2.1.1 Status and distribution of mangrove forest in the world
Experts and scientists have extensively studied the term "mangrove" for many years (Tomlison, 1986) It refers to trees and shrubs that have evolved unique morphological adaptations—such as aerial roots, salt excretion glands, and viviparous seeds—to thrive in tidal environments Additionally, the term encompasses the complex mangrove ecosystem itself, which plays a vital role in coastal protection and biodiversity.
Mangrove forests are located in the inter-tidal zones between the sea and land in tropical and subtropical regions worldwide, typically between approximately 30° N and 30° S latitude (Giri et al., 2010) Their global distribution is primarily influenced by major ocean currents and the 20°C seawater isotherm during winter months, which help define their range (Alongi, 2009).
The first comprehensive global assessment of mangrove area was conducted by FAO and UNEP in 1980, estimating that worldwide mangrove forests covered approximately 15,642,673 hectares Subsequent studies have been performed to update and refine these estimates, with their findings summarized in Table 2.1.
Table 2.1: Mangroves extent in the world (ha)
A 2010 study by Giri et al estimated the global extent of mangrove forests in 2000 at approximately 137,760 km² across 118 countries and territories The report revealed that Asia holds the largest proportion of mangroves, accounting for 42%, followed by Africa with 20%, North and Central America with 15%, Oceania with 12%, and South America with 11% Notably, about 75% of the world's mangroves are concentrated in just 15 countries, highlighting significant regional distributions of these vital ecosystems.
Table 2.2: The 15 mangrove-rich countries
No Country Area (ha) % of global total Region
Global mangrove forests have decreased by more than 50% since historical levels, and many remaining areas are heavily degraded (Spalding et al., 1997; UNEP, 2004) Coastal habitats worldwide face intense pressure from population growth, development, and frequent storms, contributing to their decline Major causes of mangrove loss include conversion for agriculture, aquaculture, tourism, urban development, and overexploitation (Alongi, 2002; Giri et al., 2008) Between 1980 and 2000, approximately 35% of mangroves were lost, highlighting the urgent need for conservation efforts.
The decline of forests, including mangroves, has accelerated faster than inland tropical forests and coral reefs (Duke et al., 2007), with sea-level rise posing the greatest threat to these ecosystems (Gilman et al., 2008) Projections indicate that 30–40% of coastal wetlands (IPCC, 2007) and up to 100% of mangrove forests (Duke et al., 2007) could be lost within the next century if current rates of destruction continue.
Recent data shows a significant decline in mangrove loss, decreasing from 187,000 hectares annually in the 1980s to 102,000 hectares during 2000-2005, highlighting increased awareness of the ecological importance of mangroves (FAO, 2007) This positive trend is driven by stronger legal protections, such as bans and restrictions on converting mangroves for aquaculture and other purposes, along with mandatory environmental impact assessments for large-scale developments Consequently, many countries have implemented new legislation and improved mangrove management practices, leading to efforts in mangrove conservation through active planting and natural regeneration.
2.1.2 Significance of mangroves carbon stock
Mangroves are among the most carbon-rich tropical forests, storing an average of 1,023 Mg of carbon per hectare This exceptional carbon sequestration capacity significantly surpasses the mean carbon storage of the world’s major forest ecosystems, highlighting the crucial role of mangroves in global carbon mitigation efforts.
Fig 2.1 : Comparison of mangrove C storage (mean ±95% confidence interval) with that of major global forest domains
Forest ecosystems play a vital role in carbon sequestration through two primary mechanisms: the growth of tree biomass (wood) via carbon fixation and the gradual accumulation of carbon in soils over time In mangrove ecosystems, carbon is stored in two main pools: above-ground (living trees, dead wood, shrubs, litter, and fallen material) and below-ground (roots and soil) Notably, the majority of carbon—often over 50% and sometimes exceeding 90%—is stored in below-ground pools, with 75–95% of tree carbon residing in dead roots However, above-ground biomass is frequently lost due to activities like clear-cutting, human use, decomposition, and export to adjacent coastal zones, impacting the overall carbon storage capacity of mangrove ecosystems.
The contribution of mangrove to global forest carbon sequestration is small It accounts for about 3 % of carbon sequestered by the world’s tropical forests although accounting for
Mangroves occupy less than 1% of the total tropical forest area (Alongi, 2016), but their high area-specific carbon stocks mean that disturbance or deforestation can lead to significant greenhouse gas emissions For instance, removing mangroves on peat soils results in CO2 emissions of approximately 2,900 tC/km²/year, which is comparable to emissions from the collapse of terrestrial peatlands (Lovelock et al., 2011) Globally, clearing mangroves and soils can produce CO2 emissions ranging from 112 to 392 tC per hectare, representing about 2–10% of total global deforestation emissions and up to 50% of emissions from tropical peatlands (Donato et al., 2011).
Preventing carbon emissions through mangrove conservation is more cost-effective than reducing emissions from regulated GHG sources in developed countries Studies show that avoiding a ton of carbon emissions from mangrove deforestation costs less than mitigating a ton of emissions from existing industrial sources (Siikamaki et al., 2012) This highlights the economic advantages of protecting mangroves as a natural solution for climate change mitigation.
2.1.3 Status and distribution of mangrove forest in Viet Nam
According to MARD of Viet Nam in 2018, Viet Nam had about 200.000 ha of mangrove forest, which divided into 4 main regions and 12 sub-regions (Hong et al., 1991) included:
The Northeast coast area, stretching from Mui Ngoc in Quang Ninh province to Do Son in Hai Phong city, features complex geomorphology, hydrology, and climate conditions While certain characteristics, such as protection from large waves and storms, create favorable environments for mangrove development, other factors like low rainfall, cold winters, and limited sediment deposition restrict mangrove growth and diversity Mangrove forests are primarily found in estuarine regions like Tien Yen – Bai Che, where environmental conditions support their proliferation.
The coastal areas of the Northern Delta, from Do Son (Hai Phong city) to Lach Truong (Thanh Hoa province), feature natural mangrove forests thriving in estuary regions These forests are characterized by sandy islands in front of estuaries that serve as natural barriers against tidal influences However, in the southern part of this region, the growth of natural mangroves is limited due to the strong effects of tides and storms The mangrove community primarily comprises brackish water plants, notably Sonneratia caseolaris, which are commonly found in estuarine areas such as Tien Lang in Hai Phong.
III) Central Coast region, from Lach Truong (Thanh Hoa province) to Vung Tau (Ba Ria - Vung Tau): Natural mangroves do not develop along the coast because of empty terrain which vulnerable to large waves, steep coastline, short rivers, less sediment Therefore, natural mangrove forests are mainly concentrated in estuary area and uneven distribution due to the influence of topography and sandy wind
The southern coastal area from Vung Tau (Ba Ria - Vung Tau) to Mui Nai, Ha Tien in Kien Giang province boasts favorable natural conditions for mangrove development, including high temperatures, abundant rainfall, fertile soil, and fewer storms This region is home to a diverse range of mangrove species, representing most of Vietnam's mangrove flora Historically, in the early 20th century, over 250,000 hectares of mangrove forests thrived here, but much of this area was lost due to war and increasing population pressure. -Protect Southern Vietnam's rich mangrove legacy with sustainable growth—discover how at [Learn more](https://pollinations.ai/redirect/draftalpha)
GOAL, OBJECTIVES AND METHODOLOGY
This study aims to provide an additional scientific foundation of estimating above- ground biomass and carbon stocks of mangrove forests based remote sensing and field survey data
Objective 1: To investigate the status of mangrove forests and management scheme in
Hai Ha district, Quang Ninh province
This article aims to answer key questions about mangrove forests, including their total extent, species diversity, spatial distribution, and the effectiveness of current management schemes within the study area Understanding the size and variety of mangrove ecosystems is essential for conservation efforts, while mapping their spatial distribution helps identify critical habitats Additionally, evaluating existing management practices provides insights into their success and areas needing improvement to ensure sustainable preservation of mangrove forests.
Objective 2: To estimate above-ground biomass and carbon stocks of mangrove forests during 2013- 2019 in Hai Ha district, Quang Ninh province
This article examines the carbon stocks per hectare in mangrove forests, addressing key questions about their distribution and variability It identifies the regions where carbon stocks are highest and lowest, providing insights into spatial differences Additionally, the study explores the main environmental and ecological drivers influencing fluctuations in mangrove carbon stocks, highlighting factors such as climate conditions, forest density, and human activity that impact carbon sequestration capacity.
Objective 3: To quantify changes in above-ground biomass and carbon stocks of mangrove forests during 2010- 2019 in Hai Ha district, Quang Ninh province
This study aims to analyze the changes in biomass and carbon stocks of mangrove forests over selected periods, providing insights into the extent of their depletion or accumulation It also identifies the key drivers responsible for these changes, such as deforestation, climate change, and human activities Understanding these dynamics is essential for effective mangrove conservation and management strategies that mitigate carbon emissions and preserve biodiversity The results highlight significant variations in biomass and carbon storage, emphasizing the urgent need for sustainable practices to protect these vital ecosystems.
Objective 4: To propose solutions to enhance carbon stocks of mangrove forests in Hai
Ha district, Quang Ninh province
This objective is going to answer the question of what the solutions should be given to enhance carbon stocks of mangrove forests in studies sites
Sentinel-2A images, which have been developed and are being operated by European Space Agency (ESA), with the spatial resolution 10 m were obtained from Earth Explore web page
Specific remotely sensed images used in this study were presented in Table 3.1
No Image code Date acquired
Source: United States Geological Survey (2019)
3.3.2 Investigating the status of mangrove forests and management scheme in Hai Ha district, Quang Ninh province
To estimate how much mangrove forest extents there are and determine where the mangrove forest has spatially distributed
We utilized Sentinel-2 imagery with various band combinations at 10-meter resolution to classify land cover using the NDVI classification method in ArcGIS 10.4 software Field survey data and Google Earth were employed to validate the accuracy of the classified map The mapping process was systematically organized and depicted in Diagram 3.2 to ensure clarity and reproducibility.
Step 1: Drawing polygon of mangrove forest area of Hai Ha district
Google Earth Software (GES) offers high-resolution images ranging from 0.1 to 2.5 meters, depending on data sources and satellite image quality For this study, images were obtained from Maxar Technologies (formerly DigitalGlobal) with a resolution of 0.3 meters, allowing for clear and precise identification of objects within the study area.
Mangrove polygon was drawn directly on GES Image in 2016 was also considered for drawing process to ensure that no mangrove areas were missed during the entire study period
At the same time, ground-truthing points were used to identify suspicious points on the map, thereby increasing the accuracy of the polygon These processes were demonstrated by Fig 3.1
Diagram 3.1: Establishment processes of land covers and NDVI map
Fig 3.1: Polygon of study area
(1) Create polygon of mangrove from Google Earth Pro software
(2) Clip band 4 and band 8 of satellite images in 2016 and 2019 by polygon created
(3) Calculate NDVI value based on band 4 and band 8 clipped
(4) Composite band 1 to band 6 of satellite data =>
Create map of study area
(5) Classify land cover types corresponding to each class of
(6) Assess the accuracy of classified map
(6.2) Collect Ground-truthing points Field survey
(7) Reclassify map => Create land cover map => Calculate area of each land cover type
(8) Separate mangrove object => Create NDVI map of mangrove
Step 2: Clip band 4 (RED band) and band 8 (NIR band) of satellite data by polygon created
NDVI values of natural forests and other vegetation are typically equal to or higher than those of mangrove forests Areas with similar NDVI values between mangroves and other vegetation are classified into the same layer, which can lead to classification errors Large NDVI ranges in the map can cause a broader distribution of NDVI values within classes, increasing the likelihood of inaccuracies Conversely, smaller NDVI ranges improve classification precision by reducing intra-class variability Therefore, clipping satellite images according to predefined polygons is essential for enhancing classification accuracy.
Clipping process could be done automatically by ArcGIS software
Step 3: Calculate NDVI value for study area by using band 4 (RED band) clipped and band 8 (NIR band) clipped according to the equation:
The calculation can be done automatically by ArcGIS software
Step 4: Composite band 1 to band 6 of satellite image data by ArcGIS software to create map of study area
Step 5: Classify land cover corresponding to each class of NDVI value into 4 types, which including Water, Bare land, Mangrove, and Other vegetation
(6.1) Classified map was exported from ArcGIS and overlaid into GES Then, the incorrect classification areas of the classification map have been reclassified
Field surveys were conducted to identify the undefined points on the GES, with their coordinates precisely determined using a Garmin Oregon 750t GPS device These accurate coordinates were then uploaded to the GES alongside the classification map, enabling an assessment of the map's classification accuracy.
Step 7: Land cover map were created by reclassify NDVI map In which, all classes represented the same object were combined into one class Then, total area of each land cover type was automatically calculated by ArcGIS software
Step 8: The NDVI value range of mangrove forest was obtained from step 5 Then, the lowest and highest values of NDVI were used to isolate the mangrove object As the result,
NDVI map of mangrove forest only was achieved and this map was used to calculate mangrove biomass and mangrove carbon later
To determine how many species there are
This study involves conducting a field survey to identify and quantify mangrove species diversity and distribution Ten representative sample plots will be established to ensure comprehensive data collection In these plots, researchers will measure key forest structural parameters, including total tree height and diameter at breast height (DBH), to assess forest health and biomass Additionally, the study will evaluate tree status to support ecological and conservation objectives.
To investigate current management scheme of local community in Hai Ha district, Quang Ninh province
The current mangrove forest management scheme of local community was obtained through directly interview with forest rangers in Forest Protection Department of Hai Ha district
3.3.3 Calculating above-ground biomass and carbon stocks of mangrove forests during 2013- 2019 in Hai Ha district, Quang Ninh province
To calculate above-ground biomass of mangrove forest
The steps for calculation were arranged in order and shown by Diagram 3.2
Diagram 3.2: Total above-ground biomass calculation process
(2) Calculate AGB of each sub- plot in 2019
(5) Choose the regression model have highest R 2 value
NDVI map of mangrove forest in 2016 and 2019
(3) Determine NDVI value of each corresponding sup-plot
(6) Calculate AGB for each pixel of map
(7) Calculate total AGB of study area
(1) Determining plot location: 10 plots were created for the study
Mangrove areas in Quang Phong commune constitute 56.28% of the total mangrove coverage in the district, leading to the establishment of five plots (50% of the total) within Quang Phong The remaining five plots were evenly distributed among the other five communes A comprehensive survey assessed species composition, tree height, and stem diameter across the study area, providing data to strategically select plot locations that accurately represent mangrove characteristics The spatial distribution and order of these 10 plots are detailed in Table 3.2 and illustrated in Figure 3.2.
No Commune Area (ha) Coordinates Establishment time
Fig 3.2: Spatial distribution of field investigation plots
Fig 3.3: Dimension of surveyed plot
Each plot measured 30 meters by 30 meters, covering an area of 900 square meters Within each plot, three sub-plots of 10 meters by 10 meters were established to facilitate detailed forest structure measurements The structure of each sub-plot is illustrated in Figure 3.3, providing a clear representation of the sampling design.
- Mangrove species identification (Maeda et al., 2016): Object-based image analysis was applied for identification
The measurement of mangrove structure involved recording species names, tree heights, and stem diameters using standardized protocols developed by Kauffman and Donato (2012) These protocols ensure accurate monitoring and reporting of mangrove forest structure, biomass, and carbon stocks, facilitating reliable assessments of ecological health and carbon sequestration potential.
In which, stem diameter of mangrove tree was measured by diameter tape as:
+ Main stem tree diameters are typically measured at 1.37 m above the ground, which is also called the diameter at breast height (DBH)
+ For trees with tall buttresses exceeding 1.37 m above ground level, stem diameter was measured at the point directly above the buttress
+ For stilt rooted species (e.g Rhizophora spp.), stem diameter was measured above the highest stilt root (Clough and Scott 1989, Komiyama et al., 2005)
- Data recording: Collected data were recorded into Table 3.3
Table 3.3: Field data collection tables
Name of plot: Plot 1 Name of investigator:
No Name of species Height
Remark Scientific name Local name
Step 2: Above-ground biomass calculation for each sub-plot
AGB of each sub-plot was estimated by equation:
Where: AGB is above-ground biomass (kg) ρ is wood density (g/cm 3 )
Wood density of mangrove species was obtained from database of World Agroforestry
Centre (2011) and presented by Table 3.4
Table 3.4: Wood density of mangrove species studied
Scientific name Wood density (g/cm³) Reference
Rhizophora stylosa 0.94 Seng et al (1951)
Avicennia marina 0.73 Louppe et al (2008)
Aegiceras coniculatum 0.64 Seng et al (1951)
Step 3: Determine NDVI value of each sub-plot
Each sub-plot have dimension of 10m x10m, which equal to the size of a pixel of the
NDVI map Therefore, each sub-plot had a corresponding NDVI value
NDVI values of sub-plot were obtained automatically from NDVI map of mangrove forest
NDVI and AGB values from field surveys were collected to develop a regression model, with AGB as the dependent variable and NDVI as the independent variable Nine different regression models were tested to identify the one with the highest correlation coefficient, following Myeong et al (2006), using SPSS software for analysis The names of the regression models and their corresponding allometric equations are detailed in Table 3.5.
Step 5: The regression model, which had the highest value of R 2 ,was chosen for the biomass calculation
Step 6: Calculate AGB for each pixel of map
The allometric equation of corresponding chosen regression model was used to calculate AGB for each pixel of NDVI map of mangrove forest in both 2019 and 2016
Step 7: Calculate total AGB of study area
The biomass of the study area was calculated by the total biomass of the all pixels
Table 3.5: Regression models acquired for the test
No Regression model Allometric equation
To calculate how much above – ground carbon per hectare there are in mangrove forest
It was common practical to covert above-ground biomass to above-ground carbon by multiplying AGB by 0.46 to 0.5 (Kauffman & Donato, 2012)
In this study, above-ground carbon was calculated from above-ground biomass multiplied with the carbon conversion factor of 0.47 (Barceclete et al., 2016; IPCC, 2006)
To determine where carbon stocks of mangrove forest are the highest or the lowest
Carbon stock map were created to determine the spatial distribution of carbon pool
3.3.4 Quantify the changes in above-ground biomass and carbon stocks of mangrove forests during 2016 - 2019 in Hai Ha district, Quang Ninh province
To determine how much biomass and carbon stocks of mangrove forest have been changed during selected periods
The steps for mapping the change in biomass and carbon stock were arranged in order and shown by Diagram 3.3
Diagram 3.3: Processes of quantifying the changes in above-ground biomass and carbon stocks
Step 1: Quantify the change of biomass and carbon stock between 2019 and 2016 Biomass and carbon stock map in 2019 and 2016 were used to quantify the change of them through selected period The change was automatically calculated by ArcGIS software by the equation: “Change” = “biomass/carbon of 2019” – “biomass/carbon of 2016” Each pixel of the map contained a corresponding value of biomass/carbon So, the essence of the above subtraction is the difference of the biomass/carbon value of the same pixel between 2019 and 2016
Three ranges of result were considered to analyze the change of biomass and carbon stock:
“change” > 0: amount of biomass/carbon increased from 2016 to 2019
“change” = 0: amount of biomass/carbon unchanged from 2016 to 2019
“change” < 0: amount of biomass/carbon decreased from 2016 to 2019
Step 3: Mapping the change of biomass/carbon from 2016 to 2019
Biomass and carbon stock map in 2019 and 2016
(1) Quantify the change of biomass and carbon stock between 2019 and 2016:
“Change” = (“biomass/carbon of 2019” - ”biomass/carbon of 2016)
+ “Change” > 0: Biomass/carbon increase + “Change” = 0: Biomass/carbon unchanged + “Change” < 0: Biomass/carbon decrease
(3) Mapping the change of biomass/carbon from 2016 to 2019
Hai Ha District is a mountainous region situated in the northeast of Quang Ninh Province, covering a natural area of approximately 51,156 hectares Notably, 64.8% of this land, about 33,189 hectares, consists of lush forest land, emphasizing its rich natural resources Geographically, Hai Ha spans coordinates from 21° 12' 40" to 21° 38' 27" N latitude, highlighting its strategic location and diverse terrain.
107 0 030'5" to 107 0 051’49" E longitude The North borders China, with a border of 17.2 km; the east: border with Mong Cai city; the South borders the East Sea with a coastline of about
35 km, located in the Gulf of Tonkin belt; and the West borders Dam Ha district and Binh Lieu district
Fig 4.1: Map of study area
The district's climate is shaped by its geographical position and topography, resulting in a tropical coastal climate characterized by two distinct seasons: hot, humid summers with heavy rainfall from April to October, and cold, dry winters with northeast winds from November to March The average annual temperature ranges between 22.4°C and 23.3°C, with summer temperatures reaching 30–34°C and winter lows dropping to 5–15°C The temperature difference between day and night is significant, typically 10–12°C Although annual rainfall is high, averaging around 3,120 mm, it is irregular, contributing to the district's lush and varied environment.
In the year with the highest rainfall of 3,830 mm, the year with the smallest rainfall is 2,015 mm
Ha Coi River and Tai Chi River are two major rivers flowing through Hai Ha district, playing a vital role in local ecosystems and communities Ha Coi River originates from a high mountain area over 500 meters elevation, stretching 28 km with a catchment area of approximately 118.4 km², and boasts a maximum flow of 1,190 m³/s and a minimum flow of 2.69 m³/s Similarly, Tai Chi River begins in the northern mountainous region, covering 24.4 km in length, with a basin area of 82.4 km², and exhibits a maximum flow of 1,490 m³/s and a minimum flow of 2.72 m³/s These rivers are essential for water resources, contributing significantly to the ecology and livelihoods within the district.
The Hai Ha coastal area experiences a diurnal tide regime with significant tidal amplitude and strong tides occurring in the months of January, February, June, July, August, and October Ocean wave patterns align with seasonal wind regimes, with summer waves predominantly coming from the east and south, while winter waves are mainly from the north and northeast The average wave height is approximately 0.5 meters, with a typical wavelength ranging from 30 to 40 meters Salt concentration in the water varies seasonally, ranging from 15-18% during the rainy season to 22-25% in the dry season.
Hai Ha is a coastal mountainous district with a significant forestry area, covering 61% of its natural land The district’s forests include two main types: production forests located in the northern mountainous areas along National Highway 18A, and protection forests concentrated in Quang Son and Quang Duc communes Additionally, Hai Ha boasts a large mangrove forest covering approximately 1,600 hectares, which plays a crucial role in socio-economic development, ecological protection, water resource preservation, landscape creation, and the conservation of cultural and historical heritage of ethnic groups To ensure the sustainable use and preservation of these mangrove resources, effective investment policies and rational exploitation strategies are essential.
In 2016, Hai Ha District had a population of 61,028 residents, with the urban area (Quang Ha town) housing 7,477 people (12%) and the rural areas accounting for 88% with 53,551 inhabitants The district is home to 11 ethnic groups, including 10 minority groups totaling 15,273 people, representing 25% of the population These minority groups include the Dao (18.70%), Tay (3.98%), San Diu (0.1%), San Chi (0.04%), Hoa (1.0%), and other groups such as Nung, Muong, Cao Lan, Thai, and Cui Chu Thanks to government policies focused on ethnic minorities, their living standards have significantly improved, and they actively participate in production activities, contributing to poverty reduction and socio-economic development in the region.
In 2016, Hai Ha district achieved an impressive economic growth rate of 56.77%, significantly surpassing the planned 18-19%, with a total economic scale reaching VND 2,075 billion compared to VND 1,323 billion in 2015 The agriculture, forestry, and fishery sector grew modestly by 6.47%, while the industry and construction sectors experienced remarkable expansion of 180.57% The service sector increased by 18.9%, reflecting a continued shift in the economic structure toward industry and services; agriculture, forestry, and fishery now account for 22.27%, representing a decline of 6.97% from the plan and 11.22% from the previous year Conversely, industry and construction now make up 47.32% of the economy—up 15.72% from the plan and 19.03% year-on-year—highlighting a trend toward industrialization The trade and service sectors contribute significantly to the economy as well The district’s per capita income reached over VND 34.8 million, a 27.9% increase from VND 27.19 million in 2015, indicating improving living standards.
5.1 Status of mangrove forests in Hai Ha district, Quang Ninh province
5.1.1 Spatial distribution of Hai Ha mangrove forests
The spatial distribution of Hai Ha mangrove forests in 2019 is depicted in Figure 5.1, highlighting four land cover types classified using NDVI values These categories include water (-0.550 to 0.018), bare land (0.018 to 0.147), mangrove forests (0.147 to 0.706), and other vegetation (0.706 to 0.768) In August 2019, the total area of Hai Ha mangrove forests was approximately 1,376.1 hectares.
Accuracy assessments of land cover map in 2019
A total of 138 ground-truthing points were selected to evaluate the map's accuracy, including 45 points obtained from field surveys and 93 points derived from Google Earth Pro software The assessment results are summarized and presented in Table 5.1, providing a comprehensive overview of the map's precision.
Table 5.1: Accuracy assessment of land cover map in 2019
User accuracy Mangrove Water Bareland & (%)
As the result, accuracy of map was 84.78% with the Kappa coefficient was 0.78
Then, NDVI map of mangrove was extracted from land cover map and was demonstrated by Fig 5.2
Fig 5.1: Land cover map of study area in 2019.
Fig 5.2: NDVI values for Hai Ha mangrove forests in 2019.
In 2016, the spatial distribution of Hai Ha mangrove forest was detailed in Fig 5.3, which identified four land cover types consistent with the 2019 map The NDVI ranges for these land covers were: water (-0.570 to -0.023), bare land (-0.023 to 0.147), mangrove (0.147 to 0.726), and other vegetation (0.726 to 0.784).
In which, total area of mangrove forest in 12/2016 was 1241.76 ha
Then, NDVI map of mangrove forest in 2016, similarly to 2019, was extracted from land cover map and presented by Fig 5.4
Between 2017 and 2018, approximately 38.55 hectares of mangrove forest in Hai Ha district were converted to other land types, with 20.55 hectares in Quang Phong and 18 hectares in Quang Thang Despite this loss, the total area of mangrove forests increased from 1,241.76 hectares in 2016 to 1,376.1 hectares in 2019, primarily due to natural regeneration and effective conservation efforts.
In 2015 and 2016, over 50 hectares of mangroves were newly planted, contributing to the expansion of mangrove ecosystems However, these areas were not classified as mangrove forests in the 2016 Sentinel image due to the presence of small, low-NDVI mangroves By 2019, Sentinel data showed a significant increase in mangrove coverage, reflecting the growth and maturation of the plantation established in 2015 and 2016.
In 2016, Sentinel-2A imagery captured during high tide resulted in small tree areas being submerged, leading ArcGIS software to classify these regions as bare land or water due to their low NDVI values Conversely, in 2019, the satellite image was taken at low tide, allowing the small tree areas to be accurately classified as mangroves, demonstrating the influence of tidal conditions on vegetation classification accuracy.
Fig 5.3: Land cover map of study area in 2016
Fig 5.4: NDVI values for Hai Ha mangrove forests in 2016
5.1.2 Species identification in study area
There were three specie presented in study area which included Rhizophora stylosa, Avicennia marina, Aegiceras coniculatum
5.1.3 Current management scheme of Hai Ha mangrove forests
Currently, mangroves across each commune in Hai Ha district are managed directly by the Commune People’s Committee, with support from the Forest Protection Department of Hai Ha district, as illustrated in Diagram 5.1.
Diagram 5.1: Mangrove management scheme in Hai Ha district, Quang Ninh province
Mangrove monitoring and protection activities are essential for detecting and preventing illegal mangrove destruction, as well as evaluating the success of mangrove planting projects These efforts are led by a dedicated group of commune representatives, including land officials, commune police, veterans, and village leaders such as the village headman Additionally, local forest rangers play a crucial role in assisting commune authorities with effective mangrove management.
Mangrove areas in Hai Ha district are managed rigorously by local authorities under the guidance of the Department of Natural Resources and Environment These authorities consistently monitor and oversee the conservation efforts, ensuring sustainable management of the mangroves Regular reports on management outcomes are submitted to higher-level government agencies to ensure accountability and compliance with environmental regulations.
However, the mangroves management still has limitations due to some main reasons Firstly, the development of mangroves is not optimally implemented because the commune people's committee does not have specialized forestry staff, especially in mangrove planting techniques In addition, funding for afforestation and protection of mangroves is not available but depends mostly on projects of foreign organizations
Secondly, mangrove areas of Hai Ha district have not been overall planned, thus a reasonable development strategy for the district has not been completed yet Also, almost communes don't have records of mangrove management, which leaded to the difficulty in the planning of forest land conversion to other uses
Raising awareness about the importance of mangrove protection among local communities has been limited, leading to a lack of understanding of their ecological and economic significance Additionally, the absence of effective policy mechanisms hinders community participation in the management, conservation, and sustainable development of mangroves.
5.2 Above-ground biomass and carbon stocks of mangrove forests during 2016- 2019 in Hai Ha district, Quang Ninh province
5.2.1 Above-ground biomass and corresponding NDVI value of sub-plots in 2019
Above-ground biomass and NDVI value of each sub-plot were shown in Table 5.2
Table 5.2: Above-ground biomass and corresponding NDVI of sub-plots in 2019
Sub_plot 1 Sub_plot 2 Sub_plot 3 Total biomass (kg)
Based on the AGB calculated of field survey plots and NDVI values generated from
Sentinel images, the study has developed the models for biomass estimation The results of the testing regression model were shown in Table 5.3
Table 5.3: R-square values and parameters estimated of regression model tested
Fig 5.5: Quadratic regression model of biomass and corresponding NDVI value
The quadratic regression model demonstrated the highest R-squared value among the nine tested models, indicating its superior fit for the data Consequently, the quadratic model was selected for estimating above-ground biomass, as illustrated in Figure 5.5.
Next, the corresponding equation of model was obtained for above-ground biomass calculation: AGB = 638.14 – 3048.32*NDVI + 27476.42*NDVI 2
5.2.3 Above-ground biomass and carbon stocks of study area
The spatial distribution of above-ground biomass and carbon stocks of study area in
2019 were illustrated by Fig 5.14 and 5.15, respectively
Similarly, above-ground biomass and above-ground carbon of study area in 2016 were shown in Fig 5.16 and 5.17
Then, above-ground biomass, carbon stock and the change of them from 2016 to 2019 throughout surveyed period were estimated and presented in Table 5.4:
Table 5.4: Above-ground biomass and above-ground carbon of study area in 8/2019 and 12/2016
According to Gustavo Estrada and Mário Soares (2016), the global average above-ground carbon (AGC) in mangrove forests is approximately 78.0 ± 64.5 tons per hectare Notably, the Hai Ha mangrove forest exhibits an AGC value that closely aligns with this worldwide average, highlighting its comparable carbon storage capacity within the global context of mangrove ecosystems.
Analysis of Figures 5.14 and 5.16 shows that the lowest AGB values were 785.8 kg/pixel in 2019 and 783.6 kg/pixel in 2016, reflecting similar conditions due to consistent low NDVI values (0.1474 in 2019 and 0.146 in 2016), which indicate small or unhealthy mangrove trees Conversely, the highest AGB in 2019 was 12,164.3 kg/pixel, while in 2016 it was 12,904 kg/pixel, representing areas with high NDVI and biomass that correspond to mature and healthy mangrove forests.
CONCLUSION, LIMITATION AND FURTHER STUDY
As of August 2019, Hai Ha District in Quang Ninh Province boasted a total mangrove area of approximately 1,376.1 hectares, an increase from 1,241.8 hectares recorded in December 2016 The management of these vital mangrove forests is directly overseen by the commune people's committees, with support from the Hai Ha District Forest Protection Department, ensuring sustainable conservation and environmental protection efforts.
In 2019, a land cover map was produced with an accuracy of 84.78%, categorizing four land types: water, bare land, mangrove, and other vegetation The total above-ground biomass (AGB) and above-ground carbon (AGC) of mangroves in 2019 were 199,553.4 tons and 93,790.1 tons, respectively, showing an increase from 153,876.5 tons and 72,321.9 tons recorded in 2016 Fluctuations in above-ground biomass were observed across different sites in both years, highlighting dynamic changes in mangrove ecosystems over time.
Between December 2016 and August 2019, total above-ground biomass (AGB) increased by approximately 45,676.9 tons, while total above-ground biomass (AGB) grew by about 21,468.1 tons, indicating overall forest biomass growth during this period However, certain regions experienced reductions in biomass due to deforestation and forest degradation, highlighting the spatial variability of forest health This study underscores the importance of monitoring biomass changes to inform sustainable forest management and combat environmental degradation.
Thus, the study suggested some solutions to enhance biomass and carbon stock of Hai
Ha district Of which, mechanism and policy solutions, technical solutions and approach to C- PFES solutions were proposed
The total biomass and carbon stock of mangroves in Hai Ha district remain unestimated due to a focus solely on above-ground carbon However, because below-ground biomass constitutes the majority of carbon stock in mangroves, including below-ground carbon calculations is essential for comprehensive assessments Incorporating below-ground biomass data will provide a more accurate understanding of mangrove carbon storage in Hai Ha district.
The study on mangroves remains limited due to the small number of surveyed plots, highlighting the need to increase both the quantity and representativeness of sampling sites To improve the accuracy and specificity of carbon stock assessments, future research should focus on analyzing carbon stocks across different age groups, heights, diameters, and forest types, including natural forests, plantation forests, and rehabilitation areas Expanding and diversifying study plots will enhance understanding of mangrove characteristics and support more precise carbon stock calculations.
Last but not least, the study on annual growth and carbon sequestration has not been conducted because of time and budget limitation
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