Understand operational risk and viability

Mosaic provided a coking coal investor, decision analysis by testing operational resilience of its barge logistics plan. We stress-tested total barging day scenarios by forecasting the cumulative effects of deforestation and near-term climate change in the watershed for period 2030. AI driven landcover projection and regional climate modelling were used to estimate the cumulative impacts on production and investment viability.

Reducing guesswork on landscape vulnerability 

 

We helped an international palm grower evaluate their conservation strategy over a 20 year + planning window. Using a deep learning workflow, we tested and ranked community drivers of forest loss, projected forest risk and identified opportunities for impact across the commodity landscape

Sizing up NDPE risk with AI

We helped investors better understand NDPE risk in a palm oil commodity landscape. Our workflow, driven by predictive algorithms tested and ranked forest resources vulnerable to loss and conversion across mill supply shed. Mosaic’s solution provided an empirical basis to factor emerging ESG risk due to forest conversion, fine tune risk management planning and action plans.

Red flags in mineral supply chains

Our remote diligence helped mining experts Britmindo assess the actual governance style at a 5,000Ha, low CV coal property supplying the Sumatran power grid. Without ‘boots on the ground’, we enabled analysis of mine development rates, potential sterilization and restoration liabilities due to communities between 2015-2019. Our proprietary hybrid detection methods, combining radar and optical satellite data streams, cut through persistent clouds, smoke and haze. Our Machine Learning procedure distinguished mining from vegetation, providing  independent and reliable analysis of potential red flags.

Analytics guiding toll road planning

We examined 40km toll alignment linking the Patimban deep sea port facility with a planned industrial city development. We provided the design team with design intelligence on surface waters between 1985-2018. Programming a classification algorithm – trained on 3 million satellite images – we identified drainage conditions across the entire alignment. 

Identifying ground risks up front

Mosaic provided a mega industrial city development with a rapid pre-construction health check including screening a third party toll road intersecting the development site. Partnering with Terradue’s virtual machine platform, we processed a year of satellite radar imagery to baseline recent ground deformation patterns and potential subsidence hot spots on and off-site.

Enhancing traceability for palm oil

Mosaic developed a proprietary mill supply accounting method to enhance sourcing and engagement plans across priority agri-commodity landscapes. Using machine learning workflows, we analyzed hundreds of roads and tracks making up local transport networks, calculated travel routing times and independently estimated smallholder potential within mill supply sheds and at-risk forest and peat resources.

Fire and Land conflict intelligence

We provided the client with insights to inform community engagement and sharpen fire risk management plans. The assignment required a deeper understanding of community dynamics across the project landscape. We prepared spatial and temporal fire pattern and land conversion analytics, which PT Business Risk Indonesia used to conduct social and political linkage analysis to examine the role of key actors and ways to improve the management of at-risk forest areas