Application of ensemble machine learning methods for modeling the heights of individual forest elements based on inventory data processing

Vagizov, M; Potapov, Alexey; Навалихин, С. В.; Bakeyeva, A.; Stepanov, S.

doi:10.1088/1755-1315/806/1/012035

Cited by 2 publications

(1 citation statement)

References 3 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…After constructing the weight map, we proceeded to place objects by superimposing tree coordinate point features from map A1 (Figure 3) over point features from modeled region B1 (Figure 4). The technology for capturing trees was previously described [24][25][26] (Figure 5). To locate an individual tree, a point identification method was used, and an ID number was manually assigned to each individual tree by the operator on the model substrate in Blender.…”

Section: Methodsmentioning

confidence: 99%

Visual Digital Forest Model Based on a Remote Sensing Data and Forest Inventory Data

et al. 2021

View full text Add to dashboard Cite

This article discusses the process of creating a digital forest model based on remote sensing data, three-dimensional modeling, and forest inventory data. Remote sensing data of the Earth provide a fundamental tool for integrating subsequent objects into a digital forest model, enabling the creation of an accurate digital model of a selected forest quarter by using forest inventory data in educational and experimental forestry, and providing a valuable and extensive database of forest characteristics. The formalization and compilation of technologies for connecting forest inventory databases and remote sensing data with the construction of three-dimensional tree models for a dynamic display of changes in forests provide an additional source of data for obtaining new knowledge. The quality of forest resource management can be improved by obtaining the most accurate details of the current state of forests. Using machine learning and regression analysis methods as part of a digital model, it is possible to visually assess the course of planting growth, changes in species composition, and other morphological characteristics of forests. The goal of digital, interactive forest modeling is to create virtual simulations of the future status of forests using a combination of predictive forest inventory models and machine learning technology. The research findings provide a basic idea and technique for developing local digital forest models based on remote sensing and data integration technologies.

show abstract

Section: Methodsmentioning

confidence: 99%

Visual Digital Forest Model Based on a Remote Sensing Data and Forest Inventory Data

et al. 2021

View full text Add to dashboard Cite

show abstract

Development of a technology for geoinformation modelling of forest ecosystems (part 3)

Vagizov

2022

Geoinformatika

View full text Add to dashboard Cite

In the third part of the article the structural components of forest ecosystems geoinformation modeling subsystems are considered, the technological map of the main components is indicated. Some objectives of forest geoinformation modelling and technological support of the forest ecosystems geoinformation modelling process are considered. The systems: mapping, modelling and management system at conceptual and logical level as a part of the instrumental support of geoinformation models’ operability are described. The objectives of forestry in the application of geo-referenced models of forest ecosystems that can improve the quality of forest management and provide a decision support system for economic tasks arising in the forestry sector are indicated.

show abstract

Application of ensemble machine learning methods for modeling the heights of individual forest elements based on inventory data processing

Cited by 2 publications

References 3 publications

Visual Digital Forest Model Based on a Remote Sensing Data and Forest Inventory Data

Visual Digital Forest Model Based on a Remote Sensing Data and Forest Inventory Data

Development of a technology for geoinformation modelling of forest ecosystems (part 3)

Contact Info

Product

Resources

About