Quantifying and Monitoring Tree Canopy Cover

Using high resolution imagery to accurately map woodland.

by | Apr 4, 2019 | Forestry

Dr Chloe Barnes

Head of Remote Sensing at 2Excel Geo

 

Chloe joined the 2Excel Geo team in 2017, following the completion of her PhD in Remote Sensing. She is a domain expert in tree disease detection using spectral imaging and LiDAR techniques from airborne platforms and is an experienced data analyst.

When managing forests, often the first and most important question to ask is ‘where are all the trees?’ Although this may seem like a simple enough question to answer, manually digitising the location of every single tree can be time consuming and cost inefficient. Instead, a top down sampling strategy using remote sensing is preferable, allowing fast calculation of canopy cover over a specified region.

Sensors operating from space-based and airborne platforms offer the capability to collect data across vast areas quickly and easily. Understanding the characteristics of trees within these datasets allows the information to be utilised for tree canopy mapping.

2Excel Geo utilise their expertise in forestry and remote sensing to derive highly accurate canopy cover maps from both airborne and satellite data sources. The high spatial resolution of the input datasets allows trees outside of woodlands such as those in hedgerows or urban environments to be included in quantification of canopy cover.

Figure 1

High resolution aerial photography of a mixed forested area

Figure 1

High resolution aerial photography of a mixed forested area

Figure 2

With canopy map applied.

Figure 2

With canopy map applied.

The canopy map outputs are compatible with GIS and other management systems and can be invaluable for a variety of forestry applications. One key operational use of this information is to inform canopy cover percentage for a particular area of interest. This information can be vital when monitoring the impacts of new planting schemes, or assessing the impacts of deforesting activities. Understanding the quantity and geographical extent of canopy cover also provides key information in natural capital-based approaches to landscape assessment and planning, in addition to informing new planting from improvements in canopy connectivity.
Figure 3

The area in red indicates canopy cover, which included individual trees located outside of woodlands.

Figure 3

The area in red indicates canopy cover, which included individual trees located outside of woodlands

2Excel Geo also use canopy mapping outputs in the derivation of more complex forestry services such as individual tree mapping and tree health assessment. If you are interested in any of these services derived from our imagery and how it may be useful for your forestry applications, please get in touch.

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