Urban Sprawl and Land Value in Batangas City,Philippines

Abstract

This article, using a combination of quantitative and qualitative approaches, illustrates that Batangas City for the period 1990–2015 was leaning towards a sprawling development. Areas where considerable sprawling has occurred were further investigated in relation to land value. The study also revealed that there is a moderate positive relationship between sprawl and land values in the city, which meant that land values have increased in areas where considerable sprawling has occurred.

Keywords

Urban sprawl land cover land value Batangas City

Introduction

According to the World Urbanization Prospects of 2018, the global urban population is projected to increase by 2.5 billion urban dwellers, with around 90% of the increase taking place in Asia and Africa (United Nations, 2019). In Southeast Asia, half of the population lives in the cities and it is expected that an additional 70 million people more will live in cities by 2025 (ASEAN, 2018). The case of Metro Manila, the capital region of the Philippines, is a classic case of rapid and uneven urbanization. Metro Manila has transformed into a megacity expanding to neighbouring regions due to sustained economic growth. The uneven urbanization between Metro Manila and its neighbouring region, however, has resulted in urban sprawl along the fringes caused by the search for cheaper land outside the capital region and weak implementation of local plans and zonal ordinances (UN Habitat, 2016).

Batangas City in the Calabarzon region, located south of Metro Manila, is among the top destination for many urban migrants. The adjacent location of Batangas City, together with its strong linkages with Metro Manila, has transformed the area into a viable source of jobs, business and other livelihood potential from other regions (UN Habitat, 2016). The economic, demographic and environmental transformation of the city has resulted in changes in the spatial configuration of the city. The rapid urbanization resulted in the rise of a sprawling development within the city.

Using Batangas City as its study area, this article uses both quantitative and qualitative approaches to explore and describe sprawl in the city. First, remote sensing and geographic information system (GIS) is used to determine the pattern of land cover change in the city over the last 25 years (1990–2015). Second, to explore and describe the pattern of urban sprawl in the city, and in recognition of the limitations of any of the metrics that determine the degree of urban sprawl, the study employed a mixed methodology by applying Shannon’s entropy in combination with different but complementary sources of data and analytical tools. To further validate the existence of sprawl in the city, several qualitative methodologies were also used. After having established the presence of sprawl in the city, the study then explored the relationship between land value and sprawl. It is hypothesized that the changes in land value manifest in the underlying locational and physical transformations that sprawl has contributed to. Describing the relationship between these two variables illustrates the economic implications of sprawl in the city.

Studies on Sprawl and Land Value

The definition of urban sprawl has been a contentious topic among scholars and planners (Bhatta et al., 2010; Ewing, 1997; Frenkel & Ashkenazi, 2008; Johnson, 2001; Nguyen, 2010; Sudhira & Ramachandra, 2007). An earlier definition states that sprawl is ‘the scattering of new development on isolated tracts, separated from other areas by vacant land’ (Ottensman, 1977). A comprehensive literature review of Galster et al. (2001) identified the prominent characteristics of sprawl, namely, (a) cause of unwanted externalities, (b) consequences of land use behaviour, (c) patterns of land development and (d) process of development. From their review, a conceptual definition of sprawl is suggested: ‘sprawl (n.) is a pattern of land use in an urban area that exhibits low levels of some combination of eight (8) distinct dimensions: density, continuity, concentration, clustering, centrality, nuclearity, mixed uses, and proximity’. While the debate on the definition of urban sprawl remains, a consensus on the definition is characterized by unplanned and uneven pattern of growth, propelled by multitude of processes, which leads to inefficient resource utilization (Bhatta et al., 2010).

Several studies have utilized various quantification devices to measure the sprawl dimensions outlined in the work of Galster et al. (2001). In determining a sprawl’s density, density gradient is among the devices used to define the ratio between urban activity and its location (Alperovich & Deutsch, 1992). Accessibility of urban sprawl was determined by measuring the road lengths, road areas and commuting time of households (Hadly, 2000) or by calculating the fractal dimensions of road networks (Benguigui, 1995). Spatial geometry devices, including Leapfrog (Galster et al., 2001), fractal dimension and mean patch size (Batty & Sik Kim, 1992) were used to quantify the configuration and composition of an urban landscape. Finally, to determine the spatial concentration or dispersion of a city, trends in population growth and built-up change, built-up area density (Bhatta, 2009) and Shannon’s entropy were used in a number of studies (Yeh & Li, 2001). Despite the abundance of various sprawl indicators, planners and scholars admit that no indicators are perfect and require further refinement (Bhatta, 2009; Nazarnia et al., 2019).

Scholars and planners are likewise divided on the consequences of urban sprawl. Critics of sprawl argue that sprawl has led to vehicle miles travelled (Bento et al., 2005; Cervero & Wu, 1998; Ewing, 1997), less energy efficient built-up area as compared to compact cities, the loss of resource lands and social segregation (Ewing, 1997), among other impacts. Sprawl supporters, on the other hand, argue that sprawl has led to low-density residential lifestyles, short commuting times for those who live and work in the suburbs, ease of movement, a broader choice of places to work, exercise strong influence on their local governments (Downs, 1998), among other benefits. Sprawl also facilitates the extension of a central business district, the development of suburban areas and the creation of new nodes of agglomeration (Archer, 1973; Cavailhes, 2003; Clawson, 1962; Nechyba & Walsh, 2004; Ottensmann, 1977; Sinclair, 1967). Such physical and economic transformations were observed to influence the property values in remote areas, farmlands and peri-urban fringes (Cavailhes, 2003; Jin et al., 1997; Livanis et al., 2005; Strassmann et al., 1994).

Most studies dealing with land value mainly focus on the factors affecting the land value (Downing, 1973; Scott & Down, 1983), the impact of urban policies on land value (Cho et al., 2008; Nelson, 1988; Ohls et al., 1974) and the relationship of land to tax (Chapman, 2017). In the context of the Philippines, most studies dealing with land focus on land reform (Otsuka, 1991), land grabbing (Bourassa, 1990; Franco & Borras, 2007) and land taxation (Booth, 2014). On the other hand, there are very few studies that investigate the relationship between sprawl and land value (Murakami & Palijon, 2005; Ortega, 2016).

Study Area

Batangas City is a local government unit and the capital of the Batangas province; it falls under the administrative jurisdiction of Calabarzon region. In 2015, Batangas City had a population of 329,874 inhabitants (PSA, 2019) and a population density of 1,165.80 per hectare (CPDO, 2009). Batangas City has a total land area of 28,541.44 hectares (CPDO, 2009). Of the total land area, 12.57% was categorized as built-up in 2009, while the remaining 87.43% was categorized as agricultural, tourism and idle lands (CPDO, 2009). The economy of the city transformed from a large agricultural town to commercial, educational, financial and industrial centre in Batangas province. Likewise, the city has developed an international port that accommodates both passengers and cargo.

Land use planning in the city derives its legal basis from Republic Act. No. 7160, known as the Local Government Code of 1991. Through the policy of devolution, local government units (LGU) are primarily responsible for preparing the Comprehensive Land Use Plan (CLUP). The CLUP is comprehensive in the sense that it encompasses the entire territorial jurisdiction of the LGU, including the private, public, and ancestral domains, and also serves as a framework for the co-management of national and local territories between the two levels of government (Serote, 2004).

To achieve positive synergistic effects, the Batangas City CLUP (2009–2018) is consistent with higher development plans, including the Provincial Development and Physical Framework Plan of Batangas and the Regional Physical Framework Plan: 2004–2030, Region-IV-A CALABARZON. The framework plan recognizes six aspects of Batangas City that directly contribute to the economic growth and development of the region, namely, improved international linkages through Batangas City International Port, well-developed industrial zone (evidenced by the nineteen large-scale industries), competitive agricultural production through the city’s contribution in the region’s overall agricultural, fishery and forestry output, improvement of human capital through quality educational and institutions, improved access among the cities and municipalities in the region through the completion of the Southern Tagalog Access Road and promotion of tourist sites evidenced by the historical, cultural, natural and man-made tourist sites in Batangas City.

The most recent Comprehensive Land Use Plan of Batangas City, which covered the decade from 2009 to 2018, adopted the management zone concept to allow and encourage for mixed land uses in the city. The purpose behind the land management zone policy was to prescribe a range of land use activities for specific locations due to shifting economic conditions and changing market preferences (CPDO, 2009). The outcome was 10 land management zones¹ with varying numbers of barangays for each zone. The Primary Urban Zone (PUZ), with 30 urban barangays in its jurisdiction, is currently utilized as an area for high-intensity mixed-used land development. This includes wholesale and retail trade, banking-finance activities and personal and community services, among others. The Secondary Urban Zone (SUZ), with 10 urban and 7 rural barangays, is currently used to provide support facilities to PUC. The area is used for low-to-medium intensity commercial uses, residential houses and government offices (CPDO, 2009). The Northern General Development Zone (NGDZ) and Southern General Development Zone South (SGDZ), with eight rural barangays, is used as the suburban residential area together with community facilities and amenities. The Northern Industrial Zone (NIZ) and Southern Industrial Zone (SIZ), with one urban and four rural barangays, is reserved for medium to heavy industries. The Agricultural Development Zone (ADZ), with 18 rural barangays, is reserved for agricultural-related activities. The Verde Island Zone (VIZ), with five rural barangays, is reserved for recreational and tourism activities. The Ecological Development Zone (EDZ), consisting of 14 rural barangays, is reserved for forestry and tourism activities, with some parts dedicated to the cultivation of tree crops and forest plants. Finally, the Strategic Crops and Livestock Zone (SCLZ) with eight rural barangays, is used for commercial and backyard raising of livestock and other farm animals, together with small to medium food processing factories.

Methodology

Remote Sensing and GIS

The integration of remote sensing and GIS has been widely used in various land use studies. It plays a vital role in mapping real-world features (Thakkar et al., 2014) to better understand a city’s morphology. Remote sensing and GIS offer an efficient, cost-effective and accessible method of data gathering and analysing land resources. Combined, they allow the detection, measurement, projection and simulation of environmental variables for spatio-temporal analysis. For these reasons, they are most commonly used in assessing the structural variation of the land cover pattern (Sarvestani, 2011).

The first phase in mapping the land cover of the city involves obtaining multi-temporal satellite images (Table 1), specifically Landsat 5 TM and Landsat 8 OLI-TIRS with 30-m grid resolution, and spatial data of the administrative boundary of Batangas City from Geological Survey Earth Explorer (US Geological Survey, 2015). Geometric rectification was applied over the satellite images to correctly overlay with the study area. Radiometric correction was also used to calibrate the radiance and reflectance of image data to remove the effects that alter the spectral characteristics of land features (Paolini et al., 2006). Finally, atmospheric correction was applied to determine the valid surface reflectance, soil visibility and temperature values (Lopez-Serrano et al., 2016). These processes aim to improve the interpretability and quality of the satellite images.

Table 1.

Dates of Satellite Imageries Used for the Land Cover Analysis from 1990 to 2015

Year	Mainland	Verde Island
1990	30 November 1988	30 November 1988
2000	21 July 1998 and	21 July 1998
	7 September 1998
2010	9 June 2006 and	6 July 2010
	6 July 2010
2015	17 April 2015 and	29 December 2016
	29 December 2016

Source: This is part of the authors’ research design and data collection limitation.

The second phase utilized ENVI 5.1 software (Exelis, Herndon, VA) to process and classify the satellite images, and ARIS Grid Editor (ARIS B.V., Utrecht, NL) on ArcGIS 10.0 software (ESRI, Redlands, CA) to classify the land cover types into five classes, built-up, agricultural land, water, bare soil and forest (Table 2), based on maximum likelihood using training sites with at least 100 pixels per land cover type. The classification of land cover used the same dataset from 1990 to 2015. The results of satellite image classification are used as an input for spatial analysis functions and area computation.

Once the area of each land cover type is computed (Table 3), the built-up area is extracted and converted to binary maps using various geoprocessing tools to determine urban dispersion or concentration in the study areas.

Table 2.

Land Cover Classification

Land Cover	Definition
Built-up	Areas of intensive use with much land covered by structures including but not limited to residential, commercial, industrial and utilities
Agricultural land	Land used primarily for production of food including but not limited to cropland, pasture, orchards and nurseries
Bare soil	Land, main composed of soils, sands and rocks, with limited ability to support life in which less than one-third of the area has vegetation or other cover
Forest	Areas with trees capable of producing timber and other wood products
Water	Areas covered with flowing or non-flowing waters, including rivers, creeks, streams, canals, lakes, reservoirs, bays and estuaries

Source: Anderson et al. (1976).

Table 3.

Land Cover Share in Batangas City, 1990–2015

Class	1990		2000		2010		2015
Class	Area (ha)	%	Area (ha)	%	Area (ha)	%	Area (ha)	%
Agricultural land	4,943.61	18.01	12,340.62	44.96	3,674.25	13.39	6,347.66	23.13
Bare soil	4,516.47	16.46	833.85	3.04	4,292.10	15.64	2,899.93	10.57
Built-up	1,143.18	4.17	2,122.74	7.73	2,997.72	10.92	3,720.40	13.56
Forest	16,501.77	60.13	12,048.57	43.90	16,343.91	59.55	14,380.28	52.40
Water	340.20	1.24	99.45	0.36	137.25	0.50	96.96	0.35
Total	27,445.23	100%	27,445.23	100%	27,445.23	100%	27,445.23	100%

Source: SHLC Philippines.

Analysis and Discussion

Indicators of Sprawl

Urban Growth and Demographic Trends

Land Cover Trends

Batangas City has a diverse ridge-to-reef geography. Forest and mountains make up the south and eastern portion of the city, while the north and western side of the city mostly contains built-up areas. A small island separated from the mainland, which forms part of the city, can be reached by boat through the Verde Island Passage. A major provincial river, the Calumpang, divides the mainland into two development areas. Figure 1 presents the land cover of the city, while Table 3 shows the area share of every land cover.

Figure 1.

Source: SHLC Philippines.

Forestlands and agricultural areas have dominated the landscape of the city. The forest area declined from 60% in 1990 to 52% in 2015, while agricultural areas increased from 18% to 23% during the same period. Mango, tamarind, banana and limited production of rice are among the agricultural products of the city. Large-scale poultry farming and backyard poultry farming are also practised in some parts of the city.

Built-up Trends

Built-up areas in Batangas City, including Isla Verde, accounted for less than 14% of its land cover in 2015. Between 1990 and 2015, the average annual increase was just 0.9%. This relatively low figure, which owes to sprawling along the fringes of the city, runs against the country-wide norm, especially as Batangas is a major port and industrial city in Southern Luzon and a provincial and regional capital in the Mega Manila conurbation. Table 4 shows the trend of built-up areas in the city.

Table 4.

Built-up Areas in Batangas City, 1990–2015

Class	1990		2000		2010		2015
Class	Area (ha)	%	Area (ha)	%	Area (ha)	%	Area (ha)	%
Built-up	1,140.84	4.2	2,117.77	7.7	2,992.60	10.9	3,717.34	13.5
Non-built-up	26,302.80	95.8	25,325.86	92.3	24,451.03	89.1	23,726.29	86.5

Source: Authors’ calculation from Landsat satellite images.

Batangas City has a dual economy. Commercial-industrial activities and international trade flourish in the north, while manufacturing, together with agriculture and fishing thrive in the south. This economic mix also manifests in the city’s urban expansion. As Figure 1 shows, the built-up areas in Batangas City in 1990 were most dense in the Primary Urban Zone. About 42% of its 883 ha land area is entirely built-up. The focal point of this urban configuration is the población—the historical and the current central business district and seat of the local government. During the study period, a third of the city’s built-up area was in the Primary Urban Zone, despite accounting for just 0.03% of the city’s total land area. Table 5 shows the share of built-up areas in each zone.

Table 5.

Built-up Area in the Zones of Batangas City, 1990–2015

Land Management Zones	Built-up Area, by Zone 1990–2015 (ha)
	1990		2000		2010		2015
	Area (ha)	%	Area (ha)	%	Area (ha)	%	Area (ha)	%
Agricultural Development Zone	82.54	7	145.01	7	125.84	4	177.62	5
Ecological Development Zone	116.83	10	226.87	11	230.65	8	412.40	11
Verde Island Zone	7.38	1	114.26	5	365.01	12	422.78	11
Primary Urban Core	373.70	33	532.93	25	599.95	20	670.01	18
Strategic Crops and Livelihood Zone	32.37	3	64.14	3	134.36	4	181.07	5
Secondary Urban Core	380.41	33	717.90	34	1,114.24	37	1,312.42	35
Southern General Development Zone	30.38	3	55.50	3	72.51	2	97.82	3
Northern General Development Zone	6.27	1	19.60	1	88.80	3	104.10	3
Southern Industrial Zone	104.76	9	209.33	10	232.32	8	297.94	8
Northern Industrial Zone	6.19	1	32.23	2	28.93	1	41.19	1
City	1,140.84	100%	2,117.77	100%	2,992.60	100%	3,717.34	100%

Source: SHLC Philippines.

The Secondary Urban Zone also saw early manifestations of urban growth. Emanating from the Primary Urban Zone, the zone displayed ribbon development forming along major provincial and city thoroughfares. In 1990, its share in the city’s built-up was 33%.

Other parts of the city were not as heavily built-up as the two highly urban zones in this period. Compact development was observable in the Northern and Southern Industrial Zones, but these were of low density and barely prominent. Scattered, leapfrogging patches of built-up have remained in other parts of the city.

As Figure 2 shows, all 10 zones exhibited urban expansion between 1990 and 2000. The highest rate of increase was observed in the Verde Island Zone, growing by a factor of almost 1.5. Development became noticeably more compact and contiguous, particularly in the western coastal portion of the island. Houses in the past were mostly made of wood and/or bamboo, while others were made with a combination of concrete and wood. Today, the majority of the houses are made of concrete, brick or stone. Economic prosperity among residents, brought by remittances from relatives abroad and employment in urban areas, alongside gains within fishing and livestock industries, contributed to this shift in choice of building material.

Figure 2.

Source: SHLC Philippines.

The Primary Urban Zone, meanwhile, appeared to have undergone infill development during the period, while the Secondary Urban Zone extended beyond major roads. The Northern and Southern Industrial Zones saw the development of industrial facilities, contributing to the emergence of new settlements and support services near the area. In a decade, the four zones grew by 4%, 9%, 42% and 10%, respectively.

By 2010, the Secondary Urban Zone continued to have the largest share in the city’s built-up area. Accounting for 37%, the zone has hosted more recent commercial establishments and residential subdivisions. Central and western portions became more compact together with prominent strip development northward. The expansion has also managed to influence urban growth in the northern and eastern neighbouring zones, namely, the Northern and Southern General Development Zones. Conversely, the share of Primary Urban Zone has dwindled to just 20%, indicating that other zones have experienced urban growth of their own.

The Primary Urban Zone and Secondary Urban Zone have become more compact, as well as the Northern and Southern Industrial Zones. Verde Island Zone has also became compact, especially along the coast with some leapfrog development inland. A concentration of compact development in the southwestern tip, emerging from the ribbon development along a provincial road can also be witnessed in the Ecological Development Zone. The recent coastal tourism industry is likely to have influenced growth in this area.

Demographic Trends

Batangas City had more than 329,000 inhabitants in 2015. About 62% of them were from the urban villages in the north and west, while the rest were predominantly from rural areas south and east of the city. Population density during this period was 12 persons per hectare, almost twice the figure in 1990 which was 7 persons per hectare.

Among all the zones, the Secondary Urban Zone was ranked the highest in terms of population. More than 129,000 inhabitants lived there in 2015, constituting 40% of the city’s population. The Primary Urban Zone was ranked second with around 70,000 inhabitants. Consistently from 1990 to 2015, the least populated zones have remained the Verde Island Zone and the Southern Industrial Zone. The former has been showing depopulation during the period, while the latter is due to its smaller area coverage.

In terms of population density, the two highly urban zones remained dominant. With 79 persons per hectare in 2015, the Primary Urban Zone was the most densely populated zone in the city. The Secondary Urban Zone, which has thrice the former zone’s land area, had 35 persons per hectare. The population count and densities are shown in Table 6.

Table 6.

Population and Population Density in Batangas City, 1990–2015

Land Management Zones	Total Population and Population Density, by Zone 1990–2015
	1990		2000		2010		2015
	Population	Persons/ha	Population	Persons/ha	Population	Persons/ha	Population	Persons/ha
Agricultural Development Zone	19,810	3	26,017	3	33,935	4	36,172	5
Ecological Development Zone	15,986	2	18,243	2	21,851	3	23,597	3
Verde Island Zone	8,088	5	6,802	4	5,497	3	5,564	3
Primary Urban Core	54,531	62	63,747	72	67,853	77	69,348	79
Strategic Crops and Livelihood Zone	8,301	3	10,853	4	13,209	5	14,970	6
Secondary Urban Core	55,559	15	88,021	24	118,421	32	129,434	35
Southern General Development Zone	4,827	5	7,094	7	12,258	12	14,022	14
Northern General Development Zone	7,349	9	12,849	16	16,426	20	18,237	22
Southern Industrial Zone	7,992	8	11,036	11	13,095	13	13,993	14
Northern Industrial Zone	2,090	28	1,855	25	2,281	30	2,306	31
City	184,533	7	246,517	9	304,826	11	327,643	12

Source: Philippine Statistics Authority.

Population Growth and Built-up Change

The relationship between population growth rate and built-up change has been used in several studies to indicate sprawl (Bhatta, 2009; Sudhira et al., 2004; Yulianto et al., 2020). Typically, the annual rate of built-up expansion in an area is compared with the annual rate of population growth. A situation where the built-up expansion exceeds the increase in population suggests a sprawling development trend (Bhatta, 2009).

Batangas City’s figures signify a highly expansive consumption of land. Between 1990 and 2015, the city’s built-up has grown by almost four times the rate of its population increase. The city’s population increased by an average of 2.3% annually, while built-up area expanded by 9.03%.

The situation is similar at the sub-city level. As shown in Table 7, all the 10 zones exhibited built-up growth rates with levels at least twice that of the population. The Northern General Development Zone and the Northern Industrial Zones showed the highest disparities, the former by a gap of 17 times the population and the latter by 58 times the population. The rise in built-up in these two zones is attributable to the establishment of relocation homes in the former during the mid-1990s and the establishment of industrial facilities and a power plant in the latter during the early 2000s.

Table 7.

Built-up and Population Growth Rates in Batangas City, 1990-2015

Land Management Zones	Population and Built-up Area Growth Rate, by Zone 1990–2015 (in % per annum)
	1990		2000		2010		2015
	Built-up (%)	Population (%)	Built-up (%)	Population (%)	Built-up (%)	Population (%)	Built-up (%)	Population (%)
Agricultural Development Zone	7.6	2.8	−1.3	2.7	8.2	1.2	4.6	2.4
Ecological Development Zone	9.4	1.3	0.2	1.8	15.8	1.5	10.1	1.6
Verde Island Zone	144.8	−1.7	21.9	−2.1	3.2	0.2	225.1	−1.5
Primary Urban Core	4.3	1.6	1.3	0.6	2.3	0.4	3.2	1.0
Strategic Crops and Livelihood Zone	9.8	2.7	10.9	2.0	7.0	2.4	18.4	2.4
Secondary Urban Core	8.9	4.7	5.5	3.0	3.6	1.7	9.8	3.4
Southern General Development Zone	8.3	3.9	3.1	5.6	7.0	2.6	8.9	4.3
Northern General Development Zone	21.3	5.7	35.3	2.5	3.4	2.0	62.4	3.7
Southern Industrial Zone	10.0	3.3	1.1	1.7	5.6	1.3	7.4	2.2
Northern Industrial Zone	42.0	−1.2	−1.0	2.1	8.5	0.2	22.6	0.4
CITY	8.6	2.9	4.1	2.1	4.8	1.4	9.0	2.3

Source: Philippine Statistics Authority and Landsat satellite images.

Verde Island Zone presents an interesting case. The zone’s urban expansion rate has more than 150 times its population growth. The gradual emigration of its residents and the construction of permanent structures by some households are likely reasons for such an imbalance. Issues of accessibility to urban services and the lack of stable and lucrative employment opportunities have induced many native residents to settle in the mainland. Some households who return would bring with them economic capital, while others have permanently settled in the urban areas.

Built-up and Population Proportion

Another way to understand a city’s urban growth is by observing the link between each zone’s proportion of households and built-up area relative to city share. The difference between the two proportions would indicate the compactness or dispersal of urban growth in each zone (Bhatta, 2009). Positive values imply compact development since household proportion is higher than the built-up area, while negative figures infer dispersed expansion. Figure 3 provides the proportions in each zone in 2015.

Figure 3.

Source: Philippine Statistics Authority and Landsat satellite images.

Between 1990 and 2015, only the Agricultural Development Zone, Ecological Development Zone and Southern General Development Zone showed positive rates of change. The other seven zones yielded gradually dispersing trends. In 2015, heavily urban areas such as the Secondary Urban Zone and the Primary Urban Zone returned higher values, as did the Agricultural Development Zone where built-up area was relatively scant as opposed to the number of households.

Built-up Area Density

One metric of sprawl is the built-up area density (Bhatta et al., 2010). Angel et al. (2007) describe this as the ratio between a city’s population and its built-up area. Higher built-up area densities suggest a greater level of compactness, as more people tend to reside in the built-up patches. Declining average densities indicate sprawl.

Batangas City consistently exhibited sprawling tendencies in terms of built-up area density, given by its declining figures. As Table 8 shows, between 1990 and 2015, the city had an average of 117 persons per hectare. In 2015, it recorded about 88 persons per hectare. On average, its built-up area density decreased by a rate of −1.82% annually.

Table 8.

Built-up Area Densities in Batangas City, 1990–2015

Land Management Zones	Built-up Area Density, by Zone 1990–2015 (in persons/ha)
Land Management Zones	1990	2000	2010	2015
Agricultural Development Zone	240	179	270	204
Ecological Development Zone	137	80	95	57
Verde Island Zone	1,096	60	15	13
Primary Urban Core	146	120	113	104
Strategic Crops and Livelihood Zone	256	169	98	83
Secondary Urban Core	146	123	106	99
Southern General Development Zone	159	128	169	143
Northern General Development Zone	1,173	655	185	175
Southern Industrial Zone	76	53	56	47
Northern Industrial Zone	337	58	79	56
City	162	116	102	88

Source: Philippine Statistics Authority and Landsat satellite images.

Likewise, all zones returned declining values of density. The zones averaged a decline of −2.07%. Verde Island Zone and Northern General Development Zone recorded the largest drops, with −3.95% and −3.40%. Even the highly urban zones, the Primary Urban Zone and the Secondary Urban Zone also yielded negative rates. The former yielded −1.16% at an average of 121 persons per hectare, and the latter by −1.30% at 118 persons per hectare. These figures suggest that expansive and dispersed urban development—a manifestation of sprawl—is prevalent throughout the city, even in the heavily urbanized areas.

Shannon’s Entropy

Shannon’s entropy (Hn) was the complementary tool used to detect sprawl in the city. It indicates the level of compactness or dispersion of a geographical phenomenon (i.e., built-up areas) in each zone. The relative entropy (Hn) of built-up areas in each ward was calculated, having values that range from 0 to 1, where 0.5 as the threshold. Results closer to zero indicate higher concentration of built-up in one area, while values closer to 1 indicate dispersal, an attribute of sprawl.

At the city level, Batangas yielded consistently high entropy measures. As Table 9 reveals, between 1990 and 2015, it almost had a value of 1 which has subsequently increased over time. Particularly notable was the range from 2010 to 2015 when it reached 0.98. The data suggests that urban development in the city has remained highly dispersed and expansive.

Table 9.

Shannon’s Entropy (Relative) in Batangas City for Three Time Periods, 1990–2015

Shannon’s Entropy (Relative, 0–1) 1990–2015
1990–2000	2000–2010	2010–2015
0.96	0.82	0.98
log e (10) = 2.30

Source: Authors’ calculation.

Meanwhile, the entropy measures in the individual zones yielded mixed yet hardly different results. As Table 10 shows, 9 of 10 zones reached values of at least 0.05. Interestingly, these zones come from both highly urban and relatively rural areas of the city. The Secondary Urban Zone had the highest value with 0.65. The Primary Urban Zone and the Verde Island Zone followed closely with the same value of 0.63. The Strategic Crops and Livelihood Zone, and Southern General Development Zone also returned high entropy with 0.62 and 0.61, respectively. The Ecological Development Zone recorded the lowest relative entropy measure with 0.46.

Table 10.

Shannon’s Entropy in the Zones of Batangas City, 1990–2015

Land Management Zones	Shannon’s Entropy (Relative, 0–1) 1990–2015
Land Management Zones	1990–2015
Agricultural Development Zone	0.50
Ecological Development Zone	0.46
Verde Island Zone	0.63
Primary Urban Core	0.63
Strategic Crops and Livelihood Zone	0.62
Secondary Urban Core	0.65
Southern General Development Zone	0.61
Northern General Development Zone	0.59
Southern Industrial Zone	0.58
Northern Industrial Zone	0.50
log e (3) = 1.10

Source: Authors’ calculation.

The entropy measures, both at city and sub-city levels, represent the occurrence and predominance of sprawl in Batangas City. They affirm the results found in the earlier analyses, where built-up expansion outstripped population growth. An interesting finding was the extent of dispersal, even in the two highly urbanized zones of the city. A plausible explanation comes from the city’s urban policy in the previous decade. The local government unit pursued a multi-nodal development with the intention of spreading growth from the población and key industrial zones outwards. The policy identified three peripheral areas as new growth centres, namely, the Ecological Development Zone, Southern General Development Zone and parts of the Secondary Urban Zone. The thrust of the policy appears to have influenced the resulting pattern of density and concentration of sprawl.

Land Value in Sprawling Zones

Land Value

Since the remote sensing images cover the years 1990 and 2015, the study used the property values for the years 1994 and 2014. The four-year interval in the observation is assumed to account for the sensitivity of the property values to the expansion of built-up area. The study collected the base values of residential and commercial properties per square metre—preliminarily arranged by barangay—and aggregated them by land management zones. The median of these values was used as this tends to deflect the effects of outlier properties (Bank for International Settlements, 2005). Nominal median values for each zone was then calculated.² The resulting figures were adjusted to constant prices to calculate each zone’s real annual average growth rate. These rates of increase in each zone will serve as the data for the land value analysis.

The market values of residential and commercial land manifest in the underlying urban-rural dynamics observed in Batangas City.³ As Table 11 shows, central and peripheral areas had significant land price gaps. For instance, in 2014, the city’s major urban clusters—Primary Urban Zone and the Secondary Urban Zone—recorded the two highest median market values of PHP 3,376.00 per square metre and PHP 1,125.00 per square metre, respectively.⁴ Meanwhile, Strategic Crops and Livestock Zone, the third-highest, only reached a value of PHP 131.00. Verde Island Zone had the lowest land value in the city since 1994, in 2014 a square metre in the area only costs PHP 23.00 in constant prices.

Growth rates between 1994 and 2014 are illuminating. In constant prices, only three zones exhibited an increase, namely, the Secondary Urban Zone, Southern Growth Development Area and Strategic Crops and Livelihood Zones. They recorded an average annual increase of 1.87%, 0.95% and 0.68%, respectively. Nonetheless, all zones with increasing land values have also returned higher entropy measures—an observation that supports the study’s primary proposition.

Table 11.

Median Base Market Values of Land in Batangas City, 1994 and 2014

Land Management Zones	1990		2014
Land Management Zones	Nominal (in PHP/sq.m)	Real^a (in PHP/sq.m)	Nominal (in PHP/sq.m)	Real^a (in PHP/sq.m)
Agricultural Development Zone	40	84	100	75
Ecological Development Zone	40	84	70	53
Verde Island Zone	20	42	30	23
Primary Urban Core	2210	4643	4500	3376
Strategic Crops and Livelihood Zone	55	116	175	131
Secondary Urban Core	390	819	1500	1125
Southern General Development Zone	45	95	150	113
Northern General Development Zone	60	126	150	113
Southern Industrial Zone	70	147	150	113
Northern Industrial Zone	290	609	150	113

Source: Authors’ calculation based on Batangas City’s Code on Appraisal and Assessment of 2014.

Note: ^aConsumer Price Index for Housing, Water, Electricity, Gas and other Fuels in areas outside Metro Manila was used, 2006 = 100.

As of 3 January 2020, US$1 = PHP 51.19.

Sprawl and Land Values

The study evaluates the assumption that the positive externalities of sprawl, such as the extension of urban development in otherwise remote parts of the city, could influence the appreciation of land values. It hypothesizes that a moderate positive association exists between the two variables. Pearson Product-Moment correlation was used to quantify the strength of the relationship. Table 12 summarizes the sprawl indicators and land value trend in each zone, while Table 13 provides the results of the correlation.

A moderate positive relationship, r(8) = 0.57, p = 0.08, exists between the entropy values and land value growth rates. The findings reinforce the proposition that urban sprawl and land values are positively correlated. However, considering the constraints in the availability and accuracy of built-up information, alongside the general variability of market values of land, the sample evidence was not sufficient to reject the null hypothesis, H_o = 0 (at α = 0.05). A separate study covering multiple cities and municipalities would be required to test the relationship with statistical significance. The link between sprawl and land value was nonetheless, sufficiently demonstrated.

Table 12.

Summary of the Indicators of Sprawl and the Trend of Land Value in Batangas City’s Zones

Land Management Zones	Population Growth Rate and Built-up Change 1990–2015 (in % per annum)									Built-up and Population Proportion 2015 (in % share to city)			Built-up Area Density 1990–2015 (in persons/ha)				Shannon’s Entropy (Relative)	Median Base Market Values 1990 and 2014 (in PHP/sq.m.)
	1990-2000		2000-2010		2010-2015		1990-2015		1990 and 2015	2015			1990	2000	2010	2015	1990–2015	1990		2014		1990–2014
	Built-up (%)	Pop. (%)	Built-up (%)	Pop. (%)	Built-up (%)	Pop. (%)	Built-up (%)	Pop. (%)	Comparison of rates of built up (B) and population growth (A) (B-A)^a100%	Built-up (B) (%)	Pop. (A) (%)	Compactness (B-A) (%)	1990	2000	2010	2015	1990–2015	Nominal	Real^a	Nominal	Real^a	Real Growth Rate (%)
Agricultural Development Zone	7.6	2.8	−1.3	2.7	8.2	1.2	4.6	2.4	2.19	4.8	10.2	5.4	240	179	270	204	0.50	40	84	100	75	−0.54
Ecological Development Zone	9.4	1.3	0.2	1.8	15.8	1.5	10.1	1.6	8.57	11.1	6.9	−4.2	137	80	95	57	0.46	40	84	70	53	−1.88
Verde Island Zone	144.8	−1.7	21.9	−2.1	3.2	0.2	225.1	−1.5	226.62	11.4	1.8	−9.6	1,096	60	15	13	0.63	20	42	30	23	−2.32
Primary Urban Core	4.3	1.6	1.3	0.6	2.3	0.4	3.2	1.0	2.22	18.0	22.4	4.3	146	120	113	104	0.63	2210	4643	4500	3376	−1.36
Strategic Crops and Livelihood Zone	9.8	2.7	10.9	2.0	7.0	2.4	18.4	2.4	16.01	4.9	4.7	−0.1	256	169	98	83	0.62	55	116	175	131	0.68
Secondary Urban Core	8.9	4.7	5.5	3.0	3.6	1.7	9.8	3.4	6.39	35.3	39.9	4.6	146	123	106	99	0.65	390	819	1500	1125	1.87
Southern General Development Zone	8.3	3.9	3.1	5.6	7.0	2.6	8.9	4.3	4.56	2.6	4.2	1.6	159	128	169	143	0.61	45	95	150	113	0.95
Northern General Development Zone	21.3	5.7	35.3	2.5	3.4	2.0	62.4	3.7	58.77	2.8	5.1	2.3	1,173	655	185	175	0.59	60	126	150	113	−0.54
Southern Industrial Zone	10.0	3.3	1.1	1.7	5.6	1.3	7.4	2.2	5.13	8.0	4.0	−4.0	76	53	56	47	0.58	70	147	150	113	−1.17
Northern Industrial Zone	42.0	1.2	−1.0	2.1	8.5	0.2	22.6	0.4	22.21	1.1	0.7	−0.4	337	58	79	56	0.50	290	609	150	113	−4.08
CITY	8.6	2.9	4.1	2.1	4.8	1.4	9.0	2.3	6.73	100.0	100.0		162	116	102	88	log e (3) = 1.10

Source: Authors’ calculation

Source: Authors’ calculation based on data from Official City Data, Philippine Statistics Authority and Landsat Satellite Images.

Note: Values highlighted in red indicate sprawling.

^a Consumer Price Index for Housing, Water, Electricity, Gas and other Fuels in areas outside Metro Manila was used, 2006 = 100.

As of 3 January 2020, US$1 = PHP 51.19; GBP 1= PHP 63.10.

Table 13.

Correlation Between Shannon’s Entropy and Growth Rate of Land Market Values in Batangas City, 1990–1995 and 2014–2015

Variables	r 2	n	n-2	p-value
Land value growth rates by zone, 1994–2014	0.57	10	8	0.08
Shannon’s entropy by zone, 1990–2015	0.57	10	8	0.08

Source: Authors’ calculations

Conclusion

Through four quantitative and qualitative indicators, this study has investigated whether Batangas City is sprawling or compacting. The land cover changes for the period of 1990–2015 already hint at the presence of sprawling in the city. The results further suggest that Batangas City is leaning towards a dispersed form of development. In the analysis of population growth and built-up change, and built-up area density analysis—all 10 zones exhibit sprawling. For the built-up and population proportion—5 out of 10 zones, suggest dispersion. Lastly, using Shannon’s entropy—8 out of 10 zones indicate dispersed development. Three zones are particularly notable as they exhibit sprawl in all four indicators, namely, the Verde Island Zone, Strategic Crops and Livelihood Zone and Southern Industrial Zone.

The study has also shown the existence of a positive relationship between sprawl and land value. Through Pearson’s r, a moderate positive relationship is present, r(8) = 0.57, p = 0.08, between entropy values and land value growth rates. However, considering constraints in the availability and accuracy of information on built-up areas and the general variability of market values of land, the sample evidence was not sufficient to reject the null hypothesis, H_o = 0 (at α = 0.05). Nonetheless, the positive link between sprawl and land value was sufficiently demonstrated.

Further studies modelling Shannon’s entropy and three other indicators can provide for a more spatially and statistically sensitive findings. Similarly, further research and modelling is required to prove causation between sprawl and land value.

Footnotes

Acknowledgements

This article was written as part of the work of the Centre for Sustainable, Healthy and Learning Cities and Neighbourhoods. Grateful to Atty. Mark Anthony M. Gamboa for the valuable comments and thorough review of the article.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.

Funding

This article was written as part of the work of the Centre for Sustainable, Healthy and Learning Cities and Neighbourhoods (SHLC), which is funded via UK Research and Innovation, and administered through the Economic and Social Research Council, as part of the UK Government’s Global Challenges Research Fund. Project Reference: ES/P011020/1.

Notes

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