Modernizing Romanian Forest Management by Integrating Geographic Information System (GIS) for Smarter, Data-Informed Decision-Making

Traditional Forest Management Plans (FMPs), which often span hundreds of pages on paper, present significant challenges due to their extensive length and lack of clear spatiotemporal context. This study aimed to integrate complex data from FMPs into an interactive, spatially referenced database. Using Gârda Forest in Romania’s Apuseni Mountains as a case study, we gathered raw data, developed the geodatabase’s spatial and alphanumerical components, and conducted spatial analyses related to ecological and production factors. Our GIS was designed to accommodate multiple attributes within the compartment layer’s attribute table. Unlike previous studies, we incorporated the full range of information from the Compartment Description, not just isolated management aspects. This comprehensive approach enabled spatial analysis to highlight, in maps, key features across the 50 compartments (totaling 752.5 ha) including dominant species (Norway spruce, silver fir, beech), target species composition (Norway spruce as the predominant target), land protection needs (required for 4% of the area), median forest volume (1565 m3 per compartment), elevation range (1020–1420 m), compartments with production functions, and silvicultural treatments. These thematic maps provide a tool for further analyses and clear spatial visualization. Our GIS-based methodology supports rapid condition assessments and aids forest professionals and decision-makers in promoting sustainable forest management.

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Publication Details

Journal
Forests
Published
2025-08-14
DOI
https://doi.org/10.3390/f16081326
Primary Topic
Remote Sensing and LiDAR Applications
Type
article
Field-Weighted Citation Impact
0.00

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article

Modernizing Romanian Forest Management by Integrating Geographic Information System (GIS) for Smarter, Data-Informed Decision-Making

Luisa Andronie, Tudor Sălăgean, Mircea-Emil Nap, Silvia CHIOREAN et al.
Forests
Remote Sensing and LiDAR Applications
article

Modernizing Romanian Forest Management by Integrating Geographic Information System (GIS) for Smarter, Data-Informed Decision-Making

Luisa Andronie, Tudor Sălăgean, Mircea-Emil Nap, Silvia CHIOREAN, Ioana Pop, Florica Matei, Sorin T. Șchiop, Horia-Dan Vlasin, Jutka Deak, Ioana Buia, Lucia Adina Truță
article en

Abstract

Traditional Forest Management Plans (FMPs), which often span hundreds of pages on paper, present significant challenges due to their extensive length and lack of clear spatiotemporal context. This study aimed to integrate complex data from FMPs into an interactive, spatially referenced database. Using Gârda Forest in Romania’s Apuseni Mountains as a case study, we gathered raw data, developed the geodatabase’s spatial and alphanumerical components, and conducted spatial analyses related to ecological and production factors. Our GIS was designed to accommodate multiple attributes within the compartment layer’s attribute table. Unlike previous studies, we incorporated the full range of information from the Compartment Description, not just isolated management aspects. This comprehensive approach enabled spatial analysis to highlight, in maps, key features across the 50 compartments (totaling 752.5 ha) including dominant species (Norway spruce, silver fir, beech), target species composition (Norway spruce as the predominant target), land protection needs (required for 4% of the area), median forest volume (1565 m3 per compartment), elevation range (1020–1420 m), compartments with production functions, and silvicultural treatments. These thematic maps provide a tool for further analyses and clear spatial visualization. Our GIS-based methodology supports rapid condition assessments and aids forest professionals and decision-makers in promoting sustainable forest management.

ForestsVol. 16(8)
University of Agricultural Sciences and Veterinary Medicine of Cluj-Napoca (RO), Forestry Research Centre (IT)
National Council for Higher Education, Council for Higher Education
Openalex Percentile: Top 80%
Remote Sensing and LiDAR Applications
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