Journal of Natural Resources and Environmental Management
http://dx.doi.org/10.29244/jpsl.15.5.791

RESEARCH ARTICLE

The Impact of National Strategic Project Development Yogyakarta International
Airport on Land Use and Land Cover Dynamic
Westi Utamia,b, Catur Sugiyantoc, Noorhadi Rahardjod
a Doctoral Program of Environmental Science, Universitas Gadjah Mada, Yogyakarta, 55284, Indonesia
b

Sekolah Tinggi Pertanahan Nasional, Yogyakarta, 55293, Indonesia

c Department of Economics, Faculty of Economic and Business, Universitas Gadjah Mada, Yogyakarta, 55281, Indonesia
d Department of Cartography and Remote Sensing, Faculty Geography, Universitas Gadjah Mada, Yogyakarta, 55281, Indonesia

Article History
Received 28 August 2024
Revised 21 May 2025
Accepted 24 June 2025
Keywords
land use change, land use
pattern, sustainable
environment

ABSTRACT
Land use has been demonstrated to exert a considerable influence on human life, ecological
functions, and environmental sustainability. The objective of this paper is to map changes in land
use and land cover (LULC) patterns and directions of built-up land development around Yogyakarta
International Airport. The data source utilised is Pleiades, and image interpretation is conducted
visually to generate a LULC map. Land use and Land Cover change data are obtained through the
process of overlay. The average nearest neighbour is known to determine the distribution pattern,
while the standard deviation ellipse is understood to determine the direction of built-up land
development. The overlay results indicate substantial changes in LULC, with a decrease in mixed
plantations of 528.2 ha and in agricultural land of 112.7 ha. Conversely, there was a substantial
augmentation in residential areas, encompassing 29.4 ha, and service and trade areas, amounting
to 11.2 ha. The findings indicate that the ratio of built-up land patterns in 2014 was 0.63, in 2018 it
was 0.59, and in 2022 it was 0.33; with this value, the built-up land pattern is clustered. The research
findings indicate a shift in the direction of built-up land, initially orienting eastward and
subsequently shifting to the northeast, in a parallel configuration to the arterial road. These findings
demonstrate the importance of monitoring LULC dynamics for controlling land use and developing
equitable and sustainable land use policies.

Introduction
Land use and land cover (LULC) have been identified as pivotal factors in the maintenance of environmental
equilibrium, carbon reserves, ecosystem sustainability, and socio-economic life of communities [1–4]. In
addition, Padmini et al. and Ma et al. [5,6], there is a strong correlation between rapid changes in LULC and
population growth, development, economic growth, and human activities. Uncontrolled land use changes
have the potential to result in excessive urban expansion, trigger climate change, and various disasters [7–
10], and if occurring in rural areas, can result in increased rural poverty and reduced food security [11,12].
The issue of land use in rural areas is a critical concern in the context of rural development [13], and this
condition also applies to the study area. The development of Yogyakarta International Airport as one of the
national strategic projects located in Kulon Progo District has had a profound impact on the transformation
of rural areas into urban areas, thereby attracting industries, warehouses, trade, services, and residential
areas [14,15]. These significant economic activities have resulted in increased land use changes, which have
the potential to exert adverse effects on communities and the environment [16].
According to data from the Regional Disaster Management Agency [17], development of airport
infrastructure has an impact on land-use change, causing flooding disasters in several villages. In addition,
Sholikah et al. and Tikuye et al. [18,19] also shows that the reduction of agricultural land (rice fields and fields)
has led to a decrease in agricultural production, which is feared to threaten the sustainability of the
Corresponding Author: Westi Utami
Mada, Yogyakarta, Indonesia.

westiutami@stpn.ac.id

Doctoral Program of Environmental Science, Universitas Gadjah

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livelihoods of farmers/agricultural communities in the study area. In this case, a detailed analysis of the
impact of airport development on land-use change is required. This data can be used as a basis for integrated
spatial planning so that the development of the airport aerotropolis area can achieve environmental, socio economic, and cultural sustainability [20,21].
Monitoring land cover change constitutes a mechanism for controlling land cover change [22–24], compiling
LULC predictions, forming the basis for disaster mitigation, and formulating sustainable land use
management policies [22–25]. A plethora of efforts have been made to monitor alterations in land use.
Nevertheless, certain endeavours persist in relying on low-resolution satellite imagery [18,19]. Whilst these
images have the advantage of covering a wider area, they also have lower accuracy [26–28] and less detailed
classification results [2]. The absence of details in LULC change monitoring is a matter of concern, as it may
result in high land use inconsistencies, spatial conflicts, and various environmental damages [29,30]. A review
of the extant literature reveals that previous studies have limitations in terms of data accuracy and have not
analysed patterns of land use change distribution [17,31]. Conversely, both the accuracy and the patterns of
LULC change are pivotal in determining regional growth patterns and in the control of uncontrolled urban
sprawl [32].
The lack of detailed analysis of the impact of infrastructure development on LULC change is feared to lead to
increased land-use change and reduced agricultural yields, which may threaten food security and the
sustainability of community livelihoods. The lack of detailed multi-temporal land use data is also feared to
have implications for the imprecision of land use regulation and control policies. This research aims to fill the
gap in previous research [18,19] to produce a land use map with a high level of accuracy and a more complete
classification of uses, where the analysis of land use dynamics is adjusted per phase, namely before, during,
and after airport construction. This research also complements the research of Zhang et al. [13];
Kamruzzaman et al. [31] in relation to the preparation of distribution patterns and changes in the direction
of land use patterns as one of the bases for the formulation of spatial and land use policies [32]. The objectives
of this study are threefold: to provide multi-temporal land use data with greater precision and accuracy, to
analyze LULC change patterns, and to provide information on the impact of large-scale development carried
out through national strategic projects on land use dynamics. It is anticipated that this data and information
will underpin the formulation of comprehensive land use policies and planning, representing a pivotal
component in achieving environmental sustainability and mitigating the adverse effects of natural
degradation and climate change.

Materials and Methods
Study Area
This research was conducted in the Temon Sub-district, Kulon Progo Regency, Yogyakarta Special Region
(Figure 1), which is affected by the development of Yogyakarta International Airport (YIA) and its supporting
infrastructure.

Figure 1. Study area, Temon Sub-district, Kulon Progo Regency, Special Region of Yogyakarta, Indonesia.

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Site selection is crucial since YIA is one of the largest infrastructure developments or megaprojects of
Indonesia's national strategy project, with a land acquisition area of 578 ha. The construction was carried out
in a rural area dominated by agricultural land, with the community mostly working as farmers. The
construction of the airport and its supporting infrastructure triggered the growth of various trade and service
facilities and encouraged the emergence of new settlements. The limited detailed monitoring of land use
changes is feared to cause urban sprawl and lead to irregularities in land use. A description of the study area
is presented in Figure 1.
Materials and Data Analysis
The data presented in this study encompasses Pleiades imagery captured in 2014, before the commencement
of airport construction, on 20 September 2014. Pleiades images are very high-resolution images that
researchers widely use to produce detailed-scale maps [33,34]. The land use classification in this study
includes 14 types; therefore, it is complete and more detailed. The visual interpretation method was chosen
because it can produce more detailed and accurate land use classifications [35], even though it takes longer
and requires the accuracy of the interpreter [36]. Accuracy testing was conducted to ascertain the veracity
of the interpretation of land use in relation to actual conditions in the field. The samples in this study were
obtained using the Slovin formula, which yielded 120 sample points. The sample was determined using
stratified random sampling, thereby ensuring representation of the number and type of land use within the
sample.
The interpretation of Pleiades imagery, which demonstrated its reliability, can produce land-use maps for
2014, 2018, and 2018. To address the primary research objective of mapping changes in land use from 2014
to 2018 and 2018 to 2022, an overlay of maps was performed. The overlay process yields two products: a
land-use change map and a multitemporal land-use change matrix. The methodology employed in the
generation of multitemporal land-use patterns involves the implementation of average nearest neighbor
analysis, which can be delineated as follows:
̅
𝐷

𝐴𝑁𝑁 = ̅ 𝑜

(1)

𝐷𝐸

̅𝑜 = The observed average distance of each feature and its nearest neighbour
𝐷
̅𝐸 = The expected distance is the average distance between neighbours in a hypothetical random
𝐷
distribution.
̅ o dan D
̅ E the following formula can be used:
To find out the values of D
𝑛

̅𝑜 = ∑𝑖=1 𝑑𝑖
𝐷

(2)

̅𝐸 =
𝐷

(3)

𝑛
0.5

√𝑛⁄𝐴

n = Total number of features
A = The area that encompasses all the features or values of a specified area
Furthermore, to ascertain the direction of the distribution pattern of built-up land change, a standard
deviation ellipse analysis was utilized. Consequently, the direction of multitemporal built-up land growth was
analyzed to determine the center point and direction of the built-up land growth pattern. A research
flowchart, which delineates the data sources, analysis process, and research results/outputs, is presented in
Figure 2.

Figure 2. Research flow diagram.

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Results
Land Use and Land Cover Accuracy
Accuracy testing was conducted to ascertain the validity of the land use interpretation results in relation to
actual field conditions. The samples used in this study were obtained using the Slovin formula, resulting in
120 sample points. The sample points were determined using stratified random sampling, ensuring the
representation of all samples according to their LULC types. Based on the accuracy test in the field, there
were errors in 9 out of 120 sample points. Based on the analysis using the confusion matrix, the accuracy of
the interpretation of the results was 92.5%. This value indicates that the results of the visual interpretation
carried out using Pleiades images were classified as high (United States Geological Survey/USGS).
Multitemporal Land Use-Land Cover Changes
The results of land use and land cover interpretation in 2014 showed that the Temon Sub-district is a rural
area where land use/land cover is dominated by agricultural land, mixed plantations, and low -density
settlements, as shown in Figure 3a. The construction of the airport has changed the land use by at least 578
ha for the airport and 10 ha for resettlement for affected residents. The construction of airports as
aerotropolis areas has triggered an increase in land conversion, including trade and services, hotels and inns,
and new settlements. The results of the interpretation of land use and land cover before (2014), during
(2018), and after the YIA construction (2022) are presented in Figure 3.

Figure 3. Land use and land cover map; (a) 2014 before construction YIA, (b) 2018 during construction YIA, (c) 2022
after construction.
The findings of this study show that the development of Yogyakarta International Airport has resulted in
significant changes in the location of the airport and the surrounding area. The findings of the study show
that before the construction of the airport in 2014, agricultural land was still very extensive, reaching up to
1,434 ha (39%), and mixed plantations were also very extensive, reaching 1,331 ha (36%). The results of the
analysis show that in 2014, almost 75% of the study area was a source of livelihood for the community in the
form of rice fields and mixed gardens/fields. However, with the establishment of the airport location in the

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Temon Sub-district, followed by land clearing, some areas in the sub-district experienced massive land
conversion. The process of land clearing and the start of YIA construction in 2018 caused a decrease in mixed
plantations; in this period, only 800 ha (22%) remained, and agricultural land covered 1,375 ha (37%). After
the construction and operation of the airport, land use change continued, especially on the north side of the
airport entrance and along the national road. During this period, agricultural land continued to decrease by
1.5% (55 ha). The airport's existence catalyzes the growth of trade and service areas, which expanded by 11.2
ha between 2014 and 2022. Additionally, hotels and guesthouses that were previously absent have been
developed, resulting in an area of 14.07 ha being built by 2022. Detailed data on land use in the study area
for 2014, 2018, and 2022 are presented in Table 1.
Table 1. Land use and land cover area, percentage in 2014, 2018, and 2022.
Land-cover and land-use type
Airport (AP)
Trade and Services (TandS)
Educational Facilities (EF)
Government Office (GO)
Green Belt (GB)
Hotels/Hostels (HT)
Medical Facilities (MF)
Mixed Plantations (MP)
Open Field (OF)
Rice Fields (RF)
Settlements (ST)
Sport Facilities (SF)
Tourism Area (TA)
Water Bodies (WB)

2014
ha
0
16.23
8.79
8.18
2.03
0
0.74
1,331.26
73.08
1,433.65
528.33
2.95
22.46
222.15

%
0
0.44
0.24
0.22
0.055
0
0.02
36.47
2,001
39.28
14.47
0.08
0.61
6.086

2018
ha
0
24.82
8.39
8.27
2.029
9.39
1.13
800.50
629.60
1,375.30
555.84
2.94
22.99
209.25

%
0
0.68
0.23
0.23
0.055
0.25
0.031
21.93
17.25
37.67
15.23
0.08
0.63
5.73

2022
ha
569.93
27.45
8.39
8.28
24.24
14.07
2.20
803.09
87.89
1,320.99
557.75
2.95
23.31
189.27

%
15.65
0.75
0.23
0.23
0.67
0.39
0.06
22.06
2.41
36.29
15.32
0.08
0.64
5.20

Table 1 shows that airport construction not only resulted in the loss of rice fields but also resulted in a
reduction in mixed gardens and fields. The results of this study show that airport development not only
biophysically changes the land use in the study area. However, the reduction in arable land has implications
for the livelihoods of people who are largely dependent on the agricultural sector. It is feared that this
condition will lead to a reduction in income, which may increase poverty. The results of the overlay analysis
of the land use and land cover maps in the period between 2014 and 2018, as shown in Figure 4a, show that
the airport development in Temon Sub-district not only changes the land use in the area where the airport is
built. The research results show that during the period 2018–2022, land use change also occurred massively
in the areas along the national road and the southern causeway. The results of this study show that the
pattern of land use change occurring in the study area, particularly around the road network, is characterized
by a non-clustered pattern. The results of further analysis show that the random pattern of change occurs
mostly in rice fields. The spatial pattern of land use and land cover change that occurs can certainly le ad to
land fragmentation, further threatening the existence of agricultural land.

Figure 4. Map of land use and land cover change in Temon Sub-district: (a) 2014–2018 and (b) 2018–2022.

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Figure 4 shows that the pattern of land use and land cover change between 2014–2018 and 2018–2022 is
quite different. In the period 2014–2018, most of the areas that changed were in the form of land clearing
for airport development in the lower part of the study area, while in the upper part, there were also some
changes intended for the relocation of residents. In the period 2018–2022, the pattern of changes in the
lower part was characterized by the development of the airport area, with some changes also occurring
around the airport. To find out in detail which types of land use changed in each period, Table 2 and Table 3
present the results of overlaying multi-temporal land use maps. Table 2 is a matrix showing the types of land
use that changed from 2014 to 2018, while Table 3 is a matrix explaining the types of LULC changes from
2018 to 2022.
Table 2. Matrix of land use and land cover changes period 2014–2018 in Temon Sub-district.

Year 2014 (ha)

Land use and
land cover type
Trade and
services
Educational
fac.
Government
office
Green belt
Hotels/
hostels
Medical
facilities
Mixed
garden
Open field
Rice fields
Settlements
Sport
facilities
Tourism area
Water bodies

Year 2018 (ha)
Trade
Education
and
facilities
services
16.23
0

Government Green
office
belt

Hotel/
hostel

Medical Mixed
fac.
garden

Open
field

Rice
fields

Settlements

Sport Tourism Water
fac.
area
bodies

0

0

0

0

0

0

0

0

0

0

0

0

8.40

0

0

0

0

0

0

0

0

0

0

0

0

0

8.2

0

0

0

0

0

0

0

0

0

0

0
0

0
0

0
0

2.03
0

0
0

0
0

0
0

0
0

0
0

0
0

0
0

0
0

0
0

0

0

0

0

0

0.05

0

0

0

0

0

0

0

1.29

0

0

0

8.15

0

800.5

434.9

0

41.62

0

0

15.41

1.44
0.24
0.25
0

0
0
0
0

0.10
0
0
0

0
0
0
0

0
0
1.24
0

0
0
0
0

0
0
0
0

51.88
79.85
25.20
0

0.19
1.34
0
0

3.33
0.42
501.2
0

0
0
0
0.15

0.41
0
0
0

0.67
0.13
0
0

0
0

0
0

0
0

0
0

0
0

0
0

0
0.2

0
42.11

0
10.48

0
0

0
0

0.90
0.08

1.48
173.9

Table 3. Matrix of land use and land cover changes period 2018–2022 in Temon Sub-district.

Year 2018 (ha)

Land use and
land cover type
Airport (AP)
Trade and
Services (TS)
Education Fac.
(EF)
Government
Ofc (GO)
Green Belt (GB)
Hotels/Hostels
(HT)
Medical
Facilities (MF)
Mixed
plantation (MP)
Open Field (OF)
Rice Field (RF)
Settlements (ST)
Sport Facilities
(SF)
Tourism Area
(TA)
Water Bodies
(WB)

Year 2022 (ha)
AP
T and S
0.00
0.00

EF
0.00

GO
0.00

GB
0.00

HT
0.00

MF
0.00

MP
0.00

OF
0.00

RF
0.00

ST
0.00

SF
0.00

TA
0.00

WB
0.00

0.00

25.41

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

8.40

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

8.62

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

2.03

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

9.48

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

1.13

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.25

0.27

0.00

0.00

0.00

0.43

0.00

792

9.64

0.06

2.09

0.00

0.00

0.00

546.86
21.2
1.9

1.92
0.51
0.00

0.00
0.00
0.00

0.00
0.00
0.00

2.76
0.00
0.00

1.97
0.11
2.17

0.90
0.17
0.00

1.85
0.09
0.00

74.23
3.12
0.00

0.00
1,352
0.00

0.92
1.30
553.84

0.00
0.00
0.00

0.00
0.00
0.00

0.46
0.45
0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

2.95

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

23

0.00

0.00

0.00

0.00

0.00

19.5

0.00

0.00

0.36

0.76

0.00

0.00

0.00

0.32

188.36

Tables 2 and 3 present a comprehensive and detailed overview of the land use changes that occurred within
the study area. The findings of this study demonstrate that trade and service LULC have undergone a
significant increase in addition to airport development. In contrast, the previous land use type is
predominantly rural, with some changes to infrastructure, trade, and service areas. The data presented in

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Rice Field
Agricultural fields
Settelemnt
Mixed Plantation
Open Field
Trade & Services
Residential
Airport

Land use and land cover

Land use and land cover

the land use change matrix for the periods between 2014 and 2018 and 2018 and 2022 show a significant
increase in built-up land growth, particularly in residential areas and trade and service areas. The construction
of YIA airport impacts five villages: Jangkaran, Sindutan, Palihan, Kebonrejo, and Glagah. To gain a more
detailed understanding of the land use change in each of these villages, a visual representation can be
provided as Figure 5.

0.0

100.0

Rice Fields
Settelement
Trade and services
Open Field
Agricultural fields
Pond
Mixed garden
Airport
0.00

200.0

2018

2014

2022

Rice Fields

Rice Fields

Residential

Residential

Settlement

Trade and services

Trade and Services
Open Field
Mixed Garden
Hotel
Airport

50.00

100.00

Land use and land cover area (ha)

2022

80.00

100.00

120.00

140.00

2018

2014

100.00

200.00

2018

Inn/homestay
Open Field
Agricultural fields
Mixed garden
Airport

0.00

300.00

Land use and land cover area (ha)

2014

2022

(c)
Land use and land cover

60.00

(b)

Land use and land cover

Land use and land cover

(a)

0.00

40.00

Land use and land cover area (ha)

Land use and land cover area (ha)
2022

20.00

2018

2014

(d)
Rice Fields

Mixed garden
Settelement
Agricultural fields
Ponds
Open Fields
Trade & Services

0.00

20.00

40.00

60.00

80.00

100.00

120.00

Land use and land cover area (ha)
2022

2018

2014

(e)
Figure 5. Land use and land cover change of villages affected by the construction of Yogyakarta International Airport:
a) Palihan, b) Jangkaran, c) Kebonrejo, d) Glagah, e) Sindutan.
Based on Figure 6, the villages that experienced the highest decrease in agricultural land and rice fields were
Glagah Village (agricultural land decreased by 216.8 ha and rice field land decreased by 25.5 ha), Palihan
(agricultural land decreased by 110 ha, and rice field land decreased by 45 ha), and Sindutan (agricultural
land decreased by 29 ha and rice field land decreased by 8 ha). The findings of this study indicate that the
development of national strategic projects has changed most of the land use conditions of the 5 villages
directly affected by YIA airport.

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(a)

(b)

(c)

Figure 6. Distribution pattern of built-up land in Temon Sub-district with a clustered pattern in (a) 2014; (b)
2018; (c) 2022.
Changes in the Pattern and Direction of Built-Up Land Growth
The objective of the average nearest neighbour analysis is to ascertain the spatial aggregation characteristics
of built-up land growth patterns that occur in rural areas both before and following the development of
airport infrastructure. The results of the nearest neighbour analysis conducted in this study are presented in
Figure 6, while the data on changes in significance values and the level of density/distance between built-up
land are presented in Table 4.
Table 4. The nearest neighbor ratio of built-up land in 2014–2022.
Year
2014
2018
2022

Coverage observation
distance (m)
90.72
91.70
43.67

Expected average
distance (m)
142.92
154.81
128.51

Nearest
neighbor ratio
0.63
0.59
0.33

Z-value

p-value

Type

–16.25
–18.17
–35.45

0
0
0

Clustered
Clustered
Clustered

The results of the analysis of the average nearest neighbor showed that the pattern of distribution of built
land at the study site in 2014, 2018, and 2022 has a significant p-value of < 0.1, so it was included in the
clustered pattern. The results of this pattern analysis support the research of Salouw and Pramono [37] where
clustered patterns are influenced by topography in the form of plains, fertile land, and the existence of
agricultural land/rice fields around residential areas. The clustered pattern of built-up land growth in the
study area is formed because it follows the geographical conditions of the area, where this area is a rural area
with agricultural land that separates settlements from one another. Based on Figure 6 and Table 2, although
the built-land pattern has the same shape, the significance value of the z value, the value of the nearest
neighbor value, and the value of the coverage observation distance have decreased. The decre ase in the
three values shows that the distance between the central point of the built land is getting closer, and the
level of built land density has increased.
In addition to examining the pattern of built-up land, this research also investigates the growth of built-up
land. To ascertain the centre point data and spatial distribution patterns of the direction of built-up land use,
a standard deviation ellipse analysis was conducted, with the results presented in Figure 7. The analysis of
built-up land growth is a crucial element in understanding the patterns of growth that occur over time. The
findings of this study can inform the formulation of land stewardship policies, the identification of key drivers
that stimulate the expansion of built-up areas, and the establishment of a regulatory framework for the rate
of built-up land growth.
The results of the analysis presented in Figure 7 demonstrate a shift in the centre of the standard deviational
ellipse, which corresponds to the centre of gravity of the built land. In 2014, the centre of the standard
deviation was located on the east side, while in 2022, the centre of the standard deviation ellipse shifted
westward. The economic growth centre had a more significant influence on the change in the ellipse point in
2014 in Wates City. In contrast, by 2022, with the operation of YIA and the growth of economic activity, the
central point shifted closer to the airport. This shift underscores the pivotal role played by the airport's
regulatory influence on the expansion of built-up land from 2018 to 2022. Concurrently, the trajectory of

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built land growth, as delineated by the ellipse line, underwent substantial alterations. In 2014, the direction
of built-land growth exhibited a tilt towards the south and east. However, from 2018 to 2022, the direction
of built-up land growth shifted towards the northeast, extending along the trajectory of the national road.

Figure 7. Standard deviational ellipse of the built-up land; (a) 2014, (b) 2018, (c) 2022, (d) changes in standard
deviational ellipse in 2014, 2018, and 2022.

Discussion
The analysis of the impact of the development of the national strategic project of the YIA airport development
produced several findings. Empirical findings demonstrate that there are significant spatial and temporal
differences in the dynamics of land use between the 2014–2018 and 2018–2022 periods. The 2014–2022
period was characterised by a more significant alteration in land use and land cover, influenced by direct
factors such as the development of the airport. In contrast, the 2018–2022 period witnessed a relative decline
in changes to land use, with the influence of proximate causes, such as the pandemic, being minimal.
Theoretically, the findings of this study corroborate those of Sisay et al. [38] in Africa, which state that
policy/political factors on land use, including for development or agriculture, have a very dominant influence
on the rate of land use dynamics. The present study's findings are consistent with the theory of land use
dynamics proposed by Lambin and Geist [39], which asserts that proximate causes, such as agriculture and
deforestation, play a pivotal role in shaping land use dynamics. The findings of this study align with the
research conducted by Indrayati et al. [28], which demonstrates that land use dynamics are also influenced
by factors related to road accessibility.
The present study provides further insights that build upon the findings of Kamruzzaman et al. [31] by
demonstrating that land use patterns in airport areas are significantly influenced by spatial planning.
However, the present study also indicates that these patterns are shaped not only by spatial planning but
also by other factors, including spatial preferences, such as land needs, land suitability levels, and business
opportunities. The intricate interplay between biophysical dimensions and political, socio-economic factors,
characterized by a high degree of complexity, exerts a significant influence on the decisions made by the
community, institutional entities, and governmental bodies concerning land use. This, in turn, gives rise to
variations like land use across different geographical areas. Theoretically, the research findings demonstrate
that the dynamics of land use, influenced by airport development, give rise to novel spatial functions that can
exert an influence on shifts in the social, economic, and cultural conditions of the community. The results of
this study serve to reinforce the research conducted by Suwanlee et al. [23], which demonstrates that
changes in land use in rural areas do not solely result in alterations to the physical aspects/land cover. The
decline in the function of mixed gardens, fields, and people's plantations as green open spaces results in a
shift in land function from ecological space to commercial space.

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The utilization of Pleiades imagery as one of the very high-resolution satellite images in this study facilitates
the presentation of more detailed land use/land cover information, thereby complementing the findings of
previous research conducted by Sholikah et al. [18]; Syafitri and Santosa [40], which was limited to the
classification of land use in built-up land classes. The spatial resolution of this study provides a more detailed
classification of built-up land, including settlements, trade and services, educational facilities, hotels, and so
on. This detailed information is undoubtedly beneficial in planning the development of aerotropolis in more
detail. Methodologically, this study contributes to the research of Almazroui et al. [41] by using Landsat
imagery to map urban sprawl, though the latter study has a lower level of accuracy. The research findings
demonstrate that the utilization of visually interpreted Pleiades imagery, in addition to its capacity to produce
detailed types of land cover/use classifications, attains a high level of accuracy of 92%.
Empirical evidence from recent research indicates that the development of airports, expansion of trade and
service areas, and the establishment of hotels and settlements have led to a decline in rice fields, fields, and
mixed gardens, which serve as crucial sources of livelihoods for communities. The spatial pattern of built -up
land growth, characterized by random occurrences on agricultural land, poses a growing threat to the
existence of rice fields. The reduction in agricultural land within the study area has a discernible impact on
the socio-economic aspects of rural areas, jeopardizing food security and the sustainability of livelihoods for
agrarian communities. Moreover, the substantial decrease in vegetation cover, which the development of
optimal green belts has not counterbalanced, has consequences for reducing water catchment areas,
increasing urban heat, and increasing carbon emissions. The findings of this study corroborate several earlier
studies conducted by Almeida et al. [42]; Humbatova et al. [43] that development oriented towards the
economic sector has a negative impact on environmental damage. The study further contributes to the
discourse on the formulation of national strategy projects in Indonesia, particularly in rural regions, where
the assessment of land value is constrained to biophysical parameters. This limitation stems from an absence
of a comprehensive framework that incorporates socio-economic, cultural, and environmental dimensions,
consequently impeding the realization of sustainable community life and environmental stewardship.
The findings of this research provide a valuable contribution to the concept of aerot ropolis area
development, a topic that has been extensively researched by Kamruzzaman et al. [31]; Kasarda and Appold
[21], the location of the aerotropolis area under study is predominantly in urban and suburban regions,
resulting in the formation of a commercial or industrial area around the airport. In contrast, this research
focuses on an airport situated in a rural area characterized by agricultural land and agrarian communities.
The concept of planned aerotropolis development prioritizes the development of superior agricultural
products. The research contributes to the feasibility of airports that not only produce regional economic
benefits but also encourage local economic growth. The strategic and planned development of commercial
areas, residential areas, agricultural land areas, local protected areas, and the establishment of corridors
connecting different regions are identified as key factors in the success of aerotropolis area development.
Conceptually, this research serves to reinforce the findings of MCNair [44] on the significance of
environmental justice in the context of airport infrastructure development. The study emphasizes that the
loss of vegetation cover due to the construction of YIA necessitates the implementation of policies to ensure
an equitable environment. This can be achieved by increasing green open spaces and establishing local
protected areas, particularly as a means of disaster mitigation (tsunamis, floods, abrasion). The challenges
inherent in the development of this aerotropolis area are complex, particularly given the location of YIA in a
rural area where most of the population is dependent on the agricultural sector. The geographical conditions
on the south side of the site are susceptible to tsunamis, abrasion, and tidal waves, while the east and west
sides are prone to flooding, and the hilly areas to landslides. The implementation of monitoring systems for
land use dynamics, as outlined in this study, serves as a fundamental aspect for the formulation of spatial
planning and sustainable regional development policies.

Conclusion
The construction of YIA and its supporting infrastructure has a domino effect on land use changes that occur
around the airport and the national road. This research shows that the existence of airports significantly
changes the land use distribution pattern, the magnetic central point of built-land growth, and the landscape
of the area, which was originally a rural area, into an urban area characterized by the growth of various
commercial, trade, and service areas and various airport facilities. The planning of airport development as an
aerotropolis area is a complex problem, particularly in the development of YIA in agrarian and disaster-prone
areas. In this context, efforts to protect agricultural land as a source of community livelihood are necessary

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so that development impacts do not cause people to lose their jobs, which can lead to increased rural poverty.
The land use monitoring data is expected to become a basis for formulating spatial planning policies so that
the development of the YIA aerotropolis area can realize increased regional and local economic growth while
still prioritizing environmental sustainability. Research on the impact of YIA's development on land use
change requires further study, especially to determine the impact assessed from the environmental and
economic sectors. This study aims to inform the alignment and complementarity of environmental and
economic aspects in the development of the aerotropolis area.

Author Contributions
WU: Conceptualization, Methodology, Software, Investigation, Writing - Review & Editing; CS: WritingReview & Supervision; NR: Writing – Review & Supervision.

Conflicts of Interest
There are no conflicts to declare.

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