Forest Analysis LiDAR
Forest Analysis LiDAR
Lendel has developed a unique system for the detection, analysis, decision-making and maintenance of large-scale forest structures. Designed for long-range areas, our system facilitates rapid decision-making in real time with high-level spatial precision. The system allows analyzing: Deforestation Tree felling is greater than natural and artificial recovery, which is mainly due to the high consumption of wood for firewood and, to a lesser degree, to fires and forest pests. Accelerated soil erosion This is due to the lack of appropriate techniques for soil conservation, especially in densely populated areas. Pollution from the use of agrochemicals The use of insecticides, herbicides, fungicides and other products has resulted in increased agricultural production, but its excessive use damages the environment and affects forests. Forest fires One of the great practical applications of continuous knowledge of forest cover is the prevention and management of forest fires. The risk and danger of fires, such as fire behavior, is conditioned by the structure of the vegetation and the characteristics and condition of the shrub layer inside and outside the forest. Accurate mapping of fuel models Analysis of forest cover that allows decisions to be made to carry out preventive work. The higher cartographic resolution allows improving the effectiveness of fire simulators, both for prevention and for extinction. High spatial resolution forestable inventories By building algorithms that combine LiDar data with field data to continuously calculate variables linked to different types of forests.
Our services
With this 3D modeling tool you can analyze and develop a detailed DTM (digital elevation model) for use in:
● Forest planning
● Forest environment planning
● Environmental Surveys
● Forest inventories
● Run-ins
● Calculation of LiDAR Vegetation Measurements
● Development of relationships between LiDAR metrics and tree and support attributes, such as volume (m3 / ha), carbon, etc., and construction of predictive models for settlement characteristics (implementation and development of the Estimation of Regression, Regression Modeling and k-approaches)
● Creation of GIS surfaces of tree and support attributes
● 3D visualizations
● Biomass studies
Forest analysis benefits
• Forest land management.
• Terrestrial LiDAR has been applied to forest inventory measurements (plot mapping, species recognition, diameter and height, tree height) and canopy characterization (virtual projection, stem density, basal area, foliage distribution) . These techniques have been extended to the value of the support and to the evaluation of the quality of the wood. Terrestrial LiDAR also provides new support for green applications, such as evaluating the physical properties of leaves, transpiration processes, and microhabitat diversity.
• It allows at the same time the organization of the forest, the planning of the location of certain institutions and buildings in areas of high population concentration.
• Location of the properties in the cadastral cartography.
• Control of growth or forest loss in the territory.
• Forest inventory: provides measurements of tree height and density.
• Analysis of wildlife habitat: determines the structural stage of the forest.
• Prediction of fuel models and determination of understory vegetation density and height.
• Extraction of characteristics: represents buildings, structures and roads
• Three-dimensional visualization: represents the forest or the terrain in realistic detail
• The entire system allows the adoption of evaluation and decision strategies.
• The Lidar system offers detailed information on elevation acquired over large areas and at a resolution higher than conventional DEMs.
• The Lidar system can reduce the costs necessary to collect field measurements over large areas.
• Lidar data helps locate points where field data will be useful.
• The Lidar's ability to penetrate dense vegetation allows data collection over large areas that would be difficult to examine in any other way.
• Morphological characteristics that could be completely lost in field measurements can be captured at a scale that would not be possible from a DEM of 10 meters.
• Interpreted data layers are easy to integrate with other data sources in a GIS.
• Forest plans can efficiently incorporate the results of Lidar data analysis.
• Lidar data can be acquired during the day or night under clear weather conditions.