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         Geoplanning 
Vol 4, No. 1, 2017, 9-18                                                                                                                                                           Journal of Geomatics and Planning 

                                                                                                 E-ISSN: 2355-6544 
http://ejournal.undip.ac.id/index.php/geoplanning 

doi: 10.14710/geoplanning.4.1.9-18 

A GIS BASED EVALUATION OF LAND USE CHANGES AND ECOLOGICAL 
CONNECTIVITY INDEX 

P. Indrayani a, b, Y. Mitani a, I. Djamaluddin c, H. Ikemi a 

 a Department of Civil Engineering, Kyushu University, Fukuoka 819-0395, Japan 
b Fajar University, Indonesia 
c Hasanuddin University, Indonesia 

Abstract: Recently, the Makassar region is a significant land use planning and 
management issue, and has many impacts on the ecological function and structure 
landscape. With the development and infrastructure initiatives mostly around the 
urban centers, the urbanization and sprawl would impact the environment and the 
natural resources. Therefore, environmental management and careful strategic spatial 
planning in landscape ecological network is crucial when aiming for sustainable 
development. In this paper, the impacts of land use changes from 1997 to 2012 on the 
landscape ecological connectivity in the Makassar region were evaluated using 
Geographic Information System (GIS). The resulted GIS analysis clearly showed that 
land use changes occurring in the Makassar region have caused profound changes in 
landscape pattern. The spatial model had a predictive capability allowing the 
quantitative assessment and comparison of the impacts resulting from different land 
use on the ecological connectivity index. The results had an effective performance in 
identifying the vital ecological areas and connectivity prior to development plan in 
areas. 

 Copyright © 2017 GJGP-UNDIP  
This open access article is distributed under a  

Creative Commons Attribution (CC-BY-NC-SA) 4.0 International license. 
 

How to cite (APA 6th Style): 
Indrayani, P., et al. (2017). A GIS based evaluation of land use changes and ecological connectivity index. Geoplanning: Journal of Geomatics and 
Planning, 4(1), 9-18. doi:10.14710/geoplanning.4.1.9-18 

 

1. INTRODUCTION 

Indonesia is one of the fastest urbanizing countries in Asia. The level of population growth in urban 
areas approximately reaches 2.75% per year or higher than the level of national population growth (1.49% 
per year). In 2015, population growth in urban areas was estimated to reach 59.35% of the total population 
(Parasati, 2013). Assuming that population growth in urban areas approximately reaches 2.75% per year; 
the Indonesian population living in urban areas in 2045 will reach 82.37% of the total population. In recent 
years, the impact of population growth on urban sprawl in many major cities in Indonesia has become a 
major issue. As the fifth fastest growing city in Indonesia, the urbanization of the Makassar region has 
followed a model characterized by a low density of built-up area, which has revealed itself as tremendously 
negative for natural habits (Turner, 2005). 

In many areas with increasing urban sprawl, fragmentation has turned out to be virtually inevitable 
(Dupras et al., 2016). Generally, high ecological connectivity and a well-designed green network are 
assumed to better facilitate flows of energy, materials, and species, and thus are important for 
environmental conservation in developing landscapes (Crooks & Sanjayan, 2006). Similarly, green 
infrastructure (GI) is used emphasizing on a system of natural areas as a backbone of landscape ecology 
(Mathey et al., 2015; Richter & Weiland, 2011). The definition of green infrastructure is strategically 
planned and managed networks of natural lands, working landscapes and other open spaces that conserve 
ecosystem values and functions also provide associated benefits to human populations (Benedict et al., 
2012; Breuste et al., 2015). Therefore, based on literatures, green infrastructures in the United States and 
the Europe are best achieved through an integrated approach to land use management and strategic 
planning in ecological network.  

Article Info: 
Received: 31 August 2016 
in revised form: 8 September 2016 
Accepted: 29 November 2016 
Available Online: 8 March 2017 
 

Keywords:  
Land use change, landscape 
pattern, ecological connectivity, 
GIS, urban planning 
 

Corresponding Author: 
Poppy Indrayani 
Kyushu University, Japan 
Email: poppy@doc.kyushu-u.ac.jp   

OPEN ACCESS 

http://dx.doi.org/10.14710/geoplanning.4.1.9-18
http://dx.doi.org/10.14710/geoplanning.4.1.9-18
mailto:poppy@doc.kyushu-u.ac.jp


 
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Ecological landscape theory has provided set quantitative methods namely landscape metrics to 
characterize landscape pattern. However, there is a lack of quantitative methods to effectively assess 
ecological connectivity at regional scale. Marulli and Mallarach (2005) proposed a methodological approach 
used in quantitative landscape ecology, allowing to turn current theories into useful spatial analysis tools 
for regional land use planning. Most of the previous research in the land use changes of Makassar area 
(Figure 1) has been carried out using a remote sensing technique. Moreover, the spatial scales of the 
research settings deal with the metropolitan region.  

Figure 1. Geographic location of the Makassar region and Tallo River area 

 

 

This study aims to evaluate land use changes using a topographical map of 1:50,000 scales with 
Geographic Information System (GIS) grid system analysis dealing with the Makassar city scale and assess 
its impacts into the landscape ecological connectivity index. In order to effectively evaluate the respective 
goal, land use maps using a 50 m grid mesh were developed from availability of the digital topographic 
maps. Land use changes during the period from 1997 to 2012 were simulated based on 50 m grid mesh 
calculation, then a number of landscape properties were identified. Adopting the ideas and methodologies 
in landscape ecology, the study provided an assessment regarding the impact of land use changes on 
landscape ecological connectivity index. Several landscape metrics were calculated, and the evolution of 
the landscape ecological connectivity was assessed using GIS. 

2. DATA AND METHODS 

2.1. Land use planning of the Makassar region  

Makassar is the largest city in Eastern Indonesia and the capital of the province of South Sulawesi 
(Figure 1). In 2016, the population counts about 1.7 million, with an average density of 8000 inhabitants 
per square kilometer. Makassar covers total area of nearly 177 km2 which is divided into 14 districts. The 
Mamminasata Metropolitan Area (covering the city of Makassar and the regencies of Gowa, Maros, 
Takalar) has a population of approximately 2.5 million which is expected to grow to 2.9 million in 2020. 
Recently, the government of Makassar city proposes to create Tallo River area where the city can 
strategically manage urban development in the currently undeveloped land. Moreover, the large area on 
downstream of Tallo River is near the city center. It has been endorsed in the Makassar City’s Spatial Plan 
(2012) identifying the Tallo River as a special development area. Therefore, an evaluation of the impact of 
land use changes on the ecological landscape pattern of Tallo River area is indispensable to ensure that the 
strategic land use planning can be optimized to protect the environment. 

2.2. Land use maps in 1997 and 2012 

In this research, the land use maps in 1997 and 2012 were developed from the availability of digital 
topographic maps of 1:50,000 scales provided by the Regional Development Planning Agency of Makassar 
shown in Figure 2 (Indrayani et al., 2016). Land use division was determined based on land use boundary 
line of the topographic maps. The land use divisions for 1997 and 2012 were reclassified into 10 categories. 

 

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2.3. Land use changes between 1997 and 2012 

In GIS process, the land use polygons from the topographic maps were intersected with 50 m grid 
mesh from grid division analysis. The grid-mesh has orientation of the world grid system. Intersected land 
use polygons were calculated to obtain the maximum area in each grid feature. Land use value for each grid 
was dissolved based on maximum area analysis in GIS. The 50 m grid mesh based scale for land cover 
values can be obtained (Zhou et al., 2014); accordingly the spatial matrix analysis of GIS for land use 
changes can be done. By utilizing the developed land use maps, an analysis of land use changes based on 
0.25 hectares area size was performed. Land uses for the period of 1997-2012 have shown important 
changes, urban surface has grown up from 4,805 to 8,098 hectares which represents almost twice the 
urban expansion of 15 years period. In the land use map of 1997, the existence of crop field, fishpond, and 
swamp field has not been clearly visible. It is revealed that urban, paddy field, garden field, and mangrove 
forest occupied 27%, 27.8 %, 26.7%, and 11.9% of the Makassar region, respectively. In the Eastern part of 
Makassar, the land area was bordered by the sea in which some of the sea areas were assumed as future 
reclaimed land. 

In 2012, urban has increased to 45.6 % of the Makassar region, in contrast that of paddy field, garden 
field, and mangrove forest has decreased to 16.3%, 9.3%, and 2.6%, respectively. The increasing 
phenomenon of urban area from 1997 to 2012 have caused the land cover of fishpond (13.5%) and swamp 
field (2.1%) existed in 2012. Moreover, a large area of fishpond was developed due to the conversion of 
mangrove forest for local peoples to practice fishery In  recent years, the impact of regular flooding could 
be potentially increased in the Tallo River basin as a natural drainage catchment area, supported the local 
peoples to create the fishpond as a livelihood. In addition, the occurrence of swamp field and fishpond 
counted as 15.6% from the Makassar region, has transformed the pattern of mangrove forest, shrubs field 
in the vicinity of Tallo River area. Figure 3 shows the comparison of the area (hectares) of land use change 
values in the Makassar region from 1997 to 2012. 

Figure 2. Development of land use maps of the Makassar region  

   

(1997)                                                                                  (2012) 
 

Figure 3. Comparison of land use change values from 1997 to 2012  
 

 

 

 

 

 

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3. RESULTS AND DISCUSSION 

3.1. Identification of Ecological Functional Areas 

The decision about the ecological functional areas that needs to be connected is essential for assessing 
the ecological connectivity (Girvetz et al., 2008; Li et al., 2013). Using the land use maps, a topological 
analysis of the land cover categories was performed (Table 1). Based on a review of existing literatures, 
depending on each land cover, simple ecological functional areas are defined by a minimum surface (Sr = 50 
hectares) (Bender, Contreras, & Fahrig, 1998). The areas that could not be considered as simple ecological 
functional areas can be grouped into forest, agricultural or agroforest mosaics (Forman, 1995). The GIS 
spatial analysis obtained six types of ecological functional areas, as shown in Table 2. Forest is considered 
as a relative small spectrum size (less than 50 hectares), thus it is not included in the ecological functional 
areas. All remaining areas were considered fragmented areas. Results of the ecological functional areas in 
the Makassar region are shown in Figure 4.  

As expected, the ecologically functional areas C’r (55.42%) of the total area in 2012 was lower than the 
ecologically functional areas C’r (87.79%) in 1997. The largest ecologically functional areas in 1997 were 
paddy field covering 98.0% of the total area, followed by garden field and mangrove forest covering 86.9% 
and 77.1%, respectively. In 2012, paddy field, garden field and mangrove forest decreased into 79.5%, 
38.2% and 50.7% of the total area, respectively. In particular, small swamp field, which hold the vertebrate 
biodiversity (13.7% of the total area) were the important habitat type, and therefore the most vulnerable. 
To deal with the landscape ecological connectivity analysis, the following sections described the Barrier 
Effect Index (BEI) and the Ecological Connectivity Index (ECI). 

Table 1. Land cover categories  

Code Land Cover 

B1 Urban 

B2 Water 

B3 Fishpond 

C1 Forest 

C2 Mangrove forest 

C3 Swamp field 

C4 Paddy field 

C5 Garden field 

C6 Shrub field 

N1 Crop field 

 
Table 2. Results of topological analysis showing the ecological functional areas  

 
 
3.2. Calculation of the Barrier Effect Index (BEI) 

Urban development often hinders the movement of ecological processes. Barriers include all artificial 
land uses that create obstacles to the flow of energy, information, or matter across the matrix, or in other 
words, the landscape resistance. To reflect the barrier effects in measuring ecological connectivity, a group 
of artificial attributes were designated with different weights on each attribute depending on the relative 
influence on the entire landscape. The maximum level of weight was given to the built-up areas comprised 
of high and medium-density residential development because for the most time the built-up areas are 
impermeable to movement of many species (Fahrig, 2003). Since this study does not consider water body 

Code Land cover Total area (ha)  Sr (ha) 1997 2012 

1997 2012  ha % ha % 
C'1 Forest 8.58 44.52  50 0 0  0 0  
C'2 Mangrove forest 2,088.57 471.69  50 1,610.20 77.10  239.13 50.70  
C'3 Swamp field 0 382.74  50 0 0.0  52.40 13.70  
C'4 Paddy field 4,805.79 2,795.54  50 4,711.80 98.0  2,222.43 79.50  
C'5 Garden field 4,705.47 1,663.63  50 4,088.34 86.9 0 634.93 38.20  
C'6 Shrub field 520.2 476.58  50 237.47 45.60  84.73 17.80  

  Total 12,128.61 5,834.70    10,647.81   3,233.62   

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related species, water bodies such as rivers, lake and fishpond were counted as medium-level barriers. The 
ecological connectivity model is primarily based on the least-cost analysis considering the ecological 
functional areas and an impedance surface which incorporates the barrier effect and the potential affinity 
matrix. To calculate the effects of artificial barriers on ecological and landscape connectivity, a barrier 
effect index (BEI) was defined (Marulli & Mallarach, 2005) as follows: 

BEI = Yi/Ymax                                    [1] 

where,  

Yi: the value of the barrier effect in a pixel,   
Ymax: the maximum value of the barrier effect calculated on a given area. 

The BEI was based on the weight that each barrier type (Table 3), the affected land use class, and the 
distance from the barrier, according to the assigned potential impact matrix and logarithmic relationship 
with distance. Thus, it reflects an impedance surface, where ai corresponds to the maximum significantly 
affected distance for each type of barrier, and Ai corresponds to the potential impact value for each type 
(Table 4). Based on Marulli and Mallarach (2005), it was assumed that the effect of a single barrier from a 
given point is logarithmic and decreasing as distance increases, according to the following expression: 

Ys = bs-ks1.ln(ks2(bs-d’s)+1)                       [2] 

where, 

bs: the weight of each barrier type, ks1 and ks2 are constants for logarithmic decreasing function 
d’s: the adapted cost distance per barrier type.  

The BEI model applies the cost distance analysis using GIS and requires two GIS layers (a source layer 
and a friction resistance layer) as the input of the model: one is origin surface for each barrier type and 
second is impedance surface from the potential impact matrix. The principal algorithm underlying the cost 
distance model is the least-cost method. In this way, the cost value in each cell represents the distance to 
the source, measured as the least effort (lowest cost) in moving over the resistance layer. The cost distance 
model individually calculates the barrier effect Ys for each sub-class type. Thus, the entire barrier effect in 
the landscape is defined as the addition of the effects of all barrier types on a given area. BEI is relative 
index to give values within an ordinal scale from 1 to 10, as shown in Table 5. The application of the BEI 
shows that in 1997 at least 61.08 % of the Makassar region was under negative impact from urban area, 
and increased at least 83.54% in 2012 (Figure 5). The maps resulting from the application of the BEI 
confirmed the distribution of areas in 2012 slightly affected by barrier in the Tallo River area (red-dotted 
lines), in contrast with the pervasive impacts spreading in the eastern part of the Makassar region. 

Figure 4. Distribution of the ecological functional areas in the Makassar region (Own Analysis, 2016) 

   

(1997)                                                                                     (2012) 

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Table 3. Weighted value system for the calculation of the BEI  

Code Type Weight (bs) ks1
a ks2

a 

B1 Urban b1= 100 k11=55.52 k21=0.051 
B2 Water b2= 60 _b _b 
B3 Fishpond b3= 60 _b _b 

a Constants for a logarithms decreasing function (α=0.3)  
b For s = 2 there is not surrrounding spatial affectation; Y2 = B2   

 
Table 4. Impact matrix for the calculation of the Barrier Effect Index (Own Analysis, 2016) 

Code Type Classes includeda Affectation 
coefficient (a1)b 

Affectation value 
(A1) 

V1 Neutral N1 a1=1000m A1=0.10 
V2 Agriculture C4, C5 a2=750m A2=0.13 
V3 "Natural" C1, C2, C3, C6 a3=500m A3=0.20 
V4 Barrier B1, B2, B3 a4=250m A4=0.40 
(An=b1/an)         
a class description in previous table   
b a1 defines the maximum significantly affected distance by each type 

 
Table 5. Ranking of the barrier effect in the landscape (modified from Marulli and Mallarach (2005)) 

Barrier Effect Index Effect Type of barriers 
0 Non existent Lack of anthropogenic barriers. Total permeability of matter, 

energy and information 
1 Low impact Small and scattered barriers, such as isolated farms 
2 High ecological permeability remains 
3 Medium impact Low density residential areas 
4 Medium ecological permeability remains 
5 High impact Scattered urban, commercial or industrial areas 
6 Low ecological permeability 
7 Very high Synergic combination of urban areas  
8 Very low ecological permeability 
9 Critical impact Synergic combination of large, high density urban areas  
10 Minimum ecological permeability 

 
3.3. Evaluation of the Ecological Connectivity Index (ECI) 

Ecological connectivity refers to the functional aspects of the actual connection between the different 
elements of the landscape (Pino & Marull, 2012). An ecological connectivity index (ECI) was defined based 
on a least-cost model that considers the different functional ecological areas and an impedance surface 
which incorporates the barrier effect and a potential affinity matrix for all the land use types. The model 
applied the cost distance analysis in GIS using two input data: one is origin surface for each type of 
ecological functional area and second is impedance surface resulting from the application the effect of the 
barriers. Finally, to transform the continuous values of the cost distance to discrete values based on a 
decimal scale, the ECI was calculated, according Marulli and Mallarach (2005) to the following expression: 

 
ECI = 10-9.ln(1+(xi-xmin))/ln(1+(xmax-xmin))3                    [3] 

 
Where, xi is the adapted cost distance value in a pixel, xmax is the maximum and xmin is the minimum cost 
distance values on a given area.  

It is considered that this index reflects a kind of general ecological connectivity, since its computation 
includes all the ecological functional areas. Thus, it is a generic approach untied to specific indicator 
species. An interesting propriety of the ECI is that it has a relativistic distribution of values, always giving 
values between 0 and 10. This feature is useful to compare different alternatives. Ranking distribution of 
ECI allows the identification of areas of low absolute value as the only viable way of connecting existing 
ecological functional areas.  

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Figure 5. Maps resulting from the application of the BEI on the Makassar region (Own Analysis, 2016) 

     
 

(1997)                                                                                    (2012) 

Forman (1995) described landscape connectivity as a degree of spatial connectedness among landscape 
elements such as patches, corridors, and matrix. Patch connectivity focuses on amount and arrangement of 
habitat patches, and thus effective distance between the patches becomes an important issue (Broquet et 
al., 2006). Corridor connectivity identifies linear features to promote dispersal through connectivity 
restoration (Graves et al., 2007). Matrix connectivity evaluates overall landscape mosaic, including 
landscape matrix to maintain maximum landscape continuity of non-built areas (Levin et al., 2007).  

Various methods were developed from general landscape ecological principles to measure landscape 
connectivity. Although there are a wide range of proposed connectivity measures and geometric analyses 
from very simple to highly sophisticated (Selman, 2006), the approaches were categorized into four groups 
(connectivity metrics, least-cost analysis, empirical models and graph-based models). The use of least-cost 
analysis has been increased in recent landscape and ecological connectivity research because it calculates 
effective distance, a measure for distance modified with the landscape resistance (Adriaensen et al., 2003). 
This method can be implemented in GIS efficiently and effectively. Comparing to the previous similar study, 
the results of GIS analysis were able to evaluate each of the land use changes and its effects on the value of 
landscape connectivity index, spatially and temporally. 

The GIS methodology employed in this study to assess ecological connectivity in the Makassar region 
revealed spatial processes, such as land use changes based on 50 m grid mesh analysis, and assess spatial 
differentiation of ecological connectivity index from urban expansion between 1997 and 2012. The analysis 
result observably showed that land use changes between 1997 and 2012 which occurred in the Makassar 
region have in turn caused profound changes on landscape pattern. While in 1997, the Makassar region 
was mainly a paddy field, garden field and mangrove forest, recently it is an urban area where urban spaces 
occupy most of the area. There has been a large decrease in ecological connectivity in the entire Makassar 
region due to the high fragmentation produced by urban sprawl (Figure 6).  

From a landscape ecological point of view, one of the main trends in the Makassar area during the last 
fifteen years has been the rapid fragmentation and transformation of the natural landscape, creating 
numbers of patches of habitat, increasingly smaller and disconnected. Conversion of each land use value 
into urban area such as paddy field to urban, garden field to urban, mangrove forest to urban and shrubs 
field to urban showed different levels of impact on the ECI (Figure 7). The distribution differentiation of ECI 
due to conversion of each land use value (1997) changed into urban (2012) using analysis of GIS showed 
that the shrub and mangrove forest in the vicinity of Tallo River Area has relatively high impact levels to the 
ECI (Figure 8).  Therefore, a development plan is currently being considered in the Tallo River Area and if 
appropriately designed it could mitigate the loss of ecological connectivity.  

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Figure 6. Comparison of ECI for ecological functional areas (Own Analysis, 2016) 

   
(1997)                                                                                  (2012) 

 

Figure 7. (a) Land use values changed into urban; (b) Differentiation of the ECI (Own Analysis, 2016) 

 
(a)                                                                                                (b) 
 

Figure 8. Differentiation of ECI resulting from the conversion of each land use (Own Analysis, 2016) 

 

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Moreover, there is an urgent need for green infrastructure strategies that facilitate the protection and 
restoration of environment, especially the remaining few mangrove forest, swamp field and agricultural 
field in the Tallo River area. Study on the GIS based green infrastructure planning coordinated with 
ecological connectivity analysis is essential (Mao et al., 2012). There is an urgent need for strategies that 
facilitate the protection and restoration of ecologically connected landscapes (Parcerisas et al., 2012; 
Tscharntke et al., 2012). 

4. CONCLUSION 

An evaluation of land use changes and landscape connectivity index was conducted using GIS. The 
ecological functional areas were identified by topological analysis using the developed land use maps of 1: 
50,000 scales. Landscape metrics method proposed by Marulli and Mallarach (2005) was adopted to 
calculate the BEI and ECI in the Makassar region. The impact of the conversion of each land use value in 
1997 into the urban area in 2012 on the differentiation of the ecological connectivity index level was 
evaluated. It is shown that the GIS has important function to proceed each step of spatial analysis for land 
use changes and landscape pattern analysis model.   

5. ACKNOWLEDGMENTS 

This work was supported in part by Indonesian Government Scholarship Program (DIKTI), Indonesia. 

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