It is predicted that urban population will gain 66% of the world’s total population by 2050, which means global urbanization, then continuing to increase at the current level, especially in developing countries [1
]. Urbanization is always accompanied by spatial expansion of urban land [2
]. In Southeast Asia, the urban expansion rate is approximately 2.8% higher when compared to other urbanized regions of the world [3
]. Consequently, green space had increasing pressure during the urban expansion and caused many serious ecological problems, psychological well-being, and the health of urban dwellers [5
]. Thus, the green space transformed into the built-up area has become one of the leading causes of urban environment destruction [6
]. Therefore, it is essential to examine and to monitor the change of green space coverage in spatial complexity of the urban landscape when rapid expansion occurs.
Recently, urban expansion is measured by horizontal and vertical urban growth. A third dimension using urban volume is used as an indicator of vertical development [7
]. Spatial information on the third dimension is a key indicator of urban expansion in dense urban areas where multiple land uses exist [9
]. Attention has been addressed to urban modeling with the integration of horizontal and vertical dimensions, not only from the perspective of the scientific community but also from that of urban stakeholder [10
]. The inclusion of the third dimension to investigate the thematic factors of urban systems is very important in monitoring urban development and detecting land use/land cover (LU/LC) changes [11
Remote sensing (RS) data with various spatial resolution and image analysis techniques have been applied to monitor urban expansion with both horizontal and vertical dimensions, while Geographic Information System (GIS) can identify and investigate the configuration of urban expansion in the regard of land use pattern [12
]. The spatial structures and configurations of land use patches have significant impressions on urban environmental attributes. Thus, numerous landscape metrics have been developed to measure the complexity of the urban landscape patterns [15
]. Landscape metrics can be applied over an entire area to reflect the overall situation of the urban expansion pattern and can also be efficiently used to provide specific information of urban expansion pattern in patch or class levels [16
]. The patch analysis has been extensively used to characterize, monitor, and assess landscape pattern and composition [17
], and to study LU/LC changes [19
Several studies have been taken to detect both horizontal (2D) and vertical (3D) urban expansions using RS data. Multi-temporal high resolution images were utilized to investigate changes in individual buildings [21
]. 3D building information was extracted from Quickbird images to examine the vertical change of urban morphology [22
]. Urban volume was estimated using elevation point data, topographic map and building block outline [9
]. The study by [23
] used the combination of historical 2D urban change and presented 3D city model acquired from LiDAR data. While the study by [24
] used high spatial resolution RS data and a statistical method to estimate the population based on the building height. Those earlier studies employed the very high resolution RS data, however, the availability might be very limited, especially in developing countries. Therefore, our study attempted to use bi-temporal RS data, including image and Digital Surface Model (DSM), having very different spatial resolutions.
Advanced Visible and Near Infrared Radiometer type 2 (AVNIR-2) image and Panchromatic Remote Sensing Instrument for Stereo Mapping (PRISM) DSM acquired by the same platform, the Advanced Land-Observing Satellite (ALOS), were used for analyzing time 1 (2010). Orthophoto and LiDAR DSM by the aerial-LiDAR mapping survey were used for analyzing time 2 (2016). The same time and same platform for acquisition address an advantage in the accuracy enhancement of urban volume [10
]. Moreover, our study investigated the green expansion both in the horizontal and vertical dimensions, which were not examined by previous studies. While considering the green space as an environmental indicator, the urban volume, including built-up and green volume, is crucial for the urban development. Green volume delivers a new perspective in quantifying the green quantity essential for urban greening study [10
We selected sub-Central Business District (CBD) of Surabaya, Indonesia as a case study, since it has experienced rapid growth in population and capital investment. To counterbalance the urban expansion, the government has set up regulation to promote the harmonized development in providing the green environment. “The Regulation of Surabaya City Number 12 Year 2014 Concerning Spatial Plan of Surabaya for 2014–2034” states that at least 30% of city area have to be green [25
]. Therefore, the purpose of this study is to examine the urban expansion, including built-up and green space for both horizontal and vertical dimensions using geospatial analysis. We have mainly three objectives: (1) the estimation of the built-up and green expansions in horizontal (area) and vertical (volume) dimensions, (2) the investigation of the structure and configuration of the area expansion using a patch analysis, and (3) the measurement of the volume expansion rate.
The BA and GA expansions were 100.48 ha and 287.98 ha, respectively. The low BA expansion was generally presented in the dense residential area in the north eastern part of Jagir Wonokromo road. The high BA expansion for offices or hotels was frequently identified in sidelong the artery roads. The GA expansion presented larger than BA expansion since the transformation of bareland to playground or park. The tree planting sidelong road was seen in sufficient numbers. The program by the government for increasing the green space accommodates the policy that new commercial building construction has to provide green patches, such as garden or backyard. However, the presence of green space portion in LU/LC 2016 revealed at 26.89%. Another strategy to accelerate the greening coverage should be considered especially in the dense residential area. The green roof or green garage may be adopted and applied in the local policy to create green neighborhood.
Applying the patch analysis, the result indicated that the mean of BA expansion was smaller than that of GA expansion. The connectedness of BA expansion was greater than the one of GA expansion. The BA expansion was smaller due to the limited land availability which caused the higher contiguity in the dense area. The low expansion for both BA and GA in discrete configuration was identified in the dense residential area. The sufficient BA expansion in the sprawl pattern was detected in industrial areas, which were dominated by the new fabric construction among the existed buildings. Interestingly, the sufficient GA expansion was also detected, which was mostly contributed by the construction of the new park in surrounding fabric to provide the green environment for their workers. Surprisingly, the high GA expansion was recorded in the sub-CBD area where the several buildings in a commercial block were established. In conjunction with the commercial block establishment, the garden designed as aesthetical façade was also constructed, then the high GA with an aggregate pattern was generated.
The result of the correlation analysis revealed that the BA expansion affected the connectedness, likewise for the GA expansion. Herein, new parks and green space into the new form of linear arrangement with high connectedness provided the high accessibility for residents. The residents with higher proximity to green space were satisfied with their accessibility to green space [68
], and they paid significant amounts of money to get a house for living close to the park [69
]. The spatial planning should be considered in the development of connective green space in neighborhood landscape at various levels [70
]. This study found that the built-up establishment filled merely the bareland or vacant land, which was located among the existed built-up to facilitate the market-oriented facilities. Thus, the Surabaya government wished to create the policy of urban land transformation in the sustainable context.
The LU/LC change showed the significant BA and GA expansion of 11.54% and 95.61%, respectively. The rapid development had addressed the increase of built-up area for commercial use along artery roads. The economic indicator became the driving force for the urban development [53
]. Thus, the industrialization and urbanization had stimulated economic growth demand on manufactory and housing [54
The result confirmed to BV and GV expansion approximately on 20.6% and 54.9%, respectively. The larger portion BV expansion than BA expansion showed that built-up growth led to vertical development rather than the horizontal. The new development was mostly designed for buildings with medium height about 7–14 m functioned as single shops or offices. The vertical dimension of urban growth reported by the previous study can enhance the land use efficiency and the economic benefit, including employment opportunity and population density [55
The prominent green area expansion was determined by the removal of the bareland. The new form of green had figured out the transformation from the big patches of natural grassland to a long structure of green shape, such as the street tree. The street trees play an essential role in the urban environment by improving air quality, providing shade, decreasing carbon footprint, and reducing the urban heat island effect [56
]. Moreover, the long configuration of trees can link among green spaces to provide a cohesive node of Urban Green Infrastructure (UGI) [57
The mean GR was higher than the mean BR for 75.394% and 78.375%, respectively. The built-up expansion was caused by the establishment of buildings with spontaneous development in the dense neighborhood. The green expansion was contributed by trees that were planted in the garden or as the street trees. The urban development integrated with small scale of green infrastructure provides an important mechanism for gaining the benefits in multi-functional level [70
]. However, the ratio of BR to GR exposed that the imbalanced expansion between BV and GV was mainly detected as the new building construction in the surrounding artery and toll roads.
The further policy and strategy of sustainable planning should be a prime concern to lead the harmonious development of built-up and green environment. The big sites without GV expansion were mainly detected in the bareland, which could be reformed to efficient land use by integrating economic and environmental development. The commercial and residential building can be established in conjunction with the green space construction. Therefore, the workers or residents will be provided by the green neighborhood environment. Positively, the proposed land conversion can improve the imbalanced development (Figure 11
b). The green volume with high trees might also be a concern for providing the high green quality environment. Regarding the landscape ecology, the dense vegetation can support a habitat diversity [71
]. Moreover, the complex configuration and structure of vegetation are considered by residents to promote aesthetical aspect [72
Our approach is in accordance with the framework by [73
] in the regard of six fundamental aspects of urban form which are organized into three overarching components. We focused on the first component of material including built-up as aspect 1 and green space as aspect 2. The built-up feature was used to represent the built infrastructure of city, and the green signature was used to represent land surface features with biological activity. Both materials reflect the visible urban form, as well as they change over time [73
]. The configuration as the second component was involved by employing the 2D and 3D space in the spatial pattern analysis. The building height shows the positive correlation with land use, and the height information reflects the plant growth over time. Without 3D information, high-rise building and single storey are represented in the same mode; moreover, the building volume can address the building occupancy or population density [74
]. Timeframe as the third component was applied in bi-temporal (2010 and 2016) to investigate the built-up and green expansion. The time selection was considered for evaluating the green program, which was formally launched by The President of The Republic of Indonesia in Law of The Republic of Indonesia Number 26 Year 2007 Concerning Spatial Management [75
Using the hybrid classification approach, the high overall accuracy can be achieved for both medium and fine resolution image. However, some limitations raised in this study regarding the accuracy of the classified ALOS image, the difference of the LU/LC maps, and the vertical reference system of DSM. The bareland and green space classes were speciously over-classified in ALOS image. More land area was assigned to those classes in the classified image compared to the ground truth references. Those over-estimations were indicated by their user accuracies being smaller than the producer’s accuracies (Table 4
). The green space containing grass with drying appearance was classified to bareland, generally occurred in the residential area. On the other hand, the bareland was occasionally classified into green space. It normally occurred when the weed grass was mixed with the bareland. This situation was frequently happened in Asian countries, as reported by [57
], where cropland is converted tentatively to bareland when the land is cleared for preparing the construction site, and this bareland would frequently be covered with weed grass during the transition period.
The LU/LC map differences were mostly caused by the difference in the spatial resolution of dataset used in this study. The classified ALOS image produced classes in more fragmented structure with slight boundary. Contrary, the classified orthophoto generated classes in more aggregated configuration with a clear boundary. The differences were mainly identified in the urban expansion area, especially in the residential areas and the commercial mixed residential areas. The overestimated bareland in LU/LC 2010 by ALOS image accounted for the reduction of the built-up and green area existence. The green space along the road was also failed to be detected in LU/LC 2010. When we checked through google earth image history, it appeared that small green patch was classified into bareland. Thus, the improvement of classification by applying an advanced fusion method will be proposed for a future study. The difference of the vertical reference system for DSM might also produce the gap between the generated SFHs. Even the highest DTM generated by grid size 45 m is close to the highest LiDAR-derived DTM. However, the systematic error may address because of undulation of the geoid. The future study is necessary to verify the detailed assessment.
This study empirically investigated the urban expansion of the horizontal and vertical development in the sub-CBD area of Surabaya. The geospatial approach was conducted for examining the urban form for bi-temporal (2010–2016) in conjunction with two material aspects (built-up and green types) and two configuration aspects (2D-3D space and spatial pattern).
The result revealed that the notable increment of built-up and green area was shown in the particular area. The green area expansion presented the adequate portion which was mainly contributed by the conversion of bareland to playground or parks. However, the built-up area expansions were less than the volume expansions, about 20.6%. It revealed that built-up growth led to the vertical development rather than the horizontal. The expansion of built-up area tended to scatter in fragment configuration. The expansion of green area tended to aggregate in the linear pattern. The high built-up volume expansion was frequently detected in sidelong artery roads where the high buildings for hotels or offices were established. While for green space, the high green volume expansion was partially detected in the low built-up volume expansion when the trees planted in sidelong roads or the backyard gardens had grown significantly. However, imbalanced development presented that the built-up growth was higher than the green growth, because more vertical buildings were established. Thus, the green improvement was needed to promote the sustainable neighborhood environment.
The proposed approach of volume expansion rate can assess the vertical development in consideration with the neighborhood growth. This approach was convenient to investigate the vertical development of built-up. However, the approach seems tough to apply for the green class, due to the irregular shape and the similar structure with road.
In this study, we used the multi-spatial resolution datasets due to the lack of the fine resolution data for 2010. A future study could refine the differences in the result generated by applying some advanced methods to enhance the accuracy of LU/LC. Also, the detailed assessment in DTM generation would improve the accuracy of SFH. Presenting the overall accuracy of LU/LC maps in the adequate threshold by applying the hybrid classification and the successful validation of SFH 2010, our result can be accepted for understanding the urban area extension and urban volume expansion. This study can be used as a reference to improve the neighborhood environment through greening programs in the context of sustainable urban development.