for less-documented places like Kabul, feel free to send me an email or something - I'm always looking for new information.