Spatiotemporal Analysis of Urban Land Cover:

Case Study - Pekanbaru City, Indonesia

Idham Nugraha

, Faizan Dalilla

, Mira Haﬁzhah Tanjung

, Rizky Ardiansyah

, and M. Iqbal Hisyam

Urban and Regional Planning Departement, Universitas Islam Riau, Pekanbaru, Indonesia

Student in Urban and Regional Planning Departement, Universitas Islam Riau, Pekanbaru, Indonesia

Keywords:

Land Cover, Remote Sensing, Spatiotemporal, Pekanbaru.

Abstract:

The number of people has an increasing pattern by years and it will impact spatial aspects. One of the impacts

was land cover changes from the non-built area into the built-up area. Pekanbaru is one of developing city

in Indonesia that has a high number of the population surge. The purpose of this paper was to analyse the

land cover change in the urban area of Pekanbaru city. The analysis spatiotemporal has been done by using

Landsat Imagery year of 2000, 2005, 2009 and 2014. The method of this paper was digital classiﬁcation

using maximum likelihood and their integration with Geographical Information Systems (GIS). Land cover

classiﬁcation divided into two classes such as built-up area and non-built up land area. Based on the results,

the built-up land area has been increased by years, on the other hand, the non-built up area has declined. The

percentage of built-up area change from 29,51% into 59,99%. The spatial distribution of and cover change

dominantly occurs in south part of Pekanbaru city. The mean of accuracy index for the land cover map in this

research was 85,17%. The land cover change of Pekanbaru city has a decreasing pattern where the year of

2000-2005 has a signiﬁcant number and decreasing by years massively.

1 INTRODUCTION

Globally, the number of populations has an increasing

pattern. Based on the report of Worldmeters (Wor,

2020), the rate of increasing population was 1,09%

by years. Speciﬁcally, Indonesia has the number of

population amount of 267.630.499. Indonesia cate-

gorized as a country that has high urbanization index

in Asia around 2,75% by years and it’s above the na-

tional index around 1,49% per year (Indrayani et al.,

2017).

The increasing population will have some con-

sequences. In the spatial aspect, the dimension of

space has been pushed out by the increasing popu-

lation. Yunus (Yunus, 2005) explained that spatial

consequences were increasing demand for space to

accommodate the population activities in the form

of infrastructure and other physical structure. That

will be seen the massive of land cover change from

the non-built area into the built-up area. Land cover

changes can be categorized by the complex interac-

tions of structural and behavioural factors associated

with technological capacity, demand and social rela-

tions that affect both environmental capacity and the

demand along with the nature of the environment of

interest (Veldkamp and Verburg, 2004) (Butt et al.,

2015). Land cover change is one of the main driv-

ing forces of global environmental change, is cen-

tral to the sustainable development debate (Hegazy

and Kaloop, 2015). Land cover change becomes one

of the signiﬁcant issues for planners and decision-

makers in urban and regional policy (Wijaya and

Susilo, 2013). In line with the issue of increasing

population, land cover change become an interesting

issue to explore in a developing country, especially in

Indonesia. Wijaya (Wijaya and Susilo, 2013) high-

light that issue has been thriving because of the lack-

ing of law enforcement and the policy inter-institution

horizontally and vertically. The study of land cover

change is very essential to understand human activi-

ties and natural phenomenon.

The study of land cover change has been devel-

oped with different methods and cases (Purwanto and

Bayuardi, 2016). One of the methods to determine

that is the integration of remote sensing data and Ge-

ographic Information Systems (GIS). For example, in

China the land cover change was obtained by using

the integrated remote sensing data and GIS at years

of 1992, 1996, 2001, 2004 and 2008 (Purwanto and

Bayuardi, 2016). In Indonesia, several studies have

Nugraha, I., Dalilla, F., Tanjung, M., Ardiansyah, R. and Hisyam, M.

Spatiotemporal Analysis of Urban Land Cover: Case Study - Pekanbaru City, Indonesia.

DOI: 10.5220/0009106300740079

In Proceedings of the Second International Conference on Science, Engineering and Technology (ICoSET 2019), pages 74-79

ISBN: 978-989-758-463-3

been done, one of them was Indrayani et al (2016). It

has been done to evaluate land cover change and its

relations with the ecological connectivity index us-

ing remote sensing data year of 1997 until 2012 in

Makasar city.

The technology advance, especially on remote

sensing and GIS, gives some beneﬁt to obtain some

information about earth surface such as land cover.

One of them is remote sensing data can give quick in-

formation and multi-series data (NUGRAHA, 2016).

GIS advance can be used for measurement, mapping,

monitoring and modelling (Star and Estes, 1990). To

ease the used remote sensing data and GIS in land

cover studies, it can be done by making land cover

classiﬁcation (NUGRAHA, 2016).

Pekanbaru is a central city in Riau Province and

categorized as a developing city in Indonesia. Pekan-

bary city connects the north-south littoral of Sumat-

era, and it also connects the East and West of this

island (Kausarian et al., 2018). Pekanbaru consists

of twelve (12) districts, there area Bukit Raya, Lima

Puluh, Marpoyan Damai, Payung Sekaki, Pekanbaru

Kota, Rumbai, Rumbai Pesisir, Sail, Senapelan, Suka-

jadi, Tampan and Tenayan Raya (ﬁgure 1). Based

on Statistical data (Pekanbaru, 2016), Pekanbaru has

total populations amount 1.038.118 in the year of

2015. For the comparison, In 2000 Pekanbaru has

the number of populations around 586.223. In 15

years, Pekanbaru has 451.895 of people accretion and

it will affect the spatial condition in Pekanbaru city.

The research purpose was to review the land cover of

Pekanbaru city year of 2000, 2005, 2009 and 2014

by using Landsat imagery and digital classiﬁcation.

To achieved purposed, some step will be done. There

were :

a) Determine the land cover of Pekanbaru city

b) Determine the accuracy of the land cover

map

c) Determine the land cover change of Pekanbaru

city

2 METHOD

To achieve the purpose of the research, some pri-

mary and secondary data were needed. The data were

Landsat imagery, Rupabumi Indonesia Map (Base

Map), The draft of Spatial Regulation Document of

Pekanbaru year of 2006. For further information, the

required data were:

Figure 1: Administrative map of Pekanbaru

Table 1: The Data Requirements

No Data Sources

1 Landsat ETM+ year of

2000, 2005 and 2009.

Landsat 8 year of 2014

USGS

2 Rupabumi Indonesia Related Institutions

3 The draft of Spatial Regula-

tion Document of Pekanbaru

year of 2006

Related Institutions

4 The form of Land Cover

Change

Field Observation

2.1 Determine The Land Cover of

Pekanbaru City

To determine the land cover of Pekanbaru city,

we used the classiﬁcation of maximum likelihood

method by using ENVI 4.5. The maximum likeli-

hood is categorized as supervised classiﬁcation. This

method is classiﬁed as the pixel based on their value

to the particular class. Technically, the sample was

collected from Landsat imagery that has spatial reso-

lution 30 m by selecting the Region of Interest (ROI).

The land cover present into two classes, there were

built up area and non-built up area.

2.2 Determine the Accuracy of The

Land Cover Map

The accuracy assessment was needed to determine the

correctness of the land cover map. The method is the

Kappa index assessment. This method is compared

to the land cover map with the actual condition on the

ﬁeld. For the sample, we used 60 points that randomly

distributed. The minimum index that allowed is 85%

(Jensen et al., 2004). The matrix of the accuracy index

is explained below.

T he total accuracy =

a + d

(1)

Spatiotemporal Analysis of Urban Land Cover: Case Study - Pekanbaru City, Indonesia

Table 2: The Matrix of Accuracy Index

Field

Interpretation

A1 A2 Total

A1 a b a+b

A2 c d c+d

Total a+c b+d T

Source: (Sutanto and Leung, 1999) with modiﬁcation

2.3 Determine The Land Cover Change

of Pekanbaru City

The land cover change was obtained by overlaid the

land cover map. This stage has been done to deter-

mine the spatial distribution of the change by using

ArcGIS. This method was using the raster calculator.

For further analysis, ﬁeld observation is needed. The

land cover change information will be guided to the

ﬁeld observation. This step will be done to obtain

information about the form of land cover change in

Pekanbaru city.

3 RESULTS AND DISCUSSION

3.1 The Land Cover of Pekanbaru City

For this stage, we used the application of ENVI 4.5.

From the Landsat images, we generated two classes

of Region of Interest (ROI). There were built-up area

and non-built up area. There were 100 samples for

each class. Here below the ﬁgure 3, shows the land

cover of Pekanbaru city 2000-2014.

Based on ﬁgure 2, we can see that the land cover

of Pekanbaru city dominantly by the built-up area

shown by the red mark on the map. Generally, the

built-up area in Pekanbaru has been developing. In

2000, the built-up area amount of 208.712 pixels or

around 29,51% from the total of land cover in Pekan-

baru City. For the comparisons, in the year of 2014,

built up area was increasing. It is shown by the num-

ber of pixels of the built-up area around 424.362 pix-

els (59,99%). For the distribution, the built-up area

distributed randomly in Pekanbaru especially in the

south part of Pekanbaru. It was because in the south

part of Pekanbaru found some of the development

centres as a triggered factor such as the centre of ed-

ucation, the centre of government and centre of trad-

ing. For the further, the pixel number of land cover in

Pekanbaru shown on the table below.

(a)

(b)

(c)

(d)

Figure 2: The Land Cover Map of Pekanbaru City; (a) year

of 2000, (b) year of 2005, (c) year of 2009, (d) year of 2014

ICoSET 2019 - The Second International Conference on Science, Engineering and Technology

Table 3: The Pixel Number of Land Cover in Pekanbaru

City

Year Built Up

Area

Non Built-

Up Area

Lake River

2000 208712 491813 5377 1451

2005 349080 351445 5377 1451

2009 402534 297991 5377 1451

2014 424362 276163 5377 1451

3.2 The Accuracy of Land Cover Map

First step of this stage was determined the training

area or point as a sample. The number of samples

were 60 points that randomly spread around Pekan-

baru city. The mean of accuracy from Landsat image

was 85.17%. For the detail information about the ac-

curacy shown on table below.

Table 4: The Accuracy of Land Cover Map

Year Accuracy

2000 84.2

2005 85.5

2009 85.0

2014 86.0

Mean 85.17

3.3 The Land Cover Change of

Pekanbaru City

The information about the land cover change in this

paper was obtained from the land cover map that ex-

tracted from the Landsat image. The thematic map

will be overlaid by using Raster Calculator tool on

ArcGIS application. The unit analysis for the land

cover change is a pixel. We used the pixel to described

the change value. The land cover change in Pekan-

baru city occurred in the form of the non-built up area

like vegetation, swamp area transforms into the built-

up area such as settlement, trading and service. The

signiﬁcant change occurred in 2000 until 2005. It

is shown on the map, that change has been noticed

by the red mark and been seen on the south part of

Pekanbaru signiﬁcantly. Meanwhile, the change be-

tween 2005-2009 and 2009-2014 has a small portion

and distribute more equal to the north part of Pekan-

baru city. Figure 3 shows the land cover change in

Pekanbaru city 2000-2015.

Based on the analysis, the land cover change in

Pekanbaru city has decreases pattern. From 2000 un-

til 2005 the land cover has been massively changed

from the non-built area into the built-up area. From

(a)

(b)

(c)

Figure 3: The Land Cover Change Map of Pekanbaru City;

(a) year of 2000-2005, (b) year of 2005-2009, (c) year of

2009-2014

the total pixel around 707.503 pixels, the land cover

change reaches 140.368 pixels (19,84%). From 2005-

2014, the change has declined pattern, it looked from

the percentage. The percentage of change 2005-2009

amount of 53.454 pixel (7,5%) and 2009-2014 around

21.828 pixels (3,0%). For the detail information, the

pattern of land cover changes Pekanbaru city present

in ﬁgure 4 below.

The next stage of the paper is the land cover anal-

ysis. We analyze the land cover change by using dis-

trict administration as a unit and classiﬁed it into two

classes (change and no change). We used the draft

of Spatial Regulation Document of Pekanbaru City

as other input. Pekanbaru city consists of 12 dis-

tricts with each district has different size and num-

ber of populations. Based on the analysis, we found

Spatiotemporal Analysis of Urban Land Cover: Case Study - Pekanbaru City, Indonesia

Table 5: The Number of Land Cover Change in Pekanbaru City 2000-2014 (pixel)

Districts

2000-2005 2005-2009 2009-2014

Change No Change Change No Change Change No Change

Tampan 30118 34024 2150 61992 1394 62748

Marpoyan

Damai

7404 26881 1252 33033 995 33290

Bukit Raya 7437 20391 1925 25903 652 27176

Sail 250 3622 ∗ 3872 ∗ 3872

Lima Puluh 346 6020 ∗ 6366 ∗ 6366

Pekanbaru

Kota

36 2316 ∗ 2352 ∗ 2352

Sukajadi 17 4258 ∗ 4275 ∗ 4275

Senapelan 81 3302 ∗ 3383 ∗ 3383

Payung

Sekaki

9240 38352 1960 45632 2290 45302

Rumbai 20101 125565 18327 127339 7627 138039

Rumbai Pe-

sisir

8289 165976 13398 160867 4956 169309

Tenayan

Raya

57049 136278 14442 178885 3914 189413

Total 140368 566985 53454 653899 21828 685525

Figure 4: The Pattern of Land Cover Change in Pekanbaru

City 2000-2014

that there were ﬁve districts has “no change” class

from 2005 until 2014. It could occur because they

located in the city centre with the least number of

the non- built up area were available. Commonly,

the other districts in Pekanbaru city have a decreasing

pattern. For example, Tampan district and Tenayan

Raya district has the high number of change during

2000- 2005, but decreasing in a heavy way by years.

It showed that during 2009-2014 there were approxi-

mately 1000-4000 pixel has been changed.

In over decades, Pekanbaru hit by land cover

change phenomenon as consequences of urban expan-

sions. The increasing of populations due to fertility

and migrations will impact the land cover conditions

in Pekanbaru city. During 2000-2014, the land cover

change in Pekanbaru city has a decreasing pattern.

The main reason was the limited access to the land

due to availability and land value. Based on the re-

search, people have the tendency to develop the land

around the edge of the city. So for the future, the

research related land cover change in the sub-urban

area of Pekanbaru city. Regarding the remote sens-

ing data, in this research, we used Landsat imagery

as the main input. It has the spatial resolution around

30 m. For future research, the used high resolution of

remote sensing data is needed.

4 CONCLUSIONS

For this paper, we can conclude some points there

were: 1) The land cover in Pekanbaru city was domi-

nantly by the built-up area. It shows by the percentage

of built-up area in 2014 was 59,99% from the total of

Pekanbaru city, 2) The accuracy of the land cover map

measured by using the short method. The mean index

of the accuracy was 85,17%, and 3) the land cover

change from the non-built up area into the built-up

area has the decreasing pattern. It’s related to land

availability and land value.

ACKNOWLEDGEMENTS

This paper is part of the research with the title “Mon-

itoring Perubahan Penutup Lahan Kota Pekanbaru

Menggunakan Citra Satelit Landsat” by Idham Nu-

graha and Faizan Dalilla. This research was funded

ICoSET 2019 - The Second International Conference on Science, Engineering and Technology

and fully support by LPPM of Universitas Islam Riau.

We thank all colleagues that involved in this research.

REFERENCES

(2020). Worldometers - real time world statistics.

Butt, A., Shabbir, R., Ahmad, S. S., and Aziz, N. (2015).

Land use change mapping and analysis using remote

sensing and gis: A case study of simly watershed, is-

lamabad, pakistan. The Egyptian Journal of Remote

Sensing and Space Science, 18(2):251–259.

Hegazy, I. R. and Kaloop, M. R. (2015). Monitoring ur-

ban growth and land use change detection with gis and

remote sensing techniques in daqahlia governorate

egypt. International Journal of Sustainable Built En-

vironment, 4(1):117–124.

Indrayani, P., Mitani, Y., Djamaluddin, I., and Ikemi, H.

(2017). A gis based evaluation of land use changes

and ecological connectivity index. Journal of Geo-

matics and Planning, 4(1):9–18.

Jensen, R., Gatrell, J., Boulton, J., and Harper, B. (2004).

Using remote sensing and geographic information

systems to study urban quality of life and urban for-

est amenities. Ecology and Society, 9(5).

Kausarian, H., Sumantyo, J. T. S., Putra, D. B. E., Suryadi,

A., et al. (2018). Image processing of alos palsar

satellite data, small unmanned aerial vehicle (uav),

and ﬁeld measurement of land deformation. Interna-

tional Journal of Advances in Intelligent Informatics,

4(2):132–141.

NUGRAHA, I. (2016). Pemodelan Spasial Perubahan

Penutup Lahan Dalam Rangka Estimasi Debit Pun-

cak di Sub DAS Sail. PhD thesis, Universitas Gadjah

Mada.

Pekanbaru, B. P. S. (2016). Kota pekanbaru dalam angka

2016. Badan Pusat Statistik Kota Pekanbaru. Pekan-

baru.

Purwanto, A. and Bayuardi, G. (2016). Monitoring the

land use change in campus 2 stkip pgri pontianak.

Geoplanning: Journal of Geomatics and Planning,

3(1):77–86.

Star, J. and Estes, J. E. (1990). Geographic information

systems: an introduction, volume 303. Prentice Hall

Englewood Cliffs, NJ.

Sutanto, D. and Leung, C. H. (1999). Automatic index ex-

pansion for concept-based image query. In Interna-

tional Conference on Advances in Visual Information

Systems, pages 399–408. Springer.

Veldkamp, A. and Verburg, P. H. (2004). Modelling land

use change and environmental impact.

Wijaya, M. S. and Susilo, B. (2013). Integrasi model

spasial cellular automata dan regresi logistik biner un-

tuk pemodelan dinamika perkembangan lahan terban-

gun (studi kasus kota salatiga). Jurnal Bumi Indone-

sia, 2(1).

Yunus, H. S. (2005). Manajemen kota: perspektif spasial.

Pustaka Pelajar.

Spatiotemporal Analysis of Urban Land Cover: Case Study - Pekanbaru City, Indonesia