Digitising Woodland Management | Article 1

As technologies advance and develop an increasing amount of data is becoming easier and cheaper to access. This is no different in woodland management where technologies and new applications and capabilities of technologies are facilitating real-time monitoring of woodlands and presenting opportunities to increase the quality and quantity of information available to owners and managers to inform decision making.

This article is one of three articles looking at digital innovations in woodland management:

• ‍Drones‍
• Remote Sensing and data processing (this article)
• Mobile technologies and digital tools

We consider the benefits, applicability, and barriers to implementation in smaller woodlands in the Northeast and Yorkshire. As the technologies continue to advance, provide more localised insights and decrease in price they may become increasingly applicable to woodlands of all scales, and more relevant to smaller woodland owners and managers. This article focuses on remote sensing, satellite technologies and the processing of digital data.

Remote Sensing

Remote sensing is using technology to gather data on objects or phenomena without making physical contact with them. Remote sensing technologies can be spaceborne satellites or airborne drones. The image below shows remote sensing technologies and their applicability at different scales. The data gathered can be photographs and video recordings or point clouds producedusing LiDAR (light detection and ranging) equipment. The different technologies both contribute numerous opportunities for woodland management but are not without their differences, barriers and disadvantages. In general, the cost of remote sensing is decreasing while the quality of results is increasing.

‍Satellite Technologies

Although the use of satellite technologies (carrying recording or lidar equipment) to study woodlands is not a new phenomenon, satellite technologies have increasing relevance at local scales. Higher resolution 3D imagery can focus on single trees and continues to advance inquality and reduce in price. A Biomass satellite is scheduled to be launched by the European Space Agency in 2024 designed to measure the height of trees from space and ‘see’ through the forest canopy in order to determine how much carbon is being stored in forests. Furthermore, advanced algorithms can quickly process images in order to detect changes with enough accuracy to inform local woodland management.

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In general, when compared to other methods of datacollection satellite imagery is limited in its ability to provide small, finerdetails so it is better for achieving a broader overview of large areas. Inthis way such technologies may have less applicability in smaller undermanagedwoodlands. In addition, although data may exist which can be accessed intheory, it requires processing in order to become meaningful and useful tothose involved in woodland management. This may not be financially viable in alot of cases.

Although localised data from satellite technologies is inits infancy it is anticipated to create opportunities for woodland management andfacilitate better informed decision making. The real-time nature of satellite data is a distinct benefit and datacan be gained about hard-to-access areas of woodland. This has positive safetyimplications and means data can be gathered that might otherwise not have been possible. Inventory of tree count, species, health, stem diameter andstraightness traditionally collected in a manual and time-consuming fashion caninstead be accomplished remotely and digitally. Moreover, rather thantraditional sample data being collected, data can be collected about the wholewoodland and stored and processed digitally.

Detailed data facilitates data-led woodland management and is invaluable for forecasting wood production, timber value, and carbon sequestration rates. One of barriers specific,but not unique, to the Northeast and Yorkshire identified by the ForestryCommission is an absence of site-specific information on woodland condition andwoodland inventory. The detailed data provided by drones and satellite technologieshas the potential to revolutionise information available to woodland owners and managers in the future.

Drones and mobile technologies for woodland management are explored in detail in separate articles.

Digital Data Processing

Large volumes of high-quality data can be gathered usingsatellites, drones, mobile technologies and handheld LiDAR. The resultingextensive digital data typically includes interconnections across devices anddatabases which require processing, analysing and presenting. Artificialintelligence is increasingly being employed for this purpose. Artificial intelligence (AI) is using machines to perform tasks that would normally require human intelligence. A multitude of AI platforms exist globallyacross different sectors and at different scales. In the forestry sector theseinclude Collective Crunch, Arboair, AFRY Smart Forestry and Treemetrics. Irish company Treemetrics’s forestmonitoring platform processes satellite and drone imagery in addition toproviding mapping tools. The platform is designed to help forest owners adoptforest certification, meets the needs of PEFC certificate holdersinternationally and facilitate transparent auditing of management practices.

LiDAR datacollected by satellite, drone or handheld technologies requires processing to createpoint clouds and ensure that output data that is meaningful and useful to those involved in woodland management. In additional to developing LiDAR-equipment-carrying drones the Deep Forestry Drones project (mentioned in the Dronesarticle) has developed an AI algorithm to process the data into a 3D visualisation/point cloud and interpret the data in order to create a detailed inventory report of the woodland – tree heights, diameter, volume and counts -and its health including the types of trees present and wood volume.

Combining data from a mixture of scales, angles and technologies is powerful when trying to establish a comprehensive picture of the woodland to aid data-driven management.‍

Conclusion

This article has provided an overview of remote sensing for woodland management with a focus on satellite technologies, discussing existing and potential opportunities. The processing of the large quantities of digital data has also been considered.

Overall current and future digitisation is anticipated to provide a powerful new dimension to information to inform woodland management where across the UK a lack of site-specific information on woodland inventory and condition is cited as a key barrier to the management ofwoodland. The technology is likely to help support on-the-ground foresters rather than replace them.  

It will be interesting to read this article in years to come and see if the feasibility of satellite technologies at a more local scale has increased and if anticipated advancements and acceptance of technologies for woodland management have become a reality.