(Luận văn) impact of urbanization on urban heat island intensity of makati city, philippines

THAI NGUYEN UNIVERSITY UNIVERSITY OF AGRICULTURE AND FORESTRY KATLEEN CZINA V CAPISTRANO IMPACT OF URBANIZATION ON URBAN HEAT ISLAND INTENSITY OF MAKATI CITY, PHILIPPINES BACHELOR THESIS Lu an Study Mode: Full-time Major: Environmental Science and Management Faculty: International Programs Office Batch: 2014 - 2017 n va ac th si d oa nl w va an lu Thai Nguyen, 20/11/2017 ll u nf t n oi m z z DOCUMENTATION PAGE WITH ABSTRACT Thai Nguyen University of Agriculture and Forestry Bachelor of Environmental Science and Degree Program Management Student Name Katleen Czina V Capistrano Student ID DTN1454290048 Impact of Urbanization on Urban Heat Island Intensity of Makati City, Philippines Tang-Huang Lin, Ph.D (National Central University) Dr Do Xuan Loan ( Thai Nguyen University) Thesis Title Supervisors an Lu Signature Abstract: This study focuses on monitoring the urbanization and its effect on the Urban Heat Island Intensity (UHII) of Makati City, Philippines during a 10-year period from 2006 to 2016 in terms of remotely sensed data Two Landsat TM (April, 2006 and May, 2010) and one Landsat OLI/TIRS (April, 2016) images during the period were utilized after geometrically corrected In the data processing, Land Cover Changes (LCC) of year 2006, 2010 and 2016 were implemented in order to quantitate the changes within a decade period and address the location of urbanization Moreover, Land Surface Temperature (LST) of 2006, 2010 and 2016 were also retrieved from thermal infrared bands of Landsat data for the investigation of UHII within study area It was observed that UHII of Makati City boosted up 0.18oC with the increase in buildup areas during the last 10 years In addition, associated with the population growth rate from Philippine Statistics Authority, the results also indicated the effect of population growth was one of the indirect factors on UHII enhancement during the urbanization On the other hand, the decrease in the areas of open land, water and vegetation was negatively proportional to UHII intensification Therefore, the increase in population and buildup areas observed in this study were the major reasons why the UHII increases However, this study only focuses on the effect of urbanization on UHII in terms of LCC and LST retrieved from satellite data For more accurate assessment in UHII, the validation of LST retrievals with in-situ measurements should be included which will be the further study of this topic Thus the results could be expected to the references for urban development and related policy Urbanization, Urban Heat Island, Land Cover Keywords: Change, Land Surface Temperature Number of Pages 61 n va ac th si d oa nl w November 20, 2017 ll u nf va an lu Date of Submission n oi m t ii z z ACKNOWLEDGEMENT First and foremost, I would like to extend my sincerest gratitude to Associate Prof Tang-Huang Lin Ph.D of Center for Space and Remote Sensing Research (CSRSR) at National Central University (NCU) for the support, patience and guidance in spite of his busy schedule just to finish and achieve the goals of this study Also, to Dr Do Xuan Luan, for his support and instructions throughout writing my manuscript With the help of the Advance Education Program of Thai Nguyen University of Agriculture and Forestry (TUAF), this research had been successful, thank you very much for everything! My best regards to this awesome yet supportive parents of mine (Mommy Tale and Daddy Chef Boy Negro) for investing not just money but also their time and sweat to support for my studies To Capistrano family, especially Kuya Babs, Neyney, Mommy Baby, Tito Fred and Ate Maida, thank you for the never ending support and help To my Tita Rose and Ate IB, thank you for supporting and an Lu helping me before, on and after I went to Taiwan and to my kindest Lola Uyang, I n va know you are watching me from above Lola, I have made it! I survived all the ac th hardships Thank you for being one of my inspirations! si My Vietnam buddies, Mish, Kenneth, Anne, Ekang, Colleene and Carlo, w d oa nl thank you so much! Through good and bad times, you are all there Thank you for making me realize that I have a lot to improve in myself and on the things I va an lu believe in I am so grateful that I have a clingy and supportive friend, Tina, thank ll u nf you for everything! You da best! I could not even be more proud to have the n oi m t iii z z bestest sissy who is always there to push me through and giving me her best advices, my Sensei Kulot, thank you so much! I consider myself lucky to meet this fabulous Fish Family (Cher, Poch, Butch, Russel, Hanh, Alison and Cang Rong), thank you very much for helping me with my research and showing me what a real college student should I never expected that my time in Taiwan would be this amazing To the prayer warriors of NCU International Fellowship, especially to Elizabeth Sitorus, who invested time and effort in helping me with this study, thank you is not enough I am beyond grateful for having people who were always ready to listen and willing to help in times of need We are indeed a family of God Lastly, I am giving all the glory to the Lord for His blessings and guidance, for making me feel I am loved and that I can things This journey will not be successful without Your presence Oh Lord! Thai Nguyen 2017, an Lu Student n va Katleen Czina V Capistrano ac th si d oa nl w ll u nf va an lu n oi m t iv z z TABLE OF CONTENTS DOCUMENTATION PAGE WITH ABSTRACT ii ACKNOWLEDGEMENT iii TABLE OF CONTENTS v LIST OF FIGURES vii LIST OF TABLES ix LIST OF ABBREVIATIONS x PART I: INRTODUCTION 1.1 Background of the Study 1.2 Investigation Area 1.3 Statement of the Problem 1.4 Objectives of the Study 1.5 Significance of the Study 1.6 Limitations of the Study PART II: REVIEW OF RELATED LITERATURE 2.1 Urban Heat Island (UHI) 2.2 Mitigation studies on Urban Heat Island (UHI) 12 2.3 Land Cover Change and Urbanization 13 Lu 2.4 Studies on Urban Heat Island (UHI) in the Philippines 19 n va an 2.5 Related studies on Urban Heat Island (UHI) around the world 14 PART III: MATERIALS AND METHODS 22 ac th 3.1 Materials 22 The objects and scope of the research 22 3.1.2 The content of research 23 si 3.1.1 d oa nl w Conceptual Framework 23 3.3 Data Collection 25 3.4 Image Pre-Processing 25 va an lu 3.2 Layer Stacking 26 3.4.2 Geometric Correction 28 3.4.3 Image Subset 28 ll u nf 3.4.1 n oi m t v z z 3.5 Land Cover Change 29 3.5.1 Training Samples Selection 29 3.5.2 Accuracy Assessment 30 3.6 Land Surface Temperature Calculation 33 3.6.1 3.7 Brightness Temperature Calculation 33 Urban Heat Island (UHI) Intensity Calculation 38 PART IV: RESULTS AND DISCUSSION 39 4.1 Results of Land Surface Temperature 39 4.1.1 Brightness Temperature 39 4.1.2 Emissivity Results 40 4.1.3 Land Surface Temperature 45 4.2 Results of Land Cover Change 46 4.2.1 Land Cover Change (LCC) 46 4.2.2 Accuracy Assessment 48 4.2.3 Change Detection 50 4.3 Urban Heat Island (UHI) Intensity 52 PART V: CONCLUSION AND RECOMMENDATIONS 56 REFERENCES 58 an Lu n va ac th si d oa nl w ll u nf va an lu n oi m t vi z z LIST OF FIGURES Figure 1.1 Map of Makati City divided into six clusters…………………… Figure 2.1 Effect of Urbanization on people, temperature and environment 10 Figure 3.1 Conceptual Framework……………………………………… 24 Figure 3.2 Methods for Pre-processing of Remotely Sensed Data……………26 Figure 3.3 Layer Stacked images of 2006 (a), 2010 (b) and 2016 (c), respectively……………………………………………………………… 27 Figure 3.4 Study Clip Area of Makati City for 2006, 2010 and 2016, Respectively……………………………………………………………28 Figure 3.5 Land Cover Change Detection……………………………… .29 an Lu Figure3.6 Flow Chart of Land Surface Temperature Calculation…………….33 Figure 3.7 Thermal Band images of Landsat TM and Landsat n va ac th OLI/TIRS………………………………………………………………34 si d oa nl w Figure 4.1 Brightness Temperature of (a) 2006, (b) 2010 and (c) 2016 band 10 and (d) band 11……………………………………………………… 39 va an lu Figure 4.2 Emissivity Maps for (a) 2006, (b) 2010 and (c) 2016…………… 41 Figure 4.3 NDVI maps for (a) 2006, (b) 2010 and (c) 2016……………… 42 u nf ll Figure 4.4 Green Vegetation Fractions of (a) 2006, (b) 2010 and (c) n oi m t vii z z 2016………………………………………………………………… 44 Figure 4.5 Land Surface Temperature Maps of (a) 2006, (b) 2010 and (c) 2016……………………………………………………………… 45 Figure 4.6 Land Cover Change Maps of (a) 2006, (b) 2010 and (c) 2016…………………………………………………………… .46 Figure 4.7 Area of each land cover type of 2006, 2010 and 2016 expressed in percent…………………………………………………………………47 Figure 4.8 Change Detection of Makati City during the period from 2006 to 2016………………………………………………………………… 50 Figure 4.9 UHII of Makati City in degree Celsius for the year 2006, 2010 and 2016………………………………………………………………… 52 Figure 4.10 Area of each land cover type vs UHII of 2006, 2010 and 2016, (a) Build up vs UHII; (b) Open Land vs UHII; (c) Vegetation vs UHII; (d) Water vs UHII.…………………………………………………… 53 Figure 4.11 Scatter Plots showing the relationship of each land cover type to Lu an UHII, (a) Build up vs UHII; (b) Open Land vs UHII; (c) Vegetation vs n va UHII; (d) Water vs UHII………………………………………………54 ac th si d oa nl w ll u nf va an lu n oi m t viii z z LIST OF TABLES Table 3.1 The images collected from Landsat TM and Landsat OLI/TIRS………………………………………………………………25 Table 3.2 Landsat TM band numbers with respective band names……… 26 Table 3.3 Same as table 3.2 but for Landsat OLI/TIRS…………………….27 Table 3.4 Thermal Constants of Landsat TM and Landsat OLI/TIRS………………………………………………………………34 Table 3.5 Rescaling Factors of Landsat TM and Landsat OLI/TIRS…………………………………………………………… 34 Table 4.1 Confusion Matrix for year 2006 form Accuracy Assessment…… 48 Table 4.2 Same as Table 4.1, but for year 2010………………………………49 an Lu n va Table 4.3 Same as Table 4.1, but for the year 2016………………………… 49 ac th Table 4.4 Percent and Area of Land Cover Change during the period from 2006 si to 2016……………………………………………………………… 51 w d oa nl Table 4.5 Population data of Makati City from 2000 to 2015……………… 55 ll u nf va an lu n oi m t ix z z LIST OF ABBREVIATIONS Advanced Spaceborne Thermal Emission DN Digital Numbers EDSA Epifanio de los Santos Avenue EPA Environmental Protection Agency ETM+ Enhanced Thematic Mapper ISA Impervious Surface Area LCC Land Cover Change LST Land Surface Temperature MODIS Moderate Resolution Imaging Spectoradiometer NCR National Capital Region NDVI Normalized Difference Vegetation Index NIR Near Infrared NMDI Normalized Multi-Band Drought Index OLI Operational Land Images RS Remote Sensing SUCI an Lu ASTER Surface Urban Cool Island SUHI n va SWIR Shortwave Infrared TIRS Thermal Infrared Sensor TM Thematic Mapper UHI Urban Heat Island UHII Urban Heat Island Intensity Surface Urban Heat Island ac th si d oa nl w ll u nf va an lu n oi m t x z z Land Cover Change Map for years 2006, 2010 and 2016 were produced as shown in Figure 4.6 The land cover types were presented with its designated or assigned color (blue-water, green-vegetation, grey-buildup and brown-open land) Moreover, the total area of Makati City is 27,355,700 square meters After running the land cover change detection, the areas for each land cover type is known and presented in Figure 4.7 Area in square meters 90 80 70 60 50 40 30 20 10 Open Land Vegetation 28.39 14.8 25.34 11.88 6.73 9.43 an Lu Build Up Apr-06 56.33 May-10 62.37 Apr-16 83.38 n va ac th Water 0.47 0.42 0.46 si d oa nl w Figure 4.7: Area of each land cover type of 2006, 2010 and 2016 expressed in percent According to the results, the area of buildup in Makati City from 2006 to va an lu 2016 increased, open land and vegetation decreased and water is unstable ll u nf during the time period Moreover, buildup covers most of the areas in Makati n oi m City which includes the houses, buildings, highways and other impermeable t 47 z z surfaces Water covers the least in Makati City since it is far from water bodies, only the Pasig River passes that area 4.2.2 Accuracy Assessment Accuracy Assessment for the years 2006, 2010 and 2016 were done to know the accuracy or how the land cover change results agree to the reference data The results of these assessments were used to evaluate and check if the land cover change results can be used or are accepted The results of this accuracy assessment were all presented in a confusion matrix (table) which can be seen in Table 4.1, 4.2 and 4.3 The land cover types in the row were obtained from the reference source while the ones in the column were from the classified maps The numbers of correctly classified land cover types are shown diagonally in red bold text Table 4.1: Confusion Matrix for the year 2006 from Accuracy Assessment an Lu Class Types determined from reference source April # Plots for Open Vegetation Built Water 2006 2010 Land Up Class 0 Open 50 Types Land from 0 Vegetation 50 classified Built Up 0 50 map 0 Water 49 Column Total 50 50 50 50 Omission Error 0 n va ac th 100% 100% si Producer’s Accuracy 100% Percent (%) Row Commission User’s Error Total Accuracy 50 100 50 51 49 200 1.96 100 98 100 Overall: 99.5% Kappa: 0.993 98% w d oa nl Shown in Table 4.1 is the confusion matrix with the values obtained after running the Accuracy Assessment for the year 2006 The overall accuracy va an lu obtained was 99.5% while the Kappa coefficient acquired was 0.993 which ll u nf were both high in value n oi m t 48 z z Table 4.2: Same as Table 4.1, but for the year of 2010 Class Types determined from reference source # Plots for Open Water Built Vegetat Row 2010 Land Up ion Total May 2010 Class Open Types Land from Water classified Built Up map Vegetation Column Total Omission Error 46 0 49 50 49 50 50 50 0 46 50 49 56 46 200 Producer’s Accuracy 92% 98% 100% 92% Percent (%) Commiss User’s ion Error Accur acy 6.12 93 10.71 100 89 100 Overall: 95.5% Kappa: 0.94 On the other hand, Table 4.2 presented above is the confusion matrix for the year 2010 After computing all the required components for the accuracy assessment evaluation, the result shows that the overall accuracy was 95.5% and the Kappa coefficient was 0.94 which were both lower than the ones in 2006 It can be seen that 2006 has higher accuracy than 2010 Table 4.3: Same as Table 4.1, but for the year of 2016 Class Types Determined from Reference Source # Plots for Vegetat Open Built Water Row 2016 ion Land Up Total April 2016 Class Types from classified map an Lu Vegetatio n Open Land Built Up Water Column Total Omission Error Producer’s Accuracy Percent (%) Commis User’s sion Accur Error acy 100 n va ac th 0 46 43 0 47 8.51 91 0 50 92% 50 14 86% 50 50 100% 41 50 18 82% 66 41 200 24.24 76 100 si 46 d oa nl w Overall: 90% Kappa: 0.8667 Lastly, in Table 4.3, the overall accuracy and Kappa coefficient for the va an lu year 2016 was 90% and 0.867, respectively Among the results of overall accuracy and Kappa coefficient of 2006, 2010 and 2016, 2016 has the lowest u nf ll accuracy and 2006 was the most accurate among those three years n oi m t 49 z z The value of Kappa coefficient is the most important in order to evaluate if the classified map is accepted or not All the results were greater than 0.80, which means that all of the values from 2006, 2010 and 2016 represent strong agreement Therefore, based on the accuracy assessment, the Land Cover Changes of 2006, 2010 and 2016 were all accepted 4.2.3 Change Detection Changes in land cover type in Makati City were evaluated and analyze by running the Change Detection and the result is shown in Figure 4.8 There is a specific color for every change on each land cover type and to differentiate each of the changes, Table 4.4 shows the rate in percent of these changes as well as the area, for each land cover type an Lu n va ac th si d oa nl w ll u nf va an lu m n oi Figure 4.8: Change Detection of Makati City from 2006 to 2016 t 50 z z In addition, Land Cover Change Detection of Makati City were analyzed and evaluated in order to get information on the rate of urbanization in the area and which of the land cover type has experienced the highest change from the year 2006 to 2016 Moreover, these results can help in assessing the impacts of the changes in people, environment and urban climate of the study area an Lu Table 4.4: Percent and Area of Land Cover Change during the period from 2006-2016 Land Cover Type Land Cover Change Area in square meters Changes (%) Buildup 19.8 17,634,593 Buildup to Open Land 1.73 49,768.22 Buildup to Vegetation 2.53 82,977.1 Buildup to Water 0.63 38,377.42 Open Land 9.08 1,221,223 Open Land to Buildup 19.74 6,686,895 Open Land to Vegetation 11.47 1,066,448 Open Land to Water 0.02 616.19 Vegetation 9.19 1,834,608 Vegetation to Buildup 16.13 1,992,486 Vegetation to Open Land 8.39 855,852.1 Vegetation to Water 0.0321 3,958,783 Water 0.6826 104,205.4 Water to Buildup 0.5782 41,205.06 n va ac th As shown in Table 4.4, the land cover types; open land, vegetation and si water that were converted to buildup areas together with the total buildup area w retained, have the highest change all in all, while land cover types which were d oa nl converted to water has the lowest With this, it can be seen that buildup areas va an lu dominated the whole land area of Makati City, Philippines ll u nf n oi m t 51 z z 4.3 Urban Heat Island (UHI) Intensity Urban areas which have a higher temperature than rural areas also known as the Urban Heat Islands were studied and analyzed Figure 4.9 shows the UHII in degree Celsius of the following years 2006, 2010 and 2016 Year 2010 was also studied in order to further differentiate and evaluate the changes between the years 2006 and 2016 The UHII results were obtained during those years by subtracting the urban temperature by the rural temperature According to the results, from 2006 to 2016, the UHII was increasing with the temperature changes from 0.33oC to 0.51oC which means the UHII boosted up a 0.18oC during this 10 year period In comparison for each of those three years, during 2006 to 2010, the temperature rise was 0.12oC while for the year 2010 to 2016; the temperature boosted up to 0.06oC 0.6 UHII in degree Celsius 0.5 0.51 0.45 0.33 UHII ac th 0.2 n va 0.3 an Lu 0.4 si 2010 2016 va an lu 2006 d oa nl w 0.1 Figure 4.9: UHII of Makati City in degree Celsius for the year 2006, 2010 and ll u nf 2016 n oi m t 52 z z In addition, the relationship of each land cover type changes (in area) from UHII from 2006 to 2016 were evaluated and analyzed in order to assess its impact Figure 4.10 shows the comparison for each of the land cover type to UHII for year 2006, 2010 and 2016 The comparison of each land cover types to UHII shows the relationship between the two an Lu n va Figure 4.10: Area of each land cover type vs UHII of 2006, 2010 and 2016, (a) Build up vs UHII; (b) Open Land vs UHII; (c) Vegetation vs UHII; (d) Water vs UHII ac th si Moreover, as scatter plot showing the relationship of each land cover w types to UHII is shown in Figure 4.11 The result shows that changes on d oa nl buildup areas were directly proportional to UHII while changes in open land, va an lu vegetation and water areas inversely affect the UHII Thus, there is a positive ll u nf correlation between buildup areas and a negative correlation was observed n oi m among open land, water and vegetation against UHII In addition, as the t 53 z z buildup area increases, the UHII also increases where it might affect the urban climate, people and the environment of Makati City Associated with the population growth, acquired from Philippine Statistics Office, population data and UHII were compared The data available were only from 2000 to 2015 since the census was not available yet and has not been done for 2016 until present year Table 4.5 shows the population data of Makati City from 2000 to 2015 (a) (b) an Lu n va (c) (d) ac th si d oa nl w va an lu ll u nf Figure 4.11: Scatter Plots showing the relationship of each land cover type to UHII, (a) Build up vs UHII; (b) Open Land vs UHII; (c) Vegetation vs UHII; (d) Water vs UHII n oi m t 54 z z Table 4.5: Population data of Makati City from 2000 to 2015 Year Population Growth Rate (%) 2000 - 2010 1.16 2010 - 2015 1.85 Source: Philippine Statistics Authority After analyzing the relationship of population growth rate and UHII, the results revealed that the Population Growth Rate from 2000 to 2015 had increased As the table presented, from 1.16% on 2000 to 2010, the rate ascended to 1.85% on the census during 2010 to 2015 Through the comparison of UHII results and the population data, it was determined that population data is considered as another factor affecting UHII Thus, UHII intensity increases as the Population Growth Rate also increases an Lu n va ac th si d oa nl w ll u nf va an lu n oi m t 55 z z PART V: CONCLUSION AND RECOMMENDATIONS The main goal of this study was to assess the effect of urbanization observed from Land Cover Change detection on Urban Heat Island Intensity of Makati City Known to be a tropical country, Philippines has only two seasons (wet and dry season) in a year and summer seasons were used for this 10-year period study Through the analyzation of results, it was found out that Makati City’s land cover has experienced modification over the past 10 years from 2006 to 2016 Hence, the UHII boosted up to 0.18oC with the increase in buildup areas which expanded during the past decade Associated with urbanization, the population growth rate of Makati City from 2000 to 2015 was compared to the UHII results It was found out that the effect of the population growth was one of the indirect factors on UHII enhancement Known as the Central Business District of the country, Makati City has experienced urbanization with the increase in population By the need of accommodations an Lu for the population increase, the land cover changed during the past decade n va Due to this, more policies were needed to be implemented Building ac th more green roofs (rooftops of buildings which were covered with vegetation) si w has a huge help since there are a lot of skyscrapers in the area, especially in the d oa nl core of the city Moreover, planting more trees and other vegetation in open areas, parking lots, alongside the roads and other possible places, can help va an lu reduce the effect of the heat islands and air pollution Considering that u nf residential areas are dominating Makati City’s total land area, planting at least ll m n oi one tree and any kind of vegetation on every household if there are enough t 56 z z spaces can help lessen the negative impacts of urbanization on UHII enhancement that can affect the people and the environment In summary, urbanization has a big impact in forming heat islands which triggers Urban Heat Island Intensity to be worse, making the temperature of urban areas warmer This study provided evidence that buildup areas and population has a big impact on the UHII of Makati City Urban planning can help in mitigating the negative impacts of heat islands Being aware by the impacts of urban heat islands can lessen its severe effect in the environment, considering the health and wellness of the people living on and near the area since people are the ones really affected by this change although, they are also one of the 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