Enhancing Forestry Governance through Geospatial Technologies: The Albanian Context

Enhancing Forestry Governance through Geospatial Technologies: The Albanian Context

Sonila Xhafa Sinjari; Dritan Lloçi, Xhulia Bygjymi

Geography Department, Faculty of History and Philology University of Tirana, Tirana, Albania

Abstract: Forests play a key role in ecological balance, biodiversity conservation and the fight against climate change. Climate change, fragmentation, invasive species, overexploitation and deforestation are among the main drivers of forest ecosystem loss. In this context, the use of innovative technologies for assessing forest health, managing forest areas and supporting sustainable resource use becomes essential for informed decision-making and effective environmental governance.

Geospatial technologies represent a set of tools and methods for collecting, processing, analyzing and visualising geographically referenced data. Their application through Geographic Information Systems (GIS) and Remote Sensing enables continuous and cost-effective monitoring of forest areas, providing accurate information on forest cover change, ecosystem condition and risks related to both climate and human pressures.

These technologies support biodiversity monitoring, the identification of stressed vegetation, the mapping of valuable habitats, the analysis of forest structure, and the detection of degradation, illegal activities, and fires. This study presents an overview of the use of geospatial technologies in the forestry sector in Albania, highlighting their importance in strengthening forestry governance, improving planning processes and supporting evidence- based decision-making, while also discussing challenges related to their implementation and institutional use.

Keywords: GIS, Geospatial Technology, Forestry, Spatial Decision Making;

1. INTRODUCTION

   Nowadays, large areas of forest ecosystems are subject to increasing abiotic and biotic pressures that lead to the loss of biological diversity, which hinders the provision of forest ecosystem services and functions. For a long time, geospatial technology has been widely used for natural resource management in general and also in the forestry sector as a tool to support decision-making and optimize actions for the conservation, management and sustainable development of forests, increasing the efficiency of biodiversity conservation in forest habitats.

   The management and conservation of forest habitats are closely linked to geospatial technology, enabling the implementation of in-depth research analyses, from the identification of these habitats through LiDAR (Light Detection And Ranging)

   remote sensing technology to the identification of plant species with Artificial Intelligence. Remote Sensing and GIS applications, as well as geographic knowledge and hyperspectral interpretations of information obtained from satellite images, support the modeling of forest surfaces, the assessment of their health, the identification of problems related to the causes that threaten the damage of forest surfaces, as useful information for forest management and their restoration based on solutions supported by measurements and evidence.

   Also, the use of multispectral and hyperspectral satellite data, as well as images taken by UAV (Unmanned Aerial Vehicles) enables the measurement of indices that extract very important information regarding vegetation, its monitoring, vegetation structure, its risk from natural and human factors, etc. Many researchers link the assessment of forest health to the presence of chlorophyll in leaves, which can be monitored through Remote Sensing (RS) technology. This approach allows the detection of vegetation stress in forests by assessing a series of factors that affect vegetation vitality and plant development.

2. LITERATURE REVIEW

   Forests play a crucial role in maintaining ecological balance, regulating the climate, conserving biodiversity and supporting the livelihoods of millions of people. In recent decades, forest ecosystems have been increasingly threatened by natural and anthropogenic stressors, such as climate change, deforestation, forest fires, pest outbreaks, and urban expansion.

   As these pressures intensify, the need for a comprehensive and proactive approach to assessing forest health and predicting future risks becomes more urgent. The integration of Geographic Information Systems (GIS) and Remote Sensing (RS) technologies provides a comprehensive framework for monitoring, assessing and predicting forest health conditions at local, regional and global scales. These two methodologies allow for the continuous and cost-effective collection, analysis and visualization of spatial and temporal data related to forest ecosystems.

   Decision support systems based on geoinformation are developing very rapidly, as a new direction for better forest management. Hence the concept of “precision forestry” was born, at the core of which lies the use of technology and innovation to support the decision-making process. Precision forestry is defined by the group of researchers S.E. Taylor, T.P.

   McDonald, F.W. Corly as the planning and implementation of site-specific forest management activities and operations to improve the quality and use of wood products, reduce waste and increase profits, and preserve the quality of the environment. [1]

   In recent years, Albania has made impressive progress in the use of geospatial technologies in environmental studies, benefiting from more accurate data and more efficient management of environmental challenges. Also in the forestry sector, the use of satellite imagery, geospatial methodologies for the assessment and classification of forest areas, open source tools, and data from the State Geospatial Information Authority has increased.

   For a review and bibliometric analysis of the Use of GIS and RS in forestry with a

   focus on Albania was used Publish or Perish platform. This platform was chosen based on its flexibility of generating scientific results indexed by Google Scholar with a comprehensive coverage of peer-reviewed journal articles focused on the study topic.

   In this platform, advanced criteria were defined through boolean logic (“geospatial” OR GIS OR “remote sensing”) AND (forest* OR forestry) AND (governance OR management OR “decision making” OR policy) AND (Albania OR Albanian) time filters for a 25-year period (from 2000 to 2025), in order to facilitate the systematic identification of publications that are clearly related to the purpose of the study.

   The existing literature for Albania shows that GIS has been used more in land use, urban planning, risk assessment and little or not at all in forest governance and management directly. We mostly find academic research from Albanian universities related to maps of land use, land cover, forest areas, deforestation areas, etc.

   The results focus mostly on the use of GIS or remote sensing in general, about 160 publications with a total number of citations of about 1637. These publications are thematized in several research areas such as post-socialist transformations of the territory, desertification, urban changes, territorial fragmentation that tangentially treat forest areas.

   This research shows that GIS has been used mainly in socio- territorial analysis and is often not integrated into the decision- making systems of the forest sector. It mostly results that scientific research has focused mostly on the use of GIS and RS to assess land use changes in Albania, highlighting the authors Müller, D., & Sikor, T. (2006) [2] the state of aquatic and environmental systems and biodiversity in a study area in Albania, highlighting the authors as Fatos Qarri, F., Lazo, P., Stafilov, T., Frontasyeva, M., Harmens, H., & others. (2014) [3], natural hazard analysis using GIS highlighting the authors Mario Parise, M., Pellumb Qiriazi, P., & Sala, S. (2004). [4] Another part of the research deals with the use of GIS as a tool for environmental analysis, addressing natural hazards and environmental degradation but not integrated into decision- making.

   Such a situation constitutes a research gap in Albania that is also related to the limitations of the use of this technology in decision-making and scientific research institutions. This gap is noted in topics related to forest governance, GIS-based

   policies, the use of geospatial technologies in decision-making, etc.

   One of the most mentioned topics in the literature affecting Albania is the limited use of geospatial data and consequently their use in decision-making. There is a particular lack of studies on forest management and governance, mainly in terms of their protection using geospatial technology, GIS-based planning, and the implementation of this infrastructure in decision-making and public policies.

   One of the articles that aims to connect GIS technology and spatial data with decision-making is by the author Dushaj, L., Sallaku, F., Tafaj, S., & Rrapo, S. (2011) [5] which emphasizes GIS as a decision-making tool for land use planning in agricultural areas of central Albania, based on land use categories, land suitability analysis for agricultural activities, etc.

   In conclusion, we can emphasize that this research gap reflects the need for research that links geospatial technologies with institutional decision-making in general and managerial decision-making mainly in the forestry sector.

3. THE USE OF GEOSPATIAL TECHNOLOGIES IN

   FORESTRY

   The use of geospatial technologies supports the management of protected areas in monitoring biodiversity, conducting soil analyses and tracking human activities, while also predicting the impact of climate change on forest health, in order to adapt forest protection and development strategies to these changes.

   1. Satellite Remote Sensing

      The use of Satellite Remote Sensing in forestry refers to data extracted from satellite recordings based on hyperspectral sensors which are responsible for data about the characteristics, structure and classifications of forest surfaces. The LiDAR sensor is a device widely used in Remote Sensing technology. The principle of LiDAR is to emit laser light towards an object on the Earth’s surface and calculate how long it takes to return to the LiDAR emitter, this definition applies to an airborne LiDAR system. [6] This technology provides valuable information for forest management, including monitoring forest loss, assessing damage, and tracking forest health. Since the launch of the first civilian Earth observation satellite in 1972, Satellite Remote Sensing has provided increasingly sophisticated information on the structure and function of forest ecosystems. [7]

      Some of the most used satellite platforms in forestry are: Sentinel-2 (ESA) developed by the European Space Agency (ESA) within the framework of the European Commission’s Copernicus program, Landsat (NASA/USGS) with a series of 9 satellites (from Landsat 1 to Landsat 9) orbiting the Earth, MODIS (NASA) which is used for global monitoring and fire detection, commercial satellites, etc. Several public institutions in Albania use the Integrated Forest Information System (ALFIS), which produces thematic data related to forests, supported in some cases by georeferenced data from the National Authority for Geospatial Information. To monitor changes over time in forest ecosystems, the management of protected areas uses the Jica system, satellite imagery (Sentinel 2), maintaining a database of forest fund growth and decline in

      cases of fire damage, illegal logging and construction, monitoring of fauna and flora through the iNaturalist program and camera traps, monitoring of climate change programs and the Hub.

      The use of LiDAR has helped researchers investigate the following: tree modeling [8], biomass assessment [9] and tree classification [10] .

      With greater access to information, increasingly advanced data collection and processing, and lessons learned from the functioning of traditional decision-making systems, more and more attention has been paid in recent decades to decision- making based on sources, data, and evidence, which reflect the results and findings of research based on scientific methodology and pass through the appropriate filters to ensure reliability. In Albania, many decision-making institutions but also scientific research institutions use satellite images from local stations N32-Satellite Nusat 32 (Albania 1) and SN33- Satellite Nusat 33 (Albania 2). In 2022, Albania signed a three- year agreement with geospatial company Satellogic to develop a dedicated satellite service that provides the country with sensitive satellite imaging capabilities across its entire territory. In January 2023, the Albania-1 and Albania-2 satellites were launched from Cape Canaveral in Florida with the following specifications: Low Earth Orbit (LEO) 490 km; Orbit: Sun- synchronous; Data Capture: 4-8 images per week; Orbital Period: 90 minutes.

      The most common sensors for assessing forestry health include the following: Visible light cameras (RGB cameras), multi- spectral cameras, hyper-spectral cameras, thermal cameras, laser detection and ranging (LiDAR) systems, terrestrial laser scanning (TLS) systems, and other common sensors. RGB cameras capture spectral information in visible light (400-700 nm), which is the same spectrum perceived by the human eye

      [11] using trichromatic red wavelengths from 620 to 750 nm, green from 495 to 570 nm, and blue from 450 to 495 nm. Multispectral sensors capture two or more bands in the visible and invisible spectrum [12] in the infrared and ultraviolet regions, valuable for assessing forest health by supporting the assessment of vegetation indices. Hyperspectral cameras have

      been used in forestry to obtain new vegetation indices to predict vegetation features such as leaf nitrogen content [13] chlorophyll, and other photosynthetic features of plants [14]. Regarding the progress of capturing and registering satellite images at the State Authority for Geospatial Information, a total of 30 high-resolution images with a pixel size of 70 cm have been used to calculate the necessary indices in support of the forestry sector. These images have also been used in the Department of Geography (University of Tirana) within the framework of a national project, funded by the National Agency for Scientific Research and Innovation with the topic: Use of GIS/RS in risk assessment and prediction of forest health for effective geo-environmental management in the Divjakë-Karavasta National Park.

      The goal of this project was to support the National Agency for Protected Areas with geospatial information regarding the forest health situation in this national park, providing a model of how geospatial technology can support the administration and management of forest areas, as well as their conservation in protected areas.

      Some of the indices based on geospatial data most used in the forestry sector are: Normalized Difference Vegetation Index (NDVI), which indicates the vegetative state of the plant; Enhanced Vegetation Index (EVI) which corrects for the influence of some atmospheric conditions, making it more accurate in areas with dense vegetation, Soil-adjusted Vegetation Index (SAVI) which adjusts for the influence of soil conditions and is used in areas with sparse vegetation, Normalized Water Change Index (NDWI) which is used to monitor changes in leaf water content, Normalized Moisture Change Index (NDMI): useful for assessing vegetation water content and monitoring drought conditions; Burned Area Index (BAI) which is used to identify burned areas and monitor vegetation recovery after a fire, etc.

      To achieve the objectives of this project, the Department of Geography managed to carry out a forest health risk assessment, through indices generated in a GIS environment such as NDVI, NDWI, GNDVI, NDMI, LCI, EVI, BAI for

      Divjaka Karavasta National Park.

      Map 1: the moisture levels in vegetation (Divjake Karavasta National Park) [15]

   2. Unmanned Aerial Vehicle

      Drones are unmanned devices that fly under command or independently using GPS and multispectral or hyperspectral

      sensors to record high-resolution images. This technology is widely used in the forestry sector, mainly for identifying diseased trees and monitoring sensitive areas, supporting the study of more limited areas in a short time. The use of drones and geographic information systems in forestry has grown intensively in Albania, referring to the opportunities offered by this technology in terms of collecting geospatial and multispectral data in a rapid manner, as well as the support that these data provide to geospatial analyses in terms of monitoring forest health, assessing plant stress, predicting this risk in the future, before symptoms become visible to the human eye, offering early and efficient interventions to reorient plant activities.

      The main benefits of using drones in Forestry and monitoring the health of forest surfaces are generated through the possibility of observing the state of plant cover in real time, tracking structural changes in forests, identifying plant stress, diseases, droughts, fires or deforestation through multispectral and thermal cameras, data generation and visual analysis, and artificial intelligence algorithms.

      Even in this case, within the framework of the aforementioned project, the Department of Geography successfully uses this technology by combining it with field verifications through the ArcGIS Survey software in the framework of involving students in professional practice in the field.

      Map 2: Reporting through arc gis survey 123 of damage to forest areas by natural

      and human factors; Overlay of geoinformation generated by UAV/GIS SURVEY 123/technologies. [16]

      Geography students, using GIS technology, are trained to make data-based decisions, contributing to the sustainable development of these spaces.

   3. Artificial Intelligence (AI)

      An important part of geospatial technology used in Forest Health and the conservation of forest areas is Artificial Intelligence as a revolution in the monitoring of forest areas and their sustainable management. This technology enables data analysis to identify patterns (e.g., tree classification, prediction of pest outbreaks).

      The State Agency for Geospatial Information (ASIG), as the central institution for the standardization and dissemination of spatial information in Albania, uses Artificial Intelligence (AI) in the processes of monitoring, analysis and management of protected natural areas.

      Fig.1: Forest Health Indices and Indicative Factors at the State Authority for Geospatial Information in Albania

      Meanwhile, Deep Learning enables the application of a trained model that automatically performs object detection, vegetation cover classification, semantic segmentation of damaged areas, and prediction of long-term trends in forest ecosystems.

      The integration of Deep Learning with Systems (GIS) and RS Technology enables the structuring, application and operation of decision-making platforms based on geoinformation,

      thereby making it possible to build intelligent platforms for real-time assessment and decision-making.

4. GEOSPATIAL ANALYSIS FOR FORESTRY

GOVERNANCE

Geospatial data-based technologies and analyses are an important tool that can support decision-making and operational and strategic management of forest development. Geospatial data, spatial modelling and multi-criteria offer opportunities to orient and prioritise environmental policies in general and forest planning. Geospatial data processing platforms such as Esri ArcGIS, QGIS etc. enable the processing of large sets of geospatial data, the generation of thematic maps and the development of analytical models that support sustainable forest use, management and protection against risks.

In this context, geospatial analyses not only enable an inventory of forest ecosystems, but also guide and play an important role in forest governance processes. Some of the geospatial analyses that can support decision-making in the forestry sector are:

• Satellite change detection (RS + GIS) supports forest monitoring and the assessment of human impacts on the environment by enabling the identification of deforestation, degradation and desertification of forest habitats. This analysis can be carried out in ArcGIS through tools such as Image Difference, Raster Calculator, Change Detection Wizard, as well as classification functions in Image Analyst.
• Vegetation Index Analysis supports decision-making in terms of monitoring, identifying and predicting plant stress in support of forest health and forest revegetation and reforestation planning. Tools such as NDVI function, Band Arithmetic, Raster Functions and Vegetation Index tools are used in ArcGIS.
• Structural Forest Classifications through satellite images, identifying forest categories and typologies, support decision-making for inventory and regeneration policies. In ArcGIS they are realized with Supervised Classification, Unsupervised Classification, Training Samples Manager, Random Trees classifier and Maximum Likelihood Classification.
• Lidar Analysis supports the process of mapping the vertical structure of forests and the assessment of biomass, important indicators for sustainable forest management and development and territorial planning. In ArcGIS, tools such as LAS Dataset tools, Point Cloud tools, Canopy Height Model derivation and Surface tools are used.
• Suitability Analysis is an analysis that enables the identification of areas for reforestation, supporting strategic decision-making. In ArcGIS, it is carried out with Weighted Overlay, Weighted Sum, Reclassify, Raster Calculator and Suitability Modeler.
• Fire Risk Modelling (GIS + RS) enables the identification of areas at risk of fire, supporting forest protection activities and emergency management. In ArcGIS, tools such as Kernel Density, Euclidean Distance, Cost Distance, Raster Calculator are used, as well as the integration of climate and vegetation data in ModelBuilder.
• Biodiversity Mapping enables the identification of areas of ecological value supporting the management of protected areas. In ArcGIS, tools such as Spatial Join, Hot Spot Analysis, Habitat Suitability tools, Buffer, Overlay tools and Landscape metrics extensions are used.
• Multi Criteria Decision Making supports strategic and tactical decision-making by mapping
• sensitive areas that require priority protection or intervention. In ArcGIS, it is realized with Weighted Overlay, Fuzzy Membership, Fuzzy Overlay, ModelBuilder and custom raster analyses.

Despite the limited recognition and implementation of geospatial technology in Albania, a good part of the national decision-making institutions constitute an important network in its use for the purpose of environmental monitoring and management in general as well as in spatial planning, while in the forestry sector it is mostly used in agencies dependent on these institutions as well as scientific research units such as universities such as the Agricultural University of Tirana, the Department of Geography at the Universit of Tirana which contribute through research, training and methodological development. The State Authority for Geospatial Information is a leading institution in the provision of geospatial data but also as a supporting institution of the national spatial data infrastructure and geoportal services. Meanwhile, the National Forestry Agency, the Protected Areas Agency, and the Natural Resources Management Agency use spatial analysis to manage and conserve biodiversity and forest habitats. In addition, the national forest information system ALFIS provides a WebGIS platform that integrates forest cadastre data, facilitating coordinated decision-making between institutions.

Fig. 2: Geospatial Forestry Governance in Albania

I. CONCLUSION:

Forest ecosystems, as one of the most important ecosystems on Earth, play a critical role in preserving biodiversity, regulating climate, and conserving soil and water. [17]

Geospatial Infrastructure is an important tool in the environmental management of protected areas, offering advanced technological methods for biodiversity protection and spatial planning. Its use enables the creation of a detailed inventory of vegetation health, enabling the creation of accurate maps of biodiversity distribution. Continuous monitoring of forest ecosystems through Remote Sensing (RS) and Geographic Information System (GIS) technologies, together with their geo-environmental management, especially when these ecosystems are part of protected areas, constitutes a significant challenge for developing countries like Albania.

The implementation of geospatial technology and its use by decision-making institutions, mainly in the forestry sector, develops new models of spatial analysis, complementing knowledge related to National Parks in wetland areas as a whole in the context of linking forest health issues with social, economic and environmental dimensions. These models can also be adapted for other areas for national policies and strategies, mainly in fulfilling Chapter 27 for Albania’s membership in the EU.

In this regard, the role of the State Authority for Geospatial Information is essential as a provider of accurate data to support decision-making in the orientation of afforestation activities, better planning of plantings by ensuring sustainable decision- making practices that promote forest regeneration.

In the last decade, Albania has made commendable progress in providing geospatial data through the National Geoportal, developed by the State Authority for Geospatial Information. This represents an important step towards Open Government, enabling researchers and professionals to access and use geospatial data more effectively.

Increased access to the use of satellite imagery and the availability of tools and software that support the processing and interpretation of information obtained from satellite imagery strengthens the application of this technology in central and local decision-making regarding the assessment of the status and changes of forest cover, their sustainable use, and the monitoring of forest health.

The use of new geospatial technologies (GIS, Remote Sensing, UAV) for forest monitoring and management offers a real opportunity to move from traditional management to an automated, accurate and data-driven approach. However, the lack of technical skills and trained human resources within these institutions significantly limits the efficiency and timely response to processes such as forest degradation, fires or illegal encroachment. Investing in increasing the technical and digital capacities of these structures is necessary to ensure sustainable, inclusive management and compliance with EU standards and the requirements of Chapter 27 for the protection of nature and biodiversity.

The results of this study are a contribution that connects technology to governance, a study that fills an institutional gap.

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