ISPRS International Journal of Geo-Information

4364 KiB

Open AccessArticle

A GIS- and Fuzzy Set-Based Online Land Price Evaluation Approach Supported by Intelligence-Aided Decision-Making

by Sheng Li, Zhigang Zhao, Qingyun Du and Yanjun Qiao

ISPRS Int. J. Geo-Inf. 2016, 5(7), 126; https://doi.org/10.3390/ijgi5070126 - 19 Jul 2016

Cited by 3 | Viewed by 5092

In recent years, with the reforms to the land use system and the development of urbanization in China, land price evaluation has tended towards marketization. Prices are determined by the government, the land transaction market and the public. It is necessary to propose [...] Read more.

In recent years, with the reforms to the land use system and the development of urbanization in China, land price evaluation has tended towards marketization. Prices are determined by the government, the land transaction market and the public. It is necessary to propose higher standards to be used in the evaluation process. This paper presents an online land price evaluation approach for convenience in evaluation. In a network environment, taking advantage of the data services provided by various departments, we propose two models to assist in decision-making: (1) a geographic information system (GIS)- and fuzzy set-based location factor quantification model, which adopts dynamic data, rules and quantification measures (based on the road network) to dynamically quantify location factors, thus transforming fuzzy sets into appropriate values; and (2) a neartude-based transaction sample push model, which quantifies the similarity between a given land and other samples, thus providing a basis for decision-making by an appraiser. This approach is applied in Shenzhen to evaluate its ability to simplify the work of appraisers and make their decisions more intuitive and objective in a real case. Full article

(This article belongs to the Special Issue Intelligent Spatial Decision Support)

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6643 KiB

Open AccessArticle

Recognition and Reconstruction of Zebra Crossings on Roads from Mobile Laser Scanning Data

by Lin Li, Da Zhang, Shen Ying and You Li

ISPRS Int. J. Geo-Inf. 2016, 5(7), 125; https://doi.org/10.3390/ijgi5070125 - 19 Jul 2016

Cited by 9 | Viewed by 6285

Abstract

Zebra crossings provide guidance and warning to pedestrians and drivers, thereby playing an important role in traffic safety management. Most previous studies have focused on detecting zebra stripes but have not provided full information about the areas, which is critical to both driver [...] Read more.

Zebra crossings provide guidance and warning to pedestrians and drivers, thereby playing an important role in traffic safety management. Most previous studies have focused on detecting zebra stripes but have not provided full information about the areas, which is critical to both driver assistance systems and guide systems for blind individuals. This paper presents a stepwise procedure for recognizing and reconstructing zebra crossings using mobile laser scanning data. First, we propose adaptive thresholding based on road surface partitioning to reduce the impact of intensity unevenness and improve the accuracy of road marking extraction. Then, dispersion degree filtering is used to reduce the noise. Finally, zebra stripes are recognized according to the rectangular feature and fixed size, which is followed by area reconstruction according to arrangement patterns. We test our method on three datasets captured by an Optech Lynx mobile mapping system. The total recognition rate of 90.91% demonstrates the effectiveness of the method. Full article

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2331 KiB

Open AccessArticle

The HD(CP)² Data Archive for Atmospheric Measurement Data

by Erasmia Stamnas, Andrea Lammert, Volker Winkelmann and Ulrich Lang

ISPRS Int. J. Geo-Inf. 2016, 5(7), 124; https://doi.org/10.3390/ijgi5070124 - 19 Jul 2016

Cited by 11 | Viewed by 6576

Abstract

The archiving of scientific data is a sophisticated mission in nearly all research projects. In this paper, we introduce a new online archive of atmospheric measurement data from the "High definition clouds and precipitation for advancing climate prediction" (HD(CP)²) research initiative. [...] Read more.

The archiving of scientific data is a sophisticated mission in nearly all research projects. In this paper, we introduce a new online archive of atmospheric measurement data from the "High definition clouds and precipitation for advancing climate prediction" (HD(CP)²) research initiative. The project data archive is quality managed, easy to use, and is now open for other atmospheric research data. The archive’s creation was already taken into account during the HD(CP)² project planning phase and the necessary resources were granted. The funding enabled the HD(CP)² project to build a sound archive structure, which guarantees that the collected data are accessible for all researchers in the project and beyond. Full article

(This article belongs to the Special Issue Research Data Management)

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Open AccessArticle

River Basin Information System: Open Environmental Data Management for Research and Decision Making

by Franziska Zander and Sven Kralisch

ISPRS Int. J. Geo-Inf. 2016, 5(7), 123; https://doi.org/10.3390/ijgi5070123 - 18 Jul 2016

Cited by 8 | Viewed by 8610

Abstract

An open, standardized data management and related service infrastructure is a crucial requirement for a seamless storage and exchange of data and information within research projects, for the dissemination of project results and for their application in decision making processes. However, typical project [...] Read more.

An open, standardized data management and related service infrastructure is a crucial requirement for a seamless storage and exchange of data and information within research projects, for the dissemination of project results and for their application in decision making processes. However, typical project databases often refer to only one research project and are limited to specific purposes. Once implemented, those systems are often not further maintained and updated, rendering the stored information useless once the system stops operating. The River Basin Information System (RBIS) presented here is designed to fit not only the requirements of one research project, but focuses on generic functions, extensibility and standards compliance typically found in interdisciplinary environmental research. Developed throughout more than 10 years of research cooperation worldwide, RBIS is designed to manage different types of environmental data with and without spatial context together with a rich set of metadata. Beside data management and storage, RBIS provides functions for the visualization, linking, analysis and processing of different types of data to support research, decision making, result dissemination and information discovery for all kinds of users. The focus of this paper is on the description of the technical implementation and the presentation of functions. This will be complemented by an overview of example applications and experiences during RBIS development and operation. Full article

(This article belongs to the Special Issue Research Data Management)

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4299 KiB

Open AccessArticle

A Point-Set-Based Footprint Model and Spatial Ranking Method for Geographic Information Retrieval

by Yong Gao, Dan Jiang, Xiang Zhong and Jingyi Yu

ISPRS Int. J. Geo-Inf. 2016, 5(7), 122; https://doi.org/10.3390/ijgi5070122 - 15 Jul 2016

Cited by 3 | Viewed by 5362

Abstract

In the recent big data era, massive spatial related data are continuously generated and scrambled from various sources. Acquiring accurate geographic information is also urgently demanded. How to accurately retrieve desired geographic information has become the prominent issue, needing to be resolved in [...] Read more.

In the recent big data era, massive spatial related data are continuously generated and scrambled from various sources. Acquiring accurate geographic information is also urgently demanded. How to accurately retrieve desired geographic information has become the prominent issue, needing to be resolved in high priority. The key technologies in geographic information retrieval are modeling document footprints and ranking documents based on their similarity evaluation. The traditional spatial similarity evaluation methods are mainly performed using a MBR (Minimum Bounding Rectangle) footprint model. However, due to its nature of simplification and roughness, the results of traditional methods tend to be isotropic and space-redundant. In this paper, a new model that constructs the footprints in the form of point-sets is presented. The point-set-based footprint coincides the nature of place names in web pages, so it is redundancy-free, consistent, accurate, and anisotropic to describe the spatial extents of documents, and can handle multi-scale geographic information. The corresponding spatial ranking method is also presented based on the point-set-based model. The new similarity evaluation algorithm of this method firstly measures multiple distances for the spatial proximity across different scales, and then combines the frequency of place names to improve the accuracy and precision. The experimental results show that the proposed method outperforms the traditional methods with higher accuracies under different searching scenarios. Full article

(This article belongs to the Special Issue Geographic Information Retrieval)

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Open AccessArticle

Modeling and Querying Moving Objects with Social Relationships

by Hengcai Zhang, Feng Lu and Jianqiu Xu

ISPRS Int. J. Geo-Inf. 2016, 5(7), 121; https://doi.org/10.3390/ijgi5070121 - 15 Jul 2016

Cited by 7 | Viewed by 4909

Abstract

Current moving-object database (MOD) systems focus on management of movement data, but pay less attention to modelling social relationships between moving objects and spatial-temporal trajectories in an integrated manner. This paper combines moving-object database and social network systems and presents a novel data [...] Read more.

Current moving-object database (MOD) systems focus on management of movement data, but pay less attention to modelling social relationships between moving objects and spatial-temporal trajectories in an integrated manner. This paper combines moving-object database and social network systems and presents a novel data model called Geo-Social-Moving (GSM) that enables the unified management of trajectories, underlying geographical space and social relationships for mass moving objects. A bulk of user-defined data types and corresponding operators are also proposed to facilitate geo-social queries on moving objects. An implementation framework for the GSM model is proposed, and a prototype system based on native Neo4J is then developed with two real-world data sets from the location-based social network systems. Compared with solutions based on traditional extended relational database management systems characterized by time-consuming table join operations, the proposed GSM model characterized by graph traversal is argued to be more powerful in representing mass moving objects with social relationships, and more efficient and stable for geo-social querying. Full article

(This article belongs to the Special Issue Location-Based Services)

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Open AccessArticle

Integrating Spatial and Attribute Characteristics of Extended Voronoi Diagrams in Spatial Patterning Research: A Case Study of Wuhan City in China

by Zuohua Miao, Yong Chen, Xiangyang Zeng and Jun Li

ISPRS Int. J. Geo-Inf. 2016, 5(7), 120; https://doi.org/10.3390/ijgi5070120 - 15 Jul 2016

Cited by 8 | Viewed by 7716

Abstract

Rapid urbanization has caused numerous problems, and the urban spatial structure has been a hot topic in sustainable development management. Urban spatial structure is affected by a series of factors. Thus, the research model should synthetically consider the spatial and non-spatial relationship of [...] Read more.

Rapid urbanization has caused numerous problems, and the urban spatial structure has been a hot topic in sustainable development management. Urban spatial structure is affected by a series of factors. Thus, the research model should synthetically consider the spatial and non-spatial relationship of every element. Here, we propose an extended Voronoi diagram for exploring the urban land spatial pattern. In essence, we first used a principal component analysis method to construct attribute evaluation indicators and obtained the attribute distance for each indicator. Second, we integrated spatial and attribute distances to extend the comparison distance for Voronoi diagrams, and then, we constructed the Voronoi aggregative homogeneous map of the study area. Finally, we make a spatial autocorrelation analysis by using GeoDA and SPSS software. Results show that: (1) the residential land cover aggregation is not significant, but spatial diffusion is obvious; (2) the commercial land cover aggregation is considerable; and (3) the spatial agglomeration degree of the industrial land cover is increased and mainly located in urban fringes. According to the neo-Marxist theory, we briefly analyzed the driving forces for shaping the urban spatial structure. To summarize, our approach yields important insights into the urban spatial structure characterized by attribute similarity with geospatial proximity, which contributes to a better understanding of the urban growth mechanism. In addition, it explicitly identifies ongoing urban transformations, potentially supporting the planning for sustainable urban land use and protection. Full article

(This article belongs to the Special Issue Advances and Innovations in Land Use/Cover Mapping)

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3550 KiB

Open AccessArticle

How Do Vegetation Density and Transportation Network Density Affect Crime across an Urban Central-Peripheral Gradient? A Case Study in Kitchener—Waterloo, Ontario

by Yikang Du and Jane Law

ISPRS Int. J. Geo-Inf. 2016, 5(7), 118; https://doi.org/10.3390/ijgi5070118 - 15 Jul 2016

Cited by 18 | Viewed by 7131

Abstract

The relationship between vegetation, transportation networks, and crime has been under debate. Vegetation has been positively correlated with fear of crime; however, the actual correlation between vegetation and occurrences of crime is uncertain. Transportation networks have also been connected with crime occurrence but [...] Read more.

The relationship between vegetation, transportation networks, and crime has been under debate. Vegetation has been positively correlated with fear of crime; however, the actual correlation between vegetation and occurrences of crime is uncertain. Transportation networks have also been connected with crime occurrence but their impact on crime tends to vary over different circumstances. By conducting spatial analyses, this study explores the associations between crime and vegetation as well as transportation networks in Kitchener-Waterloo. Further, geographically weighted regression modeling and a dummy urban variable representing the urban center/other urban areas were employed to explore the associations across an urban central-peripheral gradient. Associations were analyzed for crimes against persons and crimes against property for four specific crime types (assaults, vehicle theft, sex offences, and drugs). Results suggest that vegetation has a reverse association with crimes against persons and crimes against property while transportation networks have a positive relationship with these two types of crime. Additionally, vegetation can be a deterrent to vehicle theft crime and drugs, while transportation networks can be a facilitator of drug-related crimes. Besides, these two associations appear stronger in the urban center compared to the urban periphery. Full article

(This article belongs to the Special Issue Frontiers in Spatial and Spatiotemporal Crime Analytics)

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Open AccessArticle

A MongoDB-Based Management of Planar Spatial Data with a Flattened R-Tree

by Longgang Xiang, Juntao Huang, Xiaotian Shao and Dehao Wang

ISPRS Int. J. Geo-Inf. 2016, 5(7), 119; https://doi.org/10.3390/ijgi5070119 - 14 Jul 2016

Cited by 14 | Viewed by 7683

Abstract

This paper addresses how to manage planar spatial data using MongoDB, a popular NoSQL database characterized as a document-oriented, rich query language and high availability. The core idea is to flatten a hierarchical R-tree structure into a tabular MongoDB collection, during which R-tree [...] Read more.

This paper addresses how to manage planar spatial data using MongoDB, a popular NoSQL database characterized as a document-oriented, rich query language and high availability. The core idea is to flatten a hierarchical R-tree structure into a tabular MongoDB collection, during which R-tree nodes are represented as collection documents and R-tree pointers are expressed as document identifiers. By following this strategy, a storage schema to support R-tree-based create, read, update, and delete (CRUD) operations is designed and a module to manage planar spatial data by consuming and maintaining flattened R-tree structure is developed. The R-tree module is then seamlessly integrated into MongoDB, so that users could manipulate planar spatial data with existing command interfaces oriented to geodetic spatial data. The experimental evaluation, using real-world datasets with diverse coverage, types, and sizes, shows that planar spatial data can be effectively managed by MongoDB with our flattened R-tree and, therefore, the application extent of MongoDB will be greatly enlarged. Our work resulted in a MongoDB branch with R-tree support, which has been released on GitHub for open access. Full article

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Open AccessArticle

Exploring the Relationship between Remotely-Sensed Spectral Variables and Attributes of Tropical Forest Vegetation under the Influence of Local Forest Institutions

by Shivani Agarwal, Duccio Rocchini, Aniruddha Marathe and Harini Nagendra

ISPRS Int. J. Geo-Inf. 2016, 5(7), 117; https://doi.org/10.3390/ijgi5070117 - 14 Jul 2016

Cited by 5 | Viewed by 6131

Abstract

Conservation of forests outside protected areas is essential for maintaining forest connectivity, which largely depends on the effectiveness of local institutions. In this study, we use Landsat data to explore the relationship between vegetation structure and forest management institutions, in order to assess [...] Read more.

Conservation of forests outside protected areas is essential for maintaining forest connectivity, which largely depends on the effectiveness of local institutions. In this study, we use Landsat data to explore the relationship between vegetation structure and forest management institutions, in order to assess the efficacy of local institutions in management of forests outside protected areas. These forests form part of an important tiger corridor in Eastern Maharashtra, India. We assessed forest condition using 450 randomly placed 10 m radius circular plots in forest patches of villages with and without local institutions, to understand the impact of these institutions on forest vegetation. Tree density and species richness were significantly different between villages with and without local forest institutions, but there was no difference in tree biomass. We also found a significant difference in the relationship between tree density and NDVI between villages with and without local forest institutions. However, the relationship between species richness and NDVI did not differ significantly. The methods proposed by this study evaluate the status of forest management in a forest corridor using remotely sensed data and could be effectively used to identify the extent of vegetation health and management status. Full article

(This article belongs to the Special Issue Spatial Ecology)

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6378 KiB

Open AccessArticle

Proximity-Based Asynchronous Messaging Platform for Location-Based Internet of Things Service

by Hyeong Gon Jo, Tae Yong Son, Seol Young Jeong and Soon Ju Kang

ISPRS Int. J. Geo-Inf. 2016, 5(7), 116; https://doi.org/10.3390/ijgi5070116 - 14 Jul 2016

Cited by 7 | Viewed by 6362

Abstract

The Internet of Things (IoT) opens up tremendous opportunities to provide location-based applications. However, despite the services around a user being physically adjacent, common IoT platforms use a centralized structure, like a cloud-computing architecture, which transfers large amounts of data to a central [...] Read more.

The Internet of Things (IoT) opens up tremendous opportunities to provide location-based applications. However, despite the services around a user being physically adjacent, common IoT platforms use a centralized structure, like a cloud-computing architecture, which transfers large amounts of data to a central server. This raises problems, such as traffic concentration, long service latency, and high communication cost. In this paper, we propose a physical distance-based asynchronous messaging platform that specializes in processing personalized data and location-based messages. The proposed system disperses traffic using a location-based message-delivery protocol, and has high stability. Full article

(This article belongs to the Special Issue Applications of Internet of Things)

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Open AccessArticle

Integrating Logistic Regression and Geostatistics for User-Oriented and Uncertainty-Informed Accuracy Characterization in Remotely-Sensed Land Cover Change Information

by Jingxiong Zhang and Yingying Mei

ISPRS Int. J. Geo-Inf. 2016, 5(7), 113; https://doi.org/10.3390/ijgi5070113 - 14 Jul 2016

Cited by 14 | Viewed by 4996

Abstract

Accuracy is increasingly recognized as an important dimension in geospatial information and analyses. A strategy well suited for map users who usually have limited information about map lineages is proposed for location-specific characterization of accuracy in land cover change maps. Logistic regression is [...] Read more.

Accuracy is increasingly recognized as an important dimension in geospatial information and analyses. A strategy well suited for map users who usually have limited information about map lineages is proposed for location-specific characterization of accuracy in land cover change maps. Logistic regression is used to predict the probabilities of correct change categorization based on local patterns of map classes in the focal three by three pixel neighborhood centered at individual pixels being analyzed, while kriging is performed to make corrections to regression predictions based on regression residuals at sample locations. To promote uncertainty-informed accuracy characterization and to facilitate adaptive sampling of validation data, standard errors in both regression predictions and kriging interpolation are quantified to derive error margins in the aforementioned accuracy predictions. It was found that the integration of logistic regression and kriging leads to more accurate predictions of local accuracies through proper handling of spatially-correlated binary data representing pixel-specific (in)correct classifications than kriging or logistic regression alone. Secondly, it was confirmed that pixel-specific class labels, focal dominances and focal class occurrences are significant covariates for regression predictions at individual pixels. Lastly, error measures computed of accuracy predictions can be used for adaptively and progressively locating samples to enhance sampling efficiency and to improve predictions. The proposed methods may be applied for characterizing the local accuracy of categorical maps concerned in spatial applications, either input or output. Full article

(This article belongs to the Special Issue Advances and Innovations in Land Use/Cover Mapping)

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Open AccessArticle

Automatic Airport Recognition Based on Saliency Detection and Semantic Information

by Yetianjian Wang and Li Pan

ISPRS Int. J. Geo-Inf. 2016, 5(7), 115; https://doi.org/10.3390/ijgi5070115 - 13 Jul 2016

Cited by 8 | Viewed by 4624

Abstract

Effectively identifying an airport from satellite and aerial imagery is a challenging task. Traditional methods mainly focus on the use of multiple features for the detection of runways and some also adapt knowledge of airports, but the results are unsatisfactory and the usage [...] Read more.

Effectively identifying an airport from satellite and aerial imagery is a challenging task. Traditional methods mainly focus on the use of multiple features for the detection of runways and some also adapt knowledge of airports, but the results are unsatisfactory and the usage limited. A new method is proposed to recognize airports from high-resolution optical images. This method involves the analysis of the saliency distribution and the use of fuzzy rule-based classification. First, a number of images with and without airports are segmented into multiple scales to obtain a saliency distribution map that best highlights the saliency distinction between airports and other objects. Then, on the basis of the segmentation result and the structural information of airports, we analyze the segmentation result to extract and represent the semantic information of each image via the bag-of-visual-words (BOVW) model. The image correlation degree is combined with the BOVW model and fractal dimension calculation to make a more complete description of the airports and to carry out preliminary classification. Finally, the support vector machine (SVM) is adopted for detailed classification to classify the remaining imagery. The experiment shows that the proposed method achieves a precision of 89.47% and a recall of 90.67% and performs better than other state of the art methods on precision and recall. Full article

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5207 KiB

Open AccessArticle

A New Approach to Urban Road Extraction Using High-Resolution Aerial Image

by Jianhua Wang, Qiming Qin, Zhongling Gao, Jianghua Zhao and Xin Ye

ISPRS Int. J. Geo-Inf. 2016, 5(7), 114; https://doi.org/10.3390/ijgi5070114 - 13 Jul 2016

Cited by 42 | Viewed by 7549

Abstract

Road information is fundamental not only in the military field but also common daily living. Automatic road extraction from a remote sensing images can provide references for city planning as well as transportation database and map updating. However, owing to the spectral similarity [...] Read more.

Road information is fundamental not only in the military field but also common daily living. Automatic road extraction from a remote sensing images can provide references for city planning as well as transportation database and map updating. However, owing to the spectral similarity between roads and impervious structures, the current methods solely using spectral characteristics are often ineffective. By contrast, the detailed information discernible from the high-resolution aerial images enables road extraction with spatial texture features. In this study, a knowledge-based method is established and proposed; this method incorporates the spatial texture feature into urban road extraction. The spatial texture feature is initially extracted by the local Moran’s I, and the derived texture is added to the spectral bands of image for image segmentation. Subsequently, features like brightness, standard deviation, rectangularity, aspect ratio, and area are selected to form the hypothesis and verification model based on road knowledge. Finally, roads are extracted by applying the hypothesis and verification model and are post-processed based on the mathematical morphology. The newly proposed method is evaluated by conducting two experiments. Results show that the completeness, correctness, and quality of the results could reach approximately 94%, 90% and 86% respectively, indicating that the proposed method is effective for urban road extraction. Full article

(This article belongs to the Special Issue Big Data for Urban Informatics and Earth Observation)

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3071 KiB

Open AccessArticle

Evaluating Trade Areas Using Social Media Data with a Calibrated Huff Model

by Yandong Wang, Wei Jiang, Senbao Liu, Xinyue Ye and Teng Wang

ISPRS Int. J. Geo-Inf. 2016, 5(7), 112; https://doi.org/10.3390/ijgi5070112 - 12 Jul 2016

Cited by 45 | Viewed by 8030

Abstract

Delimitating trade areas is a major business concern. Today, mobile communication technologies make it possible to use social media data for this purpose. Few studies however, have focused on methods to extract suitable samples from social media data for trade area delimitation. In [...] Read more.

Delimitating trade areas is a major business concern. Today, mobile communication technologies make it possible to use social media data for this purpose. Few studies however, have focused on methods to extract suitable samples from social media data for trade area delimitation. In our case study, we divided Beijing into regular grid cells and extracted activity centers for each social media user. Ten sample sets were obtained by selecting users based on the retail agglomerations they visited and aggregating user activity centers to each grid cell. We calculated distance and visitation frequency attributes for each user and each grid cell. The distance value of a grid cell is the average distance of user activity centers in this grid cell to a retail agglomeration. The visitation frequency of a grid cell refers to the average count of visits to retail agglomerations by user activity centers for a cell. The calculated attribute values of 10 sets were input into a Huff model and the delimitated trade areas were evaluated. Results show that sets obtained by aggregating user activity centers have a better delimitating effect than sets obtained without aggregation. Differences in the distribution and intensity of trade areas also became apparent. Full article

(This article belongs to the Special Issue Volunteered Geographic Information)

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Open AccessArticle

Detecting Themed Streets Using a Location Based Service Application

by Byeongsuk Ji, Youngmin Lee, Kiyun Yu and Pil Kwon

ISPRS Int. J. Geo-Inf. 2016, 5(7), 111; https://doi.org/10.3390/ijgi5070111 - 12 Jul 2016

Cited by 3 | Viewed by 4808

Abstract

Various themed streets have recently been developed by local governments in order to stimulate local economies and to establish the identity of the corresponding places. However, the motivations behind the development of some of these themed street projects has been based on profit, [...] Read more.

Various themed streets have recently been developed by local governments in order to stimulate local economies and to establish the identity of the corresponding places. However, the motivations behind the development of some of these themed street projects has been based on profit, without full considerations of people’s perceptions of their local areas, resulting in marginal effects on the local economies concerned. In response to this issue, this study proposed a themed street clustering method to detect the themed streets of a specific region, focusing on the commercial themed street, which is more prevalent than other types of themed streets using location based service data. This study especially uses “the street segment” as a basic unit for analysis. The Sillim and Gangnam areas of Seoul, South Korea were chosen for the evaluation of the adequacy of the proposed method. By comparing trade areas that were sourced from a market analysis report by a reliable agent with the themed streets detected in this study, the experiment results showed high proficiency of the proposed method. Full article

(This article belongs to the Special Issue Location-Based Services)

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Open AccessArticle

The Size Distribution, Scaling Properties and Spatial Organization of Urban Clusters: A Global and Regional Percolation Perspective

by Till Fluschnik, Steffen Kriewald, Anselmo García Cantú Ros, Bin Zhou, Dominik E. Reusser, Jürgen P. Kropp and Diego Rybski

ISPRS Int. J. Geo-Inf. 2016, 5(7), 110; https://doi.org/10.3390/ijgi5070110 - 12 Jul 2016

Cited by 34 | Viewed by 7744

Abstract

Human development has far-reaching impacts on the surface of the globe. The transformation of natural land cover occurs in different forms, and urban growth is one of the most eminent transformative processes. We analyze global land cover data and extract cities as defined [...] Read more.

Human development has far-reaching impacts on the surface of the globe. The transformation of natural land cover occurs in different forms, and urban growth is one of the most eminent transformative processes. We analyze global land cover data and extract cities as defined by maximally connected urban clusters. The analysis of the city size distribution for all cities on the globe confirms Zipf’s law. Moreover, by investigating the percolation properties of the clustering of urban areas we assess the closeness to criticality for various countries. At the critical thresholds, the urban land cover of the countries undergoes a transition from separated clusters to a gigantic component on the country scale. We study the Zipf-exponents as a function of the closeness to percolation and find a systematic dependence, which could be the reason for deviating exponents reported in the literature. Moreover, we investigate the average size of the clusters as a function of the proximity to percolation and find country specific behavior. By relating the standard deviation and the average of cluster sizes—analogous to Taylor’s law—we suggest an alternative way to identify the percolation transition. We calculate spatial correlations of the urban land cover and find long-range correlations. Finally, by relating the areas of cities with population figures we address the global aspect of the allometry of cities, finding an exponent δ ≈ 0.85, i.e., large cities have lower densities. Full article

(This article belongs to the Special Issue Recent Trends in Spatial Analysis and Modelling of Built-Environment Characteristics)

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Open AccessArticle

A SMAP Supervised Classification of Landsat Images for Urban Sprawl Evaluation

by Flavia Di Palma, Federico Amato, Gabriele Nolè, Federico Martellozzo and Beniamino Murgante

ISPRS Int. J. Geo-Inf. 2016, 5(7), 109; https://doi.org/10.3390/ijgi5070109 - 6 Jul 2016

Cited by 39 | Viewed by 8381

Abstract

The negative impacts of land take on natural components and economic resources affect planning choices and territorial policies. The importance of land take monitoring, in Italy, has been only recently considered, but despite this awareness, in the great part of the country, effective [...] Read more.

The negative impacts of land take on natural components and economic resources affect planning choices and territorial policies. The importance of land take monitoring, in Italy, has been only recently considered, but despite this awareness, in the great part of the country, effective monitoring and containment measures have not been started, yet. This research proposes a methodology to map and monitor land use changes. To this end, a time series from 1985–2010, based on the multi-temporal Landsat data Thematic Mapper (TM), has been analyzed in the Vulture Alto-Bradano area, a mountain zone of the Basilicata region (Southern Italy). Results confirm a double potentiality of using these data: on the one hand, the use of multi-temporal Landsat data allows going very back in time, producing accurate datasets that provide a phenomenon trend over time; on the other hand, these data can be considered a first experience of open data in the field of spatial information. The proposed methodology provides agencies, local authorities and practitioners with a valuable tool to implement monitoring actions. This represents the first step to pursue territorial governance methods based on sustainability, limiting the land take. Full article

(This article belongs to the Special Issue Recent Trends in Spatial Analysis and Modelling of Built-Environment Characteristics)

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3519 KiB

Open AccessArticle

Volunteered Geographic Information System Design: Project and Participation Guidelines

by José-Pablo Gómez-Barrón, Miguel-Ángel Manso-Callejo, Ramón Alcarria and Teresa Iturrioz

ISPRS Int. J. Geo-Inf. 2016, 5(7), 108; https://doi.org/10.3390/ijgi5070108 - 5 Jul 2016

Cited by 21 | Viewed by 10822

Abstract

This article sets forth the early phases of a methodological proposal for designing and developing Volunteered Geographic Information (VGI) initiatives based on a system perspective analysis in which the components depend and interact dynamically among each other. First, it focuses on those characteristics [...] Read more.

This article sets forth the early phases of a methodological proposal for designing and developing Volunteered Geographic Information (VGI) initiatives based on a system perspective analysis in which the components depend and interact dynamically among each other. First, it focuses on those characteristics of VGI projects that present different goals and modes of organization, while using a crowdsourcing strategy to manage participants and contributions. Next, a tool is developed in order to design the central crowdsourced processing unit that is best suited for a specific project definition, associating it with a trend towards crowd-based or community-driven approaches. The design is structured around the characterization of different ways of participating, and the task cognitive demand of working on geo-information management, spatial problem solving and ideation, or knowledge acquisition. Then, the crowdsourcing process design helps to identify what kind of participants are needed and outline subsequent engagement strategies. This is based on an analysis of differences among volunteers’ participatory behaviors and the associated set of factors motivating them to contribute, whether on a crowd or community-sourced basis. From a VGI system perspective, this paper presents a set of guidelines and methodological steps in order to align project goals, processes and volunteers and thus successfully attract participation. This methodology helps establish the initial requirements for a VGI system, and, in its current state, it mainly focuses on two components of the system: project and participants. Full article

(This article belongs to the Special Issue Volunteered Geographic Information)

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Open AccessArticle

Modeling Change of Topographic Spatial Structures with DEM Resolution Using Semi-Variogram Analysis and Filter Bank

by Chunmei Wang, Qinke Yang, David Laurence Barry Jupp and Guowei Pang

ISPRS Int. J. Geo-Inf. 2016, 5(7), 107; https://doi.org/10.3390/ijgi5070107 - 30 Jun 2016

Cited by 10 | Viewed by 5834

Abstract

In this paper, the way topographic spatial information changes with resolution was investigated using semi-variograms and an Independent Structures Model (ISM) to identify the mechanisms involved in changes of topographic parameters as resolution becomes coarser or finer. A typical Loess Hilly area in [...] Read more.

In this paper, the way topographic spatial information changes with resolution was investigated using semi-variograms and an Independent Structures Model (ISM) to identify the mechanisms involved in changes of topographic parameters as resolution becomes coarser or finer. A typical Loess Hilly area in the Loess Plateau of China was taken as the study area. DEMs with resolutions of 2.5 m and 25 m were derived from topographic maps with map scales of 1:10,000 using ANUDEM software. The ISM, in which the semi-variogram was modeled as the sum of component semi-variograms, was used to model the measured semi-variogram of the elevation surface. Components were modeled using an analytic ISM model and corresponding landscape components identified using Kriging and filter bank analyses. The change in the spatial components as resolution became coarser was investigated by modeling upscaling as a low pass linear filter and applying a general result to obtain an analytic model for the scaling process in terms of semi-variance. This investigation demonstrated how topographic structures could be effectively characterised over varying scales using the ISM model for the semi-variogram. The loss of information in the short range components with resolution is a major driver for the observed change in derived topographic parameters such as slope. This paper has helped to quantify how information is distributed among scale components and how it is lost in natural terrain surfaces as resolution becomes coarser. It is a basis for further applications in the field of geomorphometry. Full article

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Open AccessArticle

A Local Land Use Competition Cellular Automata Model and Its Application

by Jun Yang, Junru Su, Fei Chen, Peng Xie and Quansheng Ge

ISPRS Int. J. Geo-Inf. 2016, 5(7), 106; https://doi.org/10.3390/ijgi5070106 - 30 Jun 2016

Cited by 40 | Viewed by 10125

Abstract

Cellular automaton (CA) is an important method in land use and cover change studies, however, the majority of research focuses on the discovery of macroscopic factors affecting LUCC, which results in ignoring the local effects within the neighborhoods. This paper introduces a Local [...] Read more.

Cellular automaton (CA) is an important method in land use and cover change studies, however, the majority of research focuses on the discovery of macroscopic factors affecting LUCC, which results in ignoring the local effects within the neighborhoods. This paper introduces a Local Land Use Competition Cellular Automata (LLUC-CA) model, based on local land use competition, land suitability evaluation, demand analysis of the different land use types, and multi-target land use competition allocation algorithm to simulate land use change at a micro level. The model is applied to simulate land use changes at Jinshitan National Tourist Holiday Resort from 1988 to 2012. The results show that the simulation accuracies were 64.46%, 77.21%, 85.30% and 99.14% for the agricultural land, construction land, forestland and water, respectively. In addition, comparing the simulation results of the LLUC-CA and CA-Markov model with the real land use data, their overall spatial accuracies were found to be 88.74% and 86.82%, respectively. In conclusion, the results from this study indicated that the model was an acceptable method for the simulation of large-scale land use changes, and the approach used here is applicable to analyzing the land use change driven forces and assist in decision-making. Full article

(This article belongs to the Special Issue Advances and Innovations in Land Use/Cover Mapping)

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5602 KiB

Open AccessArticle

Discovering Land Cover Web Map Services from the Deep Web with JavaScript Invocation Rules

by Dongyang Hou, Jun Chen and Hao Wu

ISPRS Int. J. Geo-Inf. 2016, 5(7), 105; https://doi.org/10.3390/ijgi5070105 - 30 Jun 2016

Cited by 10 | Viewed by 7854

Abstract

Automatic discovery of isolated land cover web map services (LCWMSs) can potentially help in sharing land cover data. Currently, various search engine-based and crawler-based approaches have been developed for finding services dispersed throughout the surface web. In fact, with the prevalence of geospatial [...] Read more.

Automatic discovery of isolated land cover web map services (LCWMSs) can potentially help in sharing land cover data. Currently, various search engine-based and crawler-based approaches have been developed for finding services dispersed throughout the surface web. In fact, with the prevalence of geospatial web applications, a considerable number of LCWMSs are hidden in JavaScript code, which belongs to the deep web. However, discovering LCWMSs from JavaScript code remains an open challenge. This paper aims to solve this challenge by proposing a focused deep web crawler for finding more LCWMSs from deep web JavaScript code and the surface web. First, the names of a group of JavaScript links are abstracted as initial judgements. Through name matching, these judgements are utilized to judge whether or not the fetched webpages contain predefined JavaScript links that may prompt JavaScript code to invoke WMSs. Secondly, some JavaScript invocation functions and URL formats for WMS are summarized as JavaScript invocation rules from prior knowledge of how WMSs are employed and coded in JavaScript. These invocation rules are used to identify the JavaScript code for extracting candidate WMSs through rule matching. The above two operations are incorporated into a traditional focused crawling strategy situated between the tasks of fetching webpages and parsing webpages. Thirdly, LCWMSs are selected by matching services with a set of land cover keywords. Moreover, a search engine for LCWMSs is implemented that uses the focused deep web crawler to retrieve and integrate the LCWMSs it discovers. In the first experiment, eight online geospatial web applications serve as seed URLs (Uniform Resource Locators) and crawling scopes; the proposed crawler addresses only the JavaScript code in these eight applications. All 32 available WMSs hidden in JavaScript code were found using the proposed crawler, while not one WMS was discovered through the focused crawler-based approach. This result shows that the proposed crawler has the ability to discover WMSs hidden in JavaScript code. The second experiment uses 4842 seed URLs updated daily. The crawler found a total of 17,874 available WMSs, of which 11,901 were LCWMSs. Our approach discovered a greater number of services than those found using previous approaches. It indicates that the proposed crawler has a large advantage in discovering LCWMSs from the surface web and from JavaScript code. Furthermore, a simple case study demonstrates that the designed LCWMS search engine represents an important step towards realizing land cover information integration for global mapping and monitoring purposes. Full article

(This article belongs to the Special Issue Bridging the Gap between Geospatial Theory and Technology)

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Open AccessArticle

Application of GPS Trajectory Data for Investigating the Interaction between Human Activity and Landscape Pattern: A Case Study of the Lijiang River Basin, China

by Jun Li, Yuan Zhang, Xiang Wang, Qiming Qin, Zhuangzhuang Wei and Jingze Li

ISPRS Int. J. Geo-Inf. 2016, 5(7), 104; https://doi.org/10.3390/ijgi5070104 - 29 Jun 2016

Cited by 17 | Viewed by 6239

Abstract

The interaction between human activity and landscape pattern has been a hot research topic during the last few decades. However, scholars used to measure human activity by social, economic and humanistic indexes. These indexes cannot directly reflect human activity and are not suitable [...] Read more.

The interaction between human activity and landscape pattern has been a hot research topic during the last few decades. However, scholars used to measure human activity by social, economic and humanistic indexes. These indexes cannot directly reflect human activity and are not suitable for fine-grained analysis due to the coarse spatial resolution. In view of the above problems, this paper proposes a method that obtains the intensity of human activity from GPS trajectory data, collects landscape information from remote sensing images and further analyzes the interaction between human activity and landscape pattern at a fine-grained scale. The Lijiang River Basin is selected as the study area. Experimental results show that human activity and landscape pattern interact synergistically in this area. Built-up land and water boost human activity, while woodland restrains human activity. The effect of human activity on landscape pattern differs by the land cover category. Overall, human activities make natural land, such as woodland and water, scattered and fragmented, but cause man-built land, such as built-up land and farmland, clustered and regular. Nevertheless, human activities inside and outside urban areas are the opposite. The research findings in this paper are helpful for designing and implementing sustainable management plans. Full article

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Open AccessReview

Volunteered Geographic Information in Natural Hazard Analysis: A Systematic Literature Review of Current Approaches with a Focus on Preparedness and Mitigation

by Carolin Klonner, Sabrina Marx, Tomás Usón, João Porto de Albuquerque and Bernhard Höfle

ISPRS Int. J. Geo-Inf. 2016, 5(7), 103; https://doi.org/10.3390/ijgi5070103 - 25 Jun 2016

Cited by 70 | Viewed by 11625

Abstract

With the rise of new technologies, citizens can contribute to scientific research via Web 2.0 applications for collecting and distributing geospatial data. Integrating local knowledge, personal experience and up-to-date geoinformation indicates a promising approach for the theoretical framework and the methods of natural [...] Read more.

With the rise of new technologies, citizens can contribute to scientific research via Web 2.0 applications for collecting and distributing geospatial data. Integrating local knowledge, personal experience and up-to-date geoinformation indicates a promising approach for the theoretical framework and the methods of natural hazard analysis. Our systematic literature review aims at identifying current research and directions for future research in terms of Volunteered Geographic Information (VGI) within natural hazard analysis. Focusing on both the preparedness and mitigation phase results in eleven articles from two literature databases. A qualitative analysis for in-depth information extraction reveals auspicious approaches regarding community engagement and data fusion, but also important research gaps. Mainly based in Europe and North America, the analysed studies deal primarily with floods and forest fires, applying geodata collected by trained citizens who are improving their knowledge and making their own interpretations. Yet, there is still a lack of common scientific terms and concepts. Future research can use these findings for the adaptation of scientific models of natural hazard analysis in order to enable the fusion of data from technical sensors and VGI. The development of such general methods shall contribute to establishing the user integration into various contexts, such as natural hazard analysis. Full article

(This article belongs to the Special Issue Volunteered Geographic Information)

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Open AccessArticle

Exploring the Influence of Neighborhood Characteristics on Burglary Risks: A Bayesian Random Effects Modeling Approach

by Hongqiang Liu and Xinyan Zhu

ISPRS Int. J. Geo-Inf. 2016, 5(7), 102; https://doi.org/10.3390/ijgi5070102 - 23 Jun 2016

Cited by 15 | Viewed by 5567

Abstract

A Bayesian random effects modeling approach was used to examine the influence of neighborhood characteristics on burglary risks in Jianghan District, Wuhan, China. This random effects model is essentially spatial; a spatially structured random effects term and an unstructured random effects term are [...] Read more.

A Bayesian random effects modeling approach was used to examine the influence of neighborhood characteristics on burglary risks in Jianghan District, Wuhan, China. This random effects model is essentially spatial; a spatially structured random effects term and an unstructured random effects term are added to the traditional non-spatial Poisson regression model. Based on social disorganization and routine activity theories, five covariates extracted from the available data at the neighborhood level were used in the modeling. Three regression models were fitted and compared by the deviance information criterion to identify which model best fit our data. A comparison of the results from the three models indicates that the Bayesian random effects model is superior to the non-spatial models in fitting the data and estimating regression coefficients. Our results also show that neighborhoods with above average bar density and department store density have higher burglary risks. Neighborhood-specific burglary risks and posterior probabilities of neighborhoods having a burglary risk greater than 1.0 were mapped, indicating the neighborhoods that should warrant more attention and be prioritized for crime intervention and reduction. Implications and limitations of the study are discussed in our concluding section. Full article

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Open AccessArticle

Simulation and Evaluation of Urban Growth for Germany Including Climate Change Mitigation and Adaptation Measures

by Jana Hoymann and Roland Goetzke

ISPRS Int. J. Geo-Inf. 2016, 5(7), 101; https://doi.org/10.3390/ijgi5070101 - 23 Jun 2016

Cited by 19 | Viewed by 8012

Abstract

Decision-makers in the fields of urban and regional planning in Germany face new challenges. High rates of urban sprawl need to be reduced by increased inner-urban development while settlements have to adapt to climate change and contribute to the reduction of greenhouse gas [...] Read more.

Decision-makers in the fields of urban and regional planning in Germany face new challenges. High rates of urban sprawl need to be reduced by increased inner-urban development while settlements have to adapt to climate change and contribute to the reduction of greenhouse gas emissions at the same time. In this study, we analyze conflicts in the management of urban areas and develop integrated sustainable land use strategies for Germany. The spatial explicit land use change model Land Use Scanner is used to simulate alternative scenarios of land use change for Germany for 2030. A multi-criteria analysis is set up based on these scenarios and based on a set of indicators. They are used to measure whether the mitigation and adaptation objectives can be achieved and to uncover conflicts between these aims. The results show that the built-up and transport area development can be influenced both in terms of magnitude and spatial distribution to contribute to climate change mitigation and adaptation. Strengthening the inner-urban development is particularly effective in terms of reducing built-up and transport area development. It is possible to reduce built-up and transport area development to approximately 30 ha per day in 2030, which matches the sustainability objective of the German Federal Government for the year 2020. In the case of adaptation to climate change, the inclusion of extreme flood events in the context of spatial planning requirements may contribute to a reduction of the damage potential. Full article

(This article belongs to the Special Issue Recent Trends in Spatial Analysis and Modelling of Built-Environment Characteristics)

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Open AccessArticle

Mapping Historical Data: Recovering a Forgotten Floristic and Vegetation Database for Biodiversity Monitoring

by Francesco Geri, Nicola La Porta, Fabio Zottele and Marco Ciolli

ISPRS Int. J. Geo-Inf. 2016, 5(7), 100; https://doi.org/10.3390/ijgi5070100 - 23 Jun 2016

Cited by 9 | Viewed by 6401

Abstract

Multitemporal biodiversity data on a forest ecosystem can provide useful information about the evolution of biodiversity in a territory. The present study describes the recovery of an archive used to determine the main Schmid’s vegetation belts in Trento Province, Italy. The archive covers [...] Read more.

Multitemporal biodiversity data on a forest ecosystem can provide useful information about the evolution of biodiversity in a territory. The present study describes the recovery of an archive used to determine the main Schmid’s vegetation belts in Trento Province, Italy. The archive covers 20 years, from the 1970s to the 1990s. During the FORCING project (an Italian acronym for Cingoli Forestali, i.e., forest belts), a comprehensive process of database recovering was executed, and missing data were digitized from historical maps, preserving paper-based maps and documents. All of the maps of 16 forest districts, and the related 8000 detected transects, have been georeferenced to make the whole database spatially explicit and to evaluate the possibility of performing comparative samplings on up-to-date datasets. The floristic raw data (approximately 200,000 specific identifications, including frequency indices) still retain an important and irreplaceable information value. The data can now be browsed via a web-GIS. We provide here a set of examples of the use of this type of data, and we highlight the potential and the limits of the specific dataset and of the historical database, in general. Full article

(This article belongs to the Special Issue Spatial Ecology)

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ISPRS Int. J. Geo-Inf., Volume 5, Issue 7 (July 2016) – 27 articles

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