Disclaimer:
Please be aware that the content herein has not been peer reviewed. It consists of personal reflections, insights, and learnings of the contributor(s). It may not be exhaustive, nor does it aim to be authoritative knowledge.
Overview
Prepared by (Name of the experimenter)
Betty Chemier
On date (Day/Month/Year)
15/02/2024
Current status of experimental activity
Completed
What portfolio does this activity correspond to? If any
Collective Intelligence for the Climate Action
What is the frontier challenge does this activity responds to?
Disaster and Risk Management
What is the learning question(from your action learning plan) is this activity related to?
How can data integration provide us with a better understanding of territorial situations and thus enable us to take better actions?
Please categorize the type that best identifies this experimental activity:
Pre Experimental (Trial and erros, prototype, a/b testing)
Which sector are you partnering with for this activity? Please select all that apply
Public Sector, Academia
Please list the names of partners mentioned in the previous question:
Municipio de Panama
Florida State Univiersity - Urban Risk Center
Design
What is the specific learning intent of the activity?
Understand the dynamics that have been transforming the territory, and how these dynamics affect the occurrence of disasters in the Juan Diaz River basin.
What is your hypothesis? IF... THEN....
If you have visual access to detailed information about the territory and its risks, it will contribute to the understanding and prediction of urban flood risks, thus improving planning and reducing adverse impacts.
Does the activity use a control group for comparison?
No, it does not use a control group
How is the intervention assigned to different groups in your experiment?
Other
Describe which actions will you take to test your hypothesis:
Data Collection: Through our collective intelligence process, a total of 30 layers of information have been gathered, obtained both from open sources and directly from various actors and institutions.
Integration in Platforms: The information collected has been uploaded and consolidated in the Tableau and ArcGIS platforms, allowing its efficient integration and facilitating territorial analysis in a comprehensive manner.
Multivariable analysis: An interactive viewer is developed that uses the information integrated into the aforementioned platforms to generate a multivariate analysis that allows. explore key data related to flooding in the Juan Díaz River basin.
Visualization of results: The multivariate analysis of the information layers is visualized using Storymaps, offering a visual narrative that illustrates the evolution of the Juan Díaz River basin and the current and future impacts, providing a holistic understanding of the situation of the basin in the present and over time
What is the unit of analysis of this experimental activity?
The pilot seeks to generate robust evidence through the presentation of collected data and territorial analysis, thus supporting the effectiveness of the data viewer in understanding and managing flood risks. This evidence seeks to inform future risk and disaster management management strategies and planning.
Please describe the data collection technique proposed
The pilot seeks to generate robust evidence through the presentation of collected data and territorial analysis, thus supporting the effectiveness of the data viewer in understanding and managing flood risks. This evidence seeks to inform future risk and disaster management management strategies and planning.
What is the timeline of the experimental activity? (Months/Days)
2 months
What is the estimated sample size?
10-49
What is the total estimated monetary resources needed for this experiment?
Between 1,000 and 9,999 USD
Quality Check
This activity is relevant to a CPD outcome, The hypothesis is clearly stated, This activity offers strong collaboration oportunities, This activity offers a high potential for scaling, This activity has a low risk
Please upload any supporting images or visuals for this experiment.
Please upload any supporting links
What are the estimated non- monetary resources required for this experiment? (time allocation from team, external resources, etc) If any.
Results
Was the original hypothesis (If.. then) proven or disproven?
Proven
Do you have observations about the methodology chosen for the experiment? What would you change?
From design to results, how long did this activity take? (Time in months)
2 months
What were the actual monetary resources invested in this activity? (Amount in USD)
$5,000.00
Does this activity have a follow up or a next stage? Please explain
We are currently signing an MOU with FSU to transfer the ownership of the dashboard to their Urban Risk Center. They will give the viewer the proper maintenance and follow up with its use.
We are also planning a hackathon of urban solutions for that area using the viewer as the base source for designing solutions.
Is this experiment planned to scale? How? With whom?
Some institutional counterparts have voiced their interest of extending the capacity of the dashboard to the whole of Panama City. Some funding from OCHA might be used for that.
Please add any supporting links that describe the planning, implementation, results of learning of this activity? For example a tweet, a blog, or a report.
Considering the outcomes of this experimental activity, which of the following best describe what happened after? (Please select all that apply)
This experiment led to partnerships
Learning
What do you know now about the action plan learning question that you did not know before? What were your main learnings during this experiment?
We have learned that there is indeed a value in integrating data to understand in more depth the territory and that this information can be crucial the take better and more informed decision when it comes to urban planning and infrastructure. Some of the resulting analyses in that sense are the following:
Urban Growth and Flood Exposure: The results highlight the trend of accelerated urban growth in the Juan Díaz River basin, especially since 2000, which has occurred predominantly in vulnerable areas, such as stubble areas, grasslands, forests and flood-prone areas. exacerbating exposure to flooding.
Recurrent Vulnerability in the Middle and Lower Basin: The vulnerability situation is more pronounced in the middle and lower basin, with the Juan Díaz district being the main focus of impacts on people (44%) and homes (44%). Recurring vulnerability affects specific communities, underscoring the need for sustainable approaches and long-term solutions.
Multi-hazard Condition and Climate Change: The Juan Díaz River basin presents a multi-hazard condition, in addition studies on sea level rise indicate that areas currently affected by floods will also be exposed to this phenomenon, highlighting the importance of addressing climate change in a manner integral.
Mostly Technical Approach to Solutions: It is highlighted that the solutions proposed have historically been mostly technical, focused on engineering for hydraulic water management, with few recommendations that incorporate regulatory changes, nature-based solutions or community participation.
What were the main obstacles and challenges you encountered during this activity?
Getting the layers of information from institutional counterparts.
Who at UNDP might benefit from the results of this experimental activity? Why?
Team working on project in the area of study, team needing to build similar tools for integrating data for other project.
Who outside UNDP might benefit from the results of this experiment? and why?
Municipality of Panama, Resilience directions, Urban Planning directions, Academia.
Did this experiment require iterations? If so, how many and what did you change/adjust along the way? and why?
Yes, we have had several rounds of iteration with the consultant that supported us to create the storymaps.
What advice would you give someone wanting to replicate this experimental activity?
Don't wait until you have all the layers you need to start the viewer because you might lose time waiting to get the information.
Can this experiment be replicated in another thematic area or other SDGs? If yes, what would need to be considered, if no, why not?
Yes, this viewer for integrated data can be replicated in many different areas. For example, we have build a similar dashboard for Solid Waste Management.
How much the "sense" and "explore" phases of the learning cycle influenced/shaped this experiment? In hindsight, what would you have done differently with your fellow Solution Mapper and Explorer?
This experiment was part of a design studio for cliamte adaptation, the entire process latest about 10 months
What surprised you?
11Sustainable cities and communities
13Climate action
17Partnerships for the goals
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