Laser airborne reflection method for remote sensing forest species composition

Белов, М. Л.; Belov, A. M.; Городничев, В. А.; Alkov, Sergey V.

doi:10.1088/1757-899x/862/2/022003

Cited by 2 publications

(1 citation statement)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Today, single-wavelength and multi-wavelength (at two or three wavelengths) lidars in the visible and/or near-infrared range are used for forest monitoring [1][2][3][4][5][6][7][8][9][10][11].…”

Section: Introductionmentioning

confidence: 99%

Multispectral lidar method for monitoring the forest ecosystem under the forest canopy

Белов

Belov

Городничев

et al. 2022

J. Phys.: Conf. Ser.

View full text Add to dashboard Cite

This study demonstrates the potential of the multispectral lidar method to monitor the forest ecosystem under the forest canopy. The mathematical modeling results of forest territories elements classification on the created neural network using experimentally measured reflection coefficients are presented. It is shown that the neural network provides a high probability of correct classification for the forest ecosystem elements classification task (when using lidar measurement data about the height of the forest ecosystem elements). Laser pulse sounding at two wavelengths in near infrared spectral range 1064 and 2030 nm and the created neural network provide the probabilities of correctly classify the undergrowth of green broadleaved and coniferous trees, swamps and soils more than 0.84 and the probability of incorrect classification less than 0.08.

show abstract

Section: Introductionmentioning

confidence: 99%

Multispectral lidar method for monitoring the forest ecosystem under the forest canopy

Белов

Belov

Городничев

et al. 2022

J. Phys.: Conf. Ser.

View full text Add to dashboard Cite

show abstract

Analysis of Capabilities of the Multispectral Optical Method in Monitoring the Forest Territories

et al. 2022

View full text Add to dashboard Cite

The paper analyzes possibilities of the multispectral remote optical method in monitoring the forest areas. Results of mathematical simulation are provided of classification of the forest areas elements in the created neural network using experimentally measured reflection of the forest vegetation coefficients. It is demonstrated that the created neural network ensures high probability of correct classification within the classification problem (according to the multispectral remote optical monitoring data) of the forest probed areas. The selected spectral probing channels in a wide spectral range of ~ 400--2400 nm and the created neural network used seven spectral channels in the visible and in the near infrared spectral range, as well as the active laser sensor to measure the trees height. They provided a probability of correct classification of the forest areas elements (green deciduous trees, green coniferous trees, dry deciduous and coniferous trees, swamps, pastures with different vegetation cover and different types of soils) of more than 0.74 and the probability of misclassification of the forest areas elements of less than 0.08. The multispectral remote optical method could be used in operational monitoring of the vast forest areas from an aircraft (light aircraft or unmanned aerial vehicle)

show abstract

Laser airborne reflection method for remote sensing forest species composition

Cited by 2 publications

References 8 publications

Multispectral lidar method for monitoring the forest ecosystem under the forest canopy

Multispectral lidar method for monitoring the forest ecosystem under the forest canopy

Analysis of Capabilities of the Multispectral Optical Method in Monitoring the Forest Territories

Contact Info

Product

Resources

About