Abstract
The substantial decline in elephant population, primarily caused by human-elephant conflict, necessitates the proactive engagement of conservationists to devise and implement effective monitoring strategies. Monitoring elephants is essential for gaining insights into their movements and ensuring the preservation of habitat corridors. Conservationists have increasingly shifted towards adopting passive acoustic monitoring as an affordable and non-invasive method for determining the spatial distribution of wild elephants through acoustic localization. The main challenge with remote sensing techniques like passive acoustic monitoring is the time-consuming data analysis, which hinders real-time tracking of elephant whereabouts. To address this issue, the study presents Eloc-Web, a web application that visualizes real-time elephant locations using elephant vocalizations recorded by acoustic sensors in the wild, which utilize machine learning to classify the captured audio. Eloc-Web has taken into account the uncertainties associated with classifying captured audio using machine learning models. This ensures that the potential uncertainty of whether the captured sound truly belongs to an elephant is appropriately considered during the visualization process. By following the user-centered design process, the study integrates expert knowledge from elephant ecologists to inform the design and functionality of the application, ensuring its relevance and usability. Eloc-Web, assessed through the System Usability Scale, ranked it in the top 10% of scores, demonstrating above-average user experience and promising potential in assisting elephant ecologists in studying and conserving elephant populations with real-time data visualization.
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Data availability
The data generated during the user-centered design process of this research are available in anonymised form upon request.
Notes
A nonprofit project protecting elephants, rainforests, and communities to preserve shared habitats, biodiversity, and ecosystems.
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Acknowledgements
We acknowledge the partial funding received from the University of Colombo School of Computing through the Research Allocation for Research and Development, under Grant No: UCSC/RQ/2023/GeoMatics/01. This financial assistance greatly contributed to the success of our research endeavor by covering various research-related expenses.
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Appendices
Appendix A. Discovery Research for Eloc-Web
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1.
Briefly describe your work/ experience in the field of elephant ecology.
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2.
What is your relation to the Eloc project?
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3.
What information would you be able to derive from knowing elephant location points across a timeline?
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4.
How can that information (e.g., behavioral patterns) be derived from the location data?
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5.
What are the environmental factors that influence elephant behavioral patterns?
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6.
Is it important to be aware of the uncertainty of the elephant’s location? Why do you say so?
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7.
Please explain your answer to the above question.
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8.
Have you used any applications to analyze elephant behavior using localization/ movement data?
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9.
If yes, what application(s) have you used?
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10.
Are you familiar with MOVE Bank?
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11.
What have you used MOVE Bank for?
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12.
If you have used MOVE Bank, what do you like about the application?
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13.
Was/Is there anything you often looked for on MOVE Bank that is missing or hard to find?
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14.
What haven’t we asked you today that you think would be valuable for us to know?
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15.
May we contact you if we have any other questions or for possible further research for this project?
Appendix B. User Interview Questions
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1.
How do you typically use location estimation data to inform your research and conservation efforts?
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(a)
What data would be most important to understand the distribution and the behavior of elephants? (eg: the surrounding environment)
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(b)
What are some of the most important factors to consider when tracking elephant populations and movements, and how can the web application help address these factors?
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(a)
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2.
Do you use any software or application currently to visualize or analyze the data that you collect about elephant populations?
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(a)
Can you tell us about your experience using that application?
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(b)
Are there any limitations or challenges you face when using the application?
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(c)
What are some of the key areas for improvement?
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(a)
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3.
What are some of the key features that you look for in a web application for monitoring elephant populations?
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(a)
What types of visualizations and tools are most helpful for you?
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(b)
What specific information would you like to see on the map?
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(c)
What would be the most helpful way to visualize that preferred information?
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(a)
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4.
How important is accuracy when it comes to estimating the spatial distribution of elephants? Are there any particular sources of error or uncertainty that you find particularly challenging to deal with?
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5.
How about the certainty of the location estimates? Do you like the way we have represented it on the map?
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6.
Are there any specific use cases or scenarios you want to see addressed in a web application for monitoring elephant populations?
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7.
How frequently would you expect to use a tool like this, and in what contexts?
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8.
How often do you need to update the information you see on the map?
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9.
How do you share and collaborate on elephant monitoring data with other researchers and conservation organizations?
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10.
Are there any other specific suggestions or feedback that you have for the development of a web application for monitoring elephant populations?
Appendix C. SUS - the System Usability Scale for Eloc-Web
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1.
I think that I would like to use Eloc-Web frequently.
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2.
I found Eloc-Web unnecessarily complex.
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3.
I thought Eloc-Web was easy to use.
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4.
I think that I would need the support of a technical person to be able to use Eloc-Web.
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5.
I found the various functions in Eloc-Web were well integrated.
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6.
I thought there was too much inconsistency in Eloc-Web.
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7.
I would imagine that most people would learn to use Eloc-Web very quickly.
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I found Eloc-Web very cumbersome to use.
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9.
I felt very confident using Eloc-Web.
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10.
I needed to learn a lot of things before I could get going with Eloc-Web.
Appendix D. System Usability Scale (SUS) Score
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Dissanayake, I., Piyathilake, V., Sayakkara, A.P. et al. Eloc-Web: Uncertainty Visualization and Real-Time Detection of Wild Elephant Locations. J geovis spat anal 8, 7 (2024). https://doi.org/10.1007/s41651-023-00169-7
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DOI: https://doi.org/10.1007/s41651-023-00169-7