The world we live in is changing and the consequences of our actions are becoming increasingly apparent. Climate change and deforestation are two of the most pressing issues that we face today, and they are interconnected in many ways. The future of our planet depends on the health of our forests, and we need to ensure that they are protected and managed in a sustainable manner.
This project involves the development of a library aimed at facilitating the analysis of data from the land sector management dataset; designed and equipped with the tools (sub-packages) and features necessary to analyze data from the same. This data will help us understand the ecological conditions in forests around the world, and enable us to conduct research into the growth and carbon sequestration of forests.
The library will be used to analyze different geographical locations, allowing us to get a comprehensive understanding of the state of our forests. This information can then be used to create models that will help us predict the future growth and also assist with accurately and affordably estimating greenhouse gas emissions and removals from forestry, agriculture and other land uses.
| Category | Rating |
|---|---|
| Difficulty | Medium |
| Priority | Medium |
| Skills | Python, Data Analysis, Django/Flask, Git |
| Project Size | Large (350 hours) |
| Preferred Contributor | Student/Professional |
| Mentors | @aornugent |
The goal of this project is to develop a Python library to ease the process of analysis of land sector dataset reducing the hassles of writing several lines of code and time consumption allowing the individuals to focus more on findings and other important factors.
This project entails:
- Studying the previous land sector data analysis notebooks and to prepare a note of important tools (sub-packages) and features to be embedded into the library to ease the process.
- Planning the architecture and interaction of functions within the library, allowing it to handle errors and exceptions to avoid mismatch and wrong outputs.
- Developing a python library with all the necessary components and features.
- Preparing a clean and detailed documentation explaining the commands to bring the library to action assisting non-technical individuals carry out the investigation on the dataset without worrying much about the code and errors.
For this project, the developer needs to have experience with Python and Data Science alongwith the ability to write clean, well-documented, and reusable code. Understanding of web framework - Django/Flask would be preferred for further development and escalation of the project.
- Land Sector Dataset: https://github.com/moja-global/Land_Sector_Datasets
- Previous Research Notebooks: https://mojaglobal.slack.com/archives/C01QQ2R8GV8/p1669501857168749
Go through the Land Sector Dataset. Join the slack workspace and have a look at the previous research notebooks to find the pattern of analysis and common snippets and tools that have been assisting the contributors with their investigation and prepare a plan of how to move ahead and approach the development task.