INTRODUCTION
Forests encompass about 30% of the world’s land area and play a vital role in sustaining life on Earth by providing essential ecological services at local, national, and global levels However, climate change poses severe threats to these ecosystems and the livelihoods of communities dependent on them, with predictions indicating a global temperature rise of 1.8 to 4°C and sea levels increasing by approximately 0.75 to 1.5 meters by 2100 Greenhouse gases such as CO2, CFCs, and CH4, produced by industrial emissions, fossil fuel combustion, volcanic activity, and nuclear explosions, significantly contribute to environmental pollution and climate change Deforestation and forest degradation are major sources of greenhouse gas emissions, accounting for nearly one-fifth of global emissions, as highlighted in reports presented at climate meetings in Bonn, Germany, in 2009 This problem is exacerbated by frequent and severe forest fires, not only in developing tropical countries but also in developed nations like the USA and Russia, leading to the destruction of thousands of hectares of forest and crops. -Protect forests and fight climate change with expert insights—start your eco-journey today [Learn more](https://pollinations.ai/redirect/draftalpha)
Forests play a crucial role in environmental protection by providing essential ecosystem services and direct resources such as timber and non-timber products Their capacity for carbon absorption significantly contributes to reducing greenhouse gases and mitigating global climate change The value of forest carbon sequestration can be monetized through mechanisms like Payment for Environmental Services (PES) and REDD+ programs, incentivizing sustainable forest management Initiatives like the Clean Development Mechanism (CDM) further promote the integration of forest conservation into international climate action efforts, with countries like Vietnam implementing these strategies to balance environmental protection and economic development.
The development mechanism outlined in Article 12 of the Kyoto Protocol under the UNFCCC allows developing countries to utilize plantation efforts to absorb CO2 as a measure to reduce greenhouse gas emissions While qualitative research highlights the environmental benefits of this approach, it remains a pioneering and relatively new concept in Vietnam, representing an important first step toward sustainable climate change mitigation in the country.
Recent advancements in Geographical Information Systems (GIS) and Remote Sensing (RS) technologies have significantly improved natural resources management by enabling large-scale image analysis and detailed vegetation monitoring Satellite imagery has become more accessible, allowing researchers to assess forest above-ground biomass (AGB) and vegetation structure through spectral reflectance measurements While optical RS does not directly measure AGB, it provides valuable insights by analyzing vegetation texture, crown size, and shadow effects, especially in infrared bands Remote Sensing is now considered the most reliable method for estimating spatial biomass in tropical regions over extensive areas, offering a cost-effective and efficient approach for large-scale biomass assessment Its application in various studies underscores its potential for accurate, repeated data collection with minimal effort, making RS an essential tool in forest biomass estimation.
Forests in Cuc Phuong National Park are considered a national treasure, offering vital resources such as grazing land, wildlife habitats, water sources, timber, and non-timber products for local communities However, increasing human activities are increasingly threatening both the quality and quantity of these forests Recent studies aim to quantify the carbon sequestration capacity of the forests, highlighting their significant role in climate change mitigation.
Understanding biomass in mountain forest ecosystems is essential for evaluating their ecological and economic value through carbon accumulation capacity These forests not only serve as vital natural resources for academic research but also provide essential eco-services that support sustainable tourism development To achieve this, our study titled "Using Geospatial Technology to Map Forest Carbon" leverages advanced spatial analysis tools to accurately assess carbon stocks in mountainous regions, promoting both conservation and responsible tourism growth.
Cuc Phuong National Park" for the student graduation thesis
GOALS AND SPECIFIC OBJECTIVES
Goals
This article assesses the carbon stock of forests in Cuc Phuong National Park, providing essential scientific data to support sustainable forest management and development By identifying key carbon storage areas, the study aims to promote environmentally responsible practices that balance conservation and economic growth The findings offer valuable insights for policymakers and stakeholders committed to preserving forest ecosystems while addressing climate change Implementing these scientific recommendations can enhance forest resilience, ensure long-term ecological health, and contribute to global efforts in reducing carbon emissions.
Scope of object
Studying the forests of Cuc Phuong national park in Cuc Phuong commune, Nho Quan district, Ninh Binh province.
Specific objectives
- Mapping the land cover in study site from SPOT 5 imagery
- Estimating and mapping the forest volume in study area from SPOT 5 imagery
- Estimating and mapping the aboveground carbon stock of forests in study area
- Proposing possible solutions to enhance forest management in study area
The forests carbon stock in Cuc Phuong Natinal Park at Cuc Phuong commune over 1,000,000 ton
STUDY AREA AND METHODOLOGY
Study area
The study site includes the forests of Cuc Phuong national park in Cuc Phuong Commune, Nho Quan District, Ninh Binh Provinces (Figure 3.1)
Figure 3.1.1: Map of study area: (a) Land border map of Vietnam (b) Ninh Binh
Province (c) Cuc Phuong commune, Nho Quan Districts
Cuc Phuong National Park is strategically located between Ninh Binh, Hoa Binh, and Thanh Hoa provinces, covering a total area of 22,180 hectares with diverse regional distributions Situated at 350 meters above sea level, the park experiences an average temperature of 20.6°C, with annual precipitation ranging from 1800 mm to 2400 mm and a humidity level consistently above 88%, creating ideal conditions for rich biodiversity The park's flora is remarkably lush, featuring a towering emergent layer of 40-50 meters, dominated by dipterocarp species such as Parashorea stellata reaching up to 70 meters, along with semi-evergreen, deciduous, and evergreen trees like Terminalia myriocarpa, Pometia pinnata, Castanopsis, and Lindera The vegetation includes multiple canopy layers, dense undergrowth, herbs, shrubs, and numerous species with practical uses, including medicinal plants, edible fruits, and spices Over 2,000 vascular plant species, including endangered and endemic varieties, thrive within the park, supported by specialized flora like Podocarpus wallichianus at higher altitudes Cuc Phuong is a vital habitat for wildlife, supporting approximately 300 bird species, 65 mammals, 37 reptiles, and 16 amphibians, making it an important ecological and conservation site in northern Vietnam.
Data sources
Studying the use inheritance to collect data with the following information:
SPOT 5 satellite images from 2015, collected for the study area, were provided by the Institute for Forest Ecology and Environment of Vietnam National University of Forestry (IFEE) Table 1 details the configuration and technical specifications of the SPOT 5 imagery used in this research.
Table 3.2.1: Technical parameters and properties of the sensors used in this study
500–590 (green) 610–680 (red) 790–890 (NIR) 1580–1750 (mid IR)
Spatial Resolution (m) Pixel Size 1.5 × 1.5 (m/pxl)
Methodology
The proposed methodology is illustrated in Figure 3.2 Software eCognition Developer v8.9, MapInfo Professional 12.5 and ArcGIS desktop 10.2 were used
Figure 3.3.1: The processing steps of study
The study used eCognition v8.9 image analysis software for pre-analysis image SOPT 5 and NDVI for key of image classification eCognition v8.9 image analysis software
Using eCognition v8.9 image analysis software (Baatz et al., 2004) for image segmentation is a fundamental step in object-based image analysis Image segmentation involves partitioning an image into distinct regions based on defined parameters, with the goal of grouping pixels with similar characteristics These parameters typically assess the homogeneity or heterogeneity of the regions, ensuring accurate delineation of features within the imagery (Myint et al., 2008; Pal et al., 1993) Effective segmentation lays the foundation for subsequent analysis and classification tasks in remote sensing studies.
Multiresolution segmentation in eCognition software effectively classifies homogeneous areas within forest images, aiding in detailed forest planning This process divides the basin into multiple small plots, also known as sub-plots, for more precise management Key parameters such as scale (set to a specific value), shape (0.1), and compactness (0.5) optimize segmentation accuracy The resulting boundary maps, exported as files, include important forest plot information, such as average values and standard deviations across different image channels, supporting comprehensive forest analysis and decision-making.
Normalized Different Vegetation Index (NDVI)
The study used NDVI to map the status of forest in Cuc Phuong National Park with 60 sample plots and 65 points in study area NDVI is calculated by following formula:
Where: Nir spectral reflectance values of the near-infrared channel (Band 3), the spectral values of channel Red (Band 2) in Spot 5
Based on the standard sample survey method outlined in Circular No 34/2009/TT-BNN, the study involved delineating forest plots and assessing forest status within the state A total of 60 plots and 65 sampling points were established to accurately evaluate the distribution and condition of forest areas across the region This approach ensures a comprehensive understanding of forest resources in accordance with official guidelines.
The study assesses forest status, reserves, and map accuracy, utilizing 20 plots and 22 test points These plots and secondary surveys are distributed across all forest regions, with variations reflecting differences in forest distribution, access, and extent in each state This approach ensures comprehensive evaluation of forest conditions and map reliability across diverse forest environments.
In Cuc Phuong National Park, sample plots exhibit high variability in topography and vegetation types, requiring careful consideration of plot size and shape to balance accuracy, precision, time, and cost A 25m x 40m square plot, accurately located via GPS, is used for data collection, measuring tree DBH and height following standardized regulations After establishing a 1000m² plot, five 4m x 4m sub-plots are designated to gather detailed information on shrubs and plant composition within the sampling area.
Figure 3.3.3: The layout of distribution points
No Name X Y D13(Average) H(Average) Note
This study involves overlaying the investigated plot positions and points onto a boundary map to accurately delineate study areas Land cover classes are tagged with their corresponding NDVI values to facilitate detailed analysis Statistical analysis of NDVI values for each land cover class is conducted to identify spectral characteristics These findings are utilized to develop a classification key, enhancing the accuracy of image classification for land cover mapping.
This study utilizes key image classification techniques to identify forest conditions within the study area By grouping NDVI values for each object-based component, the research effectively interprets and maps the forest status Reclassification with analysis tools enables precise identification of key forest reserves, providing valuable insights for forest management and conservation strategies.
Accuracy assessment is a crucial component of the image classification process, involving the evaluation of positional and thematic accuracies In this study, a matrix table was employed, as it is the most widely used method for assessing classification agreement in remote sensing The accuracy was validated using 22 ground truth points—comprising 2 points for Water, 5 points for Plantation, 5 points for Bamboo, and 10 points for Others—and 25 plots, with 5 plots designated for each forest type.
Overlay the forest allocation map with the forest status map to analyze spatial relationships Utilize the existing 60 sample plots to accurately calculate the forest volume for each forest type Generate a comprehensive forest volume map to visualize biomass distribution across the study area This integrated approach enhances understanding of forest resources, supporting sustainable management and conservation efforts.
(Source: The circular 34, Ministry of Agriculture and Rural Development)
The following formula were used to calculate carbon was assessed in five forest carbon pools, which is in accordance with the IPCC 2006 GL (Estrada 2011) These forest carbon pools are:
1 Aboveground vegetation: carbon stocked in live and standing vegetation (trees, shrubs, undergrowth and regeneration)
2 Belowground vegetation: carbon stored in roots
3 Dead wood: carbon stored in standing and fallen dead trees and shrubs
4 Litter: carbon in shed leaves and fine branches
5 Soil: carbon stored as soil organic matter
I am primarily interested in quantifying the carbon stock in aboveground biomass, which includes all aboveground vegetation Using data derived from forest volume measurements and applying Biomass Conversion and Expansion Factors (BCEF), I utilize a specific formula to accurately estimate the carbon stored in aboveground biomass.
Aboveground biomass carbon stock of trees in plot sp, in stratum i at time t=0; t
Merchantable volume of tree l of species j in plot sp in stratum i at time t=0, m3
Biomass conversion and expansion factor for conversion of merchantable volume to total aboveground tree biomass for tree species j; dimensionless Carbon fraction of biomass for tree species j;
L 1, 2, 3, … Nj,sp,i,t sequence number of individual trees of species j in sample plot sp in stratum i at time t
I 1, 2, 3, …M strata j 1, 2, 3 … S tree species t=0 0 years elapsed since start of the project activity
With =0.47 (Andreae and Merlet, 2001; Chambers et al., 2001; McGroddy et al., 2004; Lasco and Pulhin, 2003)
BCEF for nature forests in North Central Vietnam here:
(Sources: 2006 IPCC Guidelines for National Greenhouse Gas Inventories)
Evaluate carbon value for forest environmental services
Amount of CO2 absorbed = Carbon *44/12
- According to the Forest Science Institute of Vietnam
Carbon Price = Amount of CO2 * Price (USD/tonCO2)
- The price in the carbon dioxide:
• Low price: 5 USD / ton CO2
• High price: 11 USD / ton CO2
• $ 1 = 22300 VND exchange rate at the time of the study
RESULTS
Land cover classification map of Cuc Phuong National Park
This study utilized NDVI to map land cover types within the study site, identifying eight classes with distinct NDVI ranges—water, bare land, plantation, grasses, restored forest, medium forest, and rich forest GPS technology was employed to accurately mark 10 plots representing various surface cover types, including restored forest, poor forest, medium forest, and rich forest, while water bodies were also included in the mapping efforts.
8 points, Others (including bare land, grasses and residential) have 15 points, Plantation have
10 points and Bamboo forest have 10 points
Table 4.1.1: NDVI value for water
Table 4.1.2: NDVI value for others
Table 4.1.3: NDVI value for Bamboo forest based-object
Table 4.1.4: NDVI value for poor forest
Table 4.1.5: NDVI value for restored forest
Table 4.1.6: NDVI value for plantation based-object
(Sources: Cuc Phuong National Park - Studying using data and documents about forest volume of plantation at Cuc Phuong National Park managers in 2016)
Table 4.1.7: NDVI value for medium forest
Table 4.1.8: NDVI value for rich forest
The analysis of Tables 4.1.1 to 4.1.8 indicates notable variations in NDVI values across different object types, with variations in minimum, maximum, and standard deviation Water bodies exhibited NDVI values ranging from approximately -0.39336 (minimum) to -0.09021 (maximum), reflecting their unique spectral characteristics In contrast, dense forest areas showed significantly higher NDVI values, ranging from 0.78427 to 0.85263, highlighting their lush vegetation and high greenness levels These NDVI patterns effectively differentiate land cover types, emphasizing the utility of NDVI in remote sensing and land monitoring applications.
I concluded that NDVI ranging were clearly indicated in Table 4.9 (Data collected in Appendixes)
Table 4.1.9: NDVI range for each land cover class in Cuc Phuong National Park
No Land cover classes NDVI
The NDVI values for water ranged from -0.39336 to -0.09021, reflecting its strong infrared light absorption, which results in very low NDVI values Forest classes, including bamboo, restored, poor, medium, and rich, exhibited NDVI ranges from 0.53498 to 0.85263, indicating healthy vegetation cover The plantation class showed NDVI values between 0.24363 and 0.53468, characterized by high density and low shrub presence, while other land types, such as bare land with grass and small shrubs, had NDVI values from -0.09121 to 0.24263, reflecting their ability to absorb red light and reflect infrared light, leading to relatively higher NDVI values than water.
In Cuc Phuong National Park, the NDVI values are relatively high due to the presence of dense understory vegetation and a 20% canopy volume, though still lower than those in natural forests Among the different forest types, bamboo forests, restored forests, and various levels of forest quality (poor, medium, and rich) exhibit higher NDVI values, reflecting their abundance of natural trees Conversely, areas with fewer shrubs and regeneration stages show lower NDVI values, indicating less dense vegetation and earlier successional stages.
Figure 4.1.1: The status forest map in Cuc Phuong commune
To verify the accuracy of this study, five plots were established for each forest type, with water and other features marked using a GPS device The results demonstrate the accuracy statistics, which are summarized in Table 4.1.10.
Table 4.1.10: Summarized accuracy of objects
Land cover Water Others Planta- tion
The results showed that error of interpretation on the status of forests is 16.25%, the accuracy of interpretation of the status of forests is 83.75%
The Table 4.1.11 showed the area of land cover classes in study area with eight classes with responding area class
Table 4.1.11: The status forest map in Cuc Phuong commune
No Land cover classes Area (ha) %
The study area is predominantly covered by rich forests, accounting for approximately 72.07% of the total land area with around 9,447 hectares Water bodies and bamboo areas are minimal, representing only 0.03% (3.31 hectares) and 0.02% (2.15 hectares), respectively Medium forests, poor forests, and other land types each comprise roughly 8% of the total area, with estimates of 1,095 hectares, 1,085 hectares, and 945 hectares, respectively In contrast, plantation and restored forests occupy a small proportion of the landscape, covering approximately 327 hectares and 203.74 hectares, which together make up about 2% of the total land area.
The forest volume map in Cuc Phuong National Park of Cuc Phuong commune
Based on the data from Tables 4.1.4 to 4.1.8, Table 4.2.1 presents the forest volume of Cuc Phuong National Park categorized by different forest types Since non-forest classes such as Water and Other do not have volume measurements, the study focused on estimating the timber volume across five main forest classes: rich, medium, poor, restored, plantation, and bamboo forests.
Table 4.2.1: Forest volume of Cuc Phuong National Park
Class The average forest volume (m 3 /ha)
Rich forests have the highest volume at 298.1 m³/ha, while restored forests have the lowest at approximately 41.4 m³/ha Over time, the volumes of plantation, medium, and poor forests have steadily declined, with reductions of 78 m³/ha, 177 m³/ha, and 79.3 m³/ha, respectively This trend highlights the significant decline in forest volume across different forest types, emphasizing the importance of sustainable forest management.
Figure 4.2.1: The forest volume map in Cuc Phuong commune
The map of forest carbon in Cuc Phuong National Park of Cuc Phuong commune
The study calculated the carbon dioxide absorbed in study site, which illustrated in following figure
Figure 4.3.1: The forest carbon map in Cuc Phuong National Park of
Figure 4.3.1 shows the carbon stock levels at the study site, with the highest value of 133.1 tons observed in rich and medium forest objects In contrast, water bodies and bare land categories have the lowest carbon stock, registering 0 tons This data highlights the significant contribution of forested areas to carbon storage and emphasizes the minimal carbon presence in water and bare land regions.
Table 4.3.1: Total forest carbon in Cuc Phuong National Park
The average forest volume (m 3 /ha)
As the result of Table 4.3.3 indicated the total forest carbon stock in Cuc Phuong
Cuc Phuong National Park's forest stock is approximately 1,480,000 tons, with the rich forest comprising the majority at over 1,257,493.81 tons, representing 85.52% of the total carbon stock Medium, poor, plantation, and restored forests contribute 11.83%, 7.98%, 1.22%, and 0.55% respectively, totaling around 17982.83, 117383.84, 69394.54, and 8126.96 tons The study focuses solely on forest volume assessments of rich, medium, poor, plantation, and restored forests, excluding water, bare land, and bamboo forest, which are not measured for carbon stock.
Mapping the Carbon Dioxide absorbed
The study calculated the carbon dioxide absorbed in study site, which illustrated in following figure
Figure 4.4.1: The CO 2 absorbed map in Cuc Phuong commune Table 4.4.1: The CO 2 absorbed in Cuc Phuong National Park at Cuc Phuong Commune
With formula: Amount of CO2 absorbed = Carbon *44/12 The figure 4.4.1 indicated the CO2 absorbed in forest at Cuc Phuong commune with the highest value at 488.04 ton/ha
27 for rich forest and the lowest value is 146.26 ton/ha (represent 144.87 ton/ha) for restored forest
Evaluate carbon dioxide value for forest environmental services
Table 4.4.2: Evaluate carbon dioxide value for forest environmental services
CO 2 USD/ton CO 2 per ha
Ton/ha Low price High price
Figure 4.4.2: Figure carbon absorb value of different forest types in CPNP
USD/ton CO2 per ha USD/ton CO2 per ha
Rich forests have the highest carbon absorption capacity and command the highest price at $2,440.17 per hectare, highlighting their significant environmental and economic value Medium forests also offer substantial carbon sequestration, valued at approximately $1,982.75 per hectare, while poor forests have a lower market value of around $1,161.60 per hectare In contrast, plantation and restored forests show much lower economic returns, with prices of $1,008.15 and $731.20 per hectare, respectively, reflecting their comparatively limited carbon storage potential.
The primary factor contributing to these differences is that these forest types vary in age, with uneven growth indices and density levels This variation affects their capacity for carbon absorption, as younger forests typically have lower growth rates and biomass, while older forests tend to absorb more carbon due to greater size and maturity Understanding these disparities is essential for accurate carbon sequestration assessments and effective forest management strategies.
4.3 Proposing solutions to improve the management of forests in Cuc Phuong commune
Cuc Phuong National Park in Hanoi faces significant challenges related to forest volume and carbon stock, including inadequate land use planning, incomplete management structures, and ineffective management plans The park also contains large areas of mature, aging forests that have reached their maximum growth potential and are showing signs of degradation Additionally, the expansive land area increases vulnerability to erosion, especially during intense rainfall To address these issues, targeted solutions are necessary to enhance forest quality, improve carbon stock management, and increase carbon dioxide absorption in Cuc Phuong Commune.
Effective management of forest lands and inter-agency cooperation are essential for sustainable forestry development Clear legal definitions of rights and obligations for individuals and organizations assigned to manage forest and land resources are crucial, especially concerning timber usage Those responsible for forest management must be accountable under the law for any violations, including illegal encroachment and unauthorized land use conversions Strengthening inspection processes and enforcing strict regulations are vital to prevent unlawful activities and protect forest integrity.
The application of information technology into management and monitoring changes in forest resources processes such as organizations and units who own protection forest should
29 participate fully in managing and monitoring changes in forest resource by using database system on the computer at the local and the whole province
Encouraging investment in policy support by integrating ecotourism development with forest protection programs is essential, leveraging both domestic and international funding sources Additionally, prioritizing public education and awareness campaigns about the vital role of forests in sustaining the environment and human well-being—particularly targeting the younger generation—can foster greater conservation efforts and sustainable practices.
This study conducted comprehensive mapping of forest carbon in Cuc Phuong National Park, focusing on the Cuc Phuong commune Using three distinct maps—forest volume, forest carbon stock, and carbon dioxide absorption—the research provides detailed insights into the park's biomass and its role in mitigating climate change These findings highlight the significance of Cuc Phuong's forests in carbon sequestration and contribute to sustainable forest management strategies.
This study presents the first map of forest volume in Cuc Phuong National Park, covering a total area of 13,109.84 hectares within Cuc Phuong commune The analysis classifies the area into eight categories: water, plantation, bamboo forest, restored forest, poor forest, medium forest, rich forest, and others While water, bamboo, and other classes are included, the primary focus is on five forest types with the highest volume values, notably rich forest The study finds that restored forests have the lowest volume due to replanting and natural recovery efforts, highlighting the variations in forest biomass across different land types in the park.
The study estimates the total forest carbon stock in the study area at approximately 1,480,000 tons, with the highest carbon density reaching 133.10 tons per hectare, as shown in Figure 4.3.1 This value exceeds previous measurements in Kim Boi District, Hoa Binh Province, which reported around 130 tons per hectare and a total of 1,023,726 tons of carbon, according to results from Assoc Pro Dr Tran Quang Bao.
2013, identified the carbon stock of forest classes in Kim Boi District, Hoa Binh province
This thesis presents a comprehensive mapping of carbon dioxide absorption in Cuc Phuong National Park The findings reveal that Cuc Phuong Commune exhibits a significant capacity for CO2 sequestration, with absorption levels reaching a maximum of approximately 488.04 tons per hectare These results highlight the critical role of Cuc Phuong National Park in contributing to carbon sequestration and climate change mitigation efforts.
Cuc Phuong National Park's forest has a high carbon volume, stock, and capacity for absorbing carbon dioxide, highlighting its significant ecological value The park's status as a natural, evergreen broadleaf limestone forest with abundant primary forest makes it rich and diverse, supporting a wide variety of flora and fauna Compared to other regions, Cuc Phuong's forests are notably valuable and require ongoing protection to preserve its unique wildlife and plant species for future generations.
This study demonstrates that applying remote sensing technology and high-resolution satellite images, such as SPOT 5, enables highly accurate forest monitoring and mapping with an interpretation accuracy of 83.75% The research identified key land cover and land use categories in Cuc Phuong commune, including rich, medium, poor, restored, bamboo, plantation forests, water bodies, and others Covering a total area of 13,109.84 hectares, the study also estimates the total forest carbon stock at approximately 1,480,000 tons, highlighting the effectiveness of satellite-based approaches for forest assessment and carbon accounting.
The study highlights that the dense forest covers the largest area of 9,447.62 hectares, accounting for 72.07% of the total forested land, with an average volume of 298.1 m³/ha and holding approximately 1,257,493.81 tons of carbon, representing 85.52% of the total carbon stock In contrast, the restored forest area is the smallest, with a volume of only 203.74 m³/ha and containing around 8,126.96 tons of carbon, which accounts for just 0.55% of the overall carbon stock This data emphasizes the dominance of mature forests in carbon sequestration and overall forest resource distribution, highlighting the importance of preserving large forested areas for climate change mitigation.
The carbon stock and CO2 absorbed for rich forest in forest at Cuc Phuong commune with the highest value around 133.1 ton/ha and 488.04 ton/ha, respectively
The study faces limitations due to insufficient time and resources for extensive data collection, as well as the author's limited knowledge, skills, and experience To overcome these challenges and enhance the results, further research should focus on gathering more information for future planning, expanding the number of sample plots across different forest types, and improving user proficiency in applying geospatial technology.
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No Commune X Y D13(Average) H(Average) Note