Several of the key trends shaping the forestry industry in 2024 highlight the sector’s commitment to environmental conservation, technological innovation, and using data intelligence to make informed decisions that minimize environmental impact and maximize economic benefits for all stakeholders.
In this Forest Intelligence round-up, we’ll review 3 topics that have captured interest over the past year with highlights from some of the most-read stories.
1. Forest Supply Chain Transformation
In the heart of the forestry industry, a wave of innovation is underway as supply chain transformation and digitalization take center stage. Driven by a confluence of factors, these trends are reshaping the way forestry operations are managed, from sustainable forest practices to the efficient delivery of products.
Several of our most-read articles have looked at the key drivers and benefits of supply chain transformation in forestry.
Digital Forest Operations: How to Improve Efficiency and Visibility
An overview of what’s driving the need for digital transformation of forest operations, and the top opportunities for improvement. With a pragmatic approach that targets key improvement objectives, digitalizing forest operations can empower decision makers – from analysts to business users and front line – with the data and tools they need to improve business performance. Read more →
Intelligent Forestry: Bringing AI Analytics to Forest and Mill
The complexities of the forestry industry are an untapped opportunity for transformative AI analytics. This short article highlighted AI’s potential in forestry and Remsoft’s plans for bringing fully AI-enabled analytics offering to the market that focus on forest-to-mill operations. Read more →
Transforming the Forestry Supply Chain with Optimization and Artificial Intelligence
Providing a deeper dive into the application of Artificial intelligence (AI) and machine learning (ML) technologies in forestry, this article explored the use of AI/ML as a compelling complement to mathematical optimization modeling and best practices currently used to enhance forestry planning. Read more →
2. Carbon and Climate Change
Understanding the challenges associated with climate change and carbon has become increasingly critical for sustainable resource management. From optimizing harvesting schedules to strategic resource allocation, data intelligence offers a transformative approach to mitigating the impacts of climate change on forestry operations. Data-driven and optimized forestry planning processes are critical to ensuring a balance between economic viability and environmental sustainability in the face of evolving climate and carbon trends.
Managing the rising complexity of the environmental, social, and corporate governance (ESG) landscape was top of mind over the past year, and these stories focused on how to bring new efficiency and intelligence to risk mitigation and carbon forestry.
Mitigating Climate Change with Intelligence
A review of how foresters are using intelligence technologies, such as operational analytics, optimization modeling and machine learning, to ensure climate mitigation options are well planned, sustainable, and appropriately implemented.
Read more →
Optimizing forest carbon projects
Embarking on a forest carbon project, from project management to balancing other uses to harvesting regimes and carbon registry methodologies, is a significant investment for foresters. This post explored how optimization analytics can make the process simpler and more efficient. Read more →
Maximizing your carbon credits with intelligent baseline setting
The demand for forest carbon credits has never been greater with carbon storage crucial to achieving net zero. In 2023, we introduced optimization tools, developed based on American Carbon Registry methodology, that provide a solution for creating baselines and exploring carbon project management options. Read more →
3. Data-Driven Forest Management
In the post-information age of AI and Intelligence, industries worldwide are making a transformative shift towards data-driven decision-making. Forestry, a sector deeply rooted in tradition, is no exception. Using advanced analytics and optimization modeling forestry planners are empowered to make informed decisions that pave the way for more sustainable and efficient approaches to managing our woodlands.
Our top analytics stories demonstrated the practical application of AI and optimization for forestry planning.
Improving harvest accuracy with AI
AI and Machine learning has an important role to play in operational planning, and in improving the accuracy of volume estimates on a block, production rates, and the overall harvest schedule. This post looked at how AI and Machine Learning capabilities in Remsoft Operations can help planners predict when a harvest operation will be late or early. Read more →
Using Wood Basket Analysis to Adapt to Changing Dynamics
When navigating the complexities of wood supply modeling, optimization techniques like wood basket analysis are more important than ever to adapt and thrive within today’s changing economy. Still relevant today, this older post explored how wood basket analysis leverages the power of optimization to understand how decisions and adjustments made today may play out in the future. Read more →
Optimizing Crew Scheduling to Minimize Operational Costs
The ability to account for movement costs between blocks with optimization modeling can improve crew assignment and movement decisions and minimize costs. This overview of Scheduler, a Remsoft Optimization Application, examined how foresters can use this powerful tool to reduce forestry planning and harvest costs and improve bottom lines. Read more →
As we navigate through 2024, the forestry industry is at the forefront of environmental stewardship, technological advancement and supply chain transformation. By embracing these trends, foresters are paving the way for a more sustainable future, ensuring the health, vitality and productivity of our forests for generations to come.
