Affiliation of urban expansion on population growth, economic development, and surface urban heat island intensity in muntinlupa city, metro manila, philippines

THAI NGUYEN UNIVERSITY UNIVERSITY OF AGRICULTURE AND FORESTRY KRISTINA BELEN REYES AFFILIATION OF URBAN EXPANSION ON POPULATION GROWTH, ECONOMIC DEVELOPMENT, AND SURFACE URBAN HEAT ISL

THAI NGUYEN UNIVERSITY

UNIVERSITY OF AGRICULTURE AND FORESTRY

KRISTINA BELEN REYES

AFFILIATION OF URBAN EXPANSION ON POPULATION GROWTH, ECONOMIC DEVELOPMENT, AND SURFACE URBAN HEAT ISLAND INTENSITY IN MUNTINLUPA CITY, METRO-MANILA, PHILIPPINES

BACHELOR THESIS

Study Mode: Full-time

Major: Environmental Science and Management

Faculty: Advance Education Program Office

Thai Nguyen, 11/15/2018

DOCUMENTATION PAGE WITH ABSTRACT

Thai Nguyen University of Agriculture and Forestry

Thesis Title Affiliation of Urban Expansion on Population Growth, Economic

Development, and Surface Urban Heat Island Intensity in Muntinlupa City, Metro-Manila, Philippines

of SUHI correlate with land covers, the results affirm the value of taking care and multiplying natural areas especially vegetation in the city to stabilize the intensity

of urban heat island Moreover, in the context of the city economic growth, city income had a positive relationship with the city expansion And managing the number of informal settlers is also found to be a factor that can lead to a stable increase of city income Overall, beholding the results of the analyses and the existing ordinances, the study implicate that the city officials and representatives should attain advancement and consistency in implementing and monitoring the management strategies concerning the environment and socio-economic issues in Muntinlupa city

Keywords: Urbanization, LULC, UHI, City Income, & Population Growth

Number of

pages

112 pages

Date of 11/15/2018

ACKNOWLEDGMENT

First and foremost, I would like to thank the Almighty God, for being with

me all throughout this journey, and for giving the assurance that His promises will never be taken away from me That is why I will take this thesis as an offering to Him To Him be all the glory

I am also beyond grateful to Dr Ho Ngoc Son, my thesis Supervisor, for all the unending valuable advises, for being patient and supporter whenever I’m having a problem with my thesis Thank you, so much and best regards to you and your family

To my family, especially my father Edison O Reyes, my Mother Josefina

B Reyes, my siblings Ate Isyang, Ate Pat and EJ, and my other relatives (Lola Paking, Tita Cherry, Tita Cora, Ninang April, Kenneth, Kien, Tita Myrna, Tita Ester and others) thank you for not just supporting me financially but also for being there for me when I needed some help and motivation

To my second home, my JCRF family, my co-members in Worship Team and Youth Service Ministry and most especially to my Spiritual parents/leaders Ptr Nestor, Ptra Jeanie, Ptra Mhalou, T Irene, T Elsa and Ptr Jun Macaleng, thank you for all the prayers and guidance

To my beloved friends/ siblings, Francina, Joy, Pau, Enzo, Jessica, Vea, Aj, Lester, Ghia and King, thanks for sharing your thoughts and for keep on telling that we are all in this together, I know together also we will all succeed Love you guys!!

Also, I would like to extend my gratitude to the City Planning and Development office of Muntinlupa city, (especially to Ms Jireh Sagum), to Mrs Lorna Misa head of Environmental Protection and Natural Resources office, to Mrs Alita Ramirez head of Urban Poor Affairs Office for helping me in gathering the data and other information I needed for my thesis And last but not the least, to all passionate in teaching GIS and Remote Sensing techniques in the YouTube and google websites, thank you I salute you all

The Student Researcher,

Kristina B Reyes

TABLE OF CONTENTS

DOCUMENTATION PAGE WITH ABSTRACT ii

ACKNOWLEDGMENT iii

TABLE OF CONTENTS v

LIST OF FIGURES vii

LIST OF TABLES viii

LIST OF ABBREVIATIONS ix

PART I: INTRODUCTION 1

1.1 Rationale 1

1.2 Objectives 5

1.2.1 General objective: 5

1.2.2 Specific objective 5

1.3 Research questions and hypotheses 6

1.4.1 Research questions 6

1.4.2 Hypotheses 6

1.4 Scope and limitation 7

1.3.1 Location 7

1.3.2 Time of data collection: 9

1.3.3 Limitations 9

1.5 Definition of terms 10

PART II: REVIEW RELATED LITERATURE 13

2.1 Land use and land cover change 13

2.2 LULC application and approaches 15

2.3 Urban population growth 19

2.4 Population growth in the Philippines 23

2.5 Urban economic growth and related studies 25

2.6 Economic growth in the Philippines 28

2.7 Urban heat island (UHI) 30

2.8 UHI studies and approaches 33

PART III: METHODOLOGY 40

3.1 Research objects 40

3.1.1 The scope of the research 40

3.1.2 Software used 40

3.1.3 Location and data used 40

3.2 Methods 42

3.2.1 Processing the spatial data 42

3.2.2 Detection of land cover change 45

3.2.3 Evaluation of the classified maps 47

3.2.4 Retrieval of land surface temperature and SUHI intensity 50

3.2.5 Statistical analysis 55

PART IV RESULTS AND DISCUSSION 56

4.1 Land cover change detection 56

4.2 Population growth in Muntinlupa City 60

4.3 Growth of city income Muntinlupa City 63

4.4 Land surface temperature and UHI Intensity 66

4.4.1 Dynamics of land surface temperature 66

4.4.2 Dynamics of surface UHI 68

4.5 Ordinances of the city for mitigating the risk of urbanization 72

4.5.1 UHI and related environmental protection ordinances 72

4.5.2 Other city ordinances concerning poor, informal settlers and unemployed citizens 76

PART V: CONCLUSION AND RECOMMENDATION 78

REFERENCES 82

APPENDICES 108

LIST OF FIGURES Figure 1: The Location of Muntinlupa City and its corresponding districts and

barangays 8

Figure 2: Conceptual framework of the study 44 Figure 3: True color composite bands (above) and false color composite bands

(below) used for classification 46

Figure 4: Proportion of each land cover type in each selected year 56 Figure 5: Land cover maps of Muntinlupa City on 1996, 2003, 2010, and 2017.

57

Figure 6: LULCC maps of Muntinlupa city on the selected periods 58 Figure 7: Alteration of other land cover types to Developed Land (%) 59 Figure 8: Population of the whole city and of each barangay in 1996, 2003, 2010

and 2017 61

Figure 9: The city’s population density per squared hectare in 1996,2003, 2010,

and 2017 62

Figure 10: Statistical analysis of population growth and developed land Table A

shows the association between population density and percent of

developed land in each year Table B shows the relationship between annual growth of population to developed land 63

Figure 11: The city income in 1996, 2003,2010 and 2017 64 Figure 12: Relationship analysis between city income and percent of developed

land in each year 65

Figure 13: Maps of LST in 1996, 2003, 2010, and 2017 66 Figure 14: The variation of average LST of each land cover types in years 1996,

2003, 2010, and 2017 67

Figure 15: Maps of UHI intensity level in 1996, 2003, 2010, and 2017 (shown

map D) 69

Figure 16: The area distribution of UHI intensity level in each 1996, 2003, 2010,

and 2017 in the city 70

LIST OF TABLES

Table 1:Collected Satellite images and their attributes 41

Table 2: Corresponding bands of Landsat 5 TM and Landsat 7 ETM 43

Table 3: Identification of classified land cover type 45

Table 4: Kappa coefficient values and their level of agreement 50

Table 5: Rescaling factors of the respective thermal bands of landsat 5 TM and Landsat 7 ETM+ 50

Table 6: Thermal constants of the corresponding thermal bands of Landsat 5TM and Landsat 7 ETM+ 51

Table 7: Seven Levels of UHI intensity with the corresponding value 54

Table 8: Available data numbers of Informal settlers 66

Table 9: The average UHII and the percentage of its drivers (Developed land, water bodies, and vegetation) in 1996, 2003, 2010, and 2017 71

Table 10: The regression analyses of UHI intensity change and its drivers 71

Table 11: The annual environmental protection and maintenance fee of all High-risk Industrial and Establishments 73

Table 12: The annual environmental protection and maintenance fee of all Low-risk Industrial and Establishments 74

Table 13: Penalty fees for violating the all included protocols in the ordinance 75

LIST OF ABBREVIATIONS

NIR Near-Infrared

PV Percent Vegetation

PART I: INTRODUCTION

1.1 Rationale

According to World Bank Organization statistics (WBO, 2017), urban population in the world has been extensive since 1960’s, from having 33% to 54.74% currently Globalization and industrialization are the major causes of

urbanization, which are also the means of many countries to have a rapid increase

in their economy (Chen et al.,2014) In contrast, enormous studies are proclaiming

that urbanization is considered as one of the major threats to the world (UNFPA,

2015; Kabaria et al., 2017; Moore et al., 2003; Kelley and Schmidt, 1995)

Large scales of forests and other vegetated area were converted for erecting

different types of infrastructure, such as commercial buildings, private companies,

factories, roads and bridges (Huang et al., 2017) Consequently, many cities

became prone to environmental hazards (Newman, 2006) These concrete

infrastructures and roads are absorbing heat from the sun which cause extreme heat

events or urban heat island Concentrated energy use produces from burning fossil

fuel and exhaustion of automobile in cities result to extensive air pollution (Ilyas,

2007; IEA, 2016) Moreover, because of population shift from rural to urban,

environmental resource management in terms of water sanitation and waste

management are also being degraded (White, 2000)

These urban environmental problems led to the deliberation that city area is

one of the unhealthiest places for any organisms to live, especially for humans

According to studies, respiratory infections, Hypertension, and various pathogenic

diseases are some of the health issues being brought by these urban environmental

problems (Kingue et al., 2015 ; Gubler 2011 ;Walke et al., 2014)

Correspondingly, over the last couple of decades, urban areas around the

world have been engaged in increasing initiatives, practices and experiments with

a view to achieving social, economic and environmental sustainability (Tan, 2016)

Researchers have discovered different kind of approaches for urban assessments,

and continuously developing these over the years (Conte and Monno, 2016)

Application of remote sensing and Geographic Information System (GIS)

satellite data are currently the most widely used tool in observing the impact of

urbanization, specifically in the environment (Melesse et al., 2007) Likewise,

Zhang et al., (2014) used the estimation of land use/land cover (LULC) change and

land surface temperature (LST) to analyze the effects of urbanization to

spatiotemporal patterns, particularly in the city of Shanghai, China

Furthermore, Moore et al (2003) stated that urban areas contribute a larger

share in Gross domestic product per capita of many countries However, rapid and

unplanned urbanization are associated with severe environmental, social and

economic degradation Which is why comprehending LULC or land use and land

cover change is a vital tool to achieve sustainable city planning (Halmy et al.,

2015) In addition, creation of wealth in a city attracts people that will eventually

increases the demand and accelerates the urban growth (Swilling et al., 2012)

Congruently, in this study urban impacts in environment, population and

economic growth will be analyzed from Metropolitan Manila in the Philippines,

particularly Muntinlupa City Philippines was recognized as one of the countries

in East Asian Region with vastly growing urban development (Iimi, 2005)

Currently, the country partakes more than half of the country’s extent (WBO,

2017) Similar to other developing countries, several environmental problems

related to urban extension such as increasing greenhouse gas emissions, flooding,

solid waste problems, deterioration of water quality and air quality have long been

prominent in Metro- Manila (Regmi et al., 2017) And since the metropolitan area

of Manila, including Muntinlupa city are the center of socioeconomic activities in

the country, replacement of natural environment to surfaces which are

low-reflective, non-evaporating and non-transpiring infrastructures are blatant,

(Pereira, R A 2004), perhaps might lead to the existence of high UHII or urban

heat island intensity (Memon et al., 2008) Therefore, in the study, land surface

temperature will be evaluated to determine how is the intensity level of UHI or

urban heat island through the years

Furthermore, the study will also determine the of the population growth

change in the city Philippines has presented a rapid increase in human population

(Foruoka, 2010), currently carrying out more than 100 million people (PSA, 2017)

Whereas, National Capital Region has the highest population in the country and

ranked 12th of the most populous megacities in the world (Muntinlupa economic Profile, 2016) According to some studies human population change that

Socio-are linked with urban development have consequences in environment in some

parts of the world, and eventually risk economic development also (Marmara &

Usman 2015) Certainly, several studies in the Philippines also proved this

statement (Balanay & Lungu, 2009; Siador & Promentilla ,2016; WBO, 2002)

Rapid population growth obliterated the neatness of the cities, because of

numerous rural-urban migrants are residing in slums (Balesteros, 2010) Before,

Philippines are known to be an agricultural country (DLSU-Manila 2002)

However, since 1970’s agricultural share to the GDP started to decrease (Balisacan

et al., 2000) Decreasing number of Filipinos are engaging agricultural profession

(Elauria, 2015) along with the capital deficiency (for seeds, fertilizers, pesticides,

wages for hiring workers etc.) confronting by the remaining farmers are the major

reasons of agricultural degradation in the country Farmers find it less lucrative

than to sell the farm land properties in many developers who are converting these

into golf courses, residential subdivisions, manufacturing building, and industrial

parks or resorts (Nations Encyclopedia, 2018) Consequently, according to East

Asia Infrastructure Department of the World Bank organization (WBO, 2003) the

growth of GDP per capita is relatively low for the given high rate of urbanization

in the country for the past three decades Yet, contrasting to this, on the recent

years urban development is bringing positive consequences in economic growth

of the country Predominantly driven by manufacturing, trade, real estate, renting,

and business activities, according to Philippine Statistical Authority Gross

Domestic Product (GDP) grew by 6.9 percent in the third quarter of 2017 (PSA,

2017)

Furthermore, the study concerns with how city development brings sustainable

amendments in Muntinlupa City If it will be found out that urban development is

risking the environment, population, and economic growth in a city, this will act

as a representation of the community for the Government to take hold of this

problem Moreover, in case that the city is bringing positive impacts to the city,

then it could also be a tool to promote the urban management strategies which

might be applicable to other communities

1.2 Objectives

1.2.1 General objective:

The goal of the study is to assess the Urban development in

Muntinlupa city through analyzation of the relationship of LULCC among,

population growth, economic development and UHI intensity Which can

then be helpful for the city government to maintain the sustainability and

minimize the urban development trade-offs

1.2.2 Specific objective

1 To map and measure land use and land cover change (LULCC),

land surface temperature and intensity of UHI intensity in the city

within the study period using remote sensing and GIS

2 To determine the correlation of UHI intensity, population growth

and economic growth with urban expansion

3 To have knowledge about the related urban policies and

strategies in Muntinlupa city

1.3 Research questions and hypotheses

1.4.1 Research questions

To certainly achieve the main goal and the specific objectives of the study,

the research questions are: (1) What are the proportion of each classified landcover

throughout the study period? (2) What relationship does population growth and

city development have over time? (3) What effect does city expansion have in

economic development? (4) What are the dynamics of surface urban heat island

intensity over the study period? (5) What are the existing policies in the city to

confront such urban impacts?

1.4.2 Hypotheses

Null hypotheses:

1 The intensity of UHI remain stable as urban land development

increases

2 Rate of urban land expansion and population growth has no

correlation with each other

3 Urban development in Muntinlupa city has no significant

relationship with its economic growth

Alternative Hypotheses:

1 Urban Development influences the variability of UHI intensity

2 Rate of land development causes the decrease of human population

growth in the city

3 Urban Development in Muntinlupa city has a significant relationship

with the city income

1.4 Scope and limitation

1.3.1 Location

Muntinlupa city is located in the southernmost part of the national capital

region (NCR) (14° 23' 25" N, 121° 02' 51" E), bounded with Taguig City on the

north, Parañaque City on the northwest, San Pedro, Laguna on the south, city of

Bacoor on the southwest, Las Piñas City on the west, and Laguna de Bay on the

east In the early years, it was just district and boundaries of adjacent places, such

as Rizal and Laguna province Under the Presidential Decree No 824 in 1975

proclaimed by former President Ferdinand E Marcos, Muntinlupa was included in

the fourth district of Metropolitan Manila Moreover, in 1995, through House Bill

No 1440 issued in the house of representatives and Republic Act 7926 signed by

Fidel V Ramos, conversion of the municipality of Muntinlupa into a highly

urbanized city was proclaimed The city is composed of two districts, the first district has four villages or “barangay” which are Bayanan, Poblacion, Putatan, and Tunasan While the second district is represented by Barangay Sucat, Buli,

Cupang, Alabang, and Ayala Alabang (City of Muntinlupa, 2018)

Since the National Bilibid Prison is sited in the city, where the most

dangerous criminals in the Philippines are imprisoned it was covered with negative

image Nonetheless, the city proved this title wrong, the city was recently known

as the “Emerald City of the Philippines” given by the Department of Tourism The most rapid and has a tremendous urban growth among the villages in the city is Alabang During 1980’s, it was once had a large scales of cow pasture, and now turned into a supercity that houses new residential, business, industrial and

commercial establishments The biggest and famous real estate here is namely as

Filinvest Corporate City and Ayala Land's Madrigal Business Park Also, some of

the most leading shopping malls and other business buildings such as Alabang

town center, Festival Supermall, Insular Life Buildings, Northgate Business

District, and the Asian Hospital and Medical Center are all located in the city

center While each barangay in the city has its own notable housing subdivisions

(Department of Tourism, 2014; City of Muntinlupa, 2018)

Figure 1: The Location of Muntinlupa City and its corresponding districts and barangays

(Source: Shapfile from PhilGIS)

1.3.2 Time of data collection:

The research collected the past records of the data, specifically in years

1996, 2003, 2010, and 2017 These years have 7 years interval with each other to

clearly determine the changes of the variables

1.3.3 Limitations

With the use of satellite data, statistical data and other constructive

information, the study was able to achieve certain aims However, several

limitations were inevitably confronted Since the availability of cloud free spatial

data in USGS is limited, fewer samples were just collected It is also the reason

why the study was not able to use the latest image from the latest satellite and the

acquisition date of the collected data have quite time gaps The official shapefile

of the city which has the exact area measure was not able to acquire, which is why

the presented land cover measure are just written in percent Since the historical

data were used it was hard to find the location of more specified land cover and

the classification of Land use maps were restricted into 4 land cover types only

Also, this is the reason why ground truth validation in field was not obtained

Surface UHI were just analyzed regardless of atmospheric UHI, due to lack of

previous atmospheric temperature data Availability of government data restricted

the study to consider other factors that influence population dynamics and

economic growth (such as migration rate, birth rate, death rate, age/sex

distribution, employment rate, household income, gross share of each sector etc.)

Lack of time and area proximity limited the study to obtain other causes and effects

of UHI in the city environment (in water, people and biodiversity) Moreover, due

aforementioned limitation, household surveillance which can support or oppose

the secondary data were not able to perform

1.5 Definition of terms

The following definition will serve as clarification and supplementary

apprehension for the terms used in the study

Land use – refers with the human intervened patterns of change from natural

landscapes to agricultural, educational, recreational, residential, and industrial

areas

Land cover- defines the biological and physical features of the earth’s surface,

which includes water, vegetative land, bare soil and man-made structures/

landscapes

Population growth- it refers with the increase/decrease of the population in a

specific place or country Mainly reflected by the number of migrations, deaths

and births

Economic growth- it is the market value from goods and services of a particular

city or country over time It is conventionally measured as the percent rate of

increase in real gross domestic product, or real GDP

Geographic Information System (GIS)- a geographical framework that analyzes

the spatial location and coordinates information from satellite images It enables

researcher to gather more intuitive data patterns, relationship and situation

Remote Sensing- Remote sensing is the process of detecting and monitoring the

physical characteristics of an area It is done by measuring its reflected and emitted

radiation at a distance from the targeted area Special cameras collect images which

can help researchers "sense" things about the Earth

Landsat- satellite machines which were first release in 1972 with the purpose of

gathering data from the earth’s surface These satellite images carry sensors that can catch and record the light energy from the sun reflected off the earth

Income inequality- unequal distribution of income to the individual or household

members which does not reflect the high income presented by the whole

community

NDVI- a measurement that quantifies the amount if vegetation in the area of

interest through finding the difference between the reflected (NIR band) and

received light (red band) by the vegetation

Land Surface Temperature (LST) - accounts for the relative surface temperature

of a particular area It is measured by the obtained Top of Atmospheric brightness

from the spectral radiance receive by the satellites, that are also dependent on the

albedo, vegetative areas and soil moisture

Kappa coefficient- used frequently when finding the correlation between the same test or sample done by different approaches

Urban Heat Island (UHI)- defines the phenomenon which the surface and

atmospheric temperature in developed areas are higher than the nearby rural areas

due to certain anthropogenic activities

Emissivity- defined as the proportion radiated energy from a surface to that

emitted by a blackbody at the same temperature, wavelength and same viewing

conditions

Spectral radiance- spectral flux measured by remote sensing instruments per unit

area and per unit of solid angle, perpendicular to the surface of the sensor

Supervised Classification- is a manual classification of an image, the analyst

should select training area samples in each land cover that are desired to classify,

and then apply these to the entire image

Maximum Likelihood - a probability weighting method that considers the

variances and covariances of assigning pixels according to the sample cells

represented by signature file

PART II: REVIEW RELATED LITERATURE

2.1 Land use and land cover change

Land cover and land use are two associative terms which seem to be the

same in definition, but these two are totally different Land cover includes water,

vegetative land, bare soil and artificial structure or the physical and biophysical appearance of the earth’s surface (Ellis, 2007) Since determining and mapping land cover provides information and baseline monitoring, these have been a

fundamental instrument in global monitoring studies, resource management and

planning activities (Natural Resource Canada 2015) On the other hand, land use

refers to the human intervened activities mainly for socio-economic purposes and

management placed on the surface of a land area Such examples of land use are

agricultural, recreational, industrial, educational and residential areas Major

purposes of land use change are for socio-economic goals To increase the

economic growth and improve lifestyle, like urbanization which has been widely

implemented globally Such land use transformation can either stimulate increase

or destabilize the ecosystem’s processes in sustaining food production,

maintaining freshwater and forest resources, ameliorating infectious diseases, also

in regulating climate and air quality (Asadi et al., 2010, Niyogi et al 2009, Foley

et al 2005)

When land cover and land use are linked together, it will serve as

information in functional and biophysical aspect of landscapes (Duhamel et al.,

1998) In a more explanatory way, incorporated land use and land cover refers to

the classification of human activities and natural elements on the landscape within

a specific time frame based on established scientific and statistical methods of

analysis with appropriate source materials These two yields the affluence in terms

of beneficial information for many applications (European Communities, 2001)

such as improving conservation and strategies for managing communities

Consequently, many studies subjected that land use and land cover change

results several kinds of pessimistic events In biodiversity, according to Suoza et

al (2015), global and regional biodiversity loss has been influenced by the

anthropogenic practices Generally, habitat change due to LULCC had the highest

impact to biodiversity loss over the past 50 years, and was expected to likely

increase in the future (MEA, 2005) For instance, when forested areas were

converted for agricultural or industrial purposes, the habitat and lifestyle of various

species pre-inhabiting the place will alter The response of these species will either

adapt with the new environment or most probably be demised (Chauhan, 2014;

Wong & Candolin, 2015) Moreover, terrestrial biodiversity loss can also lead the

destruction to other biotic and abiotic components in an ecosystem Vegetative

areas and the atmosphere have a crucial mutual role in the environment In the

study of Wu et al (2017), impacts of LULCC on climate and ecosystem

productivity over Amazon in South America was examined The study imposed

that LULC certainly affects the climatic condition of the basin Due to local

warming within the area involve in land use change biogeochemical circulation,

particularly the hydrological cycle was intensified Also, the study concluded that

ongoing deforestation around the suburbs could influence the virgin forest by the

changes of meso-scale circulation patterns of the atmospheric and vegetative

factors.

2.2 LULC application and approaches

Land use and land cover change detection has been extensively used around

the world, especially in monitoring the environment (Han et al., 2015; Erdogan et

al., 2015) This can be applied in observing the dynamics of artificial surfaces,

agricultural areas, forest, water bodies and many others (Caetano, 2009) In

Katsina, Nigeria, Abbas et al (2010) specified that the urban sprawl resulted

continues characterization of peri-urban landscape Likewise, Sreenivasulu and

Bhaskar upheld the statement of Abbas et al., the explanation of changes in land

use can be due to urban agglomeration, the loss of agricultural land, changes in

river regimes and the effects of unstable cultivation Moreover, Hua (2017) stated

that contamination with different kinds of bacteria in Malacca River was

discovered through the statistical analysis between LULC and water quality data

The study pointed out the residential activities, industrial activities, sewage

treatment plant and animal husbandry as urban and suburban that influence the

distribution and population of bacteria and pollutants in the River Thus, the study

proclaimed that useful information in identifying pollution sources and water

quality with LULC change detection provides references to the policy makers

Subsequently in the Philippines, LULC applications are also being

practiced in many research studies, three of them are from Abino et al (2015),

Brebante et al (2017), and Estoque and Murayama (2011) With the integration of

LULC, Abino et al (2015) utilized time series change detection and identification

of transition trends in Marikina and Laguna de Bay watershed From 1999 to 2006,

substantial variations occurred in the sub-watershed as indicated by the increase of

agricultural and orchard areas at the expense of brushland areas While other land

cover types are almost unchanged such as water bodies, built-up, forest, and

grassland remain almost unchanged It was also found out that the level of

sub-sub-watershed level in Tanay had the most and transition and minimal change in

Tayabasan Generally, the study supplies not just knowledge about the landscape

dynamics of the sub-watersheds And it also promotes an awareness and ideas for

the formulation of appropriate mitigation measures and strategies toward the

sustainable management of the sub-watershed Likewise, Brebante et al (2017)

studied the influences of LULC change to run-off generation and flashflood were

evaluated particularly in the Marikina River Basin (MBR) The results showed that

upper catchment and lower floodplains of MBR are affected by the change of

landscape The analysis between the vegetative cover and run- off generation in

upstream area was presented, and insignificant effect was found out during

convective or extreme events On the other hand, urbanization in the downstream

area affects the flood extent, volume and duration Furthermore, the study also

exposed that the increase of rainfall intensity reduces the impact on vegetative land

cover to food characteristics On the other hand, Estoque and Murayama (2011)

explored the application of LULC in a landscape transition in a mountainous urban

area, in Baguio city The study exposed the major physical landscapes

transformation in the past 21 years Majority of land were transformed into

built-up area The findings facilitated the identification of how each spatial factor is

associated with the variability of annual built-up area expansion rate ABUAER in

the city Moreover, it was found out that hill became more urbanized through the

years because of higher demands for the tourist services, facilities and economic

opportunities In general, this study discovered the trend in the physical landscape

transformation of a sub-tropical hill station, and presents insights that could be

used in planning for the future development of Baguio city towards sustainable

urbanization

Nowadays, remote sensing or satellite images and digital processing

methods are the primary and common sources to collect data for monitoring earth

surface (Serneels et al., 2007) Since 1970’s when the first satellite (Landsat) designed to collect data on Earth’s Surface in USA (USA: Earth Resources Technology Satellite, ERTS-1) Remote sensing community have invested much

effort in advancing techniques for detection of LULC Technical capabilities of the

sensor, potentialities of the satellites and image processing algorithms have been

continually evolving for the observation of the Earth (Martinez and Malicone,

2012) The program had launched seven satellite images and six of them have

succeeded, which can provide four types of images The earlier imagery is called

Multispectral Scanner (MSS) (from Landsat 1-3), next to this is the Thematic

Mapper (TM) (from Landsat 4 & 5), and then Enhanced Thematic Mappers

(ETM+) (Landsat 7), and the latest image is Observation Land Images (OLI) (from

Landsat 8) (Zhu et al., 2016)

There are two types of classification method that can be applied to construct

a land cover map, these are supervised and unsupervised classification (Enderle &

Weih, 2005) Unsupervised classification is a basic method where the software in

the computer is involve in collecting the colors of the pixels to form clusters and

classify the image itself (Tou & Gonzalez, 1974) In contrast, Supervised

Classification is a manual classification of an image, the analyst should select

training area samples in each intended land cover to classify, and then apply these

to the entire image through statistical analysts (Richard, 2013) Both of these

methods include statistical classifiers such as widely use and convenient maximum

likelihood, ISO cluster classifiers which are found in several GIS packages, and

more complicated classifiers that requires knowledge specialization and several

software to implement (Calvert et al., 2015)

In the past years, accuracy assessment in image classification was not being

prioritized in studies Yet, due to augmented probabilities of error in digital

imagery, it has become a vital step in processing remotely sensed data (Congalton,

1991; Rwanga and Ndambuki, 2017) Assessment uses reference data that are

assumed to be true Google earth that are free to the public are a good source of

imagery including satellite images and air photos can be a source to utilized

reference data as well as ground verification using Global Position System (GPS)

in the field (Tilahun and Tiferie, 2015) To overcome error due to poor reference

data, one thing to consider is to use the same classification as the map (USDA,

2017) Thus, in time series data, ground verification in field and google earth are

not applicable in the past years Data sources that are drawn in spatially-explicit

manner and captured the past landscapes of a region or historical maps, such as

topographic, cadastral, and military maps, can alternatively be applied (Liu et al.,

2018) While in some studies, same data can be used to put ground control points,

which can then be validated through the insights of elderly citizens in the study

area Subsequently, in collecting ground control points, sampling methods can be

simple random, stratified random, systematic, and systematic not-aligned sampling

(USDA, 2017) Dicks and Lo (1990), stated that higher confidence in accuracy

assessment comes with larger the sample size Moreover, Hay (1979) suggested to

have minimum of 50 ground control sample points in each class of interest

Additionally, the most accuracy components that are used in numerous land

classification studies are from the error matrix or confusion matrix method

(Rwanga & Ndambuki, 2017) This approach applies four accuracy indices, these are the overall accuracy, producer’s accuracy, user’s accuracy, and Cohen Kappa-coefficient (Congalton, 1991; Campbell, 2007; Jensen, 2005) Certainly, the value

of each index should be high to determine if the classification is categorically

reliable and accurate

2.3 Urban population growth

The world currently carries 7.6 billion people, by 2050 it was expected to

reach 9.8 billion, approximately every year the population will increase at 83

million people Hence, it will continue to follow the trend even if the fertility rate

will be assumed to decline (UNDESA, 2017) The population growth in every community are basically controlled by “natural factors” or the outcome of the difference between birth over death and “migration factors” or the resettlement of individual or group to a new community (Bhatta B., 2010) The current data of

fertility rate is 18.89% (WBO, 2016b), death rate is 7.65% in 2016 (WBO, 2016b),

while migration rate is 3.4 % in 2017 (UNDESA, 2017) Rapid urban growth has

a significant influence in countries population, which is evidently demonstrated in

China and India (Colmer J., 2014; Yang X.J., 2013) According to world

population prospects (UNDESA: revision of 2017) of UNDESA, these two

countries remain most populous countries in the world, with the total inhabitants

of 1.4 billion (in China) and 1.3 billion (in India) Evidently in China, Verdini et

al (2016) found out the emerging rural migrants are searching for affordable

housing option near urban centers, which were believed to cater the demand of

middle-class standard of life Consequently, due to diversification of lifestyle and

provisions of incentives for better education, jobs with higher income than farming

or mining jobs in rural, high migration from rural to urban ensues, and eventually

urban population growth upsurges (McCAtty , 2004; Arzaghi and Rupasingha.,

2013)

However, UNFPA (2015) stated that urbanization offering both challenges

and opportunities effects for social, economic, and environmental development

Nsiah-Gyabaah (2003) detailed and state that future global health, food security,

global warming and environmental change are the significant implications of rapid

urbanization and population growth

Furthermore, Moore M et al (2003) pointed out that unplanned and rapid

urbanization withdrawing the alluring statement that cities can offer better standard

of life The study indicated that the range of health hazards and risks are intensified

by urban crowded population Since it is associated with substandard housing or

slums with poor sanitation, and pollution Likewise, Agarwal et al (2007) defined

urban slums as a place with crowded population, unclean surrounding with no

basic facilities for disposal, water supply and sanitation The study also stated that

condition in slums have more hostile influence on health status on the residents

than the rest of the urban inhabitants Subsequently, according to Chaterjee (2002),

slums account 5-6 percent in urban population annually and considered as the

fastest growing sectors Likewise, Kabaria et al., (2017) presented that

urbanization and population density have current and predicted high risk in malaria

infection It stated that densely populated urban areas across Africa shows risk of

infection That even though malaria generally had a decrease as population

increase, the infection is still evident in urban area Additionally, since the

population in Africa is expected to be almost 2 billion after 35 years, the study

suggested that improvement in managing population density and urbanization is

vital to degrade the malaria risk in Africa

Furthermore, mounting population comes with increasing food and

resources demand also (Simmons, 2016), but the question is can urbanization

provide enough food for the emerging population? Cities in developed countries

can afford the demand, like London, 80% food supply are taken through exports

from other countries (IEW-EB, 2002) Moreover, Satterthwaite et al., 2010 pointed

out the food security issues in low to middle income nations which accounts 75 %

of world population The study revealed that agriculture confronts the pressure of

higher demand from growing population Since, another challenge in agriculture

is climate change, this suggested to practice not just proper management for urban

population growth but also to build resilience in agriculture from climate change

impacts Similarly, in water demand, according to UNICEF and WHO (2008)

urban population are persistently being deprived in accessing water supply ranges

from 4-8 % in most sub-regions, except East and North-East Asia In Bangladesh,

Indonesia, Myanmar, and Nepal, urban population with access to drinking water

decline during 1990-2008 at 2-12 % Consequently, the report implicated that both

national and local government should provide efforts that will maintain the access

of water or provide alternative for the emerging urban population

On the other hand, in terms of environmental risks that are being led by

population growth Satterwaite (2009) states that the driver of greenhouse gases

(GHG) emissions is not merely the quantity of people in urban The study asserted

that the emissions are due to the quantity and level of consumption and activities

of the people Since it was found out that nations with low emission per person has

the highest urban population growth rate Thus, developed countries are the major contributor of GHG’s, but emerging urban population in developing countries are more vulnerable than them (EPA, 2017) due to lack of resources However, in other aspects of environmental problems particularly intensity of water pollution

and flooding are evidently affected by increasing population growth in urban areas

Proper sewerages and proper solid waste management are often absent in slums,

which is why all waste are being discharged in water bodies or along the roads and

drainage, in which subsequently cause flood when it rains (Kinobe, 2015)

Additionally, huge discharged of urban wastewater and drainage into urban basin

can to high biochemical oxygen demand (BOD), total coliform (TC) and low

dissolve oxygen (DO) as it is presented by Liyanage et al (2017) from the rivers

of South Asian countries

Therefore, all the above-mentioned effects perhaps affiliate with the

statement of Kelley and Schmidt (1995) which testifies that population growth has

negative on economic development Furthermore, with that, if rapid population

sprawl will continue to happen in many cities most especially in developing

countries The goal of having a better community with high living standard will

not be attained

2.4 Population growth in the Philippines

In 1970 almost 36.7 million population are inhabiting in the Philippines It

was almost tripled in year 2010 with 92.3 million in habitants (PSA,2010) The

current policies addressing the population growth are still in the viewpoint of

Philippine constitution of 1987 This openly acknowledges that spouses have the

right to decide on how many offspring will they produce, based on their various

religions, beliefs and demands as a responsible parenthood (Osias et al., 2010)

Before, under the presidency of Ferdinand Marcos in the 1970’s, the National Population Program was launched and established the Commission on

Population (POPCOM) The program aimed to reduce the fertility rate and study

population problems in the country On the other hand, in 1990 instead of reducing

fertility rate Aquino administration as well as Ramos administration concentrated

on family planning as a family health program (Senate, 2009) Moreover, under

the presidency of Joseph Estrada, reducing fertility rate was again the focus of

population program This is held by the means of introducing alternative

demographic situations and various contraceptive methods However, the followed

administration, affirms reducing fertility with the foretold ways were not

encouraged due to the conflict with the standpoint of Catholic Church (Herrin,

2002) Instead, responsible way of family planning was fostered such as informed

choice in family size, respect for life, and birth spacing (Balesteros, 2010)

The controversial population issues in the Philippines has been about the

policies and programs In December 2012, the congress sanctioned the RH Bill or

the Responsible Parenthood and Reproductive Health Act of 2012 (Republic Act

No 10354) However, due to various conflicts in the constitutionality of law and

religious beliefs, the supreme court overdue the enactment in March 2013 (Lopez

and Alvarez, 2013) The main focus of RH bill is to protect the health of the family

which will also affect the population fertility and growth It guarantees use of

universal access to reproductive health services and provisions of contraceptives,

educations for health and sexuality, prenatal care, and maternal care (Senate,

2009) As suggested by studies, two offspring are advisable to replace the parents

in the future and address the association of poverty and household size (Virola and

Martinez, 2007) Consequently, the bill suggests families to have two children, but

as it is written in section 20, all rights are given if couple desires to conform or not

(Congress, 2012)

The existence of increasing urban population is also significant in the

Philippines According to Philippine Statistical Authority in year 2010 the

population growth in the whole country reflected to the number of urban

populations Form comprising 11.7(31.80%) in 1970 to 41.9 (45.3%) in 2010

During the period between 1990 and 2000, the growth population in urban in the

whole country is 2.5% while rural has 1.5% The cities which are considered to

have the largest service sector Metropolitan Manila underwrites the 37% of GDP

and 12% of employment (as of 2009) in the Philippines The expected share of

urban activities in the city in 2035 will increase by 92% of the GDP and 88% of

total employment (Yap, 2010) Consequently, due to this perceived growth pattern,

it was found out that internal migration/urban migration was mostly significant in

the Metro-Manila In which contributed 60% (by 2000) of the region’s population

(PIDS and Cabegin, 2010)

Unfortunately, not all migrants were able to achieve higher income in

Metro-Manila Many poor people which are probably urban migrants suffer in low

income and high unemployment, due to educational filtration of workers in most

of the companies in the cities Workers with less educational background confront

considerably inferior labor market predictions The incidents eventually influence

the high risk of poverty When a survey of 3000 informal settler families in metro

manila was conducted, it was indeed evident that most of them have low level of

education tend to have limiting job opportunities Consequently, many urban poor

are engaged in self-entrepreneurship with low income (WBO, 2017)

2.5 Urban economic growth and related studies

Since the era of industrial revolution, there are three series of component

that have been shaping the society, and these are industrialization, globalization,

and urbanization (Chen et al., 2014) Urbanization has been perceived its

spectacular positive influence to the economic growth in recent and future years

There is no developed or middle-class country has ever accomplished high income

without developing land for advance industrialization, towering buildings which

are the center of businesses and other private and government services, since 70%

of global Gross Domestic Product (GDP) are contributed by the urbanization

(Marmara and Usman, 2015) That is why majority of developing countries are in

the stage of shifting agricultural production to industrial production (Xia et al.,

2013)

The productive units of agricultural production can be placed in

domiciliary Thus, the economic growth is scattered along the center and sides of

the countries On the other hand, industrialization involves enterprises In order to

attain enormous production, it requires high costs for investments for the shifting

of more advance technologies, constructing buildings, and other industrial firms

that should be concentrated in urban areas (Xia et al., 2013) Urbanization certainly

offers a lot of job opportunities, better health care, education, and lifestyle

However, unplanned urban agglomeration may result additional uneven handed

circulation of welfare and capital (Moore et al., 2003) Downie et al., (2009)

notified that some developing countries, aimed to boost their economic growth

through exploitation of natural resources Through building industrial

infrastructure, focusing on private wealth and often neglecting the importance of

proper urban management which eventually resulted significant environmental

problems Which will later on be a debt for the whole community, and eventually

cause poverty

Consequently, urban economic studies are employed by many scholars

concerning the dynamics of Gross domestic product, and poverty in urban Using

the time series analysis from 1986-2013, Marmara et al (2015) attempted to

investigate urbanization and economic growth of China This study used Engels

and Granger test which authorized the stationary and co-integration of the data

which also confirmed a bilateral causality between urbanization and economic

growth occurs Also, by employing ordinary least square method they found out

that there is a significant and positive relationship between the variables

Moreover, Lin and Song (2002), based on the statistics of 1991-1998 period

in 189 cities in a country this paper analyzed the affiliation between GDP growth

per capita and asset, investment from foreign, growth of employment, expenditure

of the government, and city establishment Through manipulation of

cross-sectional analysis, some of the factors were discovered a positive relationship to

the growth of GDP per capita, foreign direct investments, developed roads and

outflow of the government on science and technology However, the measured

government size by total investment appeared to have negative relationship with

the GDP per capita The results were opposing the economic literature, and

claimed that the total share of assets in GDP is not relevant to the growth of GDP

per capita Furthermore, the convergence of GDP per capita among the cities had

no vibrant evidences

On the other hand, using some certain theoretical model of econometric data

analysis, Martinez-Vasquez et al (2009) uncovered a U-shaped relationship of

urbanization and poverty Likewise, Arouri et al (2014) discovered an inverted

U-shaped relationship between urbanization on human capital and per capita GDP of

countries using the dynamic panel data regression Urban impacts to enrollment

rates and health variables fostered the greater and faster growth of human capital

Overall, the study suggested the government to revised the existing policies to

foster human capital Particularly, training and education for urban decision

makers; location management and subsidies, development of secondary towns,

data for urbanization management, and management of the informal economy are

the suggested factors to be considered by the policy makers

2.6 Economic growth in the Philippines

The Philippines was known to be an agricultural country before, since 47%

of the countries land area is vegetated areas (DLSU-Manila 2002) During 1960’s

the contribution of agricultural sector to the country’s GDP is 27% and increased

at 6% in early 1970’s On the other hand, when late president Ferdinand E Marcos started vast industrialization and building more infrastructures in late 1970’s, the

share of industries to country’s GDP increased from 32% to 39% Consequently,

the concern of Philippine economy in agriculture relatively changed compared to

other neighboring countries The increase of agricultural share to GDP stopped in late 1970’s, since the labor force decreased from 63 % to 57% of employment rate Subsequently, the share continued to decline in 1980’s from covering 52% to 26%

of GDP In addition, 54 % share of food for exportation in 1960’s declined to 34

% in the early 1980’s In contrast, the shares that were contributed by manufacturing products increased from 6% to 23 % during the same period

(Baliscan et al., 2000) The decrease of economic growth was slowly been

congruent with the agricultural production At the starting point of vast

industrialization which was financed in large part by foreign country, the

Philippine economy grew at high annual average rate of 6.4 % However, the

external debt emerged at $ 24.4 billion in 1983 from $2.3 billion initial debt in 1970’s (Hays, 2013) Corruption of President Marcos was the alleged reason why this immense increase of debt occurred When Marcos was replaced by Aquino in

1986, the administration revived the economy by reaching 6.7% in 1988 However,

it was not able to maintain due to trade and government budget deficit

Additionally, natural disasters worsened these economic difficulties and the

growth declined at 3% (Hays, 2013) In 1997, the stock market declined at 32 %,

likewise conversion of dollar level off at 30% at the end of the year Through the

income sent by Filipino workers abroad, bad loans never got high and stabilize the

currency (Nations Encyclopedia, 2018) The economic growth in the Philippines

was able picked up again in years 2000’s under the administration of Benigno

Aquino III The expected economic growth of the Philippines surpassed at 5% to

6 % Moreover, in year 2012, after China the Philippines was ranked as the second

to the highest economic growth rate in the world (Hays J., 2013) This increase

was triggered by $3.3 billion budget provided for building infrastructure in

2011 Moreover, it increased to $17.3 billion in 2016 which made the GDP growth from 1.8 percent to 5 percent Infrastructure project implemented faster through the participation of private sectors under Public-private-partnership (PPP) program in financing, designing, constructing, operating and maintaining the projects (PPP, 2015)

2.7 Urban heat island (UHI)

Urban heat island defines the phenomenon which the surface and

atmospheric temperature in developed areas are higher than the nearby rural areas

(Oke, 1987; EPA, 2018) There are certain reasons why UHI occurs in a city One

is when houses, roads, commercial and industrial building are compacted together

in a particular place the composition of these infrastructure insulates the solar

energy from the sun Hence, the effect of insulation makes both the surface and

atmosphere warmer In addition, exhaling carbon dioxide of a dense human

population and their activities such as burning fossil fuel for transportation and

energy consumption, also contribute to this heating occurrence (Memon et al.,

2008; Sailor and Lu, 2004)

During nighttime, the intensity of UHI remain high since the absorbed heat

of the concrete grounds during daylight are being released to the cold sky (National

Geographic, 2006) Series of studies supported this statement while the others

opposed In Brussels City of Belgium, Van Weverberg et al (2008) exposed that

among all seasons summer under clear skies with calm conditions has stronger heat

island effect Likewise, at the same season in Phoenix City, Arizona, Brazel et al

(2000) found out that daytime has less temperature with negative degrees Celsius

butduring nighttime the temperature ranges from 3 to 8 degrees Celsius However,

in Seoul, Korea, Kim and Baik et al (2005) conveyed that the intensity UHI is

higher during nighttime to early morning than daytime It was supported by

Gedzlman et al (2002) who exposed that the maximum heat island effect occurred

in the mid-night under clear condition in New York Furthermore, in London there