Using landsat vegetation indices in quantifying coastal mangrove in thai thuy district thai binh province

MINISTRY OF AGRICULTURE AND RURAL DEVELOPMENT VIETNAM NATIONAL FORESTRY UNIVERSITY STUDENT THESIS PROPOSAL Title Using Landsat Vegetation Indices in quantifying coastal mangrove cover in Thai Thuy District, Thai Binh Province Major: Natural Resources Management Code: D850101 Faculty: Forest Resources and Environmental Management Student: Tran Duy Binh Student ID:1253092057 Class: K57 Natural Resources Management Course: 2012 – 2016 Advanced Education Program Developed in collaboration with Colorado State University, USA Supervisor: Dr Nguyen Hai Hoa Co-supervisor: Ha Noi, 10/2016 ACKNOWLEDGEMENT This thesis would not have been possible without the support and help from my teachers, friends, families and several people I would like to express our special appreciation of following people who supported me with my sincere gratitude: I would like to express my sincere thanks and appreciation to my supervisor Dr HaiHoa Nguyen for his untiring and excellent guidance, valuable suggestions in my dilemmas His comments and advices have helped me to finish my thesis I am also thankful to Prof Lee MacDonald for his enthusiasm in guiding me to construct thesis proposal His comments and criticism on my proposal helped me to present better final thesis Further, I would like to thank the Department of Natural Resources and Environment in Thai Thuy district for support and giving me the chance to study in Thai Thuy District Besides, I also thank the local authorities and farmers in three communes namely: Thuy Truong, Thuy Xuan and Thuy Hai for providing valuable information and data of the area I wish to thank the Center of Laboratory and Practice of Vietnam Forestry University for providing me with survey instrument (GPS Garmin) for field survey I also thank my friends for their enthusiastic help in the process collected data in field survey Last but not least, my everlasting gratitude goes to my parents who always encouraged and supporting me all the time CONTENTS ACKNOWLEDGEMENT CONTENTS ACRONYMS LIST OF TABLES LIST OF FIGURES AND DIAGRAMS CHAPTER I INTRODUCTION CHAPTER II LITERATURE REVIEW 2.1 GLOBAL MANAGEMENT OF COASTAL MANGROVES 2.2 COASTAL MANGROVES MANAGEMENT IN VIET NAM 2.3 MANGROVE CHANGE AND METHODS 10 2.4 SIGNIFICANCE OF STUDY 10 CHAPTER III OBJECTIVES, CONTENTS AND METHODOLOGY 12 3.1 GOAL AND OBJECTIVES 12 3.1.1 Overall goal 12 3.1.2 Research objectives 12 3.2 RESEARCH CONTENTS 12 3.2.1 Investigate spatial distribution characteristics and management schemes of coastal mangroves in Thai Thuy District, Thai Binh province 12 3.2.2 Quantify changes in coastal mangrove extents in Thai Thuy district during 2001 2016 13 3.2.3 Identify key drivers of changes in coastal mangrove extents in Thai Thuy district during 2001 – 2016 13 3.2.4 Propose solutions for better management of coastal mangroves in Thai Thuy district 13 3.3 METHODOLOGY 13 3.3.1 Secondary data collection: 13 3.3.2 Quantification of coastal mangrove changes 13 3.3.3 Field data collection 17 3.4 Calculation of Vegetation indices 18 3.4.1 NDVI calculation 18 3.4.2 Difference Vegetation Index (DVI): 19 3.4.3 Ratio-based Vegetation Indices: 19 3.4.4 IPVI: 20 3.4.5 SAVI: 20 CHAPTER IV NATURAL AND SOCIOECONOMIC CHARACTERISTICS 21 4.1 NATURAL CHARACTERISTICS 21 4.1.1 Geography 21 4.1.2 Terrain 21 4.1.3 Climate 22 4.1.4 Land condition in Thai Thuy 23 4.2 SOCIOECONOMIC CHARACTERISTICS 23 4.2.1 Social characteristics 23 4.2.2 Economic characteristics 24 4.2.3 District production and commercial results 26 4.3 COASTAL MANGROVES 26 CHAPTER V.RESULTS AND DISCUSSION 28 5.1 SPATIAL DISTRIBUTION AND MANAGEMENT OF COASTAL MANGROVES 28 5.1.1 Spatial distribution of coastal mangroves 28 5.1.2 Management schemes of coastal mangroves 29 5.2 HISTORICAL CHANGES IN COASTAL MANGROVE EXTENTS 31 5.2.1 Mangrove extents using various vegetation indices 31 5.3 KEY DRIVERS OF COASTAL MANGROVES CHANGES 36 5.4 SOLUTIONS FOR BETTER COASTAL MANGROVES MANAGEMENT 38 CHAPTER VI CONCLUSION AND FURTHER STUDY 40 6.1 CONCLUSION 40 6.2 EXISTANCE AND FUTHER OF STUDY 41 REFERENCES APPENDIX ACRONYMS FAO – Food and Agriculture Organization JICA – Japan International Cooperation Agency GIS – Geographic Information System MONRE – Ministry of Natural Resources and Environment MARD – Ministry of Agriculture and Rural development GPS – Global Positioning System UNICEF – The United Nation Children’s Fund LIST OF TABLES Table 3.1: Landsat and Sentinel Data used for detecting changes in coastal mangroves 14 Table 3.2: Equation of Vegetation Indices used for mangrove mapping 14 Table 4.1: Climate characteristics 22 Table 4.2: Traffic system in Thai Thuy district 24 Table 4.3: Key indicators of Thai Thuy district economy during 2005 – 2010 26 Table 5.1: Values of Vegetation indices calculated from 2001 to 2016 31 Table 5.3: The result of table comparing the percent of accurate in vegetation index (%) 33 Table 5.4: Changes in mangrove extents different periods: 2001– 2006; 2006 – 2011; and 2011 – 2016 35 LIST OF FIGURES AND DIAGRAMS Diagram 3.1: Flow chart of mangrove classification using Landsat images from 2001- 2016 15 Figure 5.1: Spatial distribution of coastal mangrove species in Thuy Truong, Thuy Xuan and Thuy Hai communes, Thai Binh province 29 Fig 5.2 Difference between the area of mangrove in Thai Thuy district by using vegetation indices 32 Fig.5.3 Mangrove area by using Landsat image and Sentinel image 34 Fig 5.4 The maps show that LULC change using NDVI in Thai Thuy district during three periods (2001-2006, 2006-2011, 2011-2016) 36 CHAPTER I INTRODUCTION Vietnam has a coastline of 3260 kilometers, creating an appropriate environment for mangroves development According to Forest Trends- a non-profit organization based in Washington DC – Vietnam’s mangrove extent account for around 2% of the world’s total, ranked 2nd only after the Amazon river basin They play an important role for the environment and people’ livelihood such as: providing various ecosystem services including carbon storage; wood for building, setting traps, firewood; shelters for fishes and other marine species; shoreline stability and erosion prevention A large part of Vietnam’s population lives in coastal regions, where mangroves play a major role in their livelihoods Apart from providing homes, jobs, food for millions, mangroves also attenuate wind-induced waves, current and storm surges so it protects coastal inhabitants from extreme events such as tsunamis and storms Currently, there are 30 provinces and cities in Vietnam mainland that have coastal mangrove forests and wetland The mangroves vegetation is divided into zones: North-eastern coast from Ngoc cape to Do Son cape (Zone I), Northern delta from Do Son cape to Lach Truong river (Zone II), Central coast from Lach Truong to Vung Tau cape (Zone III) and Southern delta from Vung Tau cape to Ha Tien (Zone IV) [1] Total mangrove extents in Vietnam reduced dramatically from 1943 to 2000 due to natural disasters, wars and unprecedented human exploitation activities [2] Protecting and regenerating mangroves in coastal regions have been becoming an extremely important task of the Government, local authorities, organizations and individuals The coastal mangroves extents of Thai Thuy district, Thai Binh province is not out of this trend For many years, they have been protected carefully This is achieved because the Thuy Truong commune set up a specialized forest protection task force with members and some equipment Mangroves in Thai Binh have a high biodiversity level with many terrestrial and marine species They not only help create a formidable forest that withstands typhoons and waves but also form a marine ecosystem It is also the main source of income for local people Coming to Thuy Truong- a coastal commune of Thai Binh that was usually affected by floods and storms- can we see the effectiveness of mangroves? This commune has about 3.7 kilometers of sea dike and before 1994, it was often threatened by high sea waves However, nowadays, with 1,300 hectares of mangrove running along this dike system (the widest area can be up to 1.8 kilometers), it has become very safe after many typhoon seasons Especially the 2nd and 8th typhoon in 2005, with wind speed at over 10 degrees which destroyed the concrete dike systems in Hai Phong and many nearby provinces, but the one in Thuy Truong survived Apart from protecting the sea dikes, Thai Binh’s mangroves also ensure the safety of more than 3,000 hectares of aquaculture ponds Realizing the impact of tides and storms, Thai Binh has launched hundreds of mangroves plantation campaign to counter typhoons and climate change, and has planted tens of thousands of hectares of trees In particular, Thai Thuy district has the largest forest area, with about 4.700ha stretches over 27km along the coastline To promote afforestation, coastal communities have sought to allocate forest land to household management and afforestation Accordingly, the growers enjoy the planting and care funding from the district and commune, and they would enjoy all the marine resources brought from the forest, so people are actively involved in this project The district’s Resources and Environment department continues advising and implementing of the Law on Mineral (2010), the Law on Water Resources (2012) and different guiding decrees from both National and regional levels At the same time, they also effectively execute coordination regulations, checking and handling sand mining activities on the river bed between Hai Phong and bordering districts: Tien Hai, Dong Hung, Kien Xuong In the 4th quarter of the year 2014, this agency was scheduled to complete the environmental evaluation criteria (the 17th criteria) for 12 communes that finished the project before October and November of 2014; guided communes to implement the Decision No.2070/QĐ-UBND of the province’s People’s committee referring to the regulation of charges hygiene and Decision No.15/2014-QĐ-UBND referring to some mechanisms and policies to support the collection and processing of domestic waste in the province of Thai Binh Leaders and local governments would often advocate and encourage people to increase production while protecting the environment and the mangroves itself Several proposed vegetation change detection methods are based on the same image pre-processing to create a time-series dataset, requiring a geometric and radiometric image correction Coppin & Bauer (1996) and Milne (1988) reported the main methodological approaches for vegetation change detection can be distributed into four broad categories: linear procedures (difference and ratio images); classification routines (post-classification change, spectral pattern change); transformed data sets (vegetation indexes, principal components analysis-PCAs); and others, such as regression analysis, knowledge-based expert systems, or neural networks (Sader et al 2003) Several literature reviews such as suchoney and Haack (1994); Nordberg and Evertson (2004, 2005) reported the most efficient methodologies in accuracy and cost saving performances were image differencing and PCA techniques The image differencing technique is based on a cell-by-cell subtraction between different images in a time-series This technique applies differences between remotely sensed images of vegetation characteristics, and indexes derived from image radiance or reflectance differencing as NDVI (Normalized Difference Vegetation Index) or change vector differencing (Schowengerdt 1997) The NDVI differencing method uses estimated NDVI as the normalized difference between near infrared (NIR) and visible red (RED) bands, which discriminate vegetation from other surfaces based on green vegetation chlorophyll absorption of red light for photosynthesis, and reflection of NIR wavelengths (Tucker 1979) The NDVI differencing technique was widely applied for both human-induced and natural forest cover change detection as land cover conversion, forest harvesting, revegetation, or afforestation that includes natural forest expansion and human-induced landscape restoration (Lyon et al 1998, Wilson & Sader 2002, Sader et al 2003, Lunetta et al 2002, 2006, Nabuurs et al 2007, vegetation cover fraction by inversion of a four-parameter model based on isoline parametrization Remote Sensing of Environment, 111:553–566 [22] L.M Montandon, E.E Small.(2008) The impact of soil reflectance on the quantification of the green vegetation fraction from NDVI Remote Sensing of Environment, 112 (2008): 1835–1845 [23] A.J Xiao, A Moody.(2005) A comparison of methods for estimating fractional green vegetation cover within a desert-to-upland transition zone in central New Mexico, USA Remote Sensing of Environment, 98: 237–250 [24] Vescovo, L., Gianelle, D (2008) Using the MIR bands in vegetation indices for the estimation of grassland biophysical parameters from satellite remote sensing in the Alps region of Trentino (Italy) Advances in Space Research, 41:1764–1772 Websites: [25] http://khoahoc.tv/doisong/moi-truong/tham-hoa/38463_rung-ngap-man-chet-gan- mot-nua.aspx [26]http://sonnptnt.thaibinh.gov.vn/ct/News/Lists/LamNghiep/View_Detail.aspx?ParentI D=&ItemID=11 [27] http://www.baomoi.com/Tuong-thanh-xanh-o-Thai-Thuy/137/9653553.epi [28] http://vi.wikipedia.org/wiki/Th%C3%A1i_Th%E1%BB%A5y [29] http://www.geos.ed.ac.uk/~gisteac/gis_book_abridged/files/ch71.pdf [30] http://khoahoc.tv/doisong/moi-truong/tham-hoa/38463_rung-ngap-man-chet-ganmot-nua.aspx [31] Giải pháp GIS cho quản lý môi trường: http://www.esri.com/~/media/files/pdfs/library/brochures/pdfs/gis-sols-for-env-mgmt.pdf APPENDIX APPENDIX 01: Field work and ground control points for different classes Mangroves No X Y No X Y 20.5992 106.63157 41 20.61278 106.6429 20.59918 106.63168 42 20.61223 106.6427 20.59918 106.63153 43 20.61282 106.6428 20.59917 106.63153 44 20.61198 106.6426 20.59572 106.63607 45 20.61175 106.6424 20.59583 106.63615 46 20.61247 106.6435 20.59565 106.63598 47 20.6124 106.6435 20.596 106.6363 48 20.61233 106.6439 20.59555 106.636 49 20.61232 106.6434 10 20.59583 106.63647 50 20.61228 106.6435 11 20.59545 106.636 51 20.61225 106.6441 12 20.5957 106.63648 52 20.6122 106.6435 13 20.59545 106.63588 53 20.61225 106.6438 14 20.59545 106.63643 54 20.6123 106.6435 15 20.59533 106.63658 55 20.61202 106.6437 16 20.59562 106.63572 56 20.61208 106.6434 17 20.59577 106.63577 57 20.61212 106.6433 18 20.59556 106.63615 58 20.59403 106.6197 19 20.59715 106.63468 59 20.5943 106.6201 20 20.60375 106.6369 60 20.5939 106.6195 21 20.60402 106.63803 61 20.59362 106.6191 22 20.60462 106.63865 62 20.5934 106.6188 23 20.6061 106.63875 63 20.59315 106.6186 24 20.60613 106.63882 64 20.59275 106.6182 25 20.60622 106.6389 65 20.59307 106.6186 26 20.6063 106.63873 66 20.57932 106.6026 27 20.60628 106.639 67 20.57908 106.6026 28 20.6064 106.63875 68 20.57887 106.6023 29 20.60632 106.63907 69 20.57857 106.6021 30 20.60645 106.63853 70 20.57848 106.602 31 20.60633 106.6375 71 20.57792 106.6016 32 20.60660 106.63833 72 20.5778 106.6015 33 20.60643 106.63935 73 20.60638 106.6392 34 20.60648 106.63945 74 20.59927 106.6315 35 20.60648 106.63948 75 20.59935 106.6314 36 20.60652 106.63953 76 20.59947 106.6314 37 20.61263 106.64303 77 20.59965 106.6313 38 20.61265 106.64293 78 20.59962 106.6312 39 20.61272 106.64288 79 20.59952 106.6311 40 20.61242 106.64283 Wetlands/Bare soil No X Y No X Y 20.61627 106.64805 25 20.58622 106.6095 20.61657 106.64788 26 20.5863 106.61 20.61685 106.64777 27 20.58615 106.6093 20.61715 106.64783 28 20.58615 106.6102 20.61718 106.64797 29 20.58607 106.6094 20.61722 106.6476 30 20.58587 106.6101 20.61707 106.64822 31 20.586 106.6096 20.61747 106.64762 32 20.58588 106.6097 20.6176 106.64815 33 20.58573 106.6102 10 20.6174 106.6477 34 20.58557 106.61 11 20.6177 106.64802 35 20.61715 106.6477 12 20.61778 106.64777 36 20.59555 106.6351 13 20.61778 106.64757 37 20.59613 106.6356 14 20.61778 106.64728 38 20.5965 106.6359 15 20.6179 106.64733 39 20.59757 106.6354 16 20.61803 106.64728 40 20.59719 106.636 17 20.61807 106.6474 41 20.59681 106.6365 18 20.61817 106.64713 42 20.59653 106.6372 19 20.58667 106.6095 43 20.59666 106.6385 20 20.5866 106.60972 44 20.57819 106.6113 21 20.5865 106.60958 45 20.57925 106.6122 22 20.58653 106.60987 46 20.57656 106.6101 23 20.58628 106.60953 47 20.57555 106.6077 24 20.5864 106.60997 48 20.57251 106.606 Fishing ponds No X Y No X Y 20.60802 106.63273 31 20.6047 106.62347 20.60833 106.63348 32 20.60447 106.62322 20.60882 106.63358 33 20.60462 106.6238 20.60947 106.63393 34 20.60415 106.62328 20.6075 106.63113 35 20.60427 106.62373 20.60778 106.63123 36 20.60403 106.62365 20.60782 106.63103 37 20.58733 106.60292 20.60803 106.63092 38 20.58703 106.6026 20.6078 106.6315 39 20.58673 106.60233 10 20.60795 106.63157 40 20.58657 106.60257 11 20.60837 106.63127 41 20.58225 106.58663 12 20.60813 106.63157 42 20.58283 106.59825 13 20.60832 106.63148 43 20.5815 106.59708 14 20.60827 106.63092 44 20.57917 106.59475 15 20.60853 106.6309 45 20.57712 106.59283 16 20.60867 106.63093 46 20.57737 106.59113 17 20.6073 106.62932 47 20.57402 106.58933 18 20.607 106.63023 48 20.61742 106.6261 19 20.60767 106.62952 49 20.62728 106.62268 20 20.6082 106.62978 50 20.6181 106.62658 21 20.60783 106.62835 51 20.61815 106.62705 22 20.6082 106.62868 52 20.61692 106.62633 23 20.60842 106.62868 53 20.61712 106.62635 24 20.60863 106.62898 54 20.6173 106.62637 25 20.60858 106.62847 55 20.61752 106.62638 26 20.6089 106.6291 56 20.6179 106.62645 27 20.60875 106.62822 57 20.60143 106.62207 28 20.60908 106.6287 58 20.60138 106.62215 29 20.60897 106.62835 59 20.60128 106.62237 30 20.60477 106.62322 60 20.60122 106.62253 Grass No X Y No X Y 20.60032 106.63053 16 20.61265 106.64293 20.59422 106.62027 17 20.57186 106.599461 20.5941 106.62032 18 20.572494 106.600213 20.59398 106.62025 19 20.616087 106.54152 20.59393 106.62017 20 20.615682 106.641674 20.59265 106.61827 21 20.61606 106.641902 20.59267 106.61835 22 20.615996 106.680644 20.59285 106.61988 23 20.615419 106.640908 20.60222 106.62523 24 20.614972 106.641024 10 20.6016 106.6259 25 20.609904 106.641418 11 20.578 106.60133 26 20.609706 106.642219 12 20.5782 106.60148 27 20.603296 106.636854 13 20.5786 106.6019 28 20.592458 106.624316 14 20.57842 106.6017 29 20.592533 106.624049 15 20.57813 106.60177 Build-up areas No X Y 20.633895 106.623 20.605409 106.6235 20.608544 106.6251 20.615953 106.6267 20.620154 106.6292 20.60294 106.6228 20.588227 106.6049 20.586887 106.6036 20.584648 106.6014 10 20.576753 106.5952 11 20.578693 106.5947 12 20.572922 106.5915 13 20.570294 106.5925 14 20.572513 106.596 APPENDIX 02: Photos taken from field survey ... importance of coastal mangrove management efforts, we decide to perform this research: ? ?Using Landsat Vegetation Index in Quantifying Coastal Mangrove Cover in Thai Thuy District, Thai Binh Province. ”... coastal mangroves and management schemes in Thai Thuy district, Thai Binh province Objective 2: To quantify the extents of coastal mangroves using different Landsat vegetation index in Thai Thuy district, ... district, Thai Binh province Objective 3: To quantify the spatial changes in mangrove extents in certain periods of time in Thai Thuy district, Thai Binh province Objective 4: As the findings in Objective