Lidar and Forestry Management

Lidar Technology and Forestry Management

Lidar and Forestry Management

Light Detection and Ranging (LiDAR) is a breakthrough remote sensing technology for forest inventory management and forestry applications. LiDAR data processing tools and techniques are useful for mapping and determining diverse forest structural characteristics. The estimation of stand volume, canopy heights, aboveground biomass, basal areas, and other projected uses of remote sensing in forestry are common examples of how LiDAR instruments are providing accurate results to their users. Here, we intend to throw light on some important applications of LiDAR technology in forestry. Read on to know how forest managers are handling significant impediments through useful LiDAR -based accuracies and resolutions.


LIDAR Technology and Management of Forestry


1. Planning of forests and their management     

LIDAR data processing and technology is very useful in gauging the vertical structures of forest canopies. The density, height, timber volume, basal area, and biomass can be successfully attained from LiDAR data. For instance, small-footprint LiDARs provide detailed measurements of different kinds of canopy top topography. Even the largest canopies can be understood easily with LiDAR equipment. These tools provide accurate information for enabling the best possible classifications of ecological and land use. LiDAR models also help in understanding complicated forest structures for generating feasible forest inventory.

2. Forest mapping and precision forestry

LiDAR data offers in-depth and accurate analysis of geographical terrains and the suitability of forests in those areas. The quality of soil, elevation of land, and all other factors to be considered for mapping forests can be obtained through this technology. LiDAR inputs are equally useful for increasing site productivity in context to overall yield, quality of trees, etc. They provide precision data for specific forested sites so that they can be targeted to attain the desired results.


3. Prevention of forest fires

The latest LiDAR technologies are used to map, manage and monitor the spread and damages attributed to wildfires. Airborne LiDAR systems offer accurate insights regarding the terrains and forests that can be protected when a wildfire occurs. Advance planning can reduce the risks of permanent damages to a large extent. It helps response crews plan evacuation procedures and routes in sustainable ways before the fire becomes uncontrollable.


4. Ecological and Land Classification (ELC)

ELC and related remote sensing services provide high-end accurate information about specific forested areas and landscapes. Conventionally, this type of information was obtained using surveying. LiDAR technology gives off more accurate information for estimating and freezing upon the land that should be committed to forestry. The areas that should be allocated to habitat management, forest infrastructure, etc. can also be ascertained with accuracy with the help of LiDAR data.


5. Study of forest ecology

LIDAR data processing provides high-precision information pertaining to forest ecology or the habitats belonging to forested regions. The information helps researchers understand the type of animals that habitat specific forests and the species capable of surviving in them. There are several lidar system types (ground, space and air based) that suggest pathways that contribute to forest ecosystem, thereby increasing benefits to a large community of researchers.


LiDAR in Forestry @ SBL Corp


The LiDAR systems at SBL Corp are very useful in recovering forest structure elements for a wide range of vegetation through direct and simple processes. Our remote sensing techniques and tools for structure mapping and forest inventory enable the most critical forest management decisions fitfully. The LiDAR capabilities at SBL also help in planning the forest structure needed for fire behavior modeling, fuels estimation, and so forth. Reach out to our means and methods of incorporating different remote sensing data and fusion-based approaches. Derive canopy structure variables and other three-dimensional structure and imaging systems to generate a higher ROI, today.

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