
Contact
Grigorijs Goldbergs
PhD
Researcher
He has been working at the Institute of Electronics and Computer Science since 2020. Research interests: photogrammetry and remote sensing; multispectral, synthetic aperture radar image processing; unmanned aerial vehicle data processing and use in agriculture and forestry; 3D modeling using 3D laser scanner data.
In 2019, Grigorijs Goldbergs defended his doctoral thesis "Remote Sensing of Tree Structure and Biomass in North Australian Mesic Savanna" at Charles Darwin University (Australia) and obtained a PhD degree.
In addition to his research work, he teaches courses at the Latvia University of Agriculture.
Related publications:
1. Goldbergs, G., Levick, S. R., Lawes, M., & Edwards, A. (2018). Hierarchical integration of individual tree and area-based approaches for savanna biomass uncertainty estimation from airborne LiDAR. Remote Sensing of Environment, 205, 141-150.
DOI: https://doi.org/10.1016/j.rse.2017.11.010
2. Goldbergs, G., Maier, S. W., Levick, S. R., & Edwards, A. (2018). Efficiency of Individual Tree Detection Approaches Based on Light-Weight and Low-Cost UAS Imagery in Australian Savannas. Remote Sensing, 10(2), 161.
DOI: https://doi.org/10.3390/rs10020161
3. Goldbergs, G., Maier, S. W., Levick, S. R., & Edwards, A. (2019). Limitations of high resolution satellite stereo imagery for estimating canopy height in Australian tropical savannas. International Journal of Applied Earth Observations and Geoinformation, 75, 83-95.
DOI: https://doi.org/10.1016/j.jag.2018.10.021
Projects
5 results
- Comprehensive analysis of hemiboreal forest structure, species composition and ecosystem services using VHR hyperspectral and LiDAR data (HYLIFORES) 01.01.2025 – 31.12.2027 Completed
- Monitoring urban waterfront and recreation territories (Waterfront) 01.10.2024 – 31.01.2026 Completed
- EO Baltic Platform for Governmental Services (EO-BALP) 01.11.2023 – 31.05.2025 Completed
- Remote sensing based system for forest risk factor monitoring (Forest Risk) 01.03.2022 – 30.11.2023 Completed
- Satellite remote sensing- based forest stock estimation technology (WoodStock) 01.03.2019 – 28.02.2022 Completed
Publications
- 2024
Hierarchical Integration of UAS and Sentinel-2 Imagery for Spruce Bark Beetle Grey-Attack Detection by Vegetation Index Thresholding Approach(opens in a new window)
Goldbergs, G., & Upenieks, E. M.
Forests, Vol. 15 (4), p. 644, MDPI
- 2023
Comparison of Canopy Height Metrics from Airborne Laser Scanner and Aerial/Satellite Stereo Imagery to Assess the Growing Stock of Hemiboreal Forests.(opens in a new window)
Grigorijs Goldbergs
Remote Sens, Vol. 2023 (6), p. 1688, MDPI
- 2021
Impact of Base-to-Height Ratio on Canopy Height Estimation Accuracy of Hemiboreal Forest Tree Species by Using Satellite and Airborne Stereo Imagery(opens in a new window)
G. Goldbergs
Remote Sensing, Vol. 13 (15), p. 2941, MDPI
- 2021
Impact of Base-to-Height Ratio on Canopy Height Estimation Accuracy of Hemiboreal Forest Tree Species by Using Satellite and Airborne Stereo Imagery(opens in a new window)
G. Goldbergs
Remote Sensing, Vol. 13 (15), p. 2941, MDPI