Limin Jiao

Characterization and spatial modeling of urban sprawl in the Wuhan Metropolitan Area, China

Abstract Urban sprawl has led to environmental problems and large losses of arable land in China. In this study, we monitor and model urban sprawl by means of a combination of remote sensing, geographical information system and spatial statistics. We use time-series data to explore the potential socio-economic driving forces behind urban sprawl, and spatial models in different scenarios to explore the spatio-temporal interactions. The methodology is applied to the city of Wuhan, China, for the period from 1990 to 2013. The results reveal that the built-up land has expanded and has dispersed in urban clusters. Population growth, and economic and transportation development are still the main causes of urban sprawl; however, when they have developed to certain levels, the area affected by construction in urban areas (Jian Cheng Qu (JCQ)) and the area of cultivated land (ACL) tend to be stable. Spatial regression models are shown to be superior to the traditional models. The interaction among districts with the same administrative status is stronger than if one of those neighbors is in the city center and the other in the suburban area. The expansion of urban built-up land is driven by the socio-economic development at the same period, and greatly influenced by its spatio-temporal neighbors. We conclude that the integration of remote sensing, a geographical information system, and spatial statistics offers an excellent opportunity to explore the spatio-temporal variation and interactions among the districts in the sprawling metropolitan areas. Relevant regulations to control the urban sprawl process are suggested accordingly.

A self-adapting fuzzy inference system for the evaluation of agricultural land

The inference rules relating land characteristics to suitability class are crucial to the estimation of agricultural land suitability. In fuzzy logic modeling for agricultural land evaluation, the fuzzy inference, based on membership functions and rule aggregation, is constructed with predetermined evaluation criteria, including value ranges for fuzzy linguistic terms, and weights of land variables. However, most existing evaluation criteria systems are built on the basis of expert knowledge and can be highly subjective and contain uncertainty. This study integrates a genetic algorithm with a multi-criteria evaluation based fuzzy inference system (FIS) to construct a self-adapting system that calibrates its evaluation criteria by self-learning from land samples. In the proposed GA-optimized fuzzy inference model, the criteria for land evaluation are encoded into chromosomes, i.e., each chromosome represents a solution for the evaluation criteria system. The performance of the fuzzy inference system on a training set is used as the fitness of an individual chromosome. The genetic algorithm repeatedly modifies a population of chromosomes through selection, crossover and mutation. To reduce the violation of the constraints for chromosomes and the destruction of excellent genes, the subsets in chromosomes are used as the basic units in crossover and mutation. Some transformations are implemented in mutation to ensure that the new individuals are accorded with the constraints in the evaluation criteria. Three-fold cross-validation (3 CV) is employed to prevent overfitting and to evaluate the performance of the model. The optimized evaluation criteria are produced by decoding the final best chromosome. In the application of the model to the case study area, the accuracy of the evaluation criteria system for the training set increased from 72.08% to 93.34%. The results show that the model is both effective and robust.

PSOLA: A Heuristic Land-Use Allocation Model Using Patch-Level Operations and Knowledge-Informed Rules

Optimizing land-use allocation is important to regional sustainable development, as it promotes the social equality of public services, increases the economic benefits of land-use activities, and reduces the ecological risk of land-use planning. Most land-use optimization models allocate land-use using cell-level operations that fragment land-use patches. These models do not cooperate well with land-use planning knowledge, leading to irrational land-use patterns. This study focuses on building a heuristic land-use allocation model (PSOLA) using particle swarm optimization. The model allocates land-use with patch-level operations to avoid fragmentation. The patch-level operations include a patch-edge operator, a patch-size operator, and a patch-compactness operator that constrain the size and shape of land-use patches. The model is also integrated with knowledge-informed rules to provide auxiliary knowledge of land-use planning during optimization. The knowledge-informed rules consist of suitability, accessibility, land use policy, and stakeholders’ preference. To validate the PSOLA model, a case study was performed in Gaoqiao Town in Zhejiang Province, China. The results demonstrate that the PSOLA model outperforms a basic PSO (Particle Swarm Optimization) in the terms of the social, economic, ecological, and overall benefits by 3.60%, 7.10%, 1.53% and 4.06%, respectively, which confirms the effectiveness of our improvements. Furthermore, the model has an open architecture, enabling its extension as a generic tool to support decision making in land-use planning.

Analyzing the effects of scale and land use pattern metrics on land use database generalization indices

Abstract The generalization index system is one of the critical issues for computer-aided land use database generalization. This paper studies the scale and land use pattern effects on land use database generalization indices and estimates the thresholds of these indices based on a typical land use database sample. The index system of land use database generalization is discussed and constructed from macro and micro perspectives. Six land use pattern metrics, namely, land use diversity index, land use dominance index, land use homogeneity index, land use fragmentation index, the index of land use type dominance, and the index of land use type fragmentation, are designed to characterize land use patterns and are introduced into the analysis of land use pattern effect on land use database indices. The analysis framework of the scale and land use pattern effects on the land use database indices are proposed by employing statistical techniques. Based on the land use database samples at multiple spatial scales collected in various land use regions across China, the study generates rules for both scale and land use pattern effects on the indices, including map area proportion of land use types, total map load, parcel map load, and minimum parcel area. The thresholds of these indices in land use database generalization are produced at the scales of 1:50,000, 1:100,000, 1:250,000, and 1:500,000. An experimental generalization at county level demonstrates how to determine the generalization index values considering scale and land use pattern, and how to evaluate the generalization results using our macro indices.

Road Centrality and Landscape Spatial Patterns in Wuhan Metropolitan Area,China

Road network is a corridor system that interacts with surrounding landscapes, and understanding their interaction helps to develop an optimal plan for sustainable transportation and land use. This study investigates the relationships between road centrality and landscape patterns in the Wuhan Metropolitan Area, China. The densities of centrality measures, including closeness, betweenness, and straightness, are calculated by kernel density estimation (KDE). The landscape patterns are characterized by four landscape metrics, including percentage of landscape (PLAND), Shannon’s diversity index (SHDI), mean patch size (MPS), and mean shape index (MSI). Spearman rank correlation analysis is then used to quantify their relationships at both landscape and class levels. The results show that the centrality measures can reflect the hierarchy of road network as they associate with road grade. Further analysis exhibit that as centrality densities increase, the whole landscape becomes more fragmented and regular. At the class level, the forest gradually decreases and becomes fragmented, while the construction land increases and turns to more compact. Therefore, these findings indicate that the ability and potential applications of centrality densities estimated by KDE in quantifying the relationships between roads and landscapes, can provide detailed information and valuable guidance for transportation and land-use planning as well as a new insight into ecological effects of roads.

Research on land evaluation based on fuzzy neural network

This paper focuses on application of artificial neural networks (ANN) in land suitability evaluation. There are some problems in applying fuzzy system to land suitability evaluation such as self-adjusting ability of the membership functions and rules of fuzzy evaluation system. In this paper, the model of fuzzy neural network is designed for land suitability evaluation. This model is the result of integrated fuzzy system and artificial neural network. This fuzzy neural network model has five layers. The learning algorithm of the model has been designed based on the principle of error back propagation of neural networks. The learning strategy, algorithm and efficiency of the model have been tested and the results of test are satisfied.

Analysis on the dynamic balance between cultivated land supply and demand at multimeasures based on RS data

According to the specific situations in China, this paper discusses the application of RS data in analysing the dynamic balance between cultivated land supply and demand which is one of main tasks of the Ministry of Land and Resources of China. It points out that based on applying RS data to monitoring land use changes, we can make full use of RS data to extract the information required in the analysis on the balance, which is an important approach for dynamically mastering and regulating the balance. It presents the framework and main aspects for analysing the balance, including the environment of the balance, the elements of the balance, the state of the balance and the process of the balance, as well as analysis on the balance at multimeasures, such as the balance in quality, in Gross Amount, in Per capita Amount, in Region and in Time.

Relationships between Street Centrality and Land Use Intensity in Wuhan, China

AbstractAlthough the relationships between street centrality and land-use intensity have been documented, only a few studies have explained the disparities in the global relationships among different land-use types or explored the local spatial relationships among such types. In this paper, the previously mentioned problem is addressed by investigating the main urban area of Wuhan, China. The street centrality indicators of closeness, betweenness, and straightness are expanded by considering the node-based weight of the road grade and road width. Land-use intensity is measured based on the building and economic activity density in the different land-use types. Kernel density estimation is used to convert the measures to a basic raster unit, whereas the geographically weighted regression (GWR) method is used to explore the spatial heterogeneity in the relationships. The results indicate strong relationships between street centrality and land-use intensity. Furthermore, the relationships vary not only among...

Suitability evaluation of rural settlements based on accessibility of production and living: A case study of Tingzu Town in Hubei Province of China

Rural settlements are the main carriers of agriculture, rural areas and farmers; thus, optimizing the production and living space of rural settlements is highly significant to rural development. Taking the effective allocation of resources as the starting point, a suitability evaluation system of rural settlements, based on accessibility of production and living, was proposed in this study to provide scientific basis for the optimization of production and living space. The accessibility of production and living was measured by an improved two-step floating catchment area method, which considered proximity and availability based on the inclination of rural residents. The suitability evaluation system consisted of traditional suitability evaluation and newly proposed limiting factor identification based on the loss score proportion of suitability. Tingzu Town of Hubei Province, China, was chosen as the case study area. Based on the results of the suitability evaluation system, corresponding suggestions on rural land consolidation, industry division, as well as the layout of health care and education facilities were proposed to optimize the production and living space of rural settlements in Tingzu Town. It is found that the suitability evaluation based on accessibility of production and living is more scientific and accurate than the traditional ones which significantly overestimate production and living convenience. Moreover, the limiting factor identification can help us put forward suggestions according to local conditions and bring about the highly targeted optimization of production and living space of rural settlements.