[Gsoc-orga] GSoC 2025 Project Proposal: Analyzing Urban Expansion vs. Agricultural Land Loss using Historical OSM Data

[Sarah Hoffmann]

Hi Ansuman,

I'm sorry to say that you are a bit late for proposing a completely new
idea. We cannot start looking for mentors 48h before the deadline.

Regarding the specific project, I'd just like to point out that you may
have misunderstood how OSM historic data works. This data contains a
history of editing in OSM and that is not necessarily a reflection of
actual changes in the world. So the data is not suitable for your
purpose.

Kind regards

Sarah

On Sun, Apr 06, 2025 at 11:02:32PM +0530, Ansuman Mahapatro wrote:
> Dear OpenStreetMap GSoC Organizers,
> 
> My name is Ansuman and I am currently pursuing the MITx MicroMasters
> program in Data Science on edX, building upon my Bachelor's degree in
> Mechanical Engineering. This background has instilled in me a strong
> analytical mindset and a passion for data-driven solutions.
> 
> While I am in the process of developing expertise in areas such as
> geospatial analysis and working with OpenStreetMap data, the potential of
> this project – "Analyzing Urban Expansion vs. Agricultural Land Loss using
> Historical OSM Data" – deeply resonates with my interests in sustainable
> development and leveraging data for societal good. I am particularly
> inspired by the possibility of using OSM's rich historical information to
> understand and visualize critical land-use changes.
> 
> Although my direct experience with the specific technical skills required
> for this project (such as in-depth use of the Overpass API, Osmium, and
> geospatial libraries like GeoPandas/Shapely) is currently limited, I am
> actively learning these technologies as part of my data science journey. I
> am a dedicated and quick learner, and I am confident in my ability to
> acquire the necessary skills with the guidance of an experienced mentor. I
> am eager to contribute to this project and believe that with mentorship, I
> can make meaningful progress in developing the proposed tool and analysis.
> My enthusiasm for this topic and my commitment to learning make me a
> motivated candidate for this project.
> 
> Project Idea:
> 
> Urban growth often leads to the loss of valuable agricultural land,
> impacting food security and environmental sustainability. This project aims
> to develop a tool to quantify and visualize this trend using
> OpenStreetMap's historical data.
> 
> The proposed solution involves:
> 
> 
>    - Data Acquisition: Developing methods to extract historical landuse
>    data (e.g., using the Overpass API with date filters or processing
>    historical OSM data extracts) for a specified geographic region and time
>    range. This will involve querying and filtering OSM data based on tags like
>    landuse=residential, landuse=farmland, etc.
>    - Spatial Analysis: Implementing functions to calculate the area covered
>    by urban and agricultural land uses at different time points, identify
>    areas of land-use change (agricultural to urban), and compute summary
>    statistics (e.g., total agricultural land lost, rate of urban expansion).
>    Libraries like GeoPandas and Shapely in Python would be crucial here.
>    - Visualization: Creating visualizations to effectively communicate the
>    results, such as maps showing land use at different times, change maps
>    highlighting areas of transition, and charts illustrating trends in land
>    cover.
>    - Tool Development: Packaging the analysis into a reusable tool (e.g., a
>    Python library with a command-line interface or potentially a web-based
>    application) with clear documentation.
> 
> OSM Relevance:
> 
> This project directly leverages OpenStreetMap's core strength: its rich
> historical data. By analyzing landuse changes over time, we can demonstrate
> the value of OSM data for understanding and addressing critical real-world
> challenges related to land management and sustainable development. The tool
> developed would be a valuable asset for researchers, planners, and the OSM
> community.
> 
> Technical Skills:
> 
> I have a foundational understanding of:
> 
> 
>    - Python programming
>    - Data analysis concepts and libraries like Pandas and NumPy (acquired
>    through the MITx MicroMasters program)
>    - Problem-solving and logical thinking (developed through my engineering
>    background)
> 
> I am actively learning and eager to gain practical experience in:
> 
> 
>    - Accessing and processing OpenStreetMap data (Overpass API, Osmium)
>    - Geospatial data analysis (GeoPandas, Shapely)
>    - Data visualization techniques
>    - I am highly motivated to learn these skills under the guidance of a
>    mentor and contribute effectively to this project.
> 
> 
> Project Scope:
> 
> I believe this project is well-suited for a 350-hour GSoC project,
> especially with the support of a mentor. I am committed to dedicating the
> necessary time and effort to learn and contribute meaningfully. The
> deliverables would include:
> 
> 
>    - Progress towards a working tool (Python library/application) for
>    querying and processing historical OSM landuse data.
>    - Development of functions for calculating land-use statistics and
>    generating visualizations (with mentor guidance).
>    - Documentation of the learning process and the developed components.
>    - I am excited about the possibility of contributing to the
>    OpenStreetMap project and would be particularly grateful for the
>    opportunity to work with a mentor who can guide me through the technical
>    aspects of this project. I am eager to learn and contribute to the OSM
>    community.
> 
> 
> Thank you for your time and consideration.
> 
> Sincerely,
> 
> Ansuman Mahapatro
> 
> *P.S.* I would also like to acknowledge the helpful discussions with a
> language AI assistant that aided me in formulating and refining this
> project idea and proposal.

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