An estimate of plant biomass and assessment of the ecological balance capacity of the Hanoi green corridor

VIETNAM NATIONAL UNIVERSITY, HANOI VIETNAM JAPAN UNIVERSITY HOANG DINH VIET AN ESTIMATE OF PLANT BIOMASS AND ASSESSMENT OF THE ECOLOGICAL BALANCE CAPACITY OF THE HANOI GREEN CORRIDOR MASTER’S THESIS Hanoi, 2019 VIETNAM NATIONAL UNIVERSITY, HANOI VIETNAM JAPAN UNIVERSITY HOANG DINH VIET AN ESTIMATE OF PLANT BIOMASS AND ASSESSMENT OF THE ECOLOGICAL BALANCE CAPACITY OF THE HANOI GREEN CORRIDOR MAJOR: MASTER IN INFRASTRUCTURE ENGINEERING CODE: Dr LE QUYNH CHI Hanoi, 2019 ANNEX two LIST OF FORMS FOR MANAGEME TABLE OF CONTENTS TABLE OF CONTENTS i LIST OF FIGURES iv LIST OF TABLES v LIST OF ABBREVIATIONS vi ACKNOWLEDGMENT vii INTRODUCTION 1 The necessity of the research topic Contributions and objectives of the thesis Methodology Thesis’s structure 5 Terms and concepts 5.1 The concepts of Green space, Green corridor, Greenbelt are recognized by the world 5.2 Concept of GS, GC, GB according to the Master Plan of Hanoi Capital in 2011 5.3 Concept of plant biomass CHAPTER 1: LITERATURE REVIEW 1.1 Overview and assessing the effectiveness of the green space models outside urban centers in the world 1.1.1 London’s metropolitan greenbelt, Britain 1.1.2 Beijing area’s Greenbelt, China 1.1.3 Seoul’s greenbelt, Korea 11 1.1.4 Tokyo’s greenbelt, Japan 12 1.2 Overview of research related to the topic 15 1.2.1 The role of carbon pools in climate change mitigation 15 1.2.2 Studies on estimating urban plant biomass 17 1.2.3 Studies on biomass estimation using remote sensing data 21 CHAPTER 2: METHODOLOGY AND DATABASE 22 2.1 Research content 22 i 2.2 Methodologies 22 2.2.1 Perspective anh methodologies 22 2.2.1.1 Perspective on environmental science 22 2.2.1.2 Perspective on biomass research and ground carbon accumulation based on satellite image data 22 2.2.1.3 The theoretical basis of LiDAR 23 2.2.2 Research method diagram 25 2.3 Process of calculation 26 2.3.1 Site description 26 2.3.2 Data sources of satellite image 27 2.3.2.1 Landsat satellite images data 27 2.3.2.2 LiDAR data products 29 2.3.2 Identification of green corridor vegetation using GIS 30 2.3.3 Segments canopy according base on height 32 2.3.4 Plant biomass estimate base on height of canopy 33 2.2 Methodology and sources of greenhouse gas inventory data 34 2.3 Land use/land cover (LULC) of Hanoi’ Green Corridor 35 CHAPTER 3: FIDDING AND DISCUSSION 37 3.1 Fidding 37 3.1.1 Results of estimate plant biomass in Hanoi Green Corridor (No consider land use change) 37 3.1.2 Change in LULC of Hanoi’s Green Corridor 39 3.2 Discussion 42 3.2.1 Hanoi Assess the 𝐶𝑂2 balance capacity in the air of Green Corridor 42 3.2.1.1 Results of estimating 𝐶𝑂2 absorption capacity of GC compared to total of Hanoi 𝐶𝑂2 emission 42 3.2.1.2 Comparison of 𝐶𝑂2 absorption capacity of Hanoi GC with similar models in the world 42 3.2.2 Enhance the ecological balance ability of the Green Corridor in Hanoi 43 ii 3.2.3 Assess the ecological balance of the Green Corridor in the future 44 CHAPTER 4: CONCLUSION AND RECOMMENDATIONS 46 4.1 Conclusion 46 4.1.1 Thesis’s structure 46 4.1.2 Limitations of thesis 47 4.1.2.1 Methodology 47 4.1.2.2 Database 47 4.2 Recommendations 48 REFERENCES 50 iii LIST OF FIGURES Fig 1: Green Corridor Functional Map Fig 1.1: London’s metropolitan greenbelt Fig 1.2 a, b: Beijing’s green belt (a), Beijing’s green belt in phase II 10 Fig 1.3: Seoul’s greenbelt 11 Fig 1.4 a, b: Tokyo’s greenbelt in planning project 1958 (a), Tokyo’s green space in planning project 1968 13 Fig 1.5: Carbon Cycle 17 Fig 2.1: LiDAR working principle 24 Fig 2.2 Products of LiDAR technology 25 Fig 2.3 Research method diagram 26 Fig 2.4: Location of the Green Corridor in Hanoi 27 Fig 2.5: Landsat images were taken on June 4, 2016 29 Fig 2.6: nDSM model in the Green Corridor area 30 Fig 2.7 a,b,c: NDVI map 2015, 2016, 2019 31 Fig 3.1 a,b: Biomass map of Hanoi’s Green Corridor in 2015, 2016 39 Fig 3.2 a,b,c : Change in LULC of Hanoi’s Green Corridor in 2015, 2016, 2019 41 Fig 3.3: Change in LULC of Hanoi’s Green Corridor in 2015, 2016, 2019 diagram 44 Fig 3.4: Relationship between propotion of tree land and amount of 𝐶𝑂2 absorption 45 Fig 4.1: Compare biomass estimation results by using satellite images of different resolutions 48 iv LIST OF TABLES Table 1.1: The goal of developing GS outside urban centers in some cities in the world 14 Table 1.2: location and scale of green space outside urban centers in some cities in the world 15 Table 2.1: Landsat images used in the thesis 28 Table 2.2: Statistics of total pixels for each type of tree in the GC area in 2015 32 Table 2.3: Statistics of total pixels for each type of tree in the GC area in 2016 33 Table 2.4: Statistics of total pixels for each type of tree in the GC area in 2019 33 Table 2.5: Statistics on 𝐶𝑂2 emissions of Hanoi in 2015 35 Table 2.6: Characteristics of land types classified by IPCC 2006 36 Table 3.1: Biomass value estimated and 𝐶𝑂2 in 2015 38 Table 3.2: Biomass value estimated and 𝐶𝑂2 in 2016 38 Table 3.3: Biomass value estimated and 𝐶𝑂2 in 2019 39 Table 3.4: Summary table of LULC classification results 2015, 2016, 2019 40 Table 3.5: 𝐶𝑂2 absorption capacity in Hanoi’s GC, Seoul’s GB and Dakota’s GS 42 v LIST OF ABBREVIATIONS WWF-World Wildlife Fund IPCC - The Intergovernmental Panel on Climate Change AEBIOM - European Biomass Industry Association IPCC - The Intergovernmental Panel on Climate Change MNRE - Ministry of Natural Resources and Environment REDD+ - Deforestation and Forest Degradation (REDD+) VIAP - Vietnam Institute of Architecture and Urban and Rural Planning USGS - United States Geological Survey GSO- General Statistics Office of Vietnam UHI - Urban Heat Island phenomenon GIS - Geographic Information System LiDAR- Light Detection and Ranging nDSM - normalized Digital Surface Model NDVI - Normalized Difference Vegetation Index LULC – Land use, Land cover GHG- Greenhouse gas GC- Green Corridor GS- Green space GB- Greenbelt C - Carbon 𝐶𝑂2 - Carbon dioxide 𝐶𝑂2 e - Carbon dioxide equivalent vi ACKNOWLEDGMENT This master thesis has conducted in February 2019 At that time, I was still studying at Kanazawa University, Japan After months of internship in Japan, I returned to Vietnam to complete the thesis Under the guidance of Dr Le Quynh Chi, from National University of Civil Engineering (NUCE) Therefore, I would like to express my deep gratitude and special thanks to Dr Le Quynh Chi for her support, giving me the necessary guidance and valuable lessons to carry out my research I would like to give these first lines to acknowledge her contribution most respectfully I would like to send my best wishes and deepest gratitude to Professor Kato, Tokyo University and Prof Nguyen Dinh Duc, Vietnam National University, Hanoi and Dr Phan Le Binh, lecturer, JICA has long been an expert at VJU, Dr Nguyen Tien Dung, a lecturer for their careful and valuable support, which is extremely valuable for my research both in theory and in practice Moreover, I look forward to expressing my deep gratitude to Prof Zhenjiang SHEN, a very talented and humble person who has only facilitated my study and work in his Urban Planning Laboratory I also give my sincere thanks to the doctoral students, masters, and students at the laboratory who have helped me a lot in knowledge that very useful fot my thesis during my internship in Japan Last but least, my master thesis also a present to my parents for always being by my side Sincerely, Hoang Dinh Viet vii ABSTRACT The Green Corridor (GC) is a new concept of the Master planning of Hanoi to 2030, vision 2050 The role of the GC is to become an urban logistics area to preserve the landscape and ensure urban living environment In particular, balancing urban living environment is a very esential goal The GC accounts for 68% of Hanoi's natural land The tree land in the GC is the ideal carbon sink to assist the city reduce the nagative impact of Urban Heat Island (UHI), 𝐶𝑂2 balance in the air However, under the pressure of urbanization and the existence of urban, industrial development projects and other ongoing activities The area of trees in the Hanoi’s GC has been declining rapidly, which reduces the ability to absorb 𝐶𝑂2 that human activities discharge By applied the concept of plant biomass This thesis provides an approach through quantifying carbon contained in vegetation in the GC and the ability to balance 𝐶𝑂2 in the air of GC Combined with remote sensing images, which is currently the strongly tool to apply for estimating biomass in large scale and complex terrain like Hanoi city viii Table 3.3: Biomass value estimated and 𝐶𝑂2 in 2019 Type Herbacecous Height Area Biomass in 𝑪𝑶𝟐 𝒆 m 𝒌𝒎𝟐 tons tons ≤ 1𝑚 254.7 vegetation 750,600.90 1,100,881.32 Shurb ≤2m 214.1 1,080,883.85 1,585,296.31 Tall Shurb 2-5m 368.1 3,018,696.08 4,427,420.91 Tree ≥5m 142 1,612,126.00 2,364,451.47 978.9 6,462,306.83 9,478,050.01 Total Fig 3.1 a,b: Biomass map of Hanoi’s Green Corridor in 2015, 2016 3.1.2 Change in LULC of Hanoi’s Green Corridor 39 In general, the classification results show that agricultural land, including active and inactive, still accounts for a high proportion and is allocated throughout the GC (more than 30% in all three times) Trees occupy a considerable area, most concentrated in the West and Southwest In addition, high density residential areas are located along the express way connecting the city center and satellite towns, especially in 2019 types of land use are classified according to IPCC 2006 As shown in table 3.4 and fig 3.2 Look at the map, we are able to see that the land use types have changed significantly in 2016 and 2019, but the biggest change belongs to residential land, tree land and industrial land In 2015, the total proportion of residential and industrial areas was 12.23% and 5.18% These areas have continued to increase over time and these values respectively reached 14.12% and 7.37% in 2019 Therefore, from 2015 to 2019, a significant increase in construction land has been increased , namely an rase of 1.89% in residential areas and 1.82% in industrial parks Table 3.4: Summary table of LULC classification results 2015, 2016, 2019 Residential Industrial Active agriculture Inactive agriculture Water Tree Sandbars Sandbars 2015 2016 2019 12.23 12.35 14.12 5.18 5.18 7.37 35.12 36.21 32.97 9.34 9.47 11.12 7.26 7.37 6.98 29.01 28.58 26.74 0.56 0.41 0.43 1.3 0.43 0.27 40 In summary, the results of LULC analysis show significant changes in land use, mainly fluctuations in trees land and increased construction land ( accounting for 22% of the total area of 2019) In the past urbanization process, GC of Hanoi has changed significantly in LULC, this change is mainly due to urban expansion, leading to an increase in residential or industrial areas Population growth, economic development and policy reform have played an important role in promoting these changes This is a potential risk for invasion of trees in the GC and reduces the ability of the GC to be urban ecological balance a b v c Fig 3.2 a,b,c : Change in LULC of Hanoi’s Green Corridor in 2015, 2016, 2019 41 3.2 Discussion 3.2.1 Assess the 𝐶𝑂2 balance capacity in the air of Green Corridor Hanoi 3.2.1.1 Results of estimating 𝐶𝑂2 absorption capacity of GC compared to total of Hanoi 𝐶𝑂2 emission From the estimated biomass results in 2015 and 2016, we can see that the difference in carbon stocks in the Green Corridor’s plant is the amount of 𝐶𝑂2 that trees absorb between the two point times 11,799.59 tons 𝐶𝑂2 has been removed from the air by the Green Corridor in Hanoi Meanwhile, according to the report of the Ministry of Natural Resources and Environment (MNRE), Hanoi City discharges 1,358,570 tons of 𝐶𝑂2 gas into the air The Hanoi Green Corridor has met 0.87% of the city's demand for environmental services 3.2.1.2 Comparison of 𝐶𝑂2 absorption capacity of Hanoi GC with similar models in the world When considering the results of Jo (2002), 𝐶𝑂2 absorption capacity of Hanoi’s GC is only 50% of 𝐶𝑂2 absorption capacity of Seoul’s GB (0.87% and 1.5%) For the results of Chang Zhao (2015), the environmental service capacity of Dakota’s GS is significantly greater than that of Hanoi’s GC (0.87% and 7.3%) Below is a table comparing the ability to absorb 𝐶𝑂2 in the air of the Hanoi’s GC, the Seoul’s GB and the Dakota’s GS, US city green space Table 3.5: 𝐶𝑂2 absorption capacity in Hanoi’s GC, Seoul’s GB and Dakota’s GS City Biomass caculation area Uptake % Hanoi GC 2,273.2 Km2 0.87% Seoul GB 606 Km2 1,5% Dakota GS 856 Km2 7.35% 42 3.2.2 Enhance the ecological balance ability of the Green Corridor in Hanoi On the basis of calculating Biomass reserves in plants and 𝐶𝑂2 absorption capacity of the GC of Hanoi In terms of urban ecological environment balance, Hanoi Green Corridor only meets 0.87% of the ecological environment needs for the whole city The decrease in trees area and rapid increase of construction land are the reasons for the GC to meet only a small amount of ecological needs of Hanoi city In order to enhance the role of the GC, it is necessary to consider the proportion of green areas in the GC If considering the model of Seoul's GB as a basis for assessing the effectiveness of urban planning GS outside the city center, Hanoi’s GC needs to meet 1.5% to 2% of 𝐶𝑂2 balance demand If only consider changing the value of tree land and keep the value of other types of land Thus, the Hanoi’s GC needs to have a minimum area of tree of 49.2% compared to 28.58% in 2016 If we remains the tree land ratio of the GC is 28.58% (2016) Changing plant characteristic is essential Considering in 2016, the proportion of trees under meter tall (with negligible biomass) is 274.7 km2, if replaced by woody plants (with high biomass) The role of the GC will be significantly increased In addition, maintaining the ratio of construction area (including residential areas and industrial zones) is very important Because residential areas and industrial parks are the main causes of greenhouse gas emissions and not contribute to ground biomass (IPCC, 2006) 43 Fig 3.3: Change in LULC of Hanoi’s Green Corridor in 2015, 2016, 2019 diagram 3.2.3 Assess the ecological balance of the Green Corridor in the future According to the results of biomass estimation at three time points , 2015, 2016 and 2019 The amount of biomass stored in plants of the GC in Hanoi has gradually increased This reflects the development of plants However, compared to 2016, the GC absorbed 11,799.59 tons 𝐶𝑂2 , at 2019, only 1.355.19 tons 𝐶𝑂2 /year are absorbed Thus, we are able to see a marked decrease in 𝐶𝑂2 balance over years (9 times reduction) The following chart shows the relationship between the trees area of GC and the amount of absorbed 𝐶𝑂2 in the period of 2016 and 2019 The rapid reduce of trees land causes the 𝐶𝑂2 absorption capacity of the GC to decline The trend of the graph goes down, and in the near future, carbon stocks will change seriously according to the negative side If there is no control of the development of GC, the area of trees converted into other types of land will be a huge source of 𝐶𝑂2 emission to the environment 44 Fig 3.4: Relationship between propotion of tree land and amount of 𝐶𝑂2 absorption SUMMARY OF FINDDING: Through the process of calculating biomass at point times (2015, 2016, 2019) There is a large amount of biomass stored by plants in the Green Corridor However, the 𝐶𝑂2 absorption capacity of plants in the Green Corridor is quite small, only reaching 0.87% of total 𝐶𝑂2 emissions in Hanoi in 2015 ( when Seoul’s GB reaching 1.5%) Through analysis of land use maps, the change in the largest area ratioin types of land: tree land, industrial land and residential land This change has a close relationship with 𝐶𝑂2 absorption capacity of the Green Corridor Hanoi While the area of tree land decreases sharply, the construction area increases rapidly from 2015 to 2019 The reduction of green area means that 𝐶𝑂2 absorption will decrease rapidly and the amount of 𝐶𝑂2 released into the environment will increase 45 CHAPTER 4: CONCLUSION AND RECOMMENDATIONS 4.1 Conclusion 4.1.1 Thesis’s structure By applied the concept of plant biomass This thesis provides an approach through quantifying carbon contained in vegetation in the GC and the ability to balance 𝐶𝑂2 in the air of GC Combined with remote sensing images, which is currently the strongly tool to apply for estimating biomass in large scale and complex terrain like Hanoi city Chapter 1: Including an overview of the definition of Green Corridor, Greenbelt (GB), Green space (GS) recognized in the world and in Hanoi’s Master planning project (2011) In this chapter, we listed the models of GS planning outside the urban centers in the world (Beijing, London, Tokyo, Seoul) and evaluate the effectiveness of these models We not only present the research related to the topic but also review the studies that mention the estimation of biomass by remote sensing images Theory and research results are presented in the following chapters: Chapter 2: In this chapter, we showed the perspective and research methods Based on the theory of environmental science, we determined the role of trees in reducing the UHI effect In addition, to estimate plant biomass in the GC We used Landsat satellite imagines and LiDAR data In addition, important data on Hanoi's total 𝐶𝑂2 emissions were also listed Chapter 3: We have estimated the amount of carbon stored in the GC’s vegetation at three point times (2015, 2016, 2019) A significant amount of biomass is being contained in the GC green area Compared to previous data, 46 we found out that the GC area absorbs only amount of 𝐶𝑂2 equivalent to 0.87% of the city's 𝐶𝑂2 emissions by 2015 Evaluating the 𝐶𝑂2 absorbing capacity of GC, we compared the results achieved with Seoul’s Green Belt Hanoi Green Corridor is only 50% effective In addition, we found the relationship between the annual absorbed carbon amount of the Green Corridor and the proportion of green land in this area In order to enhance the 𝐶𝑂2 absorbing capacity of the GC, the solution to increase the proportion of trees area has been mentioned In addition, changing species composition in the GC is also a very effective way to improve carbon storage The important factor that needs to be done in time is to consider the proportion of construction land This is the reason for the reduction of trees land and reducing the ability to meet ecological needs of the GC 4.1.2 Limitations of thesis 4.1.2.1 Methodology The biomass estimation method using satellite images and LiDAR technology has become more and more popular However, for each area, this method needs to be compared with the field calculation model Due to the limitations of the Master's thesis, we cannot implement a field calculation model or a database to compare the estimated biomass results in the lesson 4.1.2.2 Database Landsat satellite image data is an open source for GIS researchers to exploit However, at 30m resolution, products from this data will be less accurate Raciti (2014) compared the estimation of biomass in the same city with the use of satellite images of different resolutions, the results show that satellite images have a resolution of m Results closely with the most realistic calculations 47 Fig 4.1: Compare biomass estimation results by using satellite images of different resolutions 4.2 Recommendations The results of biomass estimation and assessment of 𝐶𝑂2 balance in the air of the Hanoi’s GC may be a database to serve the planning and management of the GC In addition, the thesis recommends that there should be studies to assess the impact of species composition in the flora of Hanoi in general and the GC in particular, in order to enhance the ability to meet the ecological needs of the city Assessments of the change in LULC of the Green Corridor area in Hanoi contribute to the Urban Heat Island (UHI) phenomenon is also one of the researches that need attention in the future 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AND ASSESSMENT OF THE ECOLOGICAL BALANCE CAPACITY OF THE HANOI GREEN CORRIDOR? ?? using tools are plant biomass in the Green Corridor area of Hanoi The assessment of the ability to balance