Application of remote sensing and gis for forest cover change detection in ngoc hien district, ca mau province (1990 2016)

INTRODUCTION

Human activities such as agriculture, mining, deforestation, and construction have significantly impacted natural resources and the environment, alongside benefits gained from forest exploitation Urban growth and increasing population have dramatically altered natural vegetation cover, leading to notable effects on local climate and weather patterns Currently, the regression of natural resources and environmental degradation pose urgent challenges Sustainable development requires balancing economic growth with environmental protection through effective investigation, monitoring, and assessment Traditional methods of reporting forest cover change are often slow, complex, and outdated due to reliance on rudimentary mapping techniques To address these issues, new mapping methods that are accurate, real-time, and easily updatable are essential for better environmental management and resource conservation.

Advancements in science and technology, particularly Geographical Information System (GIS), Remote Sensing (RS), and satellite imagery, have significantly enhanced our ability to study forest cover change and natural resource management without direct contact Remote Sensing offers real-time, comprehensive coverage of Earth's surface, providing rapid, accurate data essential for analyzing environmental phenomena such as forest resource fluctuations GIS plays a crucial role in collecting, updating, managing, and analyzing geographical data, supporting effective natural resource planning and environmental management These technological tools have become vital in mapping and understanding the complex relationships and impacts of ecological changes across the globe.

Ca Mau, a coastal province in southern Vietnam, boasts significant ecological tourism potential due to its abundant natural resources However, the region faces challenges such as saltwater intrusion, pollution, and erosion affecting the entire province Additionally, recent years have seen urgent issues related to changing forest cover, particularly in Ngoc Hien district, impacting the area's ecological stability and tourism development.

From these above reasons, we chose the topic: “Application of Remote Sensing and

GIS for Forest Cover Change Detection in Ngoc Hien district, Ca Mau province (1990 - 2016)”

LITERATURE REVIEW

General definition about Remote Sensing and GIS

Remote Sensing is the science of obtaining information about objects or areas from a distance, typically from aircraft or satellites without any direct contact

A Geographic Information System (GIS) is a powerful tool designed to capture, store, manipulate, analyze, manage, and present a wide variety of geographic data By integrating different types of data onto a single map, GIS enables users to visualize and interpret patterns and relationships more easily This ability to layer and analyze spatial information enhances decision-making and provides valuable insights across various industries, making GIS an essential component of modern geographic data analysis.

Change detection is the process of identifying differences in the state of an object or phenomenon over time, enabling the quantification of temporal effects using multi-temporal data (Singh, 1989) Remote sensing serves as a cost-effective and efficient source of data for extracting updated land-cover information, facilitating effective inventory and monitoring of environmental changes Due to its repetitive coverage, consistent image quality, and short revisit intervals, change detection has become a key application of remotely sensed data (Mas, 1999).

Application of Remote Sensing and GIS

In recent years, the use of GIS and remotely sensed data has gained significant momentum in mapping natural resources and environmental modeling Historically, remote sensing efforts primarily concentrated on environmental studies, but now their application in forest cover change and urban planning is attracting increasing attention among GIS professionals These technologies play a crucial role in watershed management, urban planning, hydrological modeling, drought prediction, and forest cover mapping Remote sensed data offers advantages such as synoptic coverage, data consistency, global reach, high readability, precision, and maximum accuracy GIS and remote sensing are extensively used for single thematic analyses like land use and land cover change mapping, forest monitoring, watershed management, forest fire management, and forest strategy assessment, making them indispensable tools in environmental management.

There are many research projects applying RS and GIS in the world Such as:

“Deforestation: Change Detection in Forest Cover using Remote Sensing” of Soraya Violini (Argentina, 2013)

“Forest Cover Change Detection Using Remote Sensing and GIS – A Study of Jorhat and Golaghat District, Assam” of Shukla Acharjee, Mayuri Changmai, Smita Bhattacharjee and Junmoni Mahanta (India)

“Application of Remote Sensing and GIS for Forest Cover Change Detection (A case study of Owabi Catchment in Kumasi, Ghana)” of Adubofour Frimpong (Ghana)

“Application of Remote Sensing and GIS in Forest Cover Change in Tehsil Barawal, District Dir, Pakistan” of A Sajjad et al (Pakistan)

And many other projects These projects use main tools that are RS and GIS combine with other software like ERDAS, ENVI…

Since Vietnam first gained awareness of Remote Sensing in 1980 through its participation in the International Space Station Interkosmos program, its application remained limited before 1990 due to technological and economic constraints However, from 1990 onward, Vietnamese ministries such as the Ministry of Agriculture and Rural Development, the Ministry of Natural Resources and Environment, and the Department of Hydrology and Meteorology recognized the vital role of satellite imagery These agencies invested in satellite technology, trained personnel, and expanded applications for research and daily life, significantly advancing the country's capabilities in remote sensing.

Up to now, there have been many scientific research projects applying RS and GIS of ministries, branches, doctors, professors… even college students in Vietnam

Hua Phuc Hoang (2012) utilized remote sensing and GIS technologies to create a comprehensive map of forest cover status in Cao Ky, Cho Moi, Bac Kan The study employed SPOT 5 satellite images from 2010, processed and interpreted using ERDAS 9.1 software, enabling accurate assessment of forest distribution and changes over time This approach highlights the effectiveness of integrating remote sensing data and GIS tools for forest monitoring and spatial analysis in the region.

“Applying Remote Sensing and GIS to detect mangrove forest change” of Pham Viet Hoa (2012) The author used SPOT 5 image in periods and NDVI to assess forest change

This study, titled "Applying Remote Sensing and GIS to Detect Land Use Change in Vinh Trai, Lang Son (2003-2008)", by Le Thi Thuy Van (2010), utilizes SPOT 5 satellite imagery with a high spatial resolution of 2.5×2.5 meters The research effectively combines remote sensing data with GIS analysis using ENVI software to monitor and analyze land use changes over the five-year period in Vinh Trai, Lang Son.

“Applying Remote Sensing and GIS to detect forest area change in Dao Tru, Lap Thach, Vinh Phuc” of Nguyen Thi Tho (2009)

Remote Sensing and GIS are widely utilized across various fields, particularly in natural resources and environmental management However, Vietnam's forest mapping system faces challenges due to data inconsistencies, as maps were developed at different times using diverse sources like Landsat MSS, TM, SPOT, Aster, and Radar This variability makes it difficult for users to accurately detect and analyze forest area changes over time.

OBJECTIVES, CONTENTS AND METHODOLOGY

Goal and objectives

This study utilizes remote sensing and GIS technologies to map and analyze forest cover changes in Ngoc Hien District, Ca Mau Province, over the periods 1990, 1995, and 2016 By detecting patterns of deforestation and forest expansion, the research provides valuable insights into land use dynamics The findings support the development of effective, sustainable forest management strategies tailored to the region's ecological and socio-economic context Recommendations include implementing reforestation programs, enforcing forest protection policies, and promoting community involvement to ensure the long-term conservation and sustainable utilization of Ngoc Hien’s forest resources.

Objective 1: To collect materials related to the status of forest cover in Ngoc Hien (Ca Mau) in the period (1990 - 1995- 2016)

Objective 2: To construct map and detect forest cover change in Ngoc Hien in the period

Objective 3: To propose some solutions for effective and sustainable forest managing and using in Ngoc Hien (Ca Mau)

Contents

3.2.1 Collecting materials related to the status of forest cover in Ngoc Hien (Ca Mau) in the period (1990 - 1995- 2016)

- Collect information, data, materials, reports related to our research in Ca Mau in periods (1990 - 1995- 2016) (Fieldwork)

- Collect forest status maps in Ngoc Hien of periods (1990 - 1995- 2016)

- Collect Landsat Satellite images in periods (1990 - 1995- 2016)

3.2.2 Construct map and detect forest cover change in Ngoc Hien in the period (1990 - 1995- 2016)

- Classify, interpret visually Landsat Satellite images

- Construct map of forest cover change in Ngoc Hien- Cau Mau (1990 - 1995- 2016)

3.2.3 Propose some solutions for effective and sustainable forest managing and using in Ngoc Hien (Ca Mau)

- Refer to materials and current situation in Ngoc Hien to find out reasons and propose some solutions after surveying and constructing forest cover changing map.

Methodology

3.3.1 Collecting materials related to the study

- Collect maps: forest status maps, forest exploitation maps… of the Nhung Mien and Dat Mui Mangrove forest Management Board in 2016

- Inherit materials, reports about natural, socioeconomic condition in Ngoc Hien, Ca Mau

3.3.2 Image Acquisition and Pre-processing

To conduct effective change detection over time, temporal satellite imagery from the same periods is essential Landsat satellite images from 1990, 1995, and 2016 were downloaded from http://earthexplorer.usgs.gov/ to facilitate this analysis The study utilized Landsat 8 OLI/TIRS images, including Pre-WRS-2 data, as well as Landsat 4 and 5 TM images, ensuring consistent and accurate temporal comparisons for monitoring land cover changes across the selected years.

Table 3.1 Landsat Satellite Images used in the study

The Landsat Satellite Images must satisfy some standards as follow:

- Images must have high homogeneousness of color or position…

- When collecting data, we have to make sample plots in where we sample, measure, describe forest status and land use characteristics…

This research involved satellite image processing using ERDAS Imagine 2014 software, ensuring precise analysis of aerial data Additionally, specific image processing operations were performed with ArcGIS 10.1, enhancing the accuracy and detail of the spatial data These tools collectively facilitated effective satellite imagery analysis for the study.

Image interpretation comprises some steps below:

 Step 1: Setup some map defaults (input and output links after processing…):

- In Main menu we choose Preferences/ Preference Editor

- Default Data Directory: Input file/ Default Data Directory: Output file

- Viewing/ Viewer/ Fit to Frame and Background Transparent/ Save to save default setup process

 Step 2: Import data from storage equipment (USB, CD-ROM) into software:

To import Landsat images, navigate to the main menu and select Manage Data, then choose Import Data Ensure that the format is set to TIFF in the Format field, and specify the input file accordingly Additionally, select the output file, which defaults to the img format.

- Add band 1 to band 6 in turn

Right Click in 2D View #1→ Open Raster → change the default to file img → add bands created

Figure 3.3: Change the default and add bands created

 Step 3: Modify images: a Intensify image quality:

- Intensify image quality: is modify action to increase the readability and understandability of images for interpreters

- Stack up layer: in order to visual interpret more clearly and exactly, we need to stack up colors according to steps:

Input file: open all of color Bands (.img) from Band 1 to Band 6

Output file: Name as and navigate folder destination after stacking up bands/ OK

+ Choose color bands: Color Infrared (vegetation) red, green, blue (RGB)

+ Raster/ Multispectral: Red: band 5/ Blue: band 4/ Green: band 3

 Step 4: Create Subset Image in the study area:

Landsat images often have large file sizes, which can make processing and interpretation challenging Layer stacking helps create a comprehensive and clear representation of the study area, simplifying both analysis and visualization This technique enhances image clarity and facilitates easier processing, making it an essential step in satellite image analysis By combining multiple spectral bands through layer stacking, researchers can produce more accurate and detailed images, improving overall interpretation efficiency.

- On main menu, choose Raster/ Subset & Chip/ Create Subset Image/

Input: Name of origin file

Output File: Destination of the image after cutting

→ Click in Ignore Zero in Output Stats

- Raster/ Drawing/ click on Polygon symbol and draw

- On Box Subset, click on AOI tab/ Viewer/ OK

Figure 3.6 Process of Creating Subset Image

Figure 3.7 Image of the study area after cutting

Classify to separate information that is used to service monitoring objects or mapping This is the key step of Landsat images

Identify number of types separated in the study area: exploited forest, mangrove forest or water…

The order of steps as follow:

+ On main menu, choose Raster/ Supervised/ Signature Editor

+ Click on the zigzag symbol (black circle on the Figure 3.8) to add in

+ Name as: Name/save file *.sig

- Assess the quality of image choosing:

+ In the dialog box Signature Editor, choose Evaluate/ Reparability

+ Which Listing/ Best Average/ OK

If the value ranges from 1000-2000, the image is good

Figure 3.9 Assessing the quality of image choosing

The Blue color around the study area

The Black color is scattering and alternate with mangrove forest (Combine with exploitation map that is identified before)

The Red and Light-Red color (Combine with materials from Google Earth and fieldwork)

Base on the classified group of basic status to process the supervised classification The order of steps as follow:

+ Input files (Name of image that is need to classify); Output (Name as the image that is classified)

+ Signature File (File classified in the previous step)

+ Parametric rule: Maximum likelihood/ OK (Non – Parametric Rule: None)

Images after classification often display small, alternating land and forest type pixels, which can be challenging to verify and apply accurately Determining clear boundaries among these small plots is difficult, leading to the need for their exclusion To address this issue, specific steps should be followed to effectively filter out these problematic areas, ensuring more accurate land cover classification results.

+ On main menu, choose Raster/ thematic tool/ Neighborhood Function

+ Input file (Image that is need to purified); Output file (Name as the file after purifying) + Mark: File; Output: unsigned 8 bit

+ Function: Majority; size: 3 x 3/ OK Process 5 times

- Check and edit after classification:

Before and after classification and purification, it is essential to review the images to compare the interpreted results with the original data, ensuring accuracy and standard compliance If any subject is incorrectly classified, reclassification is necessary Additionally, individual layer checks should be conducted to verify that the identified forest types correspond accurately to the original images If discrepancies are found, re-sampling of the affected areas is required to improve the classification accuracy.

- Change the map from Raster into Vector and calculate the area of the study site (using Arcgis):

+ Open ArcGIS software and navigate folder destination, open a new empty map

When viewing classified images in ArcMap and accessing the attribute table, subjects with values equal to 0 indicate areas outside the study boundary To ensure accurate analysis, it is essential to exclude these non-relevant subjects This process involves filtering or removing features with a value of 0 in the attribute table, thereby refining the dataset to include only the areas within the study scope Properly excluding these out-of-area subjects enhances the reliability and precision of your GIS analysis.

+ ArcToolbox/ spatial analyst/ Map Algebra/ Raster calculator

+ On Box raster calculator, perform the command: rastercalc1 = Con

("supervised_neighborhood5.tif" > 0,"supervised_neighborhood5.tif")

Rastercalc1 is the new name

Supervised_neighborhood5 is the name of image file that was classified by ERDAS software

Con is the condition to choose the subject in Arcmap

Figure 3.12 Exclude subjects out of the study area

After exclude subjects out of the study area, we change the classified image file from Raster into Vector according to the order:

+ ArcToolbox/ conversion Tools/ from raster/ Raster to Polygon

+ On the Folder Input raster, we choose the classified image of the study area

+ Output Polygon features: Navigate folder destination and name as for the output file/OK

Figure 3.13 Processing of changing from Raster into Vector

After changing, we can calculate the area of the study site after classified by:

+ Open Attribute table/ Add Field (area)/ Double/ Ok

+ Right Click on Field area choose Calculate Geometry/ Units: Square Meters/ Ok

Before finalizing the map, it is thoroughly checked, edited, and completed on-site to ensure accuracy and alignment with real-world conditions Fieldwork includes detailed assessments and adjustments to ensure the map accurately reflects the geographic features and project requirements This process guarantees that all data is precise and reliable before proceeding with further development or implementation.

- With each type of forest status, we take the coordinate by using GPS

- At the points, we investigate the average silvicultural targets, the distribution of density (tree/ha)

- The history, area and time of exploitation

- Determine the reason causing the change of forest area in the study area From there, propose solutions

- Take photos in the field

Data on the field Sum on row User’s accuracy (%)

Table 3.3 Matrix to assess the accuracy

Figure 3.14 Overall steps to collect information

Analysis by using GIS combine with fieldwork

Interview local people in the study area

Collect information about natural, socioeconomic characteristics and current landuse pattern in the study area

Collect Landsat Satellite images in periods (1990- 1995-2016)

Figure 3.15 Overall steps to process information

Process data about geographical, socioeconomical characteristics and interview results in the study area

Interpret Landsat Satellite images in periods (1990-1995-2016)

Construct map of forest cover change in Ngoc Hien through periods

NATURAL AND SOCIOECONOMIC CHARACTERISTICS OF THE

Natural characteristics

Ngoc Hien is the southernmost rural district of Ca Mau Province, located in the Mekong Delta region of Vietnam It spans coordinates from 8°40′47″N latitude to 104°57′58″E longitude and is approximately 75 km from the center of Ca Mau city.

The district spans an area of 743 km², accounting for approximately 14.12% of the entire province's territory It comprises six communes—Tam Giang Tay, Tan An Tay, Vien An Dong, Vien An, Dat Mui, and Rach Goc town—and includes Hon Khoai Island, located 18 km from the mainland with an area of nearly 5 km².

Ngoc Hien is located in the northern part of Ca Mau Province, bordering Nam Can district with the Cua Lon River serving as the natural boundary between them The district is surrounded by the sea on five sides—east, west, south, northwest, and northeast—offering rich coastal access and marine resources Notably, Ngoc Hien is home to Mui Ca Mau and the Mui Ca Mau National Park, which has been recognized by UNESCO as part of the World Network of Biosphere Reserves, highlighting its global ecological significance.

Ngoc Hien District is uniquely situated as an island, separated by the Cua Lon and Bo De Rivers along its northern boundary The terrain is predominantly flat and even, but the area is characterized by a complex network of rivers and canals, including several large waterways Due to its geographical features, Ngoc Hien District is frequently affected by tidal flooding, making water management a key aspect of the region.

Ngoc Hien district features a tropical and equatorial climate, with an average temperature of 26.9°C The region experiences two distinct seasons: a dry season from December to April and a rainy season from May to November It receives the highest rainfall in Ca Mau and the Cuu Long River Delta area, averaging approximately 2,300 mm annually Rainfall decreases gradually toward the northeast, with areas bordering Nam Can district receiving about 2,200 mm of rainfall each year.

Wind direction varies seasonally, with the dry season experiencing predominantly east and northeast winds averaging 1.6 to 2.8 m/s Conversely, during the rainy season, southwest winds prevail, with average velocities ranging from 1.8 to 4.5 m/s.

Ngoc Hien District is adjacent to both the East and West Seas, with the Cua Lon River connecting the East China Sea to the Gulf of Thailand, making it directly influenced by tidal movements from both bodies of water The district experiences significant tidal effects, especially from the East Sea, where high tides can reach amplitudes of up to 300cm during flood tides In contrast, the West Sea's tides are smaller, with a maximum amplitude of approximately 100cm, impacting the local environment and coastal activities.

This district has many large river mouths like Ong Trang, Ca Moi, Rach Tau, Rach Goc, Bo De All of rivers in this area are salt intrusion

In Ngoc Hien District, forests covered an area of 65,473 hectares in 2004, accounting for 88.1% of the district's total land area The district's forests are categorized into three main types: production forests, which span 50,195 hectares; protection forests, covering 4,826.3 hectares; and special-use forests, comprising 10,451 hectares.

Water Resource: Ca Mau in general and Ngoc Hien in particular have by an intricate network of rivers Water is salt and brackish which is very suitable for aquaculture

Ocean Resource: The long coastline brings Ngoc Hien many huge sources of income (Examples: exploiting aquaculture, oil and gas in ocean

Socioeconomic characteristics

Ngoc Hien has a population of 78,861 residents as of 2012, representing 6.47% of Ca Mau Province’s total population, with an average density of 107 people per square kilometer The district is ethnically diverse, comprising mainly Kinh (97.86%), followed by Kho Me (1.46%), Hoa (0.64%), and smaller groups of Muong and other ethnicities.

Ngoc Hien has an extensive area Transportations are mostly by water The infrastructure is poor; there has not been main road to center of the districts and communes

Ngoc Hien is a coastal region with an economy primarily based on agriculture, forestry, and aquaculture Aquaculture accounts for 7.28% of economic activities, while agriculture and forestry make up 5.56% The area also has a significant commerce sector, representing 7.28%, alongside processing industries at 0.51%, and other services at 3.76% As of 2013, the average per capita income in Ngoc Hien was approximately 18.6 million Dong per year, reflecting its diverse economic landscape.

The traditional livelihood for residents here revolves around shrimp hatchery and forest planting; however, shrimp farming holds significantly higher economic value, leading farmers to prefer expanding shrimp ponds over reforestation As a result, deforestation is common to enlarge shrimp aquaculture areas Additionally, Hon Khoai Island is recognized for its strategic potential to develop a transshipment port, which would enhance its importance in both economic and defense sectors.

Mangroves and roles of mangroves in Ngoc Hien- Ca Mau

Mangroves are trees or shrubs that grow in salty water in hot places like the tropics Mangroves make a special saltwater woodland or shrubland habitat, called a mangrove

The Ca Mau mangrove forest is the largest and most extensive mangrove ecosystem in Vietnam, playing a vital role in the country's biodiversity and environmental preservation Its abundant mangrove trees thrive better here than in other regions of Vietnam, highlighting its importance for coastal protection and ecological balance Recognized for its significant size and ecological value, the Ca Mau mangrove forest is a key national natural treasure and popular destination for eco-tourism.

Mangrove forests are vital for maintaining the health of coastal environments and supporting the livelihoods of local residents, making their protection crucial for biodiversity and community well-being Despite their ecological and economic importance, the significance of mangroves is often overlooked, highlighting the urgent need for conservation efforts in Vietnam These forests serve as valuable natural resources that contribute to socioeconomic development and improve human quality of life In Ngoc Hien, mangroves provide a substantial timber resource, with wood reserves reaching approximately 210 m³/ha for 30-year-old trees, and potentially up to 450-600 m³/ha Sustainable management and responsible timber trading can ensure that mangrove forests continue to supply essential forest products for the future.

Mangrove forests are essential habitats home to many rare and valuable species, including the brackish crocodile These forests also provide organic matter—such as falling and decomposing branches, leaves, and fruits—that serves as vital nourishment for intertidal animals like shrimp and crabs.

Mangrove forests are increasingly vital in addressing climate change by reducing sea wave energy and protecting dykes, with studies indicating wave length reductions from 75% to 85% as they pass through mangroves They also help create a more stable climate by absorbing and sequestering carbon, thus aiding in climate regulation According to Professor Phan Nguyen Hong, mangroves significantly protect coastal infrastructure by diminishing wave impact, while research by Blasco (1975) highlights their role in cooling communities and lowering temperatures Additionally, mangrove ecosystems contribute to maintaining a balanced atmospheric composition by regulating oxygen and carbon dioxide levels, reducing greenhouse gases, and supporting ozone layer protection.

RESULTS

Results of fieldwork combine with interpret Landsat image

Position: Household Vo Thi Yen Oanh

Investigator: Trinh Nam Phong Latitude X: 8.654352

Longitude Y: 104.916368 Exploit area: 0.2 (ha) Dominant species: Duoc, vet, shrubs Exploit date: 17/07/2016

Position: Household Le Huu Chinh

Longitude Y: 104.901506 Exploit area: 0.1 (ha) Dominant species: Duoc, vet, shrubs Exploit date: 12/07/2016

Photo 5.2 Photo in the field 2

Position: Household Pham Van Hoai

Longitude Y: 104.88695 Exploit area: 0.5 (ha) Dominant species: Duoc, shrubs Exploit date: 16/07/2016

Position: Household Tran Van Tap

Longitude Y: 104.935414 Exploit area: 0.3 (ha) Dominant species: Duoc, Mam, shrubs Exploit date: 13/06/2016

Position: Household Nguyen Van Nam

Longitude Y: 104.951013 Exploit area: 0.7 (ha) Dominant species: Duoc, Mam, shrubs Exploit date: 10/07/2016

Position: Household Tran Van Khuoi

Position: Household Nguyen Hoang Phieu

Position: Household Nguyen Thi Be Na

Position: Household Ta Van Toan

Longitude Y: 104.865252 Exploit area: 0.5 (ha) Dominant species: Duoc Exploit date: 15/08/2016 Average silvicultural targets:

Forest cover change map in periods 1990 – 1995 – 2016

5.2.1 Forest cover change map in 1990

Table 5.1 Area of lost and exploited forest Statistic in 1990

Table 5.1 indicates that the mangrove forest covers 12,999.3 hectares, representing 36.15% of the total study area Additionally, 4,369 hectares (12.2%) of the forest have been lost The water surrounding the study site spans 18,585 hectares, accounting for 51.65% of the area These findings are based on interview data and field investigations regarding forest exploitation and loss history; however, they may not be entirely accurate.

Chart 5.1 Forest cover change in 1990

Forest cover change detection map in 1990:

Figure 5.1 Forest Cover Change detection in 1990

Table 5.2 indicates that the mangrove forest covers 14,132.4 hectares, constituting 39.42% of the total study area Conversely, approximately 4,595.3 hectares, or 13%, of the forest has been lost The surrounding water bodies encompass 17,125.5 hectares, representing 47.58% of the study site These findings are based on interviews regarding the history of forest exploitation and loss within the study area.

Figure 5.2 Forest Cover Change detection in 1995

According to Table 5.3, the mangrove forest covers a total area of 22,522.63 hectares, accounting for 89.58% of the study site The lost forest area amounts to 1,920.7 hectares, representing 7.64%, while the surrounding water bodies encompass 701.3 hectares, making up 2.78%.

Reason causing forest cover change in Ngoc Hien district and solutions

5.3.1 Reason causing forest cover change in Ngoc Hien district

From the results, we can see that mangrove forest area through period of 1990-1995-

Between 1990 and 1995, the mangrove forest area increased from 12,999.3 hectares to 14,132.4 hectares, reflecting a period of growth From 1995 to 2016, the mangrove area expanded further from 14,132.4 hectares to 22,522.63 hectares, demonstrating significant natural regeneration Despite this overall increase, Ngoc Hien experienced a substantial loss of 10,884.7 hectares of forest over the 16-year period, highlighting ongoing challenges in forest conservation.

After researching, we found some reasons of forest cover changing in Ngoc Hien district:

The rising demand for shrimp exportation in Vietnam has led to significant land-use transformation, as the supply from small-scale catches declines Consequently, in the early 2000s, most coastal areas saw mangrove and natural protection forests replaced by aquaculture zones Additionally, many forested areas were converted into tourist resorts and recreational complexes to accommodate economic development and tourism growth.

Overexploitation of forests in Vietnam, particularly mangrove forests, poses a significant environmental threat, leading to rapid degradation of forest quality and loss of biodiversity This excessive harvesting and resource extraction undermine the sustainability of these vital ecosystems, impacting their ecological functions and the livelihoods of local communities Addressing overexploitation is crucial to preserving Vietnam’s forest resources and ensuring ecological balance.

Human daily activities, such as deforestation for firewood and timber for construction, significantly contribute to the degradation of forest areas Additionally, natural factors like sea level rise, acid rain, climate change, and forest fires also pose threats to mangrove forests, further accelerating their decline Protecting these vital ecosystems requires addressing both human and environmental challenges.

From the forest cover change status we showed above, we propose some solutions for diminishing deforestation situation and improve the management working in Ngoc Hien district:

To effectively prevent deforestation, it is essential to develop concrete aquaculture zone projects and regulate their expansion, ensuring a balance between economic growth and environmental conservation not only in Ca Mau but also across the Mekong River Delta provinces Key strategies include completing irrigation infrastructure for aquaculture, enhancing producer qualifications, investing in marketing to expand consumption markets, and increasing local incomes, which collectively help reduce forest clearing Additionally, integrating forest protection with economic development through strategies such as creating employment opportunities for rural and unemployed communities, promoting eco-tourism and national parks, and raising awareness about forest conservation are vital for sustainable progress.

Reinforcing and expanding Natural Resource Conservation Areas, such as mangrove forests transformed into national parks or nature reserves, is vital for ecological preservation These forests are designated as special use forests, emphasizing their unexploited status primarily for protection In the case of plantation forests within special use areas, implementing appropriate silviculture methods is essential to ensure healthy growth and sustainable development of the forests.

To effectively utilize mangrove forests and mitigate the adverse effects of climate change and human activities, it is essential to implement strategic solutions Protecting and restoring mangrove ecosystems can enhance their resilience, while sustainable management practices help balance ecological health with economic benefits Promoting conservation initiatives, community engagement, and policy enforcement are crucial steps toward ensuring the long-term preservation of mangroves for future generations.

1 Mangrove forest plays an important role in absorbing CO 2 ; reducing greenhouse effect so we need to grow forest on fallow land of mangrove forest On average, 1 hectare of mangrove forest can absorb about 1.5 tons of CO 2 per year with Duoc (Rhizophoraceae) forest 30 years old (Ong, 1993, 2002)

2 Shrimp hatching inside mangrove forest: that solution is a combination of natural protection and economic growth because if we apply this we can supply a necessary area to create a stable environment and natural food for shrimp from the volume of fall leaf

3 Some mangrove forests need to be researched to identify forest regeneration cycle and apply forest regulation to replace some old forests by young forest From that, we can take full advantage of wood per year to supply coal made by Duoc (Rhizophoraceae) to export and supply for Vietnam market

4 Improve awareness of local people; educate them about the important value of mangrove ecosystem to make them have responsibility about forest protection Explain to them that forest is not fallow land or forest has no economic value Improve personal skill of technicians to approach GIS technology in mangrove forest management.

CONCLUSION, LIMITATION AND FUTHER STUDY

Conclusion

The use of remote sensing and GIS, combined with other data sources, offers a diverse range of applications for constructing forest cover status and change maps These technologies provide visual, objective, and rapid analysis, making them especially useful for monitoring and predicting changes in mangrove forests By transforming data into comprehensive maps, remote sensing facilitates effective visualization of forest cover dynamics Processing Landsat images to assess coastal forest area changes is a standard practice for mangrove management, helping to identify correlations between forest cover loss and coastal erosion Overall, integrating remote sensing and GIS enhances the ability to manage and conserve mangrove ecosystems effectively.

Monitoring mangrove forests is challenging due to dense canopies that hinder direct survey and movement, making field assessments time-consuming Utilizing remote sensing and GIS technologies significantly streamlines this process, providing objective and comprehensive data The study reveals that the mangrove area has been preserved effectively, with continuous growth observed from 1990 to 2016, indicating increased local awareness and efforts toward forest conservation.

Limitation and further study 44 REFERENCES

Despite achieving some valuable results, the study faced notable limitations The large geographical scope and predominantly waterway traffic made comprehensive surveying challenging Consequently, we limited our survey to three communes—Vien An Dong, Vien An, and Dat Mui—due to constraints in time and funding, with fieldwork conducted over just two weeks Additionally, limited experience among the research team may have impacted the accuracy and reliability of the collected data and overall findings.

To enhance accuracy and address current limitations, increasing the number of sampling points is essential for improving authentication and verification during data interpretation Additionally, dedicating more time to fieldwork will strengthen research quality and provide deeper insights into the subject matter.

Tiêu đề	Application of remote sensing and GIS for forest cover change detection in Ngoc Hien district, Ca Mau province (1990 – 2016)
Người hướng dẫn	Assoc. Prof. PhD. Phung Van Khoa
Trường học	Vietnam National University of Forestry
Chuyên ngành	Forestry and Remote Sensing
Thể loại	Graduation project
Năm xuất bản	2016
Thành phố	Vietnam

Định dạng
Số trang	54
Dung lượng	9,54 MB