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Best-Laid Incentive Plans Case Study C4

1. Introduction

Since the start of economic reform in 1978, China has achieved remarkable economic progress. Today, China is among the fastest growing economies in the world, but this growth has not come without a price. The state of the environment in China is deteriorating fast, adversely affecting human health, productivity of land and natural resources. It was estimated that the damage caused by environmental pollution and degradation of natural resources consumes up to 8% of China’s GDP, roughly equal to the annual growth of the country’s economy [1]. Rapid urbanization and industrialization are exacerbating the environmental problems [2,3,4], especially given the enormous scale of these processes [5]. The level of urbanization in China has increased from 17.9% in 1978 to 40.5% in 2003, and is expected to further increase to 50% by the end of 2020 [6]. The food supply cannot meet the domestic demand due to the rapid urbanization [7]. During the 10th Five-Year Plan period (2000–2005), China lost over 6 million hectares of arable land, amounting to 4.7% of the total in 2000. In 2006, arable land reduced to 121.8 million hectares. Moreover, a staggering 10% of the arable land is contaminated due to polluted water, excessive fertilizer use, heavy metals and solid wastes. Heavy metals alone contaminate 12 million tons of grain each year, causing a loss of 20 billion Yuan (2.6 billion US$). Therefore, national targets have been set to ensure food security [8]. The targets are to maintain 120 million hectares of arable land by 2010 and keeping up a 95% self-sufficiency rate by 2030, when the population will stabilize at a projected 1.6 billion people. Land-use planning and environmental management are considered essential to meet these targets and to protect the arable land and natural resources.

During the last decade, a comprehensive regulatory and institutional framework for environmental management and protection has been set up. However, these policies have not been very effective in saving arable land and reducing environmental impacts [9]. The current spatial planning system is unable to manage and guide the process of urbanization. Some important reasons are the ineffective top-down policy and planning, conflicting interests at the different administrative levels, and a lack of engaging relevant stakeholders and the general public [10]. For example, the current land-use planning system puts too much emphasis on quotas rationing, and neglects a proper spatial allocation, especially at the regional level. In order to maximize the benefits from land resources, local governments (the executors of the land-use planning system) often take dramatic steps to pursue urbanization without considering where construction land is being allocated, lacking a proper suitability assessment and assessment of the consequences to other land uses. Therefore, the processes of urbanization do not only waste and destroy other land resources (e.g., arable land), but also damage the ecological environment of cities. In 2006, at the start of the third revision of land-use master plans, the Department of Land and Resources of Jiangxi Province assessed the effectiveness of previous land-use master plans and concluded that the land-use planning system failed to balance urbanization and the protection of arable land and natural resources. One of the key questions the department identified was: How to balance economic development and urbanization on the one hand and to protect arable land and natural resources on the other hand? The Jiangxi Agricultural University in Nanchang started a research project to analyze this problem. The objectives of the project were: (1) to develop a land-use optimization model to support regional land-use planning and allocation; and (2) to apply the model in a case study area. This article describes the approach of the method that has been developed and presents the results of its application in the Poyang Lake Region in Jiangxi Province.

2. Land-Use Master Planning in China

China’s land-use planning system, which initiated from the former Soviet Union, can be characterized as centralized and hierarchical [5]. The land administration law (adopted in 1986 and revised in 1998 and 2004) provides the legal framework for China’s land-use planning system. This land administration includes strong regulations to protect arable land and the environment [11]. The system covers five administrative levels: state, province, city, county and township, and prescribes the establishment of land-use master plans, special topic plans and project plans [11]. The master plans are long-term plans (10 years on average) that determine and balance the size and distribution of the various types of land use. The special topic plans cover specific objectives set by the master plans, and the detailed project plans include specific engineering designs. The land-use master plans, the core of the planning system, are implemented at each of the five administrative levels. The departments and bureaus of land administration are responsible for preparing and organizing the process [11]. Land-use master plans especially aim to protect arable land, manage (restrict) construction land and conserve nature, in order to achieve sustainable land use. Therefore, the master plans have adopted a system of quotas which regulate the area of arable land, construction land, and the conversion of arable land to construction land. Each master plan sets the quotas for a lower level master plan. The quotas are derived from a process of area demands prediction.

In 2004, China started the third round of land-use master plan revision. An assessment of the results of the previous land-use master plans, which were implemented during the 1990s, showed that many of these plans were poorly executed. The master plans failed to guide urban development, especially in the more sensitive areas such as Poyang Lake Region in Jiangxi Province. One reason is that the land-use master plans primarily manage land-use quota (“how much”) and do not provide much guidance to the spatial allocation of new developments (“where”). Consequently, land allocation basically takes place as a bottom-up process at the local level. Coherent, holistic perspectives on spatial development at the regional level (provincial and city level) are lacking.

Moreover, the cooperation between local governments has declined due to the economic reforms in the previous decades. Since 1978, the central government has been decentralizing economic decision making. As a consequence, local governments have transformed from passive regulators in the previous planned economy to entrepreneurial agents that initiate local developments. Under the pressure of economic growth, the local governments usually emphasize on the one-sided pursuit of economic benefits from urban development, neglecting the protection of arable land and natural resources. Local governments tend not to cooperate closely with neighboring administrations. The Jiangxi Province government aims to achieve a more coherent, sustainable land-use planning. Therefore, a more regional, holistic approach is required to guide the future spatial development in the area, especially in the Poyang Lake Region, located north of the province capital city Nanchang. This region is important for its rapid socio-economic development, and it is also one of the main rice growing areas in China [12]. Furthermore, Poyang Lake Region accommodates wetlands of international importance by providing a habitat for many world major migratory birds [13]. From late autumn to early winter, thousands of migratory birds fly from Siberia, Mongolia, Japan, North Korea and the northern parts of China to Poyang Lake for over-wintering [14]. A main challenge in the area is to guide economic development and urbanization on the one hand and to protect arable land and natural resources on the other hand [15]. Given the complexity of the task at hand, the province government expressed the need for supporting tools for the future spatial planning of the region. These tools should allow the design and optimization of a more sustainable land-use allocation at province and city level, providing a framework for the spatial developments at the local level. The framework of such a tool will be described in the next section.

3. A Land-Use Optimization Model

FAO defines land-use planning as “the systematic assessment of physical, social and economic factors in such a way as to encourage and assist land users in selecting options that increase their productivity, are sustainable and meet the needs of society” [16]. In this definition, land-use planning is perceived as a land-use optimization process, based on land assessment and directed by economic and social needs. Land-use optimization, both in size and pattern, is a complex process and a main topic in land-use planning research. As early as in the 1960s, spatial pattern optimization models were put forward. Based on mathematics and statistics, these models tried to incorporate spatial variables in multiple regression models or as land-use conversion probabilities in transition probability matrices. With the progress of computer technology, and especially after the introduction of geographical information systems (GIS), land-use allocation and optimization modelling became more wide-spread [17,18,19,20,21,22]. Land-use optimization models typically involve the optimization of the size as well as the spatial pattern of land use [23]. Today, spatial pattern analysis [24,25,26,27,28] and spatial modelling [29,30,31,32] are widely used. Differences between models are often related to differences in context, purpose and scale of the study area. Two common groups of models are simulation models, which explore possible changes of land use in the near future as a function of driving forces, and descriptive models, which produce alternative, optimized designs for land use, based on biophysical characteristics and socio-economic input and goals [22]. Simulation models focus on spatially explicit simulation of near future land-use patterns, and descriptive models aim to calculate optimal land-use configurations that best match a set of goals and objectives. These two groups of land-use models are fit for optimizing land-use patterns in land-use planning systems characterized as “bottom-up” (participatory planning). Since these characteristics, input and goals usually vary over space and time, most models are context specific and cannot be universally applied. The land-use planning systems in many developing countries, such as China, were initiated from the former Soviet Union and can be characterized as “top-down”. Although land-use optimization is very relevant for deriving more sustainable land-use master plans, the present models are not well equipped to deal with the Chinese context. Therefore, a land-use optimization model was constructed that deals with the specific Chinese planning context. The model aims to support the spatial planning of future land use at the province and city level, by providing guidance to municipal governments in their process of allocating the amount of arable land, construction land and land for nature conservation, in view of the Chinese land-use quota system. The model uses GIS-based multi-criteria techniques to assess the land suitability, which are commonly applied in land-use optimization processes [33,34]. The flow chart of the model is presented in Figure 1.

Figure 1. Flow chart of the land-use optimization model.

Figure 1. Flow chart of the land-use optimization model.

The model includes four basic steps. In the first step, the demand for arable land, construction land and land for nature conservation in a target year are predicted using statistical data (Step A). The second step includes a suitability assessment (Step B). In Step C, three land-use scenarios are developed that provide three perspectives for single-objective pattern optimization. The last step involves a multi-objectives pattern optimization process, with special emphasis on spatial analysis and relationships, resulting in an integrated land-use allocation map (Step D). Moreover, the model and results were assessed by governmental officials and experts from planning practice. The four steps and the model assessment are explained in more detail in the next sections.

3.1. Step A Demand Prediction

The arable land demand is predicted based on the theory of land carrying capacity [35,36]. It starts with predicting the population size and the consumption of rice, as a strategic commodity, in a region in a given target year. The rice productivity per hectare is estimated by modelling the historical rice production trend using statistical data. The arable land demand in the target year is then calculated as:

where x1 is the total rice consumption (in tons), x2 the average rice production (in tons/ha) and x3 the ratio of rice to other food products. The import or export of rice is included as percentage decrease or increase in arable land demand, estimated based on the historical trend derived from statistical data.

The current Chinese land-use regulation system is primarily based on productive land. Despite the need to preserve land for nature conservation (see introduction section), the land-use quota system does not incorporate procedures for land to be allocated as such. Therefore, in the model three land-use types from the land-use regulation system are selected to represent areas with a high potential for nature conservation. These are forests, water bodies and grassland. Allocating land as forests, water bodies and grassland supports bio-productivity goals, such as fruit, fuel wood, timber, hay for cattle and fishing grounds, which are included in the current system. The land demand for forest, water and grassland is predicted using the principle of Ecological Footprint (EF). EF represents the human demand on bio-productivity [37], by assessing how much biologically productive land and water area are required to uphold the consumption of a given human population [38]. EF is calculated by estimating the consumption of resources in terms of mass units and transforming these mass units into an area of required land [23,39]. The formula used in the model is:

where Ci is the consumption per capita of product i in kg/year, Pi is the regional productivity of product i in kg/ha/year. Based on a trend analysis of the EF for grassland, forest and water, a linear regression model is calculated with year as dependent variable and footprint as independent variable. The land demand in the target year is calculated as the estimated EF multiplied by the estimated population. An extra 12% is added for reasons of biodiversity protection, according to the proposal of the World Commission of Environment and Development (WCED) [38].

The demand for urban and rural construction land is estimated using land-use standards of the Ministry of Construction, published in the “Classification of land use and norms of city planning” (1990) and “Standard of township planning” (1994). The required area of construction land is derived by multiplying these standards per capita by the estimated population in the target year.

3.2. Step B Suitability Assessment

The frame work for land evaluation of the FAO [40] is used as guideline for the land-use suitability assessment. The guideline provides principles and procedures for the qualitative evaluation of the suitability of land for alternative uses based on biophysical, economic and social criteria. The procedures include the appraisal and grouping of specific areas of land in terms of their suitability for defined uses [40]. The spatial data for the suitability assessment include a land-use, soil, landform and elevation map. The first step of the suitability assessment involves the identification of unsuitable areas, such as built-up area and surface water, and restricted areas, such as nature reserves and military areas. For the remaining areas, a land suitability assessment along the FAO framework is carried out by choosing the limiting factors determining the land suitability [33]. The suitability class of an area is determined by the factor with the lowest suitability class (the limiting factor) (Table 1). The selected factors are: slope gradient, soil parent material or mother rock, soil organic matter content, and landform. Suitability maps for arable land (including paddy field and dry land), forest and grassland are created using four suitability classes: high suitable, moderate suitable, low suitable and unsuitable.

Table 1. The suitability assessment factors and classes.

Limiting factors

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