Calibrating a neural network‐based urban change model for two metropolitan areas of the Upper Midwest of the United States

We parameterized neural net‐based models for the Detroit and Twin Cities metropolitan areas in the US and attempted to test whether they were transferable across both metropolitan areas. Three different types of models were developed. First, we trained and tested the neural nets within each region and compared them against observed change. Second, we used the training weights from one area and applied them to the other. Third, we selected a small subset (～1%) of the Twin Cities area where a lot of urban change occurred. Four model performance metrics are reported: (1) Kappa; (2) the scale which correct and paired omission/commission errors exceed 50%; (3) landscape pattern metrics; and (4) percentage of cells in agreement between model simulations. We found that the neural net model in most cases performed well on pattern but not location using Kappa. The model performed well only in one case where the neural net weights from one area were used to simulate the other. We suggest that landscape metrics are good to judge model performance of land use change models but that Kappa might not be reliable for situations where a small percentage of urban areas change.     

An environmental decision‐support system for the management of water pollution in a tidal river network

This paper is about the development of a decision‐support system for water‐pollution management and environmental planning. More specifically, the paper first presents the overall concept and the system architecture of a generic environmental decision‐support system (EDSS) and then develops an EDSS especially for analysing the tidal flow pattern and water quality of China's Pearl River Delta. The EDSS developed here employs the object‐oriented approach to design the environmental database and utilizes the system integration technology to develop the overall user‐friendly system that operates in the Windows environment. Furthermore, the system can be expanded to facilitate automated model selection and analysis. The EDSS should be of value for managing water quality of river networks with complicated flow patterns, such as that found in the Pearl River Delta.     

GIS‐based multicriteria decision analysis: a survey of the literature

The integration of GIS and multicriteria decision analysis has attracted significant interest over the last 15 years or so. This paper surveys the GIS‐based multicriteria decision analysis (GIS‐MCDA) approaches using a literature review and classification of articles from 1990 to 2004. An electronic search indicated that over 300 articles appeared in refereed journals. The paper provides taxonomy of those articles and identifies trends and developments in GIS‐MCDA.     

Computation of the third‐order partial derivatives from a digital elevation model

Loci of extreme curvature of the topographic surface may be defined by the derivation function (T) depending on the first‐, second‐, and third‐order partial derivatives of elevation. The loci may partially describe ridge and thalweg lines. The first‐ and second‐order partial derivatives are commonly calculated from a digital elevation model (DEM) by fitting the second‐order polynomial to a 3×3 window. This approach cannot be used to compute the third‐order partial derivatives and T. We deduced formulae to estimate the first‐, second‐, and third‐order partial derivatives from a DEM fitting the third‐order polynomial to a 5×5 window. The polynomial is approximated to elevation values of the window. This leads to a local denoising that may enhance calculations. Under the same grid size of a DEM and root mean square error (RMSE) of elevation, calculation of the second‐order partial derivatives by the method developed results in significantly lower RMSE of the derivatives than that using the second‐order polynomial and the 3×3 window. An RMSE expression for the derivation function is deduced. The method proposed can be applied to derive any local topographic variable, such as slope gradient, aspect, curvatures, and T. Treatment of a DEM by the method developed demonstrated that T mapping may not substitute regional logistic algorithms to detect ridge/thalweg networks. However, the third‐order partial derivatives of elevation can be used in digital terrain analysis, particularly, in landform classifications.     

A proposed framework for feature‐level geospatial data sharing: a case study for transportation network data

Current data sharing in the Internet environment is supported using metadata at the file level. This approach has three fundamental shortcomings. First, sharing data from different sources with different semantics, data models, and acquisition methods usually requires data conversion and/or integration like data conflation. This can be tedious and error‐prone. Second, data updated from one source cannot be automatically propagated to other related data or applications. Finally, data sharing at the file level makes it difficult to provide feature‐level data for searching, accessing, and exchanging in real time over the Internet. This paper addresses these three issues by proposing a standards‐based framework for sharing geospatial data in the transportation application domain. The proposed framework uses a standard data model—geospatial data model proposed by the Geospatial One‐Stop initiative to harmonize the semantics and data models without the use of data integration methods. It uses Geography Markup Language (GML) for geospatial data coding and feature relationship, which provides a basis to propagate the data update from one source to related other sources and applications, and to search and extract data at the feature level. The framework uses the Web Feature Service (WFS) to search, access and extract data at the feature level from distributed sources. Finally, the Scalable Vector Graphics (SVG) standard was used for data display on the Web browser. Two transportation network datasets are used in the prototype case study to implement the proposed framework. The prototype allows the user to access and extract data at the feature level on the Web from distributed sources without downloading the full data file. It shows that the proposed standards‐based feature‐level data‐sharing system is capable of sharing data without data conflation, accessing, and exchanging data in real time at the feature level. The prototype also shows that changes in one database can be automatically reflected or propagated in another related database without data downloading.     

Temporal variability of climate in south‐eastern Australia: a reassessment of flood‐ and drought‐dominated regimes

Inter‐decadal periods of high and low flood activity have been considered to be the dominant factor driving river metamorphosis in catchments along the New South Wales coast. Recent work has questioned the data analysis techniques used in delineating the so‐called flood‐and drought‐dominated regimes (FDRs/DDRs). Concerns have also been raised about the validity of invoking a climatic control for river metamorphosis documented during the post‐European period, when extensive anthropogenic alteration of catchment and riparian vegetation has also occurred. This paper reviews the evolution of the FDR/DDR concept. We examine the evidence for FDRs/DDRs, and highlight problems with the original hydrological data sets, as well as with the techniques employed in the time‐series analysis. We discuss conceptual problems encountered in applying flood‐frequency analysis, and the failure of the proponents of the FDR/DDR theory to consider large‐scale climatic circulation patterns and the geographical boundaries of their influence. We conclude that the validity of the FDR/DDR notion has been seriously over‐stated, and that managing rivers on the basis that FDRs/DDRs have occurred in the past, and will continue to occur in the future, is likely to be ineffective.     

Representing geographical objects with scale‐induced indeterminate boundaries: A neural network‐based data model

The degree of uncertainty of many geographical objects has long been known to be in intimate relation with the scale of its observation and representation. Yet, the explicit consideration of scaling operations when modeling uncertainty is rarely found. In this study, a neural network‐based data model was investigated for representing geographical objects with scale‐induced indeterminate boundaries. Two types of neural units, combined with two types of activation function, comprise the processing core of the model, where the activation function can model either hard or soft transition zones. The construction of complex fuzzy regions, as well as lines and points, is discussed and illustrated with examples. It is shown how the level of detail that is apparent in the boundary at a given scale can be controlled through the degree of smoothness of each activation function. Several issues about the practical implementation of the model are discussed and indications on how to perform complex overlay operations of fuzzy maps provided. The model was illustrated through an example of representing multi‐resolution, sub‐pixel maps that are typically derived from remote sensing techniques.     

Preferential treatment in a transition economy: the case of state‐owned enterprises in the textile and garment industry in Vietnam

The article examines the role and contribution of preferential treatment of state enterprises to growth in the textile and garment industry. State enterprises are still the largest single sector in the textile and garment industry in Vietnam, but are losing market shares to private Vietnamese enterprises and foreign‐owned enterprises despite the benefits that they enjoy. However, in the present context of economic transition and keen competition in the global market, well‐managed state enterprises are attractive to foreign buyers of their products and have a role to play in market access abroad. This contrasts with the neoliberal notion that privatization is essential to competitiveness in the global market.     

Searching for a new dynamic of industrialization and urbanization: anatomy of China’s characteristic town program

The characteristic town program is one of China’s latest industrialization and urbanization strategies. Originating in Zhejiang, characteristic towns are expected to serve as platforms for industrial upgrading and the promotion urbanization. This paper attempts to analyze the characteristic town program by examining the reasons behind the origination of characteristic towns, as well as elucidating the towns’ components. The paper argues that this exploratory local program has been leveraged into a national-level strategy because the primary idea underlying characteristic towns has been in accordance with several of China’s critical policies. Furthermore, the paper presents the challenges that the characteristic town program has encountered. The characteristic town program can be viewed as a new effort of entrepreneurial governments and a spatial fix for capital during the period of industrial upgrading. This paper helps us to better understand one of China’s explorations in searching for a new dynamic of industrialization and urbanization.     

The spatial—temporal dynamic characteristics of the marsh in the Sanjianlg Plain

Using the methods of combining landscape ecology with GIS spatial analysis,this paper analyses the dynamics of the marsh landscape stucture of the Sanjing Plain in the past 20 years,furthermore,taking Fujin County,located in the north of the plain,as an example,analyzes the conversion between marsh and other land use types.It is shown that the marsh in the Sanjiang Plain decreased greatly in the past 20 years,but the trend has begun to reverse,The marsh area decreased by 51.33% from 1980 to 1996,whereas it decreased by 4.19% from 1996 to 2000.The fragmentation of the marsh increased;the number of the patches increased by 326 from 1986 to 1996,whereas it only increased by 18 patches from 1996 to 2000,It is obvious that the speed of patches number diminished and the marsh fragmentation decreased,which shows that the reclamation of the marsh converted from the fragmentation to the brim in a large area of the marsh.The reclaimed marsh has mainly converted to paddy field and dry land .Large area of the marsh.The reclaimed marsh has mainly converted to paddy fiedld and dry land.Large-scale reclamation in the Sanjiang Plain influences its natural environment directly:the climate of the region turns from cold and wet to warm and dry,which makes the marsh both in the low-temperature northern part and in the deeply stagnant eastern part suitable for further agricultural development.     

A network Kernel Density Estimation for linear features in space–time analysis of big trace data

ABSTRACT

Kernel Density Estimation (KDE) is an important approach to analyse spatial distribution of point features and linear features over 2-D planar space. Some network-based KDE methods have been developed in recent years, which focus on estimating density distribution of point events over 1-D network space. However, the existing KDE methods are not appropriate for analysing the distribution characteristics of certain kind of features or events, such as traffic jams, queue at intersections and taxi carrying passenger events. These events occur and distribute in 1-D road network space, and present a continuous linear distribution along network. This paper presents a novel Network Kernel Density Estimation method for Linear features (NKDE-L) to analyse the space–time distribution characteristics of linear features over 1-D network space. We first analyse the density distribution of each linear feature along networks, then estimate the density distribution for the whole network space in terms of the network distance and network topology. In the case study, we apply the NKDE-L to analyse the space–time dynamics of taxis’ pick-up events, with real road network and taxi trace data in Wuhan. Taxis’ pick-up events are defined and extracted as linear events (LE) in this paper. We first conduct a space–time statistics of pick-up LE in different temporal granularities. Then we analyse the space–time density distribution of the pick-up events in the road network using the NKDE-L, and uncover some dynamic patterns of people’s activities and traffic condition. In addition, we compare the NKDE-L with quadrat method and planar KDE. The comparison results prove the advantages of the NKDE-L in analysing spatial distribution patterns of linear features in network space.     

Local‐government data sharing: Evaluating the foundations of spatial data infrastructures

This paper presents a typology of local‐government data sharing arrangements in the US at a time when spatial data infrastructures (SDI) are moving into a second generation. In the first generation, the US National Spatial Data Infrastructure (NSDI) theoretically involved a pyramid of data integration resting on local‐government data sharing. Availability of local‐government data is the foundation for all SDI‐related data sharing in this model. However, first‐generation SDI data‐sharing activities and principles have gained only a tenuous hold in local governments. Some formalized data sharing occurs, but only infrequently in response to SDI programmes and policies. Previous research suggests that local‐government data sharing aligns with immediate organizational and practical concerns rather than state or national policies and programmes. We present research findings echoing extending these findings to show that local‐government data sharing is largely informal in nature and is undertaken to support existing governmental activities. NSDI principles remain simply irrelevant for the majority of surveyed local governments. The typology we present distinguishes four distinct types of local‐government data sharing arrangements that reflect institutional, political, and economic factors. The effectiveness of second generation, client‐service‐based SDI will be seriously constrained if the problems of local government take‐up fail to be addressed.     

Evaluating the effects of land‐use development policies on ex‐urban forest cover: An integrated agent‐based GIS approach

We use a GIS‐based agent‐based model (ABM), named dynamic ecological exurban development (DEED), with spatial data in hypothetical scenarios to evaluate the individual and interacting effects of lot‐size zoning and municipal land‐acquisition strategies on possible forest‐cover outcomes in Scio Township, a municipality in Southeastern Michigan. Agent types, characteristics, behavioural methods, and landscape perceptions (i.e. landscape aesthetics) are empirically informed using survey data, spatial analyses, and a USDA methodology for mapping landscape aesthetic quality. Results from our scenario experiments computationally verified literature that show large lot‐size zoning policies lead to greater sprawl, and large lot‐size zoning policies can lead to increased forest cover, although we found this effect to be small relative to municipal land acquisition. The return on land acquisition for forest conservation was strongly affected by the location strategy used to select parcels for conservation. Furthermore, the location strategy for forest conservation land acquisition was more effective at increasing aggregate forest levels than the independent zoning policies, the quantity of area acquired for forest conservation, and any combination of the two. The results using an integrated GIS and ABM framework for evaluating land‐use development policies on forest cover provide additional insight into how these types of policies may act out over time and what aspects of the policies were more influential towards the goal of maximising forest cover.     

Measuring the spatiotemporal variation and evolution of transport network of China’s megaregions

Megaregion has become a prominent feature of modern China. Reflecting upon China’s recent path of transport infrastructure construction, this research examines the spatiotemporal characteristics of transport network development and its accessibility impacts in China’s ten megaregions from 1982 to 2010. Using historical transport network data and multiple national censuses (1982, 1990, 2000 and 2010), we computed two levels of indicators of megaregional transport network: megaregion level and county level, and analyzed the intra-megaregion and inter-megaregion disparities of transport network of the ten megaregions of China. Transport networks at the megaregion level are measured by three indicators: 1) transport network density; 2) infrastructure endowment per capita; and 3) size of transport network’s standard ellipse. Two accessibility indicators for measuring transportation network at the county level are calculated: weighted average travel time and potential accessibility. The research results show the following: 1) Road and rail network densities witnessed the greatest growth during the 2000–2010 period, and growth was more significant for railway network. 2) By 2010, average road endowments per capita in inland megaregions became higher than in coastal megaregions, while average rail endowments per capita in coastal megaregions became higher than in inland megaregions. 3) The sizes and directions of the standard deviational ellipses of road and rail network changed continuously during the study period. However the changes of road network ellipses were relatively small, while the changes of railway network ellipses were more significant. 4) Megaregions have all benefited significantly from transportation infrastructure improvement in the past few decades in terms of WATT and potential accessibility, but the three giant megaregions benefited most.     

GIS,multi‐criteria and multi‐factor spatial analysis for the probability assessment of the existence of illegal landfills

This work deals with the identification of potentially contaminated areas using remote sensing, geographic information systems (GIS) and multi‐criteria spatial analysis. The identification of unknown illegal landfills is a crucial environmental problem in all developed and developing countries, where a large number of illegal waste deposits exist as a result of fast, and relatively unregulated, industrial growth over the past century. The criteria used to perform the spatial analysis are here selected by considering the characteristics which are ‘desirable’ for an illegal waste disposal site, chiefly related to the existence of roads for easy access and to a low population density which facilitates unnoticed dumping of illegal waste materials. A large dataset describing known legal and illegal landfills and the context of their location (population, road network, etc.) was used to perform a spatial statistical analysis to select factors and criteria allowing for the identification of the known waste deposits. The final result is a map describing the likelihood of an illegal waste deposit to be located at any arbitrary location. Such a probability map is then used together with remote sensing techniques to narrow down the set of possibly contaminated sites (Silvestri and Omri, 2008 Silvestri, S. and Omri, M. 2008. A method for the remote sensing identification of uncontrolled landfills: formulation and validation.. International Journal of Remote Sensing, 29(4): 975–989. [Taylor & Francis Online] , [Google Scholar]), which are candidates for further analyses and field investigations. The importance of the integration of GIS and remote sensing is highlighted and represents a key instrument for environmental management and for the spatially‐distributed characterization of possible uncontrolled landfill sites.     

Analysis on the evolution of city network based on the flow of highly cited Chinese scientists北大核心

The geographical flow of talents is affecting innovation activities worldwide, so the research on the spatial structure evolution of talent flows is particularly important. This article uses the 2014-2015 global list of highly cited scientists as raw data to retrieve the study and work experience of scientists, uses cities as the research scale, and uses the P-space model to build a highly cited Chinese scientist flow network. At the same time, uses quantile regression analyzes the impact of whether scientists in core cities are more productive. We found that: (1) The city network of highly cited Chinese scientists has the characteristics of a small-world network, and the network space structure presents a "Y-shaped" structure. China-U. S., China-Europe, and China-Australia are the main sides. (2) This article analyzes the source cities and the target cities in which scientists move, and finds that Beijing, Cambridge(UStates), Shanghai are the city with a high degree. (3) The distribution of scientists shows a trend of spreading with the development of the stage. (4) Scientists in core cities have more high-quality paper output. The increase in the degree of centrality of scientists' target cities has a greater impact on the output of scientists. © 2023 World Regional Studies.     

The population of the southern Alps: a new equilibrium?

Recent demographic trends in the Alpine areas of France are examined. It is found that a shift of population away from the Cote d'Azur has occurred since 1975. The importance of tourism for population growth in the Alpine areas is noted.     

Extensions of GAP‐tree and its implementation based on a non‐topological data model

This paper discusses extensions of GAP‐trees from three aspects and its implementation based on non‐topological structure in order to enhance access to large vector data sets. First of all, we apply cartographic generalization rules to build a generalization procedure of the GAP‐tree, which makes coarse representations more consistent with human cognition. Second, we replace the three‐dimensional (pseudo‐) Reactive‐tree index with a 2D R‐tree index and a B‐tree index to improve the system efficiency. Finally, we compress a binary GAP‐tree into multi‐way GAP‐trees in order to reduce data redundancy. The shallower multi‐way GAP‐trees not only eliminate redundant data but also accelerate the system's response time. The extensions have been successfully implemented in PostgreSQL. A test of Beijing's land‐use data at the 1:10 000 scale demonstrates that the extended GAP‐trees are efficient, compact, and easy to implement.