Hello, I'm glad to see you again for our third week of Geodesign: Change your World. This week we're going to begin to put some flesh onto the Geodesign bones, or the components that we outlined last week. And I'll start to show you, how those are deployed in the service of geodesign. To facilitate this, I thought it would be helpful to explain these as the three C's of Geodesign. These three C's are, complexity, computation and collaboration. We'll begin with complexity, since you've heard me use that term several times now in the past two weeks. When well I know I said Geodesign is exciting, I also know, I never said it's easy. That's because Geodesign is best suited for the tough challenges. What is perplexing and sometimes even hard to get your head around. I want to tell you about the first time, I became a true believer that the Geodesign process is very effective. Dr. Karl Steinitz who's one of the chief proponents of Geodesign. Was a visiting professor at my university and he participated in a course that was addressing at the time an emerging energy extraction issue in my state of Pennsylvania. Marcellus Gas "Play" as its been called is very complicated. And I'll admit I wondered, how in a 15 week studio they were going to make even a dent in that topic. And on top of that Dr. Steiner's only residence for the first half of the semester. So imagine my surprise when I participate in project reviews at mid semester, and saw a level of resolution, and specificity, I didn't even think was going to be possible for an entire semester of work. This Geodesign challenge has now been run as a studio for the past several years. Each time taking another aspect of the Marcellus shale gas extraction impacts. Because of my familiarity with that project, I'm going to use The Marcellus Gas case study from last week to help illustrate our 3 Cs this week. Honestly, it's not like a I'm a fan of the number 3, although I am one of three siblings in my family, but it turns out the best way to describe complexity is with. Three Ps: the complexity of the problem, place and people. Your awareness about the complexity of problems we're facing should be growing as we review the change agents each week. Our challenges both locally, and globally are increasingly multi-faceted. I trust you've noticed that the change agent cards, are in fact not discussed in isolation. In order to make a topic comprehensible, is discussed singularly on a two sided card. But each of the drivers of change topics is also discussed as part of the, the STEEP framework, the social, technological. Economic, environmental, and political aspects. The level of cos, complexity is sometimes dependent on the scale of the place, or the extent of the problem. We'll discuss that more next week. The second P is the complexity of place. Greek philosopher Aristotle is attributed to the saying, The whole is greater than the sum of the parts. For example, let's consider the parts needed for a building: a pile of bricks, plumbing fixtures, wood flooring, paint, and so on. These all have much more value when they're assembled into a house, than as separate entities. This is the same concept for a place. Consider our discussion in week one. When we talked about location, location, location. Well, if you look at the parts that make up a place; the trees, building, paving, people, wildlife, and what about what's underground, there are often pipes, such as water, and sewer lines, there's even bedrock in places, and on, and on. Taken individually, each component is interesting. Because when they're combined in just that certain way, unique to that place, that is becomes apparent that the whole is greater than just adding up all the parts. This complexity of the interconnection of all the parts of a place is at the root of the science of ecology. This is based on the recognition that everything has a role, or a niche within a system or a place. Trying to understand all the roles of all the parts makes each place quite complex. Even if at a quick glance a place doesn't appear to have much going on. Our third P in our definition of complexity in geodesign is people. We'll talk more about that in just a minute, when we're looking at the third C. But here the point is to emphasize because a place is complex, it follows that there will need to be many people involved. Such as experts who understand the specifics of science or engineering issues and there, then there are all those people who live and work in that place. This people of the place wheel, we will discuss more next week. I'm showing it here to illustrate the complexity inherent in just the local, people part of the design, process. Referring then to the Marcellus case study, the three P's of complexity, in a very short overview are first, the problem, which are the impacts of the Marcellus Gas drilling and transportation infrastructure. Because of unprecedented speed of this aggressive development. The place is our three counties in northeastern Pennsylvania called Wilds. There forests, farms and small towns. It's also fragmented political jurisdictions. And the people, there's a population about 6500, call them regular people, the citizens. The shale gas industry and related businesses, scientists, others concerned with environmental impacts. Those interested in economic implications. Government authorities, tourists, recreationalists such as hunters and hikers. So, how does one deal with all this complexity? Well this is where collaboration and computation come into play. So, let's first look at computation and the supportive role that, that can play. So, now you and I may, we may be pretty sharp, but in reality, our human mind can only keep track of so much information at once. Thankfully, technology continues to evolve in ways that make dealing with all this complexity more manageable. So, I'm going to quickly discuss how computation, or more precisely, the use of digital computing power can assist in three important ways. Here I go again with those threes. So the first is analyze and manage information. The second is measure performance, and illuminate and reveal consequences, and the third is to dynamically visualize alternatives. Last week we discussed the value of mapping the data about a place. Important to consider is that all that data has attributes that can be analyzed. We can post questions about a location, such as which soils are too unstable or too wet to support development. Or shown here. We can assess development potential by looking at natural hazards. All these can then be weighted, or in other words, we can place an emphasis on certain aspects in order to develop suitability maps. So analysis provides support to the design process by telling us where our desired project should, or maybe should not go. Shown here, the spots in red are the places to be avoided. Or low suability based on the parameters that were set. Another example has combined land use and demographic information, to determine where parks are needed in US cities. the data that the trust for public land has analyzed falls into three categories. The acreage of park land. Service and investment, and how accessible the parks are. This information was then ranked for comparison with other cities. You can see the categories of data arrayed along the top of this chart. Let's look closer at Omaha, which is at the bottom row of the chart. When this is mapped spatially, gaps and accessible parkland can easily be seen. Orange and red indicate locations in need of parks. This next example is is from the Cape Cod commission which is in the US state of Massachusetts. They devised a visually powerful way to help citizens understand data about their place. You just can zoom in to explore different areas, and when selected, an array spins to quickly display the analysis of all factors. Factors that are specific for that particular spot. This clearly shows the power of computing as there's a lot of data at work behind the scenes, in order to make the information more understandable to everybody. Our second point in regard to computation is about measuring. And we want to understand, how well a design performs relative to certain criteria. Recall from last week the importance of decision makers. They established metrics for the design and how well it should perform. Computation such as comparing factors is used to reveal the consequences of various actions. This measuring performance computation step is one of the things that distinguishes Geodesign. And in particular the ability to understand the level of performance on the fly. Real time feedback is extremely valuable for engaging community, and recognizing that different choices will have different consequences, and impacts on their goals. This example provided by GIS software company ESRI. Shows a planned view of a design solution where the different colors represent different types of land uses. The measurement indicators, are displayed on the bottom there, in a chart and a graph. When using this on the computer, as the design is manipulated and changed, the chart adjusts immediately. In this case, it's displaying land use percentages, and ecological impact of open spaces. The next example of measuring is courtesy of the University of British Columbia in Canada. It's from a case study you'll review in more detail next week. They've modeled different housing units by each one's energy emissions, and transportation indicators. As community participants work with these, and explore various development scenarios, the designs impacts are shown by calculation widgets. The widgets from left to right show travel distances, and modes of transport, dwelling types, and individual missions, which is actually calculated, and tied to the dwelling types, and transportation. Looking at our Marcellus case study from last week, we have another example of how measurement can be valuable to help community understand performance related to their desired criteria. The Marcellus shell team modeled scenarios based on three different goals. This is a quick view of the behind the scenes work that goes into putting together models in GIS. Without knowing all the details, you could still recognize that there are relationships, and hierarchies, and a process that they are going to run through in their modeling. The resulting modeling, or measuring, reveals distinctions what can be, which can be displayed graphically. As different pipeline routes. As well as listing of metrics, outline impacts on each of the modeled criteria, which is shown below each pipeline route in this image. The last point regarding computation is to visualize alternatives. Now there are many ways that computing power can assist with this. And it's really exciting stuff. Anything from computer graphics packages that allow photo realistic renderings. To something called procedural modeling, which uses rules to create 3D designs on top of existing maps. There were several links in this week's readings, and in the resources section that provide further examples of all these technologies. Here's an example of an Asian city that uses rules-based 3D modeling software called City Engine. In this example parameters are set to preserve views from a new train station to a historic tower, and other landmark sites. The visualization shows how the building placement avoids blocking the views. There are also concerns about the impacts of new development of views from the lake, so building height restrictions are in place. And the softer you can take the building parameters and adjust them on the fly, and the results are displayed in real time. One last example of visualization, is from weeks Marcellus case study. As you probably noticed when looking at the other 3D examples, most people tend to understand perspective use better than two dimensional plan views. This relates to back to our week one discussion about spatial thinking. This 3D view is more akin to how we relate to our world. These two renderings here were developed with the aid of a computer. And the details were hand drawn. And they show the visual impact of two different approaches to placement of infrastructure on the exact same site. To wrap up our discussion on computation, referring to our week two Marcellus case study, that project used computation in several ways. First, they showed the existing situation. Second, they illuminated anticipated changes. Third, computation provided insights into alternative ways to address the changes. Fourth, they examined and evaluated the options and any trade-offs that the need to be considered. And, fifth, they visualized a future informed by the community's priorities. Now, before moving into collaboration, our third C for this week, I do have to issue a caution about technology. Many are rightfully very excited about the ever evolving capabilities of these digital technologies, and some imply that this is Geodesign. I'm sorry, but no, these are only tools. Albeit they're essential tools, but they are just another key part of the geodesign process. These digital tools alone cannot be geodesign all by themselves. If you're only using tools, you're truncating the process, which produces a higher likelihood of failure. However, digital computation does provide key leverage when working with people. And that brings us to collaboration. Our third and last C for this week. I want to start this brief discussion about collaboration by asking you to think back about creative change. Remember that from the first week? Typically creative problem solving is not the domain of a lone thinker. Most of the world's important innovations emerged out of teamwork. For example, millions around the world use this everyday. The iPhone. And it's from a team at Apple. Innovation nearly always comes from collaboration, bringing diverse ideas together. Since we know we're addressing complex challenges with Geodesign, I hope it makes sense to you that we need multiple perspectives at the table. One of the biggest questions with collaboration is, who should be brought together? There are those champions of Geodesign, who believe the greatest asset for this is that it brings together science and design. Traditionally, there have been barriers through scientists and designers working together, but I and others believe that through the aid of computation, what we just talked about, and. Focusing on what we have in common, these barriers can be overcome. A key thing designers and scientists share is that both are seeking answers. And both are doing this through periodicity. Scientists are looking to better understand the world as it is, they're seeking universal truths. Whereas designers are looking to discover how the world can be. They're seeking specific solutions. Understanding this, plus using computation to facilitate the dialogue, will help promote productive working relationships amongst scientists, and designers. The Geodesign process fills a gap between science and design, and this is important because both have key skills that need to come together. Of course all the other people we've mentioned before are part of the collaborative process as well. And Dr. Steinitz advocates using a frame work to structure the interactions that foster collaboration. We'll discuss his framework for Geodesign in week five. In the Marcellus Shale case study the collaboration was between the experts, who in this case were university students and their professors. And members of the community science volunteer program. That program empowered local citizens as citizen scientists to run community based, not expert based workshops to engage with local citizens. So starting with the case of these this week, and for the final two weeks, I hope you'll be sure to look at all of these through the lens of what makes them complex. How is computation involved? And who participated in the collaborative effort on that Geodesign process? I realize that some of this can maybe seem a bit overwhelming. But that's precisely why we want to use Geodesign. Recall my skepticism about the Marcellus Shale project, and how a Geodesign approach is illuminating creative solutions to that tough challenge.
