Narrow Results

Urban Park green space is an essential carrier and form of urban recreation space, playing an important role in improving the ecological environment and enhancing the image of the city. With the process of urbanization and the continuous improvement of residents’ living standards, urban park construction has become increasingly important to meet people’s growing needs for a better life. However, the evaluation indicators for urban park green space in China mostly consider macroscopic levels, such as the area, number and per capita green area of parks. This cannot fully reflect the level of park green space services. Accessibility can reflect the convenience of residents to reach the park, provide guidance for the reasonable layout of parks and have various evaluation methods relying on geographic information technology. Therefore, it is necessary to quantitatively study the layout and accessibility of park green space. Taking the central urban area of Nanjing as the research object, this paper summarizes existing research and focuses on evaluating the accessibility of park green space while analyzing the layout of parks from multiple perspectives, combined with the existing pressure appraisal of park green space services. Relevant data on Nanjing, including overall planning and statistical yearbooks, were collected and analyzed using geographic information system (GIS) tools, network analysis and Thiessen polygon theory to analyze the service pressure, demand and accessibility of park green space in the central urban area under different transportation methods. Based on the results, targeted optimization strategies are proposed.

Nowadays, translating information about hydrologic and soil properties and processes across scales has emerged as a major theme in soil science and hydrology, and suitable theories for upscaling or downscaling hydrologic and soil information are being looked forward. The recognition of low-order catchments as self-organized systems suggests the existence of a great amount of links at different scales between their elements. The objective of this work was to research in areas of homogeneous bedrock material, the relationship between the hierarchical structure of the drainage networks at hillslope scale and the heterogeneity of the particle-size distribution at pedon scale. One of the most innovative elements in this work is the choice of the parameters to quantify the organization level of the studied features. The fractal dimension has been selected to measure the hierarchical structure of the drainage networks, while the Balanced Entropy Index (BEI) has been the chosen parameter to quantify the heterogeneity of the particle-size distribution from textural data. These parameters have made it possible to establish quantifiable relationships between two features attached to different steps in the scale range. Results suggest that the bedrock lithology of the landscape constrains the architecture of the drainage networks developed on it and the particle soil distribution resulting in the fragmentation processes.

In this paper, a GIS-based method was developed to extract the real-time traffic information (RTTI) from the Google Maps system for city roads. The method can be used to quantify both congested and free-flow traffic conditions. The roadway length was defined as congested length (CL) and free-flow length (FFL). Chengdu, the capital of Sichuan Province in the southwest of China, was chosen as a case study site. The RTTI data were extracted from the Google real-time maps in May 12–17, 2013 and were used to derive the CL and FFL for the study areas. The Multifractal Detrended Fluctuation Analysis (MFDFA) was used to characterize the long-term correlations of CL and FFL time series and their corresponding multifractal properties. Analysis showed that CL and FFL had demonstrated time nonlinearity and long-term correlations and both characteristics differed significantly. A shuffling procedure and a phase randomization procedure were further integrated with multifractal detrending moving average (MFDMA) to identify the major sources of multifractality of these two time series. The results showed that a multifractal process analysis could be used to characterize complex traffic data. Traffic data collected and methods developed in this paper will help better understand the complex traffic systems.

Geographical information system (GIS)-based noise simulation software (N-GNOIS) has been developed to simulate the noise scenario due to point and mobile sources considering the impact of geographical features and meteorological parameters. These have been addressed in the software through attenuation modules of atmosphere, vegetation and barrier. N-GNOIS is a user friendly, platform-independent and open geospatial consortia (OGC) compliant software. It has been developed using open source technology (QGIS) and open source language (Python). N-GNOIS has unique features like cumulative impact of point and mobile sources, building structure and honking due to traffic. Honking is the most common phenomenon in developing countries and is frequently observed on any type of roads. N-GNOIS also helps in designing physical barrier and vegetation cover to check the propagation of noise and acts as a decision making tool for planning and management of noise component in environmental impact assessment (EIA) studies.

The purpose of this work is to study the land cover and land types of Nanji Island. A scene IKONOS image was taken to classify the land types including village, farmland, shrubbery, meadow, reservoir, sands and so on. Then several models were built base on fractal theory to analyze the land types. Condition of the land cover and land use was analyzed at three aspects as following: 1) effects of patch area; 2) fractal characters of land types; 3) test of difference of fractal character between every two land types. The results show that the values of D of meadow and shrubbery are higher, and those of farmland and village are smaller, and that the fractal characters are determined by the degree of interferes of human activities.

Fluid modeling covers a wide range of principles describing the motion of matter and energy in dependence on spatial scales, time scales and other attributes. In order to provide efficient numeric calculations, the information systems have to be developed for management, pre-processing, post-processing and visualization. In spite of that many software tools contain sophisticated subsystems for data management and implement advanced numerical algorithms, there is still need to standardize data inputs/outputs, wide used data analyses, and case oriented computational tools under one roof. Thus, the geographic information system (GIS) is used to satisfy all the requirements. As an example, the case study focused on dust dispersion above the surface coal mine documents the GIS ability to solve all the tasks. The input data are represented by terrain measurements of meteorological conditions and by estimates of the emission rates of potential surface dust sources. Remote sensing helps to identify and classify the coal mine surface in order to map erosion sites and other surface objects. GPS is used to improve the accuracy of the erosion site boundaries and to locate other point emission sources such as excavators, storage sites, and line emission sources such as conveyors and roads. The 3D mine surface for modeling of wind flows and dust dispersion is based on GPS measurements and laser scanning. All data inputs are integrated together with simulation outputs in the spatial database in the framework of the GIS project. In case of dispersion modeling, a few ways can be used to provide numeric calculations together with GIS analyses. The traditionally used way represents using of standalone simulation tools and the input/output data linkage through shared data files. The more advanced way is the implementation of dispersion models in the GIS environment. The methods are demonstrated by using U.S. EPA modeling tools and by linking standalone numerical calculations in the GIS environment with using case oriented programming libraries and GIS development tools.