Study on the role of uban forest types toward iar temperature reduction : a case study in Bogor City-West Java

STUDY ON THE ROLE OF URBAN FOREST TYPES

TOWARD AIR TEMPERATURE REDUCTION

(A

Case

Study

in

BOGOR

City

-

West

Java)

ETTY MARLMA

GRADUATE SCHOOL

Study

on

the Role

of

Urban Forest Types

Toward Air Temperature Reduction

(A Case Study in Bogor City

-

West Java)

ETTY MARLINA

This Thesis submitted for the degree of Master of Science of Bogor Agricultural University

MASTER OF SCIENCE IN INFORMATION TECHNOLOGY

FOR NATURAL RESOURCES MANAGEMENT

GRADUATE SCHOOL

BOGOR AGRICULTURAL

UNIVERSITY

STATEMENT

Etty

Marlina, here by stated that thesis entitled:

Study on the Role of Urban Forest Types toward Air Temperature Reduction (A Case Study in Bogor City - West Java)

Are result of my own work during the period of January until August 2007 and that it has not been published before. The content of this thesis has been

examined by advising committee and the external examiner

Bogor, August 2007

ABSTRACT

ETTY MARLINA (2007). Study on the Role of Urban Forest Types toward

Air Temperature Reduction (Case Study: in Bogor City - West Java). Under the

supervision of I Nengah Surati Jaya and Antonius Bambang Wijanarto.

Nowadays, quality of urban environment is challenging problem. Urban

development indicated by the increase of population as well as development in all

aspects, it is not only give positive impacts but also negative impacts and ultimately, it can impact the degradation of environment quality. This fact is indicated by environment problems in urban area, for instance: air pollution which

reduces oxygen supply and overwhelms production of Carbon dioxide (COz), also

air temperature rising.

From the foregoing problems, "back to natureee concept is needed to solve

environment problem in urban area. Urban forest was introduced to recover

environment and ecological condition. Yet, one of constraints in urban forest

development is limitation of space for urban forest. Therefore, alternative solution

can

be employed by increasing the effectiveness of existing

urban

forest in

controlling quality of urban environment. This research is intended to analyze the effectiveness of urban forest types based on its structures and forms toward urban temperature reduction.

The methods used in this research consist of selecting location of field

measurement over GIs analysis using "digitizing on screen technique", air

temperature measurement was conducted during 13 hours and twice repetitions,

and data analysis over statistic analysis comprising of analysis of effectiveness urban forest types based upon time of measurement and analysis of effectiveness of urban forest types based upon distance of measurement. Research area was in Bogor area, having high concentration of air pollution.

In this study, there were five urban forest types chosen for temperature

measurement, namely: 1) Urban Forest having linear form with second structure,

2) Urban Forest having linear form with multi structure, 3) Urban Forest having

dispersed form with second structure, 4) Urban Forest having clustered form with

second structure, 5) and Urban Forest having clustered form with multi structure.

Based upon both time of measurement and distance of measurement, the result of this research shows that urban forest having dispersed form and second structure is most effective toward air temperature reduction. The study shows the rank of importance of urban forest is as follows: urban forest having dispersed form with

second structure @S), urban forest having linear form with second structure ( L S ) ,

urban forest having linear form with multi structure (LM), urban forest having

clustered form with multi structure (CM), and urban forest having clustered form

Research Title Study on the Role of Urban Forest Types toward Air

Temperature Reduction (A Case Study in Bogor City,

West Java)

Name : Etty Marlina

Student ID : G.051050051

Study Program : Master of Science in Information Technology for Natural

Resources Management

Approved by,

Advisory Board

Dr. h t o n i u s ~a#bang Wiianarto Co- Supervisor

Endorsed by,

Program Coordinator

- - p p

i

Dr. Ir. Tania June

' - . , ...?.- .-:..

- ..-..w

Date of Examination:

August, 21" 2007

Date of Graduation:

ACKNOWLEDGEMENT

There are many people I should thank in regard to this work and no doubt I

will not be able to name them one by one. I would like to give my grateful to the

Mercy Allah SWT, because of His blessing and kindness I could accomplish this

thesis, and I also wish to thank to my parents for their support and pray through

all month of my research

I would like to thank to my supervisor Dr. I Nengah Surati Jaya and my Co-

Supervisor Dr. Antonius Bambang Wijanarto for their guidance, technical

comments, and constructive criticism through all month of my research.

I would like to thank to my external examiner of this thesis Dr. Muhammad

Buce Saleh and MIT Program Coordinator for their positive inputs and ideas. I

would like to thank to all lecturers who taught me the very important knowledge

for my future.

I would like to thank to all MIT staffs for their patience and support our

administration, technical and facility, and I would like to thank to all my friends, I

really appreciate our togetherness and I also would like to thank to my air

temperature surveyor (Wenwen, Mbak Candra, Mas Muklis, Mas Panji, Mas

Toto, Indah, Delon, Hapsari, Ima, Aang and Apip) who measured air temperature

during 13 hours.

Finally, I feel deeply gratehl to my best supporter, Fakhrizal nashr, for his

CURICULUM

VITAE

Etty Marlina was born

in

Palembang, South Sumatera,

Indonesia at March 1 9 ' ~ 1983. She received her Diploma 3

fiom Bogor Agricultural University in 2003 in the field of

Forest Protection, Faculty of Forestry. From 2003-2004, she

continued her bachelor degree in Winayamukti University,

Bandung-West Java, in the field of Forest Management, Faculty of Forestry.

In the year of 2005, Etty Marliia continued her graduate study in international

program of Bogor Agricultural University. She received her Master of Science in

Information Technology for Natural Resources in 2007 respectively. Her thesis

was on " Study on The Role of Urban Forest Types toward Air Temperature

TABLE OF CONTENTS

Table of

Contents

...

i

List of Tables

...

iv

List of Figures

...

v

List of Appendices

...

vi

...

I

.

INTRODUCTION

1

1

.

1 Background

...

1

.

.

1.2 Problem Defmaion

...

4

1.3 Objectives

...

4

1.4 outputs

...

4

1.5 Research Assumption

...

5

...

1.6 Research Framework 5

11

.

LITERATURE

REVIEW

...

7

2.1 Temperature

...

7

2.2 Urban Forest

...

9

...

2.2.1 Definition of Urban Forest and Urban Forestry 9 2.2.2 Types and forms of Urban Forest

...

I0 2.2.3 Benefits o f Urban Forest

...

12

...

2.2.4 Challenges in urban forestry development 16 2.3 Remote Sensing (RS)

...

18

2.5 Role and Importance of Geography Information System (GIS) and

...

Remote Sensing (RS) in Urban Forest Development and Plannimg 19

I11

.

METHODOLOGY

...

21

3.1 T i e and Location

...

21

...

3.2 Equipment and Data Requirement 23

...

3.2.1 Data Collection 23

...

3.2.2 Equipment Used 23

...

3.3 Selecting Location of Field Measurement 23

...

3.3.1 Geometric Correction 23

...

3.3.2 Image Classification 24

3.4 Temperature Measurement

...

34

...

3.5 Data Analysis 40

3.5.1 Effectiveness of Urban Forest Types toward

Aii

Temperature

...

Based upon Time of Measurement 40

3.5.2 Effectiveness of Urban Forest Types toward Air Temperature

Based upon Distance of Measurement

...

41

IV

.

RESULT

AND DISCUSSION

...

32

4.1 Field Data Analysis

...

44

4.1.1 Effectiveness of Urban Forest Types toward Aim Temperature

Based upon Time of Measurement

...

45

4.1.2 Effectiveness of Urban Forest Types toward Air Temperature

Based upon Distance of Measurement

... 51

REFERENCES

...

...

63

LIST OF

TABLES

Tables Pages

2.1 IKONOS Satellite System: Sensor Characteristics

...

18

3.1 Number of population in Bogor City based on gender

...

21

3.2 Number of vehicle in Bogor City

...

21

...

3.3 List of Equipment used 23 3.4 Ground Control Points for Geometric Correction

...

24

3.5 Combmation of urban forest structures and forms

...

28

3.6 Combmation of urban forest types and residential area

...

28

3.7 Number of possible location for air temperature measurement

...

30

3.8 Distance between each point in each urban forest type

...

35

3.9 List of Equation Used for Homogeneity Test

...

43

4.1 Ai temperature average in each urban forest type

...

4

4.2 Number oftrees and vegetation species in each urban forest type

...

45

4.3 Air temperature changing (At) toward time changing in each urban forest type

...

45

4.4 Temperature reduction in each urban forest based on time of measurement.48

...

4.5 Polynomial regression model of each urban forest type 50 4.6 Significant value of each pair of urban forest type

... 54

4.7 Pairs of urban forest types which having equal role

...

56

4.8 Pairs of urban Forest Types which have equal role and effectiveness

...

56

LIST

OF FIGURES

Figures Pages

1.1 Average Global Temperature by Decade

...

2

...

1.2 Research kamework 6 2.1 Tempature decreases and humidity increases downward though Forest canopy

...

8

2.2 Structure of GIs

...

19

...

3.1 The Research Area 22

...

3.2 U r h Forest Structure 26

...

3.3 Urban Forest Forms 27

...

3.4 Possible location for temperature measurement 29

...

3.5 Linear form and second structure 30 3.6 Linear form and multi structure

...

31

3.7 Dispersed form and second structure

...

31

...

3.8 Clustered form and second structure 32 3.9 Clustered form and multi structure

...

32

3.10 Flowchart of Research

...

33

3.1 1 General Design of Temperature Measurement

...

34

3.12 Design of Temperature Measurement in urban forest LS

...

35

3.13 Design of Temperature Measurement in urban forest LM

...

36

3.14 Design of Temperature Measurement in urban forest DS

...

37

3.16 Design of Temperature Measurement in urban forest CM

...

39 4.1 Graphic of Temperature average in each urban forest type

...

46

4.2 Graphic of Temperature changing trend toward time changing in each

...

urban forest type 49

...

4.3 Air temperature changing in each urban forest type based upon distance 5 1

4.17 Regression model in each urban forest type

...

53 4.18 Analysis of Slope and Elevation Regression Model in Each Pair of Urban

Forest Type

...

58

LIST OF APPENDICES

Appendices Pages

1 List of species of vegetation in each urban forest type

...

67

2 Polynomial regression analysis in each urban forest type

...

68

3 Tukey test of air temperature based upon distance in each urban forest

type

...

76

...

4 Raw data of temperature measurement 81

I.

INTRODUCTION

1.1. Background

Urban area is center of population which facilitates development of social,

culture, and economic (Irwan, 2005). Urban development

is

indicated by the

increase of population

as

well as development in all aspects, for instance office

and industry area, super and hyper market, medical and education facilities, also

road network. These facilities are provided to support people activities.

In the other hand, urban developments also give negative impacts and

ultimately, it can impact the degradation of environment quality. Urban

environments only progress economically but decline ecologically, whereas

ecology stability in urban area as important as economy stability (Dahlan, 1992).

This fact is indicated by environment problems in urban area, for instance:

air

pollution which reduces oxygen supply and overwhelms production of Carbon

dioxide (COz), also air temperature rising.

Air temperahre in urban area is hotter than its surrounding area and it is

called

"urban

heat-island" effect. There is a direct link between urban heat islands

and global warming. First,

the

greenhouse effect could aggravate rising

urban

temperature significantly. Second, heat islands may contribute to the greenhouse

effect. According to Herlianto (2007) starting fkom 1960 to 1969, the average

global temperature was 13.9OC and in the period of 2000-2004, it is about 14.6OC

and it

is

projected to raise 1.4--5.g°C by 2100 (see Figure 1.1). Prinanto, eta1

(1991) in Jaelani (2006) states that Indonesia is the biggest producer of Carbon

will increase five times bigger than COz emission in 1986, i.e. it will reach 469

million ton In Indonesia, symptoms of global warming have been seen, i.e. the

last decade, Indonesia has experienced long dry spells which were occurred in

1982-1983,1987, and 1991, and this T i e r gave negative impacts to people.

Average Globsl Temperaurn by Deia.de. lS804oO4

I

I

Year

I

Figure 1.1 Average Global Temperntore by Decade. Source: Brown (2002)

Meanwhile, Bogor as buffer zone for Jakarta tends to have high

concentration of air pollution (Lestari 2005). It is indicated h m rapidly growth

of vehicles and population. Total vehicles in 2003 were 66.541 and it increased

twice bigger than total vehicle in 2000 (Polresta Kota Bogor, 2004), then number

of population in 2005 reached 855.085 and it increased 1.2 times bigger than

population in 2000 (BPS, 2006). In line with the growth of population, landcover

change fiom naturally vegetated area to build up area also increased rapidly, and

several types of landcover change tending to increase temperature significantly

are: residential, industry, and bare land (Tursilowati, 2005).

From the foregoing problems, "back to nature" concept is needed to solve

environment problem in urban area. Urban forest was introduced to recover

environment and ecological condition, for instance: temperature reduction and

compounds and tree maintenance emissions, energy effects on buildings reduce

air pollution) (Nowak, 2000).

Urban forest research in Bogor city has been conducted by Lestari (2005).

She assessed minimum size of urban forest based on oxygen need. Based on this

research, minimum size of urban forest to fulfill oxygen need in 2003 was

51397.706 ha while existing urban forest in 2003 was only 4,214.39 ha, then

minimum size of urban forest to fulfill oxygen need in 2020 will be 571,191

ha,

and it will be even larger than total large of Bogor City (only 11,850 ha).

Research conducted by Lestari (2005) shows that the constraint in urban

forest development is l i i a t i o n of space for urban forest. Moreover many

conflicting interests relate with land and expensiveness of land value in urban

area. Therefore, alternative solution can be employed by increasing the

effectiveness of existing urban forest in controlling quality of urban environment.

Urban forest development needs good planning and management in order

optimal f u n d i n and role of urban forest can be achieved. Accurate and efficient

information will be very helpful for urban forest development, and Remote

Sensing technology is precise tool which can give accurate and efficient

information over large area (Jaelani, 2006). In this research, high resolution image

is used to classify urban forest type (structure and form) and residential area.

Meanwhile, geography information system (GIs) offers facilities to manage

spatial data, starting &om input data, store and manage data, analyze and

manipulate, until produce the expect output. Therefore, in this study GIs is

1.2. Problem Definition

Common problems faced in urban forest development, include: the

limitations of space for urban forest, many conflict of interests related with

landuse, and the expensiveness of land price

in urban

area. Moreover, urban

forests are frequently suffered fiom land conversion causing urban forest space

decrease than ever. To solve the l i i a t i o n of urban forest space, alternative

solution should be employed. The solution is the optimize function and role of

existing urban forest, by analyzing relationship between urban forest structures

(second-storey and multi-storey) and

urban

forest forms (linear, clustered, and

dispersed) in reducing negative effects liom urban activities.

From the foregoing problem, it is important to make problem definition on

how the difference of urban fotest types (structure and form) can give different

effectiveness toward air temperatwe reduction.

1.3. Objective

The objective of this research is to find out the effectiveness of several

urban forest types based on their structures and forms toward urban temperature

reduction

1.4. Output

Output of this research is information regarding the effectiveness of urban

1.5. Research Assumption

The assumption of this research is heat sources in the study area are

assumed as homogeneous.

1.6. Research Framework

Research framework can be seen in Figure 1.2. Urban area as centre for

multiple functions such as: entertainment, economic, industry and governmental

activities, city offers opportunities, dream and enjoyment. Therefore, many people

put their dream and come to urban area to set their better life, so this phenomenon

stimulates population break out in urban area.

In l i e with the growth of population, infrastructures and facilities

development also increase rapidly for example: buildings, public facilities,

business area, office, settlements, factories, and road network. During 1994-2001,

landcover change fiom vegetated area into residential in Bogor was 11.3% and

deforestation was 32.73% (Tursilowati, 2005). This facts impact environment

problems in urban area, for instance:

air

pollution which reduces oxygen supply

and overwhelms production of Carbon dioxide (COz), also air temperature rising.

Facing this problem, urban forest was introduced to m i n i 6 environment

problem because of negative effects of urban activities. Yet, several constraints

are also faced, for instance: limitation of available land for urban forest and

conversion greenery space into other need. Optimizing function of urban forest is

one of effort to overcome the constraints and research is needed to analyze

function of combination of urban forest structure and form in order, alternative of

term of temperature reduction in residential area.

7

InGastruoture and facilities:

1. Industryarsa Ctty as center for multiple function:

2. Residential area

1. EEamomy

Ned 3. Recreation area 2. Industry

4. Road networkand

3. Governance

traosportation facilities

4. Entertainment

5. Business h i l i t i e s 6. Offices

z

3,

5'

Wtyo f human life:

-

1. PoUution (water, air, noise) C 2. Tempnahln in- (climate obangc)

3. Less natural vegetated s p " &lion

Urbpn forest development

1

C o ~ t s :

Limitation of space land for urbao forest

Conversion existing urban f o m t into other need

1

Optimizing function ofurban forest

I

1

Research:

Anrlydngrdatim Ma. u h f m d shuEhlre rmd llrbm forest form

in mbddzhg newlive cffccb h ubu, xtivi6es

11.

LITERATURE

REVIEW

2.1. Temperature

Temperature is a degree of hotness or coldness the can be measured using a

thermometer (Weatherkidz, 2007), and actually thermometer is not only one of

devices used to measure temperature, termohigrograf is also other device that can

be used to measured it. Temperature is measured in degrees on the Fahrenheit,

Celsius, Reamur and Kelvin scales. Based on four temperature degrees can be

derived conversion formula (Manan, et.al, 1986):

1. tT = [ (t - 32) x 419

1%

= [ (t

-

32) x 519 I0C = [ (t

-

32) x 519

+

273

1%

2. tOR=[(t+32)x9l4]OR=5/4t0C=[(5I4t)+273]9(

3. t°C = [ (915 t)

+

32 ] O F = 415 t O R = ( t

+

273 ) 9(

4. t " K = [ 9 / 5 ( t - 2 7 3 ) + 3 2 ] ° F = 4 / 5 ( t - 2 7 3 ) 0 R = ( t - 2 7 3 ) 9 (

Temperature measurement is primary data needed in this study; therefore

several aspects should be noticed, namely: 1). Influence of direct sun radiation, 2).

Rainfall, 3) Blown of wind, 4) Influence of Earth's radiation. To solve this

problem, weather cage is used and inside this device, temperature measurement is

placed (Manan, et.al, 1986).

Related to temperature issue, almost every city in the world today is hotter

-

usually between 1 to 4OC hotter - than its surroundiig area. This difference

between urban and rural temperatures is called the "urban-heat-island" effect",

and it has been intensifying throughout this century. During hot months a heat

People also believe there is a direct link between global warming and urban

heat islands. First, the greenhouse effect could aggravate rising urban temperature

significantly. Second, heat islands may contribute to the greenhouse effect. Those

effects can be reduced by planting trees, for instance: pilot project was conducted

a retail shopping centre parking lot containing shaded and unshaded portions was

located in Davis, California, a community approximately 120 km (75 mi)

northeast of San Francisco, located in California's Central Valley. This research

was

performed to measure the diierence in parking lot microclimate resulting

kom

the

presence or absence of shade tree. cover in Davis, CA., a very modest

level of shading resulted in an air temperature reduction of approximately 1 to 2O

C (1.8 -3.6OF), compared to an unshaded lot (McPherson, et.al., 2002).

Moreover, Grey and Deneke (1986) state in a forest situation on a calm

day, temperature decreases and relative humidii increases downward through the

canopy profile (See Figure 2.1)

2.2. Urban Forest

2.2.1. Definition of Urban Forest and Urban Forestry

Urban forest and urban forestry has profound different in term of definition.

There are several literatures which have mentioned about definition of urban

forest and urban forestry.

1. Urban forest

Fakuara (1987) states urban forest is plants or vegetations in urban area

giving several environmental benefds such as: protection, esthetical, recreation

and other benefits,

and

Miller (1988) defines urban forest as the

sum

of all woody

and associated vegetation in and around dense human settlements, ranging fiom

communities in rural setting to metropolitan regions. Nowak (1994) refers urban

forest as complex ecosystems created by the interaction of anthropogenic and

natural processes, while Sekjen Kehutanan (2002) states urban forest is the unity

of ecosystem as large land contains natural resources dominated by trees and other

elements that integrated each other around urban area.

2. Urban forestry

Several literatures have cited definition of urban foreshy, they are:

Jorgensen (1965) in Gerhold & Frank (2002), Deneke (1993) in Tree Canada

Foundation (2004), Konijnendij, et.al, (2005), Wikipedii (2007).

Jorgensen (1965) in Gerhold & Frank (2002) define urban forestry as a

specialized branch of forestry (that) has as its objective the cultivation and

management of trees for their present and potential contributions to the

physiological, sociological, and economic well-being of urban.

in Tree Canada Foundation (2004), he states urban forestry as the sustained

planning, planting, protection, maintenance, and care of trees, forests, green space

and related resources in

and

around cities and communities for economic,

environmental, social, and public health benefits for people. The definition

includes retaining trees and forest cover

as

urban populations expand into

surrounding rural areas and restoring critical parts of the urban environment after

construction. In addition, urban and community forestry includes the development

of citizen involvement and support for investments in long-term on-going tree

planting, protection, and care.

Meanwhile, Konijnendij, et.al, (2005) refers urban forestry is generally

defined as the art, science

and

technology of managing trees and forest resources

in and around urban community ecosystem for the physiological, sociological,

economic, and aesthetic benefits trees provide society, and the famous odme

dictionruy, W i p e d i a (2007) defines urban forest as a collection of trees that

grow within a city, town or a suburb. In a wider sense it may include any kind of

woody plant vegetation growing in and around human settlements. In a narrower

sense it describes areas whose ecosystem are inherited kom wilderness leftovers

or remnants.

2.2.2. Types and forms of Urban Forest

Dahlan (1992) and Sekjen Kehutanan (2002) refer six types of urban forest,

they are: urban forest for residential area, industry area, biodiversity conservation,

recreation and tourism, recreation, and safety.

Residential area prefers park resembles trees combined with shrubs and

owned and maintained by a local government. Trees are chosen for their beauty

and to provide shade, grass is typically kept short to discourage insect pests, allow

for the enjoyment of picnics and beautifid landscape make dwellers find most

retaxing. Generally, it is used for sport, relaxing, playing, and recreation etc.

Available industry area is one of wban area characteristic; industry

produces particles, aerosols, gas and liquid bothering human healthy. Moreover,

those wastes produce noise and smell pollution causing discomfort condition.

Several trees are able to absorb pollutants, therefore

urban

forest development in

industry area should consider about types of tree having high capability in

absorbing pollutants.

Botanical garden and zoo are types of wban forest for biodiversity

consewation There are two main objectives, namely: Biodiversity collection area

and H a b i t , in particular for endanger animaL

Nowadays, dwellers require places for relaxing; refreshing their mind and

body, and

urban

forest offers those benefits. Meanwhile, certain wban area having

steep slope or around coastal area need wban forest help protect erosion,

landslide, seashore abrasion, and sea intrusion

While adding to environmental aesthetics, trees, and shrubs may be used to

aid traffic control. This includes not only vehicular traffic but also pedestrian,

trees can serve as a buffer between moving vehicle and pedestrians.

Irwan (1994) in Irwan (2005) grouped several forms of wban forest:

a. Clustered: wban forest with green community clustered in certain area,

minimal trees are 100 trees and each tree is close each other, which is

b. Dispersed: urban forest which does not have certain pattern, green community

disperses in small group of vegetation

c. Lined / strip: this form includes trees and shrubs in street side and trees in

riparian areas.

Invan (1994) in Irwan (2005) also grouped urban forest structure which will

be used in this research:

a. Second-storey urban forest: vegetation community in urban forest only

composed by trees and grasses or other coverage.

b. Multi-storey urban forest: vegetation community in urban forest composed by

trees, grasses, bushes, and other vegetation covering ground.

2.23.

Benefits of Urban Forest

Benefits of urban forest have been mentioned in several literatures, for

example: Grey and Deneke (1986) and Mills (2005). Grey and Deneke (1986)

state that urban forest is important to the city dweller in many ways. Its trees

provide shade, beauty, and long list of other benefds. The various benefits are

grouped under the following four broad categories:

1. Climate amelioration

The major elements that affect us are solar radiation, air temperature, air

movement, and humidity.

Temperature modz~cation Human comfort essentially depends on the

factors that effect s k i temperature and the perception of heat and cold. The

optimum core temperature for human body is 98.6"F (37°C).

Wind protection and air movement. Air movement, or wind, also affects

on the presence or absence of urban vegetation

Precipitation and humidity. Trees intercept and filter solar radiation, inhibit

wind flow, transpire water, and reduce evaporation of soil moisture. Thus, beneath

a forest canopy, humidity is usually higher and evaporation rates are lower.

Temperature beneath the canopy is also lower

than

surrounding air during the day

and warmer during the evening.

2. Engineering uses

Erosion control and watershed protection Plants reduce water-caused soil

erosion by intercepting rainfall, by holding soil with their roots, and by increasing

water absorption through the incorporating of organic matter. In addition, plants

are more attractive

than

mechanical water erosion control devices.

Wastewater management. Wastewater treatment as a water use because it is

so interconnected with the other uses of water. Much of the water is used by

homes, industries, and businesses must be treated before it is released back to the

environment Nature has an amazing ability to cope with small amounts of water

wastes and pollution, but it would be overwhelmed if people didn't treat the

billions of gallons of wastewater and sewage produced every day before releasing

it back to the environment. Treatment plants reduce pollutants in wastewater to a

level nature can handle.

Noise abatement. Plant can mask unwanted sounds; it makes their own

sounds, for example: the rustle of oak leaves, or the quaking of aspens. These are

pleasant sounds that tend to make us less aware of more offensive noises. In

addition, plants support animals and birds that may make desirable sounds.

pollutants through absorption, particulates air pollutants can be reduced by the

presence of trees and other plants in several ways. They aid in the removal of

airborne particulates such as sand, dust, fly

ash,

and smoke. Leaves, branches,

stem, and their associated surface structures tend to trap particles that are later

washed off by precipitation

3. Architectural uses

Each species has its own characteristic kom, color, texture, and size. Plants

can vary in their use potential as they grow or as the season change. Their proper

use will vary with the designer and user. Trees, when used in group, can form

canopies or walls of varying texture, height, and density. Trees are alive

and

growing (they are dynamic) with regard to their functionality in architectural

design Trees make an area more attractive by providiig privacy, enhancing

building designs, acting as a barrier to unpleasant sounds and sights and reducing

glare.

4. Aesthetic uses

Trees and shrubs provide their own inherent beauty in all settings. They are

aesthetic elements in our surroundings. They can be beautiful simply because of

the lines, f o m , colors, and texture they project. They also provide unique

patterns through reflection fiom glass and water surfaces and can produce

beautihl shadow patterns.

While, Mills (2005) refers benefit of urban forestry into seven main

categories, they are:

(1) Water protection: Trees reduce topsoil erosion, prevent harmful land

storm water run-o& and ensure that our groundwater supplies are

continually being replenished. For every 5% of tree cover added to a

community, storm water runoff is reduced by approximately 2% (Coder,

1996).

(2) Energy conservation: The United States Forest Service estimates well-

positioned trees can save 20-25% of the annual energy use for a

conventional house when compared to a house in a wide-open area

(3) Air wllutants reduction: Keep Indianapolis Beautiful (2007) compiles five

important functions of tree in reducing air pollution, they are: first, trees

help to clean the air by "catching" airborne pollutants such as ozone,

nitrogen oxides, sulphur dioxides, carbon monoxide, carbon dioxide, and

small particulates less than 10 microns in size. Second, planting trees

remains one of the cheapest, most effective means of drawing excess C02

from the atmosphere. Third, there is up to a 60% reduction in street level

particulates with trees. Fourth, one tree that shades your home in the city

will also save fossil h e l cutting C02 build up as much as 15 forest trees,

and

fifth,

each year an average acre of mature trees absorb up to 26 pounds

of carbon dioxide from the air, which is equal to the amount of Co2

produced by driving a car 26,000 miles.

(4) Im~roving Economic Sustainability: Apartments and offices in wooded

areas rent more quickly and have higher occupancy rates. Trees enhance

community economic stability by attracting businesses and tourists. People

linger and shop longer along tree-lined streets.

housing development, women who lived in apartment buildings with trees

and greenery immediately outside reported committing fewer aggressive

and

violent acts against their partners in the preceding year than those living in

barren but otherwise identical buildings. In addition, the women in greener

surroundings reported using a smaller range of aggressive tactics during

their lifetime against their partner. And, in this study, even small amounts of

greenery-+ few trees and a patch of grass-helped inner city residents have

safer, less violent domestic environments. Greenery lowers crime through

several mechanisms. First, greenery helps people to relax and renew,

reducing aggression. Second, green spaces bring people together outdoors,

increasing surveillance and discouraging criminals. Relatedly, the green and

groomed appearance of an apartment building is a cue to criminals that

owners and residents care about a property and watch over it and each other.

(Kuo and Sullivan, 2001).

(6) Aesthetics enhancement: Trees make an area more attractive by providing

privacy, enhancing building designs, acting as a barrier to unpleasant sounds

and sights and reducing glare.

2.2.4. Challenges in urban forestry development

Kuchelmeister (1998) states threats which impede the creation and

sustaining of the urban forest in developing countries include:

1. Valuation: the monetary value of urban forest is not easy to estimate, and very

little hard data is available for cities in developing countries. The challenge is

to make a sound social cost-benefit analysis to see whether an urban forestry

and intangible) are include.

2. Institutional challenges: deficiencies in coordination between national,

provincial and local level lack of well-organized local groups to work with or

the lack of strong administrative or managerial and technical skill among

existing groups are some of the major institutional challenges.

3. Local participation: Preference and willingness, especially of the poor, to

invest and manage urban green space has not been sufficiently approached,

documented and communicated.

4. Ecological constraints: urban growing conditions differ greatly fiom rural

ones. Urban forestry related technology transfer in developing countries is

slow, and many practices are only suitable for wealthier cities.

5. Legislation, tenure and custom: Insecure or unclear ownership andor rights to

the use of urban forests can impede any involvement of the poor. Insufficient

or inflexible tree ordinances tend to discourage participation of low-income

citizens in urban forestry.

6. Financial sustainability. The facts that f h d s are required for regular

maintenance and protection of urban forests is often overlooked, for this

reason much urban forest management is more like crisis management.

7. Integrating urban forestry into urban planning. Urban forestry is part of the

city's green fiastructure. The challenge to city planners is (i) to anticipate

the direction and magnitude of the growth, (ii) to secure resources for the

establishment and maintainiig of green areas to serve local communities; (iii)

to evaluate the problems and uses of green areas so they can provide the

2.3. Remote Sensing (RS)

IKONOS was the first commercial high resolution satellite to be placed

into orbit in space, and it is often used for natural resources inventory @akker,

et.al, 2000). IKONOS satellite imagery provides access to any location on the

Earth's surface and its applications include both urban and rural mapping of

natural resources and of natural disasters, tax mapping, agriculture and forestry

analysis, mining, engineering, construction, and change detection (SIC, 2007),

and in this study, IKONOS image is used to classify urban forest

type

(structure

and form) and residential area.

Spatial resolutions of IKONOS consist of 1 m (panchromatic) and 4 m

(multispectml), more detail about spatial resolution of IKONOS can be seen in

Table 2.1

I

~ o r c e ~ a s e , California, USA

-

Orbit

1

98.1 degree, sun synchronous

Table 2.1 IKONOS Satellite System: Sensor Characteristics

Altitude

1

681 kilometers

Resolution at Nadir

1

0.82 meters mchromatic: 3.2 meters

System IKONOS

I

Band 4: (Near-IR) 0.76 - 0.90

Source: Satellite Imaging Corporation (2007) with modification)

Launch Date

1

24 September 1999 at Vandenberg Air

Resolution 26O Off-Nadir

Revisit Time

Spectral Bands (pm)

multispectral

1.0 meter panchromatic; 4.0 meters multispectral

Approximately 3 days at 40° latitude Pancromatic: 0.45 - 0.90

Multispectral:

Band 1: Blue 0.45 - 0.52 Band 2: Green 0.52 - 0.60

2.4. Geographical Information System (GIs)

GIs is defined as a computerized system that hcilitates the phase of data

entry, data analysis, and data presentation especially in cases when we are d e a l i i

with geo-referenced data (de By, 2000). Related to this meaning, this system has

four main capabilities to handle geographic reference data, they are: data entry,

data management, data manipulate and analyze, and data output (Aeronoff, 1989).

Structure of GIs is described in Figure 2.2.

Figure 2.2 Structure of GIs (Malczweski, 1999).

GIs Data Storage

and Management

I

I

I

The process fiom data input become output is

a

connecting structure that is

started ftom real world and recorded on image and airborne photo, then by GIs

facility, data are stored and processed to generate output that will be used for

decision making in the real world. In this study, GIs facility is used to analyze

possible location for temperature measurement and present temperature trend

spatially.

Data Input Data _{and Analysis} Manipulation

2.5. Role and Importance of Geography Information System (GIs) and

Remote Sensing (RS) in Urban Forest Development and Planning

Urban forest development is much related to spatial condition. Therefore, Data Output

User Interface

the effective, efficient and accurate spatial information provided by GIs and RS

are highly required. Several study and research had used GIs and

RS

to derive,

store, manage and analyze spatial information

Kali, (2006), used satellite image (Landsat

ETM

2002) and GIs to identify

the potency and spatial distribution of urban forest development. In her study, she

classified Landsat ETM image in to several classes based on vegetation type as

oxygen supplier. While GIs capabilities are used to develop database

management and spatially analyze the supply of oxygen and production of C02.

Jaelani, (2006), has used IKONOS and geography information system (GIs)

to determine urban forest in North Jakarta and Centre Jakarta Integrating of GIs

capabilities, IKONOS image and other secondary data will provide worthwhile

information about large and distribution of existing urban forest and potential area

for urban forest.

Meanwhile, Giting (2006), developed environment spatial database based

on GIs capabilities, satellite image, field data, secondary data, and developed

111.

METHODS

3.1. Time and Location

This research was conducted fiom January until August 2007 in Bogor -

West Java. The study area is located in Bogor City - West Java, Indonesia,

approximately between 6' 30' 30" and 6' 41' 00" South Latitude and 106" 43'

30" and 106' 51' 00" East Longitude (Figure 3.1). In Bogor city, number of

population tends to increase every year. Bogor population reached 855,085 at the

end of 2005, and it increased almost 1.2 times bigger than 2001 (Table 3.1).

Meanwhile, number of vehicle also increased especially number of motorcycle.

Total vehicles in 2003 were 66.541 and it increased twice bigger than total vehicle

in 2000 (Table 3.2).

Table 3.1 Number of population in Bogor City based on gender

1 3 ) Motorcycle

1

23.783

1

28.979

1

37.255

1

50.589

1

(Source: Polresta Kota Bogor (2004))

Table 3.2 Number of vehicle in Bogor City

Year 2001 2002 2003 2004 2005 No 1 2

(Source: Badan Pusat Statistik Kota Bogor (2006)) Male 382,896 397,820 419,252 424,819 431,861 Female 377,433 391,603 401,455 406,751 423,223 Total Population 760,329 789,423 820,707 831,571 855,085 Vehicle types Private car Public car

Total vehicle per year

3.2. Equipment and Data

3.2.1. Data Collection

The types of data that was used for

this

research are:

a.

Primary

data

1. IKONOS 2003.

2. Temperature data derived fiom field measurement.

b. Secondary data used to accomplish this research is Bogor administrative

3.2.2. Equipment

Used

The following equipment was used for ground measurement in

this

study.

Global Positioning System (GPS)

1

Determine Position

Table 3.3List of Equipment used

Name of Equipment

I

I

measurement

I

Function

I

3.3. Selecting Location of Field Measurement

Study on the role of urban forest in term of temperature reduction in

residential area was analyzed using geography information system

(GIs).

Figure

3.10 depicts the conceptual flow of research approach completely.

3.3.1. Geometric Correction

Bogor administrative map was used for geometric correction as referencing.

A polynomial rectification with linear order was selected and applied using 10

references points 1 Ground Control Points (GCP's). The number of GCP's was

used 10 points which is spread out over study area.

The accuracy of each point is shown in Table 3.4. This can be seen in the

resulting average and sum of the RMS errors, average of RMS in this study is

0.23 and total of RMS is 2.3 1. The smaller RMS value indicated that the accuracy

of geometric correction is better. RMS error is standard statistical measure that

attempts to describe the difference between the actual point location and

mathematically estimated point location In general term the KMS error should be

less than 1. This means that the average error in X and Y is less than 1 image cell

Table 3.4 Ground Control Poinb for Geometric Correction

3.3.2. Image Classification

The first step before selecting location of field measurement was digitizing

IKONOS image to produce thematic map. The digitizing process was conducted

by using "digitizing on screen" technique. There were three types of thematic

layer, which produced namely:

1. Urban forest structure

Urban forest structure is vegetation community composing urban forest.

This was classified into two classes, namely:

composed by trees and grasses or other coverage.

b. Multi-structure urban forest: vegetation community in urban forest composed

by trees, grasses, bushes, and other vegetation covering ground.

Based on urban forest structures, there are 139 urban forests classified into

two classes, namely: 40 urban forests are multi s t r u c m and 99 urban forests are

second structures (Figure 3.2)

2. Urban forest form

There are three type of urban forest form (Irwan (1994) in Irwan (2005)):

a. Clustered: urban forest with green community clustered in certain area,

minimal trees are 100 trees and each

tree is

close each other, which are

unarranged.

h. Dispersed: urban forest which does not have

certain

pattern, green community

disperses in small group of vegetation.

c. Linear / strip: this form includes trees and shrubs in street side, trees in

riparian areas.

Based on this classification, there are 139 urban forests classified in this

study, they are: 25 urban forests are clustered forms, 54 urban forests are

dispersed forms, and 60 urban forests are limed forms (Figure 3.3)

3. Residential area

This thematic layer was used to determine urban forest types which are next

to residential area. Urban forest types should be around 50-70 meter ftom

P€

City Boundtry --

SUbdiklrid muni

Created B r EUy Marlina

URBAN FOREST FORMS

: PUE

Legend:

Subdistrict

---- strest

Created By EUy Marlins

After getting classification of urban forest structures, urban forest forms and

residential area, the next step was join attribute between urban forest structures

map and urban forest forms map to obtain six combinations of urban forest types.

Table 3.5. describes six combinations of urban forest

structures

and forms.

Table 3.5 Combination of urban forest structures and forms

Note:

Structures

Second-storey (S) Multi-storey (M)

LS = Linear form with second-structure

LM = Linear form with multi-structure

CS = Clustered form with second-structure

CM = Clustered form with multi-structure

DS = Dispersed form with second-structure

DM = Dispersed form with multi-structure

Thereafter, map of urban forest type was overlaid with residential area thus Forms

six types of urban forest next to residential area was derived. These combinations

were used to determine possible location for air temperature measurement. Dispersed (D) DS DM Lined (L) LS LM Clustered (C) CS CM Note:

LSR = Linear form with second-structure next to residential area

LMR = Linear form with multi-structure next to residential area

CSR = Clustered form with second-structure next to residential area

CMR = Clustered form with multi-structure next to residential area

DSR = Dispersed form with second-structure next to residential area

DMR = Dispersed form with multi-structure next to residential area

Table 3.6 Combination of urban forest types and residential area

Urban Forest Types

Figure 3.4 Possible locations for temperature measurement.

Figure 3.4 provides urban forest types based on their forms and structures,

were six combinations of urban forest types next to residential area and these

combmations show in Table 3.7.

Table 3.7 Number of Possible Lwation for Air Temperature Measurement

I

No

I

Urban Forest Types

I

Number of possible

I

Number of observation

I

From previous analysis, there were 93 possible locations for temperature

measurement and only one location of each urban forest types are chosen for

temperature measurement.

In this study, there were five urban forest types chosen for temperature

measurement because one urban forest type (Dispersed form with multi structure)

was eliminated because it was difficult to be measured.

1. Linear Second: Location of this type is in Tangkuban Prahu Street and this

area is arranged residential (Figure 3.5), temperature measurement was done

in three points and detail design of temperature measurement is described in

Figure 3.12.

Figure 3.5 Linear form and Second structure

2. Linear Multi: location of this type is in Ceremai street and this area is also

arranged residential (Figure 3.6), temperature measurement was done in three

points and detail design of temperature measurement is described in Figure

Figure 3.6 Linear form and Multi structure Y = 9271621.975 m, X = 698985.1180 m

3. Dispersed Second: location of this type is in Kencana Garden located in Bogor

Tengah (Figure 3.7), functions of this urban forest are as relaxing place and

increase aesthetic value of city. It is also next to arranged residential. In this

location, temperature measurement was also done in three points and detail

design of temperature measurement is described in Figure 3.14.

Figure 3.7 Dispersed form, Second structure

Y = 9271333.554 m, X = 699224.0800 m.

4. Clustered Second: location of this urban forest type is experiment garden in

Jabaru I1 street Ciomas. This location is next to arranged residential and

unarranged residential (Figure 3.8), temperature measurement was also done

in three points and detail design of temperature measurement is described in

Figure 3.15.

Figure 3.8 Clustered form and Second structure

Y = 9269553.888 m, X = 697105.2690 m.

5. Clustered Multi: location of this type is in Gunung Batu (Figure 3.9), this

urban forest is collection garden of Forestry Research and Development

Center in Bogor. In this study, temperature measurement was done in three

points and detail design of temperature measurement is describe in Figure

3.16.

Join Attribute

Statistic Analysis

L-.-.--.---...---:

3.4. Temperature Measurement

To know mle of urban forest structure and form on air temperature

reduction, the measurement of air temperature was done at five types of urban

forest next to residential area

Observation of urban forest role toward temperature reduction was done

by measuring temperature per hour, which was done during thirteen hours,

starting from 8.00

AM

to 8.00 PM.

Three points, which were located at approximately straight line, and it was

taken in each urban forest

type,

namely: The first point, located inside urban

forest (PI), the second point is at urban forest's edge (P2), and the third point was

located outside urban forest (P3). Those points were measured at the same time

with twice repetitions in each urban forest

type.

During temperature measurement,

geographical coordinate positions of each point were recorded all once using GPS.

General design of temperature measurement is described in Figure 3.1 1, and

detailed designs of each urban forest

type

are respectively described in Figure

3.12 to F i e 3.16.

Jrban forest

Figure 3.11 General design of temperature measurement.

While, the distance between each point in each urban forest type is described in

Figure 3.12 Design of Temperature Measurement in Linear form and Second structure. Located in Tangkuban Prahu Street Bogor-Tengah (without scale).

Table 3.8Distance between each point in each urban forest type

P1 (inside urban forest) X= 699277.2830, Y= 9271671.797 P2 (urban forest's edge) X= 699267.2572, Y= 9271651.925 P3 (outside urban forest) X= 699263.8554, Y= 9271628.71 1

Urban Forest Types

LM

LS DS

CM

CS

Distance between PI-P2

12 15 55 50 30

Distance between P2-P3

30 30 45 100

Figure 3.13 Design of temperature measurement in Linear form and Multi structure. Located in Ceremai Street Bogor-Tengah (without scale).

P1 (inside urban forest) X= 698997.3118, Y= 9271629.673

P2 (urban forest's edge) X= 698985.1 180, Y= 9271621.975

Figure 3.14 Design of temperature measurement in Dispersed form and Second structure. Located in Taman Kencana (without scale).

P1 (inside urban forest) X= 699224.0800, Y= 9271333.554

P2 (urban forest's edge) X= 699227.5936, Y= 9271387.735

Figure 3.15 Design of temperature measurement in Clustered form and Second structure. Located in Jabaru I1 street, Ciomas (without scale).

P1 (inside urban forest) X= 697105.2690, Y= 9269553.888

P2 (urban forest's edge) X= 697066.6800, Y= 9269587.206

Figure 3.16 Design of temperature measurement in Clustered form and Multi structure. Located in collection garden of Forestry Research and Development

Center in Bogor, Gunung Batu - Bogor (without scale).

P 1 (inside urban forest) X= 697044.2499, Y= 9270427.836

P2 (urban forest's edge) X= 697070.521 1, Y= 9270661.105

3.5. Data Analysis

3.5.1.Effectiveness of Urban Forest Types toward Air Temperature

Reduction Based upon Time of Measurement

Tukey Test

Tukey's method considers all possible painvise diierences of means at the

same time. The Tukey method applies simultaneously to the set of all pairwise

comparisons. To compute t for each pair of me& using the formula:

Where: Mi

-

Mj

is the diierence between the i

and

j means, MSE is the

Mean Square Error, and n is the harmonic mean of the sample sizes of groups i

and j.

Trend Analysis

Trend analysis was done to analyze and predict the change of temperature

toward the change of time measurement and also analyze how these changes

influenced by urban forest are. Temperature trend toward the change of time in

three points measurement (PI, P2, and P3) was derived ftom polynomial (non-

linear) regression and time of measurement is independent variable (XI).

Exponential regression provides in model (2).

Note:

Y = Dependent Variable (Temperature)

3.5.2.Effectiveness of Urban Forest Types toward Air Temperature Reduction Based upon Distance

Sim~le Reeression

Simple regression analysis was chosen to analyze the relationship between

dependent variable

gr)

and one independent variable

0.

While, dependent

variable in this research is Temperature (OC) and independent variable is distance

of temperature measurement (m).

The simple regression equation takes the following form.

Note:

Y= Temperature

XI= Distance of Measurement

Bo= Actual Constant, where the regression line intercepts the Y axis. BI= the regression coefficient of eight independent variables.

F test for comprehensive significance

Model (3) was useful if value of B1 is not zero, and analysis of variance is

used to test the significance of the variation in the dependent variable that can be

attributed to the regression of one or more independent variables. Its significance

can be tested with the F test fiom calculations performed in an Analysis of

Variance table. Using the Analysis of Variance (ANOVA) procedure, the

regression is tested by determining the calculated F statistic:

SS (Reg) 1 2

...

F =

SS (Res) 1 (n-3) (4)

Note:

SS (Reg) = Sum of Square for Regression

SS (Res) = Sum of Square for Residual

In this test, the relationship was deemed significant (receive HI) if the

Hypothesis:

HO=

(variable X does not have contribution toward variable Y)

H1=

(variable

X

has contribution toward variable Y)

Paired-t Test

To test whether there are significant mean different between two

urban

forest types, paired-t test was employed to derive this information. The test

statistic is calculated as:

d bar

...

(5)

t = d s z / n

Note:

d k = the mean diierence sZ = the sample variance

n = the sample size

t = Student t quantile with n-1 degrees of fieedom

Homo~eneity Test of Regression

Homogeneity test of regression is used to test homogeneity of slope and

elevation of regression The hypothesis used to test both slope and elevation are:

1) HO= pol= po2

H1= pol$ pol

2) HO = pll= $12

H1= p l l # p12

To test homogeneity of slope, F-test was employed by using this equation:

F-value = MS of Residual (Coef Reg) I MS of within

While, to test homogeneity of elevation, F-test was also employed by using

this equation:

In this test, the relationship was deemed significant (receive HI) if the

calculated F value is greater than the F-table (F value > F-table).

Several equations are used to derive F-value are provide in Table 3.9.

Regression

1

Regression

1

Deviation of Regression

Table 3.9 List of Equation Used for Homogeneity Test Some of Square (SS) Deviation of

I

Total

I

yi(tota1) - {qtotal)

*

mxi(total)}

I

SS(total) I df (total) -1

Mean of Square (MS)

Common

Within Residual (Coef

Reg)

(Adjust Means)

1

SS(tota1) - SS(wmmon)

1

(common) -1))

zyi(common) - @(common)

*

Cyixi(wmmon)}

z

m a

SS(common)- SS(within)

I I

SS(common) I (df (common) -1)

SS (Within) l Z(ni-m) SS (sisa) 1 {(df (common) -I) - (ni-

IV. RESULT AND DISCUSSION

4.1. Field Data Analysis

In this study, air temperature is chosen as parameter because air temperature

is one of weather element which can directly impact human lie. The results of

temperature average in five urban forest types, namely: linear form with second

structure (LS), linear form with multi structure

(LM),

dispersed form with second

structure @S), clustered form with second structure (CS), and clustered form with

multi structure (CM)) are provided in Table 4.1. This table shows that average

temperature inside urban forest (PI) is always lower than on perimeter of urban

forest (P2) and outside urban forest (P3) in each urban forest type. It also shows

that five urban forest types can reduce air temperature.

Table 4.1 Air Temperature average in each urban forest type

During temperature measurement, several data were also collected included:

number of trees and vegetation species in each urban forest type (Table 4.2). Each

urban forest was found to have different vegetation species. Clustered multi with

multi structure urban forest has high biodiversity of vegetation species. More

information about vegetation species in each urban forest type can be seen in

Table 4.2 Number of trees and vegetation species in each urban forest type

4.1.1. Effectiveness of Urban Forest Types toward Air Temperature Reduction Based upon Time of Measurement

Number of trees Number of vegetation species

The results of air temperature average in five urban forest types are

illustrated visually in Figure 4.1. Generally, air tempature in P1 of all urban

LM 201 6

forest type is lower than air temperature in P2 and P3.

Air temperature in P3 of Clustered form with multi structure (CM) urban

LS

30 3

forest reached 36"C on day time, and it is the highest temperature recorded during

this

study. At the same time, the temperature in P2 was only 29OC, while in P1 is

DS

35

4

28 OC. It shows that inconvenient temperature occurred at midday (noon) and it

also means clustered form with multi structure (CM) is very effective to reduce air

CM *500

16

temperature inside urban forest but it is ineffective to affect air temperature in its

CS

450 1

surrounding area. In clustered form with multi structure urban forest, the

difference of air temperature (At) between inside urban forest and outside urban

forest at midday was very high in amount of 5.76"C (Table 4.3).

Table 4.3 Air Temperature Changing (At) toward Time Changing in Each Urban Forest Type CC)

Note:

PI = Point inside urban forest

P2 = Point on perimeter P3 = Point outside urban forest

(-) = Air temperature is increased

l- 11119

P2=on perimeter of Urban P3=Outside Urban Forest

Figure 4.1 Graphic of temperature average in each urban forest type (LS, LM, DS, CS, CM).

In clustered form with second structure (CS) urban forest, the diierence of

air temperature (At) between inside urban forest and outside urban forest at

midday was about 2.5S°C. It also shows inconvenient temperature also occurred

While, air temperature in P3 of dispersed form with second structure (DS)

urban forest was 31.5"C on 14.00 PM. At the same time, air temperature in P2 and

PI respectively was 29.5 OC and 29.4 "C. It shows that air temperature inside and

outside DS urban forest do not change significantly, it indicates DS urban forest

still influence air temperature on its perimeter and outside urban forest during

midday. In l i e with DS urban forest, air temperature P3 of l i e u form with

second structure (LS) urban forest was 29 "C on 14.00 PM. At the same time,

air

temperature in P2

and

P1 respectively was 28.5 OC and 28 OC. It

also

shows that

air temperature inside and outside LS urban forest do not change significantly, it

indicates LS urban forest

also

influence air temperature on its parameter and

outside urban forest during midday.

Table 4.3 and Figure 4.1 illustrates that air temperatures in P1 were lower

than P2 and P3 in morning time and even in day and afternoon time, air

temperatures in P1 of all urban types were still lower than air temperature in P2

and P3