In the recent years there has been a marked increase and uptake of remote sensing technologies – drones, LiDAR and satellite imagery. In a sense they all have a place provided they are cost-effective, provide consistent results, and add value. Not to go unnoticed is the increased availability of satellite imagery and advances in technologies that allow cost-effective repeat assessment of forests. The two main catalysts have been the launch of more satellites and the development of cloud-based processing engines – enabling the development of near real-time monitoring applications.
New satellites are being launched monthly with most designed to record and monitor vegetation change. The increased temporal resolution (allowing daily revisit) represents an important shift towards continuous monitoring of resources. The ability to monitor the same location repeatedly enables the detection of subtle changes in vegetation vigour and identification of trends. The real analytical efficiencies are accomplished by leveraging off cloud computing architecture which hosts and serves petabytes of historical and recently acquired images on-demand. With data held in this environment there is no need to individually review, download, or process and analyse satellite imagery as was the norm in the recent past.
The resource monitoring team led by Dr Pete Watt at Indufor have developed a Continuous Plantation Monitoring System (CPMS) that leverages off both free and commercial satellites (such as Planet) to provide timely and accurate information. The CPMS enables the monitoring of harvesting and plantation development across large areas.
Identification of wind damage using satellite imagery
The rationale is that the increased frequency of satellite overpasses (temporal frequency) at high resolution adds a further dimension that enables planning managers to more efficiently allocate field resources, resulting in a more structured approach to monitoring and the area update process.
Dr Pete Watt, Head of the resource monitoring team, says the data layers produced save time and resources by allowing our foresters conducting field inspections to quickly validate harvest areas, pinpoint areas of un-mapped change, disease or failed areas.
For example, prior to going to the field we run our Canopy Index (CI) model over the satellite image to check for any unusual deviations from expected benchmark values, like areas impacted by foliar diseases, or as in the example to identify wind damage. Often such areas if located in remote locations will remain unnoticed until the next round of mapping updates.
Other algorithms we use allow monitoring of planned operations such as harvesting, roading and plantation thinning. These events can be tracked by comparing images acquired at different points in time. The detection algorithm identifies the change and groups all similar pixels to produce a change layer that can be loaded into a GIS, including a summary of area harvested at that point in time.
The inclusion of daily imagery from the likes of Planet’s constellation of of around 200 satellites makes the process of month-end area reconcilations a far less onerous task.
With the increased frequency of high resolution satellite data linked to near real-time processing has removed many of the barriers that have prevented the operational use of satellite imagery. The purpose of the CPMS is to provide additional information and value that leads to efficient management of forest resources.
Progressive Harvest Mapping
Resource Monitoring team website.