LiDAR for Tree Crown Mapping

TREE CROWN MAPPING USING LiDAR

 

 Importance of Tree Surveying

We are well aware of the fact that trees are the integral part of our eco system as well as our flora and fauna. Mapping forest reserves and vegetation is critical to economic development and to understanding our environment; it provides information about the age of the trees, type of the trees and some information about species of animals residing on the trees.

Lidar, which stands for Light Detection and Ranging, is a remote sensing method that uses light in the form of a pulsed laser to measure ranges (variable distances) to the Earth. LiDAR signal provides information to characterize forest structural characteristics such as vegetation height, density, and volume in discrete vertical slices above ground level. This data can provide information regarding structural characteristics of individual trees as well as dense forest. The resulting vertical forest characteristics derived from airborne LiDAR can improve our understanding and mapping of animal-habitat relationships from the stand to the landscape scale.

Conventional manual surveying usually takes about 15 minutes to assess one tree, and there are numerous trees in a particular area, the traditional way of collecting data by field inspection is impossible, Remote sensing made it possible to meet the needs that could not have been fulfilled on this scale and with this complexity.

Which Industries benefits from Tree Crown Mapping:

Canopy cover measurement is common in many industries such as

• Natural Sciences
• Real Estate
• Watershed Management
• Production industry
• Horticulture
• Silviculture
• Agriculture
• Hydrology

 

Why do we need Tree Crown Mapping?

• Site Selection: Obtaining permission and access to state owned or private property as well as Airborne data and imagery acquisition for each of these areas.

 

• Tree Height Detection: a high-frequency laser pulse thrown by LiDAR is used to measure the range from a sensor to a target using the TOF (time of flight). Each of the laser pulse is recorded as a point and provides the vertical difference between the last return (DTM) and the first return (DSM). The forest height can be determined by calculating the difference between the DTM and the DSM.

 

• Tree Species Detection: It involves field survey for certain species of trees. Field work is conducted to measure tree locations, tree species and heights, crown base heights, and crown diameters of individual trees of different species. LIDAR points from individual trees are identified using the field-measured tree location, Points from adjacent trees within a crown are excluded using a procedure to separate crown overlap, Mean intensity values of laser returns within individual tree crowns are compared between species.

The used tree finding algorithm is based on a regression linking the crown-width to the tree-height:

Maximum Crown Diameter (in m) = a + b*Tree Height (in m)

Where ‘a’ is the smallest possible crown width.

 

• Forest Area Determination

Remote sensing techniques are efficient methods of extracting forest height quickly, with cost-effective tools. The forest height is determined using common remotely sensed data, such as discrete-return LiDAR data, SRTM, Optical data etc. The forest area is extracted by overlapping NDVI and forest height data above 2 m allowing the sensors to complement each other. In this way each sensor has the potential for not only determining forest height but also extracting complementary forest area.

 

Conclusion

The advancing capabilities and availability of LiDAR data allow professionals to characterize forest structure with higher precision.

In addition to providing an efficient method for forest inventory, this data provides foresters with critical information for managing the health and diversity of the canopy across the forested parks and private lands.