Update on Project Activities
After our trip to the GIS center on Wednesday, we realized that we had hit a bit of a snag in our attempts to coordinate on ArcGIS online. Unfortunately, due to miscommunication and mistakes made on ArcGIS’ free trial, we were unable to fully transfer our completed map to a new map file on Stanford’s Esri account. However, we talked with David at the GIS center, and with his help we were able to get Stanford accounts and link them to our free accounts. This means we should be able to keep the content that we’ve made on the free accounts without losing it once the free trial period of ArcGIS online expires. Unfortunately, it did mean a bit of delay with moving our actual project forward. We also started work on the final paper and presentation. With the presentation needing to be somewhat complete by Monday, we are definitely feeling some pressure. However, we plan to meet this weekend to sit down and get some real work done. So far, we’ve completed our outline and literature review, so work is in coming along at a decent pace. We haven’t done much other than an outline for our presentation, however, so that’s the main object of our focus for the next few days. There’s definitely going to be a bit of mad scramble in the waning hours of this project, but it’ll all come together by the end! Had an update with David this week! It’s a bit overdue, but the parks department has been a bit busy addressing flooding issues over the past few weeks. It seems like for now we’re just staying the course, and he’s excited to see our final product next week! What We Observed and Learned We continue to learn more about the GIS services offered by different platforms. ArcGIS posed an interesting dilemma because of the format our data was uploaded in making it impossible to share with other people. This meant that after our 60 day free trials were over no one would be able to access the map. Because of this we transferred over to Stanford accounts and re-uploaded all the data and started to reformat the visualization. After this, we received a BI data visualization format from our community partner David but because we do not have accounts yet we cannot see the data visualization aspect yet. However, this weekend we will download Microsoft BI and see what the “ideal” visualization would look like. Though we don’t have any formal experience with the tool, and it’s doubtful we’ll do anything with it at this point in the project, it will be really interesting to see what the San Mateo County Parks Department could do with the data we’ve collected! For the most part, our “learning” in regards to the data sets is over. Every once and a while, however, we discover a new excel function we can use to better organize the data! Critical Analysis / Moving Forward In terms of the data visualization side of the project, to move forward we need to create accounts in Microsoft’s power BI platform and check out the data visualization provided by David. Following this we will need to decide whether to continue with building our own map or simply converting data for them to add to their platform. While we have been asked to simply convert data at this point, we already have the other data visualization almost done and it could offer an interesting alternative for them given the pros and cons that we figure out about their platform. Because of this new development, we feel that the “data” next steps are to simply compare the new data David has given us, compare it to the work we’ve done, and ask ourselves if we want to make large changes. Moving forward with the presentation and paper: right now, the presentation is the first priority. We’ve started moving forward with the paper, but we have yet to come together and really work on the presentation. Since the presentation is coming up next week, we are meeting this Sunday (and probably Monday morning as well) to crank out at least a good preliminary version of the presentation that we will finalize by Tuesday night. In terms of the research we’ve done for the paper, we have done a lot of background research into the history of the land itself. Luckily, the papers and government documents published by the parks have been generative and thorough, which is beneficial because we can work within the framework of the parks themselves. Some of the issues within the data, therefore, have also come to the surface, such as inconsistencies between the what species are actually there vs what species are said to be there. Some of the species’ special statuses (such as being endangered or not) are also out of date, and in fact the list of species in the area that are under threat was last fully updated in 1986. This has changed some of the framework for paper, as we feel it will be important to comment on the quality of the data itself, and why it may be so (i.e. due to lack of funding, etc.). Update on Project Activities
We are finally putting our animal data into ArcGIS online! We managed to divide up our raw data into different species and converted the sheets into CSV files (which are the only files that ArcGIS online will take). We then uploaded all of the files to our shared map. Now that we’ve done this, we can freely manipulate the data in the platform. We’ve sent out a message to the good people at the Stanford Geospatial Center in the hopes of setting up a bigger, potentially more productive meeting. On top of adding the data we are creating notes on the map such as area identifiers to portray the areas that are county parks/land versus private land. What We Observed and Learned This week has been a big learning week in Excel and ArcGIS. We continued our journey in manipulating Excel data, using a combination of filters and formulas to narrow down then separate our camera data. We then faced compatibility issues between Google Sheets and ArcGIS, since sheets isn’t in a format that can be uploaded to ArcGIS. In order to transfer the data, we needed to download the animal data in the form of CSV documents, then re-upload them into ArcGIS one species at a time. This took a bit of tedious work, but the results are promising! Since we’ve uploaded all of the species data to ArcGIS now, we’re starting to learn our way around the tools and features. By mapping out the county land we have figured out that a lot of our camera trapping data is not on/in county land. Thus the conclusions reached by the images and amalgamation of data might not directly correlate to what species and quantities lie in the parks. Critical Analysis / Moving Forward Moving forward, we have begun planning out our final paper and consolidating and completing research. The last push for reaching unreached contacts and community members is also happening this week. We don’t feel that we can write up the paper without adequate time to consider the respective voices properly, so we are investing a large portion of our energy into making those connections as fast as we can. If we cannot find the sources from outside campus (such as from the Muwekma tribe, which has yet to get back to us), we will try to find sources on campus that provide a similar viewpoint (as in the case of the Muwekma Ohlone tribe, there are organisations on campus that have contacts/information). Work has mostly been on the data analysis and processing side of the project this week, and so we have not been thinking on the critical level. This is fine, as we have had to put our heads down and do the necessary work for our deliverable. We will pick up the big picture thinking again as we do our research for our final paper. Update on Project Activities
We continued to work with our ArcGIS map this week including transforming the excel data into the comma separated format readable by ArcGIS and have begun trying different options for the data visualization aspect. We’re having some difficulties using ArcGIS online, so we are getting in contact with the GIS center person (another David), and trying to set up time with him to help us figure out how to make the platforms work. Downloaded Tableau software for data manipulation. Tableau is a software designed to take in large amounts of data and help users better navigate, then visualize it. Though we’ve just begun trying out the tool, we hope that with it, we will be able to better break down the large data sets we’ve been given and visualize them in graphical form. We’re communicating with Dave (our partner) to better coordinate what the results of our Tableau analysis will be. What We Observed and Learned After converting our data into an ArcGIS readable format we discovered all the options there are for the visualization aspects of the data. From individual points to heat maps there are a variety of options for displaying the same data. ArcGIS also has tools like deriving new locations which could prove informative for things like potential puma locations. In discovering all these possibilities, we also learned that it might take more time to fully utilize all that ArcGIS has to offer. After our field day last week, we’ve been working to really put all of our work in context. Specifically, we’re trying to see how we could frame our final project deliverable and report around the concepts of land management and balance between urban and wildlife communities. Since the bulk of our project is fairly straightforward (just data organization and visualization), putting it into the right environment is key to building our understanding of the significance of our work. On a side note, we learned that one of our partners, Tanya, is also working to compile a large database of camera trap data in the Peninsula. At this point we are unsure if she is working on visualizing the data (putting it into ArcGIS or similar). We also don’t know if she will be finished within the timeframe of our project. However, we feel that if we got the chance to work with all of Tanya’s (clean) data, we could see something interesting. Working with that data is almost certainly outside of our original project scope, but the prospect is exciting! Critical Analysis/ Moving Forward With regards to our ArcGIS visual, now that we have minimized the data to its core essentials and have transformed it into a readable format for ArcGIS, what remains are the decisions on how to display the information and what information to focus on. In order to decide this we need to relook at who our target audience is and what point the information is trying to get across. The major things to keep in mind are: How understandable/ readable the maps are - In thinking about this, size and color will come into play as well as decisions about borders and transparency. What seem like aesthetic decisions only will play a role in how easy the maps are to understand. How effectively the map portrays the story we want to tell about the data - We should probably show the maps to some friends who know nothing about the project before we finish it to make sure that it is understandable at all levels of knowledge on the subject. Is there enough/ not too much information to get the point across - While more data means more extrapolations from the data set, more data can also just mean more confusing. We need a good balance of interesting points but not too many that the key points are muddled by inconsequential ones. David has been addressing the interdisciplinary aspect of our project (reaching out to various community members), but unfortunately was out of commission for health reasons this week. Because of this, we were set back on getting qualitative research on the community stakeholders’ opinions. This has caused some frustration on David’s part because of trying to balance external deadlines with responsibilities to the group and to the stakeholders and with taking care of one’s self. This, of course, is a common point of learning, but as this is a project with people outside of Stanford involved, it has reinforced the importance of taking care of yourself in advance and communicating with partners should an error come up so that we stay on track. To that end, a small part of what we’ve learned this week has certainly been simple work dynamics and how to manage responsibilities with delays. During our field trip to the farm this week, Patrick brought up an issue that was echoed by Ramona on our field day in the county park. People - particularly in minority communities - experience a profound disconnection to nature, their food, and by extension the communities to which they are linked. Parks, like farms, are seen as being isolated entities apart from people’s actual lived experience in cities. The consumption of public parks has been commodified much in the same that food has; a prepackaged experience that can be accessed cheaply and without thought for the process involved. Also similar to food, the low access to good quality spaces has impacts on community health and mental wellbeing. The challenge to link people and nature is prevalent, and the absence of this connection is at the root of many issues our society faces today from public health to a sense of community. The work to undo problematic and systemic approaches to both wild and domesticated ecosystems must apply to both parks and our food systems as the problems are intrinsically linked, as are their solutions. Update on Project Activities
Our Team had a productive week where we met with our community partner Dave in San Pedro Valley Park and also met separately as a team to debrief and analyze our existing datasets. On Tuesday February 14th, our team gathered on campus and drove to San Pedro Valley park and met Dave Jaeckel, Ramona Arechiga (San Mateo County Natural Resource Manager) and Courtney Coon (with the Bay Area Puma Project and Felidae Fund). Once there we walked to scope out new locations for the cameras that would be added for San Mateo County’s Wildlife Index Project. We spoke and discussed the techniques for finding an ideal place for the cameras and worked together to install them in several locations. We had hours of conversation with Ramona, Courtney and Dave and debriefed on our conversation on the hour-long car ride way back. Additionally we met on Thursday to further debrief and discuss our field day and find the best way to organize our data for our final deliverable. Our main objective is to format and consolidate the existing data points so that we can best use ArcGIS to represent the information to our client. What We Observed and Learned During our trip to San Pedro Valley Park, we had the opportunity to ask Ramona (the Natural Resource Manager), Courtney and Dave many of our previously unanswered questions. Our notes are detailed below: Puma Facts/Behaviors Pumas (a large focus for local wildlife conservation groups) largely spend their time sleeping during day and hunt for deer and other large mammals at night. Their diets consist 50-80% of deer. Males will separate at 1-2 years old to find their own territory. Males cannot be within 100 square miles of another male or they will kill each other. Land Management Land management is tricky, habitat fragmentation is critical because this means wildlife have less dense habitat. Courtney Coon made the comment, "We don't know what our children in 100 years will want" and commented on the inherent need to make assumptions for future generations in land management decisions. Ramona emphasized finding the highest quality habitat and insulating it, and ultimately recreate it through restoration. Emphasis on eliminating invasive wildlife and plant species. Budget Issues Parks is for greater good, these were formed and protected specifically for human recreation. SM park department is primarily recreation, now trying to improve resource management. Don't have a specific fund for San Mateo Parks. Rather they are funded out of county general fund. Because of this the Parks funding are the first to get cut because parks are not providing essential services (as opposed to health care, food markets, etc.). Operate off of open spaces, survive off of property tax. Excel Data We figured out that much of our collected data is repetitive. We started off with 63000 images and when we filtered out repeat images of the same animal standing in front of the camera (the time stamps are less than ~9 minutes apart). By filtered by the time stamps and through this process we limited our dataset down to 20,000 images. Following this we filtered out images of humans, domestic cats and dogs, and unknown images which eliminated another ⅔ of the photos leaving us with 7200 unique data points for our final deliverable. National Parks vs National Forests Similar to how each park has two different aspects (recreation vs resource management), there are two different federal bodies that govern federally owned lands differently as well. National Parks’ funding and focus is on recreation, but the National Forests’ interests lie in conservation and natural resources. This does not mean it is devoid of human use; timber and mining industries are also affected by National Forests deciding how the land is to be used. San Bruno Mountain San Bruno Mountain was protected from demolition precisely because an engaged community got involved and petition for its protection. However, the butterfly species that used San Bruno Mountain as a habitat provided the political ammunition needed to ensure the lasting preservation of the area and the declaration of the region as a government sanctioned park. Literature Discrepancies According to the data already found by the Puma Project, there are discrepancies between the data in the Critical Linkages Paper and what we are currently observing in the data. This means that in the years that have passed since the data was first collected, the distribution of species may already have changed. It is yet to be determined whether this is positive or negative. Housing Despite the parks not officially being used for human necessities such as housing, the parks actually provide a quiet place for a number of homeless people to sleep. This is hardly a direct reason to keep the parks, but is an interesting service that the parks provide in lieu of what the county fails to offer. Accessibility The park managers are aware of the housing issues in the Bay Area, and are also aware that the recreational services provided by the parks are traditionally services used only by the wealthy. This is frustrating as the parks are free and are a wonderful resource in terms of education and health, but are nonetheless underutilized. It is a goal for the parks to reach more people in the Bay Area, but how this is to be accomplished is yet to be understood. Endangered Species Act The ESA provides a critical legal loophole that is one of the only ways to veto a demolition project. Should an area be proven to sustain a species in danger of extinction, then the area can be preserved in perpetuity so long as the service to the endangered species is maintained Critical Analysis/Moving Forward In terms of mapping the data, the first step ahead involves talking to David, the GIS guru in the Earth Systems library, to figure out the best/easiest GIS software to display the data points we have given it comes from an excel spreadsheet. After choosing a software we will need to choose a base map and the layers to go over it such as park lines and potentially including ecosystem boundaries. Each layer adds another potential facet to our analysis. The next step will involve transferring the data onto the map. The length and ease of this task are highly dependent on the software and our understanding of the software. The software can also either limit or inspire our potential visualizations. Another tool that Dave (our partner) has mentioned utilizing is Tableau, software that allows for the easy graphing and layout of excel data. It doesn’t do GIS mapping, but can create a variety of graphs that compare and contrast different aspects of the data. Dave has yet to fully detail his plans for using Tableau, but one of our team members has some experience with it. When we discuss and define what we want to use Tableau for, we will be able to produce the desired outputs in a fairly short time. Finally we will use the analysis functions provided in the software to reach conclusions about the data we currently have. We still want to continue reaching out to the few contacts who have yet to respond to our data requests, along with touching base with a contact that didn’t think they had data for the regions we’re focusing on. Though they insist on this, we feel that (politely) asking them to provide what camera trap data they do have couldn’t hurt. Since the camera trapping program is intended to result in a much larger-scale Wildlife Picture Index, having data a little outside our current parameters could still be useful. We may end up discovering important insights from the data anyway. Update on Project Activities
The biggest event of this week was our team check-in with Dave on Tuesday. We were able to take about 45 minutes to talk through the work we’ve done and get his take on how we are going to format the data we gathered. Unfortunately, we still haven’t gotten information from all the organizations, but we began to consolidate the data we do have. This check-in allowed us to make sure we were on the right track and that the end product we envision continues to match that of our community partners. Organizing the data is proving to be a bit of a challenge as well. As we mentioned before, the data we received from the Felidae Fund alone was over 60,000 rows, so combing through them to get a full sense of scale is a little intimidating. However, with the magic of copy-pasting, we’ve been able to make progress in organizing the mess and getting unique data. For example, the 6k+ rows contain multiples of camera locations. By filtering the spreadsheet to only show unique latitude and longitude numbers, we can accurately pin the camera locations to actual maps in our GIS software. We’re still reading up on background/context literature on the subject of “critical linkages” between the parks. The issue of connectivity is one that we’re getting more and more familiar with, and it’s interesting to see what various sources say on the topic. What We Observed and Learned Data observations: The spreadsheets we have currently include columns like date, time, species observed, latitude/longitude, and whether the photo is “unique” (the first photo showing that animal) or not. As far as organizing the data goes, we may only need to add a column specifying the original source of the data (i.e. “Felidae Fund”), or we could separate the various spreadsheets by “sheet” and label each sheet differently. The real learnings, I feel, have been from trying to either sort or isolate data so that it could easily be integrated into GIS platforms like ArcGIS online. There’s definitely still some struggle in doing so, but we’re making baby steps forward in terms of progress. Contacts have been made with a variety of peripherally related Bay Area communities and we are hoping to hear back from them soon. The insect museum in Berkeley, the San Francisco Bay Bird Observatory, the Muwekma Ohlone Tribe, and Outdoor Afro have all been contacted, and we are waiting for responses from them. In our call with Dave earlier this week he was in support of looking into the interdisciplinary aspects of the project, and that confirmation has revitalised our efforts into researching the issues of park accessibility. Also, while we had assumed that the broad scope goal of our project was to protect our parks, we weren’t certain until we had that conversation with Dave. He made us aware of the fact that in issues of government budget cuts, park services are frequently the first to go, and he confirmed that this data may be very important in the face of an unstable political and financial climate and the pressures of urbanization. We are now much more confident in moving forward now that we are certain we are on the same page. Critical Analysis/Moving Forward The main priority moving forward is choosing a GIS platform to use and creating a visualization for the data we have collected. This task carries with it the complication of figuring out how best to display the data. In order to achieve maximum benefit, the user display must be easily understood by the target audience while the database to display aspect must be easily understood by future editors of the data. Good labeling and explanations where useful or needed will prevent the display from being esoteric like the CEQA document. This point was also brought up by the Salinas group in their quest to create an easily understood questionnaire and we see valid ramifications to our project. A highlight in the near future: (next Tuesday, February 14th) we are headed as a team to the San Pedro park to install tracking cameras to create some of the data they will add to the database after we hand the project over. Looking over the data we have been given sets a frame for the data we need from our photos such as latitude and longitude as well as making sure the date and time are correct in the camera so later the data will be accurate and perhaps tell a larger story. Seeing the sites should broaden our view and understanding of the concept of capturing the photos and their potential effect. |
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