MODELING THE DISTRIBUTION OF LAKE REEDS USING GIS
DOI:
https://doi.org/10.17770/etr2025vol2.8619Keywords:
Reeds, modeling, renewable resources, satellite data, QGISAbstract
So far, no significant modeling of reed biomass availability or assessment of the sustainability of reed products based on life cycle analysis has been conducted in Latvia. Nevertheless, these aspects are crucial for the development of reed-based products, as they help evaluate their market potential and overall socio-economic and environmental impact. This work aims to establish a methodology for modeling the extent of available reed distribution to forecast its future availability, as the availability of reed biomass is a vital prerequisite for utilizing this resource in the national economy. The novelty of this research lies in predicting reed areas based on existing historical data. The modeling is performed using GIS and satellite data.
References
“Plant family,” [Online] Available: https://www.britannica.com/plant/Poaceae [Accessed: Feb. 20, 2025].
E.Čubars and G. Noviks, “Influence of Different Factors on Productivity of Reed Growths,” Environment. Technology. Resources, Proceedings of the 9th International Scientific and Practical Conference. Volume 1, Rezekne, Latvia, 2013. https://doi.org/10.17770/etr2013vol1.801
E.Tiškus, D.Vaičiūtė, M.Bučas, and J. Gintauskas, “Evaluation of common reed (Phragmites australis) bed changes in the context of management using earth observation and automatic threshold,” European Journal of Remote Sensing, 2022. https://doi.org/10.1080/22797254.2022.2161070
L. Sciuto, F. Licciardello, A.C. Barbera, and G. Cirelli, “A GIS‐based multicriteria decision analysis to reduce riparian vegetation hydrogeological risk and to quantify harvested biomass (Giant reed) for energetic retrieval,” Ecological Indicators, Volume 144, November 2022, https://doi.org/10.1016/j.ecolind.2022.109548
S. Baier, N.C. Meneses, J. Geist, and T.Schneider, “Assessment of Aquatic Reed Stands from Airborne Photogrammetric 3K Data,” Remote Sens. 2022, 14(2), 337, https://doi.org/10.3390/rs14020337
H. Runkui and L.Yuqin, “Application of remote sensing technique to the investigation on reed resources of Bosten Lake,” Chinese Geographical Science, Volume 2, pages 266–276, (1992), https://doi.org/10.1007/BF02664604
“Latvian lakes database.” [Online] Available: https://www.ezeri.lv/database/2196/ [Accessed: Feb. 20, 2025].
“Copernicus project,” [Online] Available: https://www.copernicus.eu/en [Accessed: Feb. 20, 2025].
“SentiWiki Home Page,” [Online] Available: https://sentiwiki.copernicus.eu/web/sentiwiki [Accessed: Feb. 20, 2025].
“QGIS project,” [Online] Available: https://qgis.org/project/overview/ [Accessed: Feb. 20, 2025].
C.Wells, “A guide to CHAID: a decision tree algorithm for data analysis,” [Online] Available: https://www.adience.com/blog/how-to/a-guide-to-chaid-a-decision-tree-algorithm-for-data-analysis/ [Accessed: Feb. 20, 2025].
L. Breiman, “Random Forests. Machine Learning,” 45(1), 5–32, 2001. https://doi.org/10.1023/A:1010933404324
F.Li and R.Klette, Euclidean Shortest Paths: Exact or Approximate Algorithms, Springer, 2011.
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Copyright (c) 2025 Peter Grabusts, Jurijs Musatovs, Ērika Teirumnieka
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