Quantify the landscape effect and environmental sustainability of rural region planning at town scale near metropolis

Abstract

The urban fringe, which can be seen as a special form of regional ecosystem with a spatial transition from urban to rural areas, has strong heterogeneity and is a typical ecologically sensitive area. The expansion of cities and the landscape effect of the changes have attracted wide attention. The primary aim of this study is to obtain an understanding of the spatial patterns of landscape conversion and the corresponding environmental sustainability. With the help of GIS and Fragstats software, the changes of landscape patterns before and after town planning were compared in An-Ding town of Beijing, of which the sustainability was also revealed based on the ecological footprint using social and economic statistic data. The results showed that the landscape pattern changed greatly during its conversion from several villages to a small town and the landscape fragmentation increased due to road construction. Meanwhile, human disturbance increased with the constructed land extension. For the gap between the ecological footprint and the biological capacity, An-Ding town ran an ecological deficit at that period, which means it was unsustainable. However, the environmental sustainability decreased after planning due to the degraded green land and forest. The results suggested that ecological management should be strengthened during the town planning period.

Keywords

environmental sustainability / landscape / ecological footprint / ecological capacity / town development

Introduction

The land use of Beijing changed greatly with the economic development corresponding to the fast urbanization. The urban area was 484.86 km² in 1984 and increased to 1496.88 km² in 2005 (Mu et al., 2007). During the past 20 years, land use types in Beijing had been converted gradually, which was caused by many factors, including economic development, population growth and construction of satellite towns. Though urbanization and economic transformation–the growth of non-farm, industrial and service sectors–offers many opportunities for the improvement of people’s living standard, an expanding human population and the associated demands for goods and services are exerting an increasing pressure on the ecological systems. Sustainable development is desirable and hopeful at multiple scales. At the regional scale, the sustainability development of towns under the press of metropolis extension has attracted much attention (Li et al., 2005). Nevertheless, the relationship between land use planning and its ecological impacts at this scale still remain to be revealed.

The concept of sustainability has become a key idea among national and international discussions in the publication of the Brundt land Report (WCED, 1987), Our Common Future, in which sustainable development is defined as a pattern of regional system that aims to meet “the needs of the present without compromising the ability of future generations to meet their own needs”. Many topics, such as ecosystem capacity and consumption pattern, have been emphasized from the viewpoint of environmental sustainability (Rees, 1996).

Environmental or ‘ecological’ footprint has been widely used in recent years as a partial indicator to illustrate the sustainability, for which the resource consumption and waste absorption required by a defined population are transformed on the areas of the biologically productive land (Rees, 1992; Wackernagel and Rees, 1996). The average footprint of the world population in 2002 was estimated to be 2.3 ha/person, with a global deficit of 0.4 ha/person when compared with the global biological capacity of 1.9 ha/person which commenced in the1980 s (Wackernagel et al., 2002). However, there are little ecological footprint literatures at the town scale, especially for that of landscape change near the metropolis. This study provides such case to compare the landscape pattern before and after the town planning and the ecological footprint was calculated to analyze the environmental sustainability of the town.

Study area

An-Ding town, covering an area of 77 square kilometers, is located in Daxing District, the southeast suburbs of Beijing near Hebei Province. It is an important agricultural and industrial base and the central town in Daxing District is one of the 27 key planning towns in Beijing. There are 24 administrative villages with a total population of approximately 28000 residents. The transport facility and transportation network have been developed there. The climate in An-Ding is warm and semi-arid with sub-continental monsoon which combines with ample sunshine throughout the year. At present, farmland is the main landscape type in this region. Though land use planning has been brought out to regularize the land use and adjust the industry structure, its ecological effects were not well known.

Materials and methods

Data Sources

Current land use type map was derived from SPOT image in 2006. RS and GIS software was used to classify the landscape. The 1∶30000 scale topographic maps were used for geometric rectification. Then image-to-image registration was conducted between the SPOT image and a 1∶30000 map using the nearest neighbor resampling algorithm. Root mean square (RMS) errors of each registration were maintained below 0.5 pixels (<1 m). Also, a field survey was conducted to rectify the maps. The land plan map was digitized from the papery land plan map (1∶30000). A consistent classification was used to compare the results of different maps. The statistic data about social, economic and land conditions were derived from functional departments, remote sensing and GIS. In this paper, a uniform classification of landscape types was used to avoid the error from different classifications (Yan, 2004). The landscape in An-Ding town was divided into seven types as farmland, transport, green land (mainly forest orchard), built land, village, industry, and other land (see Fig. 1).

Methods

Landscape analysis

Landscape consists of different sizes of patches, and the spatial distribution of patches is called as landscape pattern, which is a result of long-term natural or anthropic effect (Fu et al., 2001) and it can also directly affect the landscape process. With concentrated information, the landscape patterns and associated quantitative landscape indicators can be used to reflect the landscape composition and spatial configuration (Wu, 2007).

Based on the regional landscape features, we selected indices involving patch number, patch density, edge density, average patch area, fractal dimension, split index and Simpson index to characterize the effect of landscape planning. With the support of ArcInfo, land use and land planning vector map was converted into landscape grid map (grid resolution of 2 m). The landscape indices were calculated by FRAGSTAT program (Deng et al., 2005; Yang et al., 2005).

Calculation of the ecological footprint (EF)

Regional land use change data that can be easily derived by GIS, is required to calculate the ecological footprint (EF) of a region. Ecological footprint calculations involve several steps. There are mainly six human impact categories that are accounted for in the EF: (a) cropland (crops for food, animal feeding, fibre and oil), (b) grazing land (to produce meat, hides, wool and milk), (c) forest area (e.g. harvesting trees for timber or paper making and gathering fuel wood),(d) fishing ground (fish for human consumption),(e) built up land (e.g. areas occupied by infrastructures for industrial activities, transportation and housing), and (f) CO₂ area (forest area needed to absorb CO₂ from combustion processes) (Wackernagel et al.,1999). The extension of each area type sustaining consumptions of resources or goods is obtained by dividing their amount by specific coefficients of production:

Area_i(ha)=Consumption(t)/Yield (t•ha^-1),

where i stands for the ith area type, and Yield is the number of tons per hectare (t•ha^-1 ), which is used to compute the area required to get each Consumption (t) from the land type i. Then, each Area_i is corresponded with a consumption pattern.

All the area types are summed up to obtain the EF value. To make this calculation unified on a global level, the EF value of each land type is converted into global hectares (gha), and a standardized unit of biologically productive area is characterized by an ideal productivity which is equal to 11.4 billion ha of bioproductive area, the earth’s average bioproductive area. Equivalency factors are used in the equation:

EC(\mathrm{gha})={\displaystyle \sum _{i=\mathrm{1}}^{n}Are{a}_i(\mathrm{ha})·EquivalenceFacto{r}_i(\mathrm{gha}·{\mathrm{ha}}^{-1})},

where n stands for the total number of the area types (n=6). Equivalence Factor for cropland is 2.17 gha•ha^-1, meaning that 1 world average cropland hectare produces 2.17 times of 1 global average bioproductive hectare (gha•ha^-1 ) (Wackernagel and Rees, 1996).

Biocapacity (B) quantifying the productive land at disposal is computed as:

B(gha)={\displaystyle \sum _{i=\mathrm{1}}^{n}Are{a}_i(\mathrm{ha})·EquivalenceFacto{r}_i({gha·ha}^{-1})·YieldFactor,}

where the Yield Factor, specific for each area type, relates the local productivity to world average productivity (Wackernagel and Rees, 1996). Ecological Footprint is then subtracted from the biocapacity to confirm whether the community runs an Ecological Deficit.

Ecological Deficit(gha)=Biocapacity(gha)-EF_Consumption(gha)

Results

Land use change before and after town planning

Land use change at class level

Figure 1 shows the type of land use changes greatly before and after planning. The main land use type is farm land, which accounts for 51% at present and 56% after planning. Therefore, the agricultural landscape is the dominant landscape type in An-Ding town and the land intensive utilization in planning will convert more farmland. The green land and village land will also reduce after planning while the industry and transport land will increase.

At class level, patch number, patch density, edge density and average patch area can reflect the degree of landscape fragmentation. After planning, the patch number, density, edge density of the farmland, transport, and built land will increase. In contrast, the average area of these patches will generally decrease, which suggests the degree of fragmentation will increase (see Table 1).

The values of fractal dimension are closely related to the complexity of the shape of the patches and the human interference and those indices mentioned above reflect the complex patch shape. After planning, the arable land and village land will be regular, while other landscape types will become more complex with shape.

Land use change at landscape level

The ecological features of the landscape will have a marked change after planning. It is characterized by the increase of patch number, patch density and the decrease of average patch area, which suggest the intensifying landscape fragmentation (Table 2). The fractal dimension will reduce from 1.250 to 1.134 which shows that the factor of shape complexity will decrease after planning. Split index can also reflect the degree of landscape fragmentation and the isolation of different patch classes. The result shows the index will increase after planning. Simpson diversity index can reflect the diversity of landscape. After planning, the index will slightly decrease since more arable land occupies the space.

Environmental sustainability at town scale

The ecological footprint of An-Ding town

The calculation of ecological footprint are based on the equations above and are composed of two parts: (1) biological resources, (2) energy resources, which are listed in Table 3 and Table 4, respectively. Considering the actual conditions of An-Ding town, we ignored the commerce part for adjustment.

Referring to the productive land area of An-Ding town (Table 5), we summarized the ecological footprint in Table 6. Due to the great difference of production per unit area among farmland, grassland, forest, built land, and energy land, the equivalence factors were adopted as follows: farmland and built land 2.8, forest and energy land 1.1, grass land 0.5 and water body 0.2. Using the equations mentioned above, we further gauged the ecological capacity on a worldwide basis. The final ecological capacity should subtract the area for biodiversity conservation which accounted for 12% of the total area.

For the supply of EF, as very different outputs of productive land area in various countries or regions, the area should be transformed into a comparative area by multiplying the local production factor. Then the world’s average ecological carrying capacity also can be derived by the equations above. At the same time, calculation of the ecological carrying capacity should be deducted by 12% of the biodiversity conservation area.

From the tables, we can see that the average footprint per capita of An-Ding is about 1.88 ha and the ecological capacity is 0.33 ha. The final ecological capacity per capita for utilization is 0.29 ha. So the footprint deficit is 1.59 ha. From the supply and demand structure of the footprint, we can see that the ecological bioproductive land cannot counteract the demand of economic development. This is mainly due to the lack of ecological land such as forest land, grassland and water body. But in contrast, the demand of the construction land is ever-increasing. The result suggests that human disturbance could lead to a reduction in the ecological capacity.

Ecological capacity change after land use planning

After planning, the ecological capacity per capita will be 0.19 ha (Table 7), showing an obvious decrease. The reason is that the construction land will increase greatly. Although the farmland will have an increase of 5%, the population will grow more rapidly. With the development of the town, the capacity per capita will increase greatly. The results show that the ecological sustainability will reduce after planning.

Discussion and Conclusion

Land use of urban fringes is driven by the expansion of the central city and the development of the local town. At the town scale, the development is facing many new opportunities. As one of 33 central towns which in the next 10 years have been oriented as commerce and trade towns, An-Ding town was selected as a case in the paper. It is predicted that the land use will change greatly in the future. In this study, landscape analysis and ecological footprint method are used to assess the effect of land use change after planning and to evaluate the sustainability.

The results show that the landscape pattern will change greatly after planning. In detail, the results of change mainly exhibit the increase of patch number, shape complexity and the decrease of average patch area. Also, at the landscape level, the split index will increase and the diversity index will decrease respectively.

This article has presented the results of the analysis of the ecological footprint and the biocapacity of An-Ding town. Land use in this town will change greatly in the near future. The study suggests that ecological footprint model could be a method to evaluate the environmental sustainability level. Some researchers advised that planning could be assessed by ecological footprints (McManus, 2006). The results show that the ecological deficit is 1.59 ha per capita at present, while the ecological capacity will decrease after planning. Because the footprint is a static analysis method, the actual sustainability can be improved through many ways. To achieve sustainable development of An-Ding town, the planning is taken to: 1) make the population growth under control; 2) use the land resources rationally especially the unused land; 3) utilize the existing resources efficiently and modify the people’s production and consumption patterns; 4) improve the unit area of production and 5) develop the tourism resources.

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Higher Education Press and Springer-Verlag Berlin Heidelberg