About us

FSOS (Forest Simulation Optimization System) is a cloud-based forest modelling platform (https://fsos.ca) with visual interfaces, GIS tools and self-learning growth and yield stand dynamic tools for spatial forest modelling. Sustainable forest management must consider many functions such as wood flow, watershed condition, carbon storage, wildlife habitat, biodiversity, recreation, visual quality, and economic contributions. The resilience of fires, insects and diseases is also a management objective. The sustainability of so many forest functions make forest management complicated and difficult.

Figure, Interfaces of cloud-based digital forests https://fsos.ca.

In FSOS, pre-trained MI (ML) is used to predict the future stand dynamics, and the real-time MI is used to generate strategies to sustain, balance and optimize multiple functions of the forests. The cut blocks, roads, patches for the entire planning horizon are dynamic and optimized to create desired future forests in terms of wood flows, socioeconomics, carbon storage capacities, wildlife habitat, biodiversity, visual quality, and the resilience of forests to fires and insects.

Figure, Digital forests https://fsos.ca and real forests.

Forest models become digital forests in FSOS, you can build digital forests for the real forests in the cloud or on your own network. The digital forests accumulate knowledge, learn from history, explore opportunities, and generate management strategies to create desired future forests. The real forests follow the digital forests to implement on the ground and provide feedback. The digital forests adapt and rebalance automatically. The digital forests and the real forests work together shoulder to shoulder, and the forest landscape management is automated.

With digital forests in FSOS, forest management decisions can always be made based on balancing the interests of all users. All interests can be considered in decision-making. The digital forests never forget the interests of any parties and always work toward balanced objectives. The objectives can be achieved surely and slowly because people can see the future results and roadmaps of different management scenarios through digital forests. Forest management will have fast adaptive abilities without rebuilding models when new information is available because the smart digital forests are standing behind the real forests all the time.

Who We Are

We are a group of people who build digital systems to mimic real systems. The virtual system can help us understand, explore, optimize, and design the real system. The real system follows the virtual systems to implement in the real systems and feedback. The virtual systems adjust and rebalance automatically. The virtual systems and the real systems work together, hands by hands, a complex system can be fully formed as an autonomous driving system.

our Products


Forest Simulation Optimization System (FSOS)

FSOS is developed for multiple-objective forest analysis and planning. You can see the future forests, explore opportunities and generate strategies to create desired future forests. Forest carbon storage capacity is one of the objectives in FSOS.


Field Data Collection (FC)

The Field Data Collection and Landscape Modeling are integrated, you can design your own field data collector and cloud data storage system. In the cloud, you can define a field data collection task including tables, points, lines, polygons, photos, videos and assign the task to field crews. The field crews can login and collect data in the field. The data can be stored in the mobile devices and uploaded to the cloud database when the internet connection is available.

our Technology

Artificial intelligence

AI technologies are used to generate strategies to achieve and balance a number of objectives with millions of variables and constraints.

Big data

The system accumulates data and learns itself; the future work is easier and better.


Customize and support cloud-based forest landscape modeling platforms.

HPC cloud computing

EasyCloud is a high-performance computing framework. The idea behind EasyCloud is to build a HPC computing cluster using spare computers in the cloud or the private network whenever you need at any places with low cost. The low performance computers work together and become a high-performance computing cluster. The objective of developing EasyCloud is to meet the Artificial Intelligence iterative calculation needs and reduce the software development difficulties.

Contact us

Location: 3150 Chaucer Ave, North Vancouver, BC, Canada V7K2C3( Google Map ).

3150 Chaucer Ave, North Vancouver,
BC, Canada V7K2C3

1 604 288 5888 (o)

1 604 889 6787 (c)