shango.ai Fellows Bright Aboh and Aimable Ishimwe Manzi worked alongside the data science team at Philip Morris International (PMI) on a project leveraging satellite image data to remotely identify different crops. The potential of such technology is vast within the agricultural sector as it generates insights and data on huge areas of land which can be harnessed to better understand ecosystems and improve yields.
The project successfully resulted in the creation of an application that can classify land types, creating the potential for PMIl to apply the technology to locate tobacco fields in order to better support and improve the economic wellbeing of tobacco farming communities in Africa. After the initial impressive results, PMI have offered further contracts to the fellows to explore the technology further.
In a series blog posts, Bright Aboh shares more about his work in remote sensing and highlights the importance of data science in this area:
Having worked in the intersection of data science and remote sensing for a while, I wish to bring to the limelight the amazing benefits shrouded in the unison of these two fields.
Read more here