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Volume 6
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ISPRS Int. J. Geo-Inf., Volume 6, Issue 5 (May 2017) – 29 articles

Cover Story (view full-size image): Tourism is one of the most economically important industries worldwide. It is, however, vulnerable to disaster events. Geotagged social media data, as one of the forms of volunteered geographic information (VGI), has been widely explored to support the prevention, preparation, and response phases of disaster management, while little effort has been put on the recovery phase. Our study develops a scientific workflow and methods to monitor and assess post-disaster tourism recovery using geotagged Flickr photos, which involve a viewshed-based data quality enhancement, a space-time bin-based quantitative photo analysis, and a crowdsourcing-based qualitative photo analysis. View this paper
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1222 KiB  
Review
The Standardization and Harmonization of Land Cover Classification Systems towards Harmonized Datasets: A Review
by Hui Yang, Songnian Li, Jun Chen, Xiaolu Zhang and Shishuo Xu
ISPRS Int. J. Geo-Inf. 2017, 6(5), 154; https://doi.org/10.3390/ijgi6050154 - 19 May 2017
Cited by 47 | Viewed by 9179
Abstract
A number of national, regional and global land cover classification systems have been developed to meet specific user requirements for land cover mapping exercises, independent of scale, nomenclature and quality. However, this variety of land-cover classification systems limits the compatibility and comparability of [...] Read more.
A number of national, regional and global land cover classification systems have been developed to meet specific user requirements for land cover mapping exercises, independent of scale, nomenclature and quality. However, this variety of land-cover classification systems limits the compatibility and comparability of land cover data. Furthermore, the current lack of interoperability between different land cover datasets, often stemming from incompatible land cover classification systems, makes analysis of multi-source, heterogeneous land cover data for various applications a very difficult task. This paper provides a critical review of the harmonization of land cover classification systems, which facilitates the generation, use and analysis of land cover maps consistently. Harmonization of existing land cover classification systems is essential to improve their cross-comparison and validation for understanding landscape patterns and changes. The paper reviews major land cover classification standards according to different scales, summarizes studies on harmonizing land cover mapping, and discusses some research problems that need to be solved and some future research directions. Full article
(This article belongs to the Special Issue Analysis and Applications of Global Land Cover Data)
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4863 KiB  
Article
A Novel Analysis Method of Geographical Centrality Based on Space of Flows
by Jiwei Li, Jing Qian and Yaolin Liu
ISPRS Int. J. Geo-Inf. 2017, 6(5), 153; https://doi.org/10.3390/ijgi6050153 - 17 May 2017
Cited by 6 | Viewed by 9361
Abstract
Geographical centrality is an evolving concept that differs from one perspective to another at different stages. The unprecedented development of high-speed information and transportation networks has highlighted the important role of space of flows and has restructured the mode of spatial interaction. The [...] Read more.
Geographical centrality is an evolving concept that differs from one perspective to another at different stages. The unprecedented development of high-speed information and transportation networks has highlighted the important role of space of flows and has restructured the mode of spatial interaction. The geographical centrality analysis method based on relational networks currently becomes the mainstream, but most related methods ignore the spatial structure. In this study, we first analyze the impacts of space of flows on geographical space based on spatial interaction theory. We argue that geographical space and space of flows dominate short- and long-distance interactions, respectively. Based on this hypothesis, the concept of geographical centrality based on space of flows is proposed. The new concept categorizes spatial units into four types: global centers, isolated units, externally oriented units, and locally oriented units. Then, two quantitative measures, namely, global and local geographical centrality indexes, are defined. In the case study, we analyze the geographical centrality of cities in China at three different spatial scales and compare the result with three other geographical centrality analysis methods. City attribute is concluded to be more important than spatial distance in urban spatial interaction at the national scale, and this situation is caused by the effect of space of flows on geographical space. The similarities and differences between the proposed geographical centrality analysis method and the classic spatial autocorrelation analysis method of Moran’s I are also discussed. Full article
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16300 KiB  
Article
Accuracy Assessment and Inter-Comparison of Eight Medium Resolution Forest Products on the Loess Plateau, China
by Zhiqi Yang, Jinwei Dong, Jiyuan Liu, Jun Zhai, Wenhui Kuang, Guosong Zhao, Wei Shen, Yan Zhou, Yuanwei Qin and And Xiangming Xiao
ISPRS Int. J. Geo-Inf. 2017, 6(5), 152; https://doi.org/10.3390/ijgi6050152 - 14 May 2017
Cited by 28 | Viewed by 6139
Abstract
Forests play an important role in maintaining ecosystem services, especially in ecologically fragile areas such as the Loess Plateau (LP) in China. However, there is still great uncertainty in the spatial extent and distribution of forests in such a fragmented region. In order [...] Read more.
Forests play an important role in maintaining ecosystem services, especially in ecologically fragile areas such as the Loess Plateau (LP) in China. However, there is still great uncertainty in the spatial extent and distribution of forests in such a fragmented region. In order to examine the advantages and disadvantages of existing forest mapping products, we conducted a thorough accuracy assessment on the eight recent, medium resolution (30–50 m) products by using the LP in 2010 as the region of interest. These mapping products include Landsat and/or PALSAR images (including the forest products from GlobeLand30), FROM-GLC, Hansen, ChinaCover, NLCD-China, GLCF VCF, OU-FDL, and JAXA. The same validation data were used to assess and rank the accuracy of each product. Additionally, the spatial consistency of the different forest products and their dependence on the terrain were analyzed. The results showed that the overall accuracies of the eight forest products on the LP in 2010 were between 0.93 ± 0.003 and 0.97 ± 0.002 with a 95% confidence interval, and GlobeLand30 presented the highest overall accuracy (0.97 ± 0.002). Among them, the PALSAR-based products (OU-FDL and JAXA) indicated relatively high accuracies, while the six Landsat-based products showed a large diversity in the accuracy. According to the eight products, the total estimated forest area of the LP varied from 7.627 ± 0.077 to 10.196 ± 0.1 million ha with a 95% confidence interval. We also found that the consistency in the spatial distribution of forests between these maps: 1) increased substantially with increasing elevation until 2000m, but then decreased at higher elevations, and 2) showed mild variation along increasing slope, but had a slight rate of increase. Our findings implied that future forest mapping studies should consider topographical attributes such as elevation and slope in their final products. Our results are fundamental in guiding future applications of these existing forest maps. Full article
(This article belongs to the Special Issue Analysis and Applications of Global Land Cover Data)
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6103 KiB  
Article
Spatio-Temporal Behavior Analysis and Pheromone-Based Fusion Model for Big Trace Data
by Luliang Tang, Qianqian Zou, Xia Zhang, Chang Ren and Qingquan Li
ISPRS Int. J. Geo-Inf. 2017, 6(5), 151; https://doi.org/10.3390/ijgi6050151 - 12 May 2017
Cited by 5 | Viewed by 5329
Abstract
People leave traces of movements that might affect the behavior of others both online in cyberspace and offline in real space. Previous studies, however, have used only questionnaires, network data, or GPS data to study spatio-temporal behaviors, ignoring the relationship between online and [...] Read more.
People leave traces of movements that might affect the behavior of others both online in cyberspace and offline in real space. Previous studies, however, have used only questionnaires, network data, or GPS data to study spatio-temporal behaviors, ignoring the relationship between online and offline activities, and overlooking the influence of previous activities on future behaviors. We propose a Pheromone-based Fusion Model, viewing human behaviors as similar to insect foraging behaviors to model spatio-temporal recreational activity patterns, on and offline. In our model, website data were combined with GPS data to evaluate the attractiveness of destinations over time using twenty-nine landscapes in Beijing, China; big website data and GPS trajectories were gathered from 181 users for 57 months. The datasets were portioned into two periods. Online and offline recreational pheromones were calculated from the first period, and the visitation rates were extracted from the second period. These data were subsequently applied in a regression analysis to determine unknown parameters and estimate the attractiveness of destinations. The proposed method was compared with two other approaches that use either GPS data or online data alone, in order to verify effectiveness. The results show that the proposed method can estimate future behaviors, based on real world and online past actions. Full article
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21139 KiB  
Article
Change of Land Use/Cover in Tianjin City Based on the Markov and Cellular Automata Models
by Ruci Wang and Yuji Murayama
ISPRS Int. J. Geo-Inf. 2017, 6(5), 150; https://doi.org/10.3390/ijgi6050150 - 11 May 2017
Cited by 29 | Viewed by 6419
Abstract
In recent years, urban areas have been expanding rapidly in the world, especially in developing countries. With this rapid urban growth, several environmental and social problems have appeared. Better understanding of land use and land cover (LULC) change will facilitate urban planning and [...] Read more.
In recent years, urban areas have been expanding rapidly in the world, especially in developing countries. With this rapid urban growth, several environmental and social problems have appeared. Better understanding of land use and land cover (LULC) change will facilitate urban planning and constrain these potential problems. As one of the four municipalities in China, Tianjin has experienced rapid urbanization and such trend is expected to continue. Relying on remote sensing (RS) and geographical information system (GIS) tools, this study investigates LULC change in Tianjin city. First, we used RS to generate classification maps for 1995, 2005, and 2015. Then, simulation models were applied to evaluate the LULC changes. Analysis of the 1995, 2005, and 2015 LULC maps shows that more than 10% of the cropland areas were transformed into built-up areas. Finally, by employing the Markov model and cellular automata (CA) model, the LULC in 2025 and 2035 were simulated and forecasted. Our analysis contributes to the understanding of the development process in the Tianjin area, which will facilitate future planning, as well as constraining the potential negative consequences brought by future LULC changes. Full article
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4149 KiB  
Article
Investigation on the Expansion of Urban Construction Land Use Based on the CART-CA Model
by Yongxiang Yao, Jia Li, Xingguo Zhang, Ping Duan, Shuang Li and Quanli Xu
ISPRS Int. J. Geo-Inf. 2017, 6(5), 149; https://doi.org/10.3390/ijgi6050149 - 11 May 2017
Cited by 19 | Viewed by 5708
Abstract
Change in urban construction land use is an important factor when studying urban expansion. Many scholars have combined cellular automata (CA) with data mining algorithms to perform relevant simulation studies. However, the parameters for rule extraction are difficult to determine and the rules [...] Read more.
Change in urban construction land use is an important factor when studying urban expansion. Many scholars have combined cellular automata (CA) with data mining algorithms to perform relevant simulation studies. However, the parameters for rule extraction are difficult to determine and the rules are simplex, and together, these factors tend to introduce excessive fitting problems and low modeling accuracy. In this paper, we propose a method to extract the transformation rules for a CA model based on the Classification and Regression Tree (CART). In this method, CART is used to extract the transformation rules for the CA. This method first adopts the CART decision tree using the bootstrap algorithm to mine the rules from the urban land use while considering the factors that impact the geographic spatial variables in the CART regression procedure. The weights of individual impact factors are calculated to generate a logistic regression function that reflects the change in urban construction land use. Finally, a CA model is constructed to simulate and predict urban construction land expansion. The urban area of Xinyang City in China is used as an example for this experimental research. After removing the spatial invariant region, the overall simulation accuracy is 81.38% and the kappa coefficient is 0.73. The results indicate that by using the CART decision tree to train the impact factor weights and extract the rules, it can effectively increase the simulation accuracy of the CA model. From convenience and accuracy perspectives for rule extraction, the structure of the CART decision tree is clear, and it is very suitable for obtaining the cellular rules. The CART-CA model has a relatively high simulation accuracy in modeling urban construction land use expansion, it provides reliable results, and is suitable for use as a scientific reference for urban construction land use expansion. Full article
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1240 KiB  
Article
Analysis of Burglary Hot Spots and Near-Repeat Victimization in a Large Chinese City
by Zengli Wang and Xuejun Liu
ISPRS Int. J. Geo-Inf. 2017, 6(5), 148; https://doi.org/10.3390/ijgi6050148 - 10 May 2017
Cited by 29 | Viewed by 6113
Abstract
A hot spot refers to numerous crime incidents clustered in a limited space-time range. The near-repeat phenomenon suggests that every victimization might form a contagion-like pattern nearby in terms of both space and time. In this article, the near-repeat phenomenon is used to [...] Read more.
A hot spot refers to numerous crime incidents clustered in a limited space-time range. The near-repeat phenomenon suggests that every victimization might form a contagion-like pattern nearby in terms of both space and time. In this article, the near-repeat phenomenon is used to analyze the risk levels around hot spots. Utilizing a recent burglary dataset in N (a large city located in southeastern China), we examine the near-repeat phenomenon, the results of which we then use to test the contributions of hot spots. More importantly, we propose a temporal expanded near-repeat matrix to quantify the undulation of risk both before and after hot spots. The experimental results demonstrate that hot spots always form. Space-time areas of high risk are always variable in space and time. Regions in the vicinity of hot spots simultaneously share this higher risk. In general, crime risks around hot spots present as a wave diffusion process. The conclusions herein provide a detailed analysis of criminal patterns, which not only advances previous results but also provides valuable research results for crime prediction and prevention. Full article
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27323 KiB  
Article
Impact of High-Resolution Topographic Mapping on Beach Morphological Analyses Based on Terrestrial LiDAR and Object-Oriented Beach Evolution
by Xuelian Meng, Xukai Zhang, Rodolfo Silva, Chunyan Li and Lei Wang
ISPRS Int. J. Geo-Inf. 2017, 6(5), 147; https://doi.org/10.3390/ijgi6050147 - 9 May 2017
Cited by 7 | Viewed by 5367
Abstract
This research applied terrestrial LiDAR for laboratory beach evolution experiments to quantify the impact of resolution on topographic mapping and change analyses. The multi-site registration and multi-temporal scanning processes produced high accuracy (−0.002 ± 0.003 m) topographic models in a wave tank environment. [...] Read more.
This research applied terrestrial LiDAR for laboratory beach evolution experiments to quantify the impact of resolution on topographic mapping and change analyses. The multi-site registration and multi-temporal scanning processes produced high accuracy (−0.002 ± 0.003 m) topographic models in a wave tank environment. Morphological analyses based on surface change and profiles showed that models of all resolutions were capable of capturing major sediment changes in relatively smooth areas. However, higher resolution models were necessary in areas with rough surfaces and sudden elevation changes, while coarser resolution models smoothed the roughness and underestimated feature height (e.g., peaks and troughs). Decreasing resolutions from 1 to 10 cm resulted in a 2% underestimation of erosional volumes with a linear regression of y = −0.0964x + 0.4185 (R2 = 0.9651) and 3.5% overestimation of depositional volumes with a linear regression of y = 0.0664x + 0.3308 (R2 = 0.3645). However, its impact on erosion and deposition volume assessment based on object-oriented beach evolution analysis is less significant, except when fragment objects dominate the sediment changes. For Coastal Morphology Analyst (CMA), the impact of resolution is more observable through 2D object mapping in terms of object size, number, and spatial distribution. Finally, wave modeling experiments proved that resolutions caused significant changes on the behavior of the maximum wave height, the shape of the wave fronts and magnitudes of the currents. Full article
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10391 KiB  
Article
Exploring the Relationship between the Arid Valley Boundary’s Displacement and Climate Change during 1999–2013 in the Upper Reaches of the Min River, China
by Yalin Guo, Qing Wang and Min Fan
ISPRS Int. J. Geo-Inf. 2017, 6(5), 146; https://doi.org/10.3390/ijgi6050146 - 6 May 2017
Cited by 9 | Viewed by 5305
Abstract
The arid valley is a unique type of ecological fragile landscape in the Hengduan Mountain Area, China. The boundary of the arid valley is one of the response indicators to mountainous climate change. Based on the meteorological data from 1999 to 2013 and [...] Read more.
The arid valley is a unique type of ecological fragile landscape in the Hengduan Mountain Area, China. The boundary of the arid valley is one of the response indicators to mountainous climate change. Based on the meteorological data from 1999 to 2013 and the SPOT remote sensing images in 1999 and 2013 this study explored the response characteristics of the arid valley boundary to regional climate change in the upper reaches of the Min River in the Hengduan Mountains. The results are as follows: (1) During 1999–2013, the temperature, precipitation, and evaporation increased, and the sunshine duration and relative humidity showed decreasing trends at the rates of 0.008 °C/a, 2.25 mm/a, 5.51 mm/a, −8.72 h/a, and −0.19%/a, respectively. Meanwhile, the climate showed the warm-dry tendency in the southern region and the warm-humid tendency in the central and northern areas. (2) On the whole, the arid valley boundary mainly distributed between 1601–3200 m and moved downward to 2428 m at the speed of −0.76 ± 0.26 m/a along with global warming. The descent speeds in different regions showed the same decreasing order as the regional distributions of precipitation and sunshine duration. (3) The arid valley boundary’s displacement in the whole basin had significant negative correlations with current climate change (p < 0.05), as well as with variations of moisture factors. Additionally, with the enhancements of the drought degree and humidity tendency, the variations of temperature, evaporation, and relative humidity, respectively, became the main factors that had significant correlations with the arid valley boundary’s displacement. Therefore, climate change during 1999–2013 shows beneficial effects on the improvement of the arid valley habitat in the upper reaches of the Min River. The study provides a new method and gives basic data for research on climate change. Full article
(This article belongs to the Special Issue Earth/Community Observations for Climate Change Research)
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3708 KiB  
Article
Design of a Model Base Framework for Model Environment Construction in a Virtual Geographic Environment (VGE)
by Chunxiao Zhang, Gang Ai, Xinqi Zheng, Kun Fang and Jiayang Li
ISPRS Int. J. Geo-Inf. 2017, 6(5), 145; https://doi.org/10.3390/ijgi6050145 - 4 May 2017
Cited by 2 | Viewed by 5815
Abstract
The model environment is a key component that enables a virtual geographic environment (VGE) to meet the scientific requirements for simulating dynamic phenomena and performing analyses. Considering the comprehensiveness of geographic processes and the requirements for the replication of model-based research, this paper [...] Read more.
The model environment is a key component that enables a virtual geographic environment (VGE) to meet the scientific requirements for simulating dynamic phenomena and performing analyses. Considering the comprehensiveness of geographic processes and the requirements for the replication of model-based research, this paper proposes a model base framework for a model environment of a VGE that supports both model construction and modelling management, resulting in improved reproducibility. In this framework, model management includes model metadata, creation, deposition, encapsulation, integration, and adaptation; while modelling management focuses on invoking the model, model computation, and runtime control of the model. Based on this framework, to consider the problem of ever-worsening air quality, we applied the Linux-Apache-MySQL-Perl stack plus Supervisor to implement the model base to support a VGE prototype using professional meteorological and air quality models. Using this VGE prototype, we simulated a typical air pollution case for January 2010. The prototype not only illustrates how a VGE application can be built on the proposed model base, but also facilitates air quality simulations and emergency management. Full article
(This article belongs to the Special Issue Smart Solutions for Disaster Risk Reduction: Big Data Concepts for Disaster Risk Reduction (DRR))
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3764 KiB  
Article
Monitoring and Assessing Post-Disaster Tourism Recovery Using Geotagged Social Media Data
by Yingwei Yan, Melanie Eckle, Chiao-Ling Kuo, Benjamin Herfort, Hongchao Fan and Alexander Zipf
ISPRS Int. J. Geo-Inf. 2017, 6(5), 144; https://doi.org/10.3390/ijgi6050144 - 3 May 2017
Cited by 42 | Viewed by 12253
Abstract
Tourism is one of the most economically important industries. It is, however, vulnerable to disaster events. Geotagged social media data, as one of the forms of volunteered geographic information (VGI), has been widely explored to support the prevention, preparation, and response phases of [...] Read more.
Tourism is one of the most economically important industries. It is, however, vulnerable to disaster events. Geotagged social media data, as one of the forms of volunteered geographic information (VGI), has been widely explored to support the prevention, preparation, and response phases of disaster management, while little effort has been put on the recovery phase. This study develops a scientific workflow and methods to monitor and assess post-disaster tourism recovery using geotagged Flickr photos, which involve a viewshed based data quality enhancement, a space-time bin based quantitative photo analysis, and a crowdsourcing based qualitative photo analysis. The developed workflow and methods have also been demonstrated in this paper through a case study conducted for the Philippines where a magnitude 7.2 earthquake (Bohol earthquake) and a super typhoon (Haiyan) occurred successively in October and November 2013. In the case study, we discovered spatiotemporal knowledge about the post-disaster tourism recovery, including the recovery statuses and trends, and the photos visually showing unfixed damages. The findings contribute to a better tourism rehabilitation of the study area. Full article
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5334 KiB  
Article
A Country Profile of the Czech Republic Based on an LADM for the Development of a 3D Cadastre
by Karel Janečka and Petr Souček
ISPRS Int. J. Geo-Inf. 2017, 6(5), 143; https://doi.org/10.3390/ijgi6050143 - 3 May 2017
Cited by 35 | Viewed by 7070
Abstract
The paper presents a country profile for the cadastre of the Czech Republic based on the ISO 19152:2012 Land Administration Domain Model (LADM). The proposed profile consists of both legal and spatial components and represents an important driving force with which to develop [...] Read more.
The paper presents a country profile for the cadastre of the Czech Republic based on the ISO 19152:2012 Land Administration Domain Model (LADM). The proposed profile consists of both legal and spatial components and represents an important driving force with which to develop a 3D cadastre for the Czech Republic, which can guide the Strategy for the Development of the Infrastructure for Spatial Information in the Czech Republic to 2020. This government initiative emphasizes the creation of the National Set of Spatial Objects, which is defined as the source of guaranteed and reference 3D geographic data at the highest possible level of detail covering the entire territory of the Czech Republic. This can also be a potential source of data for the 3D cadastre. The abstract test suite stated in ISO 19152:2012—Annex A (Abstract Test Suite) and the LADM conformance requirements were applied in order to explore the conformity of the Czech country profile with this international standard. To test their conformity, a mapping of elements between the LADM and the tested country profile was conducted. The profile is conformant with the LADM at Level 2 (medium level) and can be further modified, especially when legislation is updated with respect to 3D real estate in the future. Full article
(This article belongs to the Special Issue Research and Development Progress in 3D Cadastral Systems)
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1301 KiB  
Article
Modeling Spatial Effect in Residential Burglary: A Case Study from ZG City, China
by Jianguo Chen, Lin Liu, Suhong Zhou, Luzi Xiao, Guangwen Song and Fang Ren
ISPRS Int. J. Geo-Inf. 2017, 6(5), 138; https://doi.org/10.3390/ijgi6050138 - 3 May 2017
Cited by 28 | Viewed by 6382
Abstract
The relationship between burglary and socio-demographic factors has long been a hot topic in crime research. Spatial dependence and spatial heterogeneity are two issues to be addressed in modeling geographic data. When these two issues arise at the same time, it is difficult [...] Read more.
The relationship between burglary and socio-demographic factors has long been a hot topic in crime research. Spatial dependence and spatial heterogeneity are two issues to be addressed in modeling geographic data. When these two issues arise at the same time, it is difficult to model them simultaneously. A cross-comparison of three models is presented in this study to identify which spatial effect should be addressed first in crime analysis. The negative binominal model (NB), Bayesian hierarchical model (BHM) and the geographically weighted Poisson regression model (GWPR) were implemented based on a three-year residential burglary data set from ZG, China. The modeling result shows that both BHM and GWPR outperform NB as they capture either of the spatial effects. Compared to the NB model, the mean absolute deviation (MAD) of BHM and GWPR was decreased by 83.71% and 49.39%, the mean squared error (MSE) of BHM and GWPR was decreased by 97.88% and 77.15%, and the R d 2 of BHM and GWPR was improved by 26.7% and 19.1%, respectively. In comparison with BHM and GWPR, BHM fits the data better with lower MAD, MSE and higher R d 2 . The empirical analysis indicates that the percentage of renter population, percentage of people from other provinces, bus line density, and bus stop density have a significantly positive impact on the number of residential burglaries. The percentage of residents with a bachelor degree or higher, on the other hand, is negatively associated with the number of residential burglaries. Full article
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20072 KiB  
Article
Multi-Objective Emergency Material Vehicle Dispatching and Routing under Dynamic Constraints in an Earthquake Disaster Environment
by Jincheng Jiang, Qingquan Li, Lixin Wu and Wei Tu
ISPRS Int. J. Geo-Inf. 2017, 6(5), 142; https://doi.org/10.3390/ijgi6050142 - 2 May 2017
Cited by 14 | Viewed by 6498
Abstract
Emergency material vehicle dispatching and routing (EMVDR) is an important task in emergency relief after large-scale earthquake disasters. However, EMVDR is subject to dynamic disaster environment, with uncertainty surrounding elements such as the transportation network and relief materials. Accurate and dynamic emergency material [...] Read more.
Emergency material vehicle dispatching and routing (EMVDR) is an important task in emergency relief after large-scale earthquake disasters. However, EMVDR is subject to dynamic disaster environment, with uncertainty surrounding elements such as the transportation network and relief materials. Accurate and dynamic emergency material dispatching and routing is difficult. This paper proposes an effective and efficient multi-objective multi-dynamic-constraint emergency material vehicle dispatching and routing model. Considering travel time, road capacity, and material supply and demand, the proposed EMVDR model is to deliver emergency materials from multiple emergency material depositories to multiple disaster points while satisfying the objectives of maximizing transport efficiency and minimizing the difference of material urgency degrees among multiple disaster points at any one time. Furthermore, a continuous-time dynamic network flow method is developed to solve this complicated model. The collected data from Ludian earthquake were used to conduct our experiments in the post-quake and the results demonstrate that: (1) the EMVDR model adapts to the dynamic disaster environment very well; (2) considering the difference of material urgency degree, the material loss ratio is −10.7%, but the variance of urgency degree decreases from 2.39 to 0.37; (3) the EMVDR model shows good performance in time and space, which allows for decisions to be made nearly in real time. This paper can provide spatial decision-making support for emergency material relief in large-scale earthquake disasters. Full article
(This article belongs to the Special Issue Smart Solutions for Disaster Risk Reduction: Big Data Concepts for Disaster Risk Reduction (DRR))
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3031 KiB  
Article
Topographic Spatial Variation Analysis of Loess Shoulder Lines in the Loess Plateau of China Based on MF-DFA
by Jianjun Cao, Jiaming Na, Jilong Li, Guoan Tang, Xuan Fang and Liyang Xiong
ISPRS Int. J. Geo-Inf. 2017, 6(5), 141; https://doi.org/10.3390/ijgi6050141 - 2 May 2017
Cited by 16 | Viewed by 6178
Abstract
The Loess Plateau in China is internationally known for its unique geographical features and has therefore been studied by many researchers. This research exploits the regional differences in the spatial morphological characteristics of Loess shoulder lines in different landform types as an important [...] Read more.
The Loess Plateau in China is internationally known for its unique geographical features and has therefore been studied by many researchers. This research exploits the regional differences in the spatial morphological characteristics of Loess shoulder lines in different landform types as an important basis for geomorphological regionalization. In this study, we used ensemble empirical mode decomposition (EEMD), multi-fractal detrended fluctuation analysis (MF-DFA), and detrended cross-correlation analysis (DCCA) to analyze topographic data series extracted from shoulder lines. Loess shoulder-line land variations series data from the Suide, Ganquan, and Chunhua areas on the Loess Plateau were selected and a combination of the two above-mentioned methods was used to study land variations at these three sample sites. The results revealed differences in the topographic variations of the multi-fractal characteristics and the topographic spatial variation in the Loess shoulder line of the three sample sites. Furthermore, the extent to which the results were affected by noise and the analysis scale differed among the three areas. Full article
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5246 KiB  
Article
A Comparison of Terrain Indices toward Their Ability in Assisting Surface Water Mapping from Sentinel-1 Data
by Chang Huang, Ba Duy Nguyen, Shiqiang Zhang, Senmao Cao and Wolfgang Wagner
ISPRS Int. J. Geo-Inf. 2017, 6(5), 140; https://doi.org/10.3390/ijgi6050140 - 30 Apr 2017
Cited by 42 | Viewed by 7847
Abstract
The Sentinel-1 mission provides frequent coverage of global land areas and is hence able to monitor surface water dynamics at a fine spatial resolution better than any other Synthetic Aperture Radar (SAR) mission before. However, SAR data acquired by Sentinel-1 also suffer from [...] Read more.
The Sentinel-1 mission provides frequent coverage of global land areas and is hence able to monitor surface water dynamics at a fine spatial resolution better than any other Synthetic Aperture Radar (SAR) mission before. However, SAR data acquired by Sentinel-1 also suffer from terrain effects when being used for mapping surface water, just as other SAR data do. Terrain indices derived from Digital Elevation Models (DEMs) are easy but effective approaches to reduce this kind of interference, considering the close relationship between surface water movement and topography. This study compares two popular terrain indices, namely the Multi-resolution Valley Bottom Flatness (MrVBF) and the Height Above Nearest Drainage (HAND), toward their performance on assisting surface water mapping using Sentinel-1 SAR data. Four study sites with different terrain characteristics were selected to cover a very wide range of topographic conditions. For two of these sites that are floodplain dominated, both normal and flooded scenarios were examined. MrVBF and HAND values for the whole study areas, as well as statistics of these values within water areas were compared. The sensitivity of applying different thresholds for MrVBF and HAND to mask out terrain effect was investigated by adopting quantity disagreement and allocation disagreement as the accuracy indicators. It was found that both indices help improve water mapping, reducing the total disagreement by as much as 1.6%. The HAND index performs slightly better in most of the study cases, with less sensitivity to thresholding. MrVBF classifies low-lying areas with more details, which sometimes makes it more effective in eliminating false water bodies in rugged terrain. It is therefore recommended to use HAND for large scale or global scale water mapping. However, for water detection in complex terrain areas, MrVBF also performs very well. Full article
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2631 KiB  
Article
Novel Algorithm for Mining ENSO-Oriented Marine Spatial Association Patterns from Raster-Formatted Datasets
by Xue Cunjin and Liao Xiaohan
ISPRS Int. J. Geo-Inf. 2017, 6(5), 139; https://doi.org/10.3390/ijgi6050139 - 30 Apr 2017
Cited by 5 | Viewed by 4124
Abstract
The ENSO (El Niño Southern Oscillation) is the dominant inter-annual climate signal on Earth, and its relationships with marine environments constitute a complex interrelated system. As traditional methods face great challenges in analyzing which, how and where marine parameters change when ENSO events [...] Read more.
The ENSO (El Niño Southern Oscillation) is the dominant inter-annual climate signal on Earth, and its relationships with marine environments constitute a complex interrelated system. As traditional methods face great challenges in analyzing which, how and where marine parameters change when ENSO events occur, we propose an ENSO-oriented marine spatial association pattern (EOMSAP) mining algorithm for dealing with multiple long-term raster-formatted datasets. EOMSAP consists of four key steps. The first quantifies the abnormal variations of marine parameters into three levels using the mean-standard deviation criteria of time series; the second categorizes La Niña events, neutral conditions, or El Niño events using an ENSO index; then, the EOMSAP designs a linking–pruning–generating recursive loop to generate (m + 1)-candidate association patterns from an m-dimensional one by combining a user-specified support with a conditional support; and the fourth generates strong association patterns according to the user-specified evaluation indicators. To demonstrate the feasibility and efficiency of EOMSAP, we present two case studies with real remote sensing datasets from January 1998 to December 2012: one considers performance analysis relative to the ENSO-Apriori and Apriori methods; and the other identifies marine spatial association patterns within the Pacific Ocean. Full article
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692 KiB  
Article
Within Skyline Query Processing in Dynamic Road Networks
by Yuan-Ko Huang
ISPRS Int. J. Geo-Inf. 2017, 6(5), 137; https://doi.org/10.3390/ijgi6050137 - 29 Apr 2017
Cited by 10 | Viewed by 4303
Abstract
The continuous within skyline query is an important type of location-based query, which can provide useful skyline object information for the user. Previous studies on processing the continuous within skyline query focus exclusively on a static road network, where the object attributes and [...] Read more.
The continuous within skyline query is an important type of location-based query, which can provide useful skyline object information for the user. Previous studies on processing the continuous within skyline query focus exclusively on a static road network, where the object attributes and the conditions of roads remain unchanged. However, in real-world applications, object attributes and road conditions inevitably vary with time, which severely limits the applicability of previous studies in practice. Therefore, in this paper, we address the issue of efficiently processing the continuous within skyline query in dynamic road networks with time-varying information. We design three elaborate data structures, the object attribute dominating matrix (OADM), the road distance sorted list (RDSL) and the skyline object expansion tree (SOET), to maintain the information of objects and the road network. Combined with OADM, RDSL and SOET, we develop an efficient algorithm, namely the within skyline object updating algorithm, to provide real-time processing of the time-varying information. Finally, a thorough experimental evaluation is conducted to show the merits of the proposed approaches. Full article
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7118 KiB  
Article
Ranking the City: The Role of Location-Based Social Media Check-Ins in Collective Human Mobility Prediction
by Omid Reza Abbasi, Ali Asghar Alesheikh and Mohammad Sharif
ISPRS Int. J. Geo-Inf. 2017, 6(5), 136; https://doi.org/10.3390/ijgi6050136 - 28 Apr 2017
Cited by 19 | Viewed by 6312
Abstract
Technological advances have led to an increasing development of data sources. Since the introduction of social networks, numerous studies on the relationships between users and their behaviors have been conducted. In this context, trip behavior is an interesting topic that can be explored [...] Read more.
Technological advances have led to an increasing development of data sources. Since the introduction of social networks, numerous studies on the relationships between users and their behaviors have been conducted. In this context, trip behavior is an interesting topic that can be explored via Location-Based Social Networks (LBSN). Due to the wide availability of various spatial data sources, the long-standing field of collective human mobility prediction has been revived and new models have been introduced. Recently, a parameterized model of predicting human mobility in cities, known as rank-based model, has been introduced. The model predicts the flow from an origin toward a destination using “rank” concept. However, the notion of rank has not yet been well explored. In this study, we investigate the potential of LBSN data alongside the rank concept in predicting human mobility patterns in Manhattan, New York City. For this purpose, we propose three scenarios, including: rank-distance, the number of venues between origin and destination, and a check-in weighted venue schema to compute the ranks. When trip distribution patterns are considered as a whole, applying a check-in weighting schema results in patterns that are approximately 10 percent more similar to the ground truth data. From the accuracy perspective, as the predicted numbers of trips are closer to real number of trips, the trip distribution is also enhanced by about 50 percent. Full article
(This article belongs to the Special Issue Location-Based Services)
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871 KiB  
Article
Indoor Fingerprint Positioning Based on Wi-Fi: An Overview
by Shixiong Xia, Yi Liu, Guan Yuan, Mingjun Zhu and Zhaohui Wang
ISPRS Int. J. Geo-Inf. 2017, 6(5), 135; https://doi.org/10.3390/ijgi6050135 - 28 Apr 2017
Cited by 212 | Viewed by 15941
Abstract
The widely applied location-based services require a high standard for positioning technology. Currently, outdoor positioning has been a great success; however, indoor positioning technologies are in the early stages of development. Therefore, this paper provides an overview of indoor fingerprint positioning based on [...] Read more.
The widely applied location-based services require a high standard for positioning technology. Currently, outdoor positioning has been a great success; however, indoor positioning technologies are in the early stages of development. Therefore, this paper provides an overview of indoor fingerprint positioning based on Wi-Fi. First, some indoor positioning technologies, especially the Wi-Fi fingerprint indoor positioning technology, are introduced and discussed. Second, some evaluation metrics and influence factors of indoor fingerprint positioning technologies based on Wi-Fi are introduced. Third, methods and algorithms of fingerprint indoor positioning technologies are analyzed, classified, and discussed. Fourth, some widely used assistive positioning technologies are described. Finally, conclusions are drawn and future possible research interests are discussed. It is hoped that this research will serve as a stepping stone for those interested in advancing indoor positioning. Full article
(This article belongs to the Special Issue 3D Indoor Modelling and Navigation)
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4542 KiB  
Article
Uncovering Distribution Patterns of High Performance Taxis from Big Trace Data
by Luliang Tang, Fei Sun, Zihan Kan, Chang Ren and Luling Cheng
ISPRS Int. J. Geo-Inf. 2017, 6(5), 134; https://doi.org/10.3390/ijgi6050134 - 28 Apr 2017
Cited by 23 | Viewed by 4913
Abstract
The unbalanced distribution of taxi passengers in space and time affects taxi driver performance. Existing research has studied taxi driver performance by analyzing taxi driver strategies when the taxi is occupied. However, searching for passengers when vacant is costly for drivers, and it [...] Read more.
The unbalanced distribution of taxi passengers in space and time affects taxi driver performance. Existing research has studied taxi driver performance by analyzing taxi driver strategies when the taxi is occupied. However, searching for passengers when vacant is costly for drivers, and it limits operational efficiency and income. Few researchers have taken the costs during vacant status into consideration when evaluating taxi driver performance. In this paper, we quantify taxi driver performance using the taxi’s average efficiency. We propose the concept of a high-efficiency single taxi trip and then develop a quantification and evaluation model for taxi driver performance based on single trip efficiency. In a case study, we first divide taxi drivers into top drivers and ordinary drivers, according to their performance as calculated from their GPS traces over a week, and analyze the space-time distribution and operating patterns of the top drivers. Then, we compare the space-time distribution of top drivers to ordinary drivers. The results show that top drivers usually operate far away from downtown areas, and the distribution of top driver operations is highly correlated with traffic conditions. We compare the proposed performance-based method with three other approaches to taxi operation evaluation. The results demonstrate the accuracy and feasibility of the proposed method in evaluating taxi driver performance and ranking taxi drivers. This paper could provide empirical insights for improving taxi driver performance. Full article
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13775 KiB  
Article
Statistical Evaluation of No-Reference Image Quality Assessment Metrics for Remote Sensing Images
by Shuang Li, Zewei Yang and Hongsheng Li
ISPRS Int. J. Geo-Inf. 2017, 6(5), 133; https://doi.org/10.3390/ijgi6050133 - 28 Apr 2017
Cited by 24 | Viewed by 6496
Abstract
Image quality assessment plays an important role in image processing applications. In many image applications, e.g., image denoising, deblurring, and fusion, a reference image is rarely available for comparison with the enhanced image. Thus, the quality of enhanced images must be evaluated blindly [...] Read more.
Image quality assessment plays an important role in image processing applications. In many image applications, e.g., image denoising, deblurring, and fusion, a reference image is rarely available for comparison with the enhanced image. Thus, the quality of enhanced images must be evaluated blindly without references. In recent years, many no-reference image quality metrics (IQMs) have been proposed for assessing digital image quality. In this paper, we first review 21 commonly employed no-reference IQMs. Second, we apply these measures to Quickbird images with three different types of general content (urban, rural, and harbor) subjected to three types of degradation (average filtering, Gaussian white noise, and linear motion degradation), each with 40 degradation levels. We evaluate the robustness of the IQMs based on the criteria of prediction accuracy, prediction monotonicity, and prediction consistency. Then, we perform factor analysis on those IQMs deemed robust, and cluster them into several components. We then select the IQM with the highest loading coefficient as the representative IQM for that component. Experimental results suggest that different measures perform differently for images with different contents and subjected to different types of degradation. Generally, the degradation method has a stronger effect than the image content on the evaluation results of an IQM. The same IQM can provide opposite dependences on the level of degradation for different degradation types, and an IQM that performed well with one type of degradation may not perform well with another type. The training-based measures are not appropriate for remote sensing images because the results are highly dependent on the samples employed for training. Only seven of the 21 IQMs were found to fulfill the requirements of robustness. Edge intensity (EI) and just noticeable distortion (JND) are suggested for evaluating the quality of images subjected to average filter degradation. EI, blind image quality assessment through anisotropy (BIQAA), and mean metric (MM) are suggested for evaluating the quality of images subjected to Gaussian white noise degradation. Laplacian derivative (LD), JND, and standard deviation (SD) are suggested for evaluating the quality of images subjected to linear motion. Finally, EI is suggested for evaluating the quality of an image subjected to an unknown type of degradation. Full article
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13010 KiB  
Article
A G-Super4PCS Registration Method for Photogrammetric and TLS Data in Geology
by Rongchun Zhang, Hao Li, Lanfa Liu and Mingfei Wu
ISPRS Int. J. Geo-Inf. 2017, 6(5), 129; https://doi.org/10.3390/ijgi6050129 - 28 Apr 2017
Cited by 6 | Viewed by 5857
Abstract
Photogrammetry and Terrestrial laser scanning (TLS) are the two primary non-contact active measurement techniques in geology. Integrating TLS data with digital images may achieve complementary advantages of spatial information as well as spectrum information, which would be very valuable for automatic rock surface [...] Read more.
Photogrammetry and Terrestrial laser scanning (TLS) are the two primary non-contact active measurement techniques in geology. Integrating TLS data with digital images may achieve complementary advantages of spatial information as well as spectrum information, which would be very valuable for automatic rock surface extraction. In order to extract accurate and comprehensive geological information with both digital images and TLS point cloud, the registration problem for different sensor sources should be solved first. This paper presents a Generalized Super 4-points Congruent Sets (G-Super4PCS) algorithm to register the TLS point cloud as well as Structure from Motion (SfM) point cloud generated from disordered digital images. The G-Super4PCS algorithm mainly includes three stages: (1) key-scale rough estimation for point clouds; (2) extraction for the generalized super 4-points congruent base set and scale adaptive optimization; and (3) fine registration with Iterative Closest Point (ICP) algorithm. The developed method was tested with the columnar basalt data acquired in Guabushan National Geopark in Jiangsu Province, China. The results indicate that the proposed method could be used for indirect registration between digital images and TLS point cloud, and the result of which would be prepared for further integration research. Full article
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2255 KiB  
Article
Semantic 3D Modeling Based on CityGML for Ancient Chinese-Style Architectural Roofs of Digital Heritage
by Lin Li, Lei Tang, Haihong Zhu, Hang Zhang, Fan Yang and Wenmin Qin
ISPRS Int. J. Geo-Inf. 2017, 6(5), 132; https://doi.org/10.3390/ijgi6050132 - 27 Apr 2017
Cited by 32 | Viewed by 22697
Abstract
Ancient Chinese-style architecture has received increased attention during the last century as a segment of cultural heritage and is of great significance, specifically in regard to the process of digitizing and modeling these buildings to preserve and protect this heritage. Because the roof [...] Read more.
Ancient Chinese-style architecture has received increased attention during the last century as a segment of cultural heritage and is of great significance, specifically in regard to the process of digitizing and modeling these buildings to preserve and protect this heritage. Because the roof form reflects the age of the structure, the structural character and the historical culture of the ancient building, constructing a refined model for the roof is a primary aspect of the 3D modeling procedure. To avoid cumbersome traditional modeling approaches that use geometry units, such as points, lines and triangles, a flexible semantic method is proposed in this study to improve modeling efficiency and reduce the professional requirements. In this method, a two-level semantic decomposition of the roof is presented according to the characteristics of ancient Chinese-style architecture. The structural level reveals the basic components that determine its structural shape, and the decorative level refers to the attached components that influence the exterior appearance. The assembly validity of the decomposed elements and the combined diversity of the integrated entities are ensured by topological constraints and derived transformations of the semantic components. This proposed method was implemented by utilizing CityGML (City Geography Markup Language) via the ADE (Application Domain Extension) mechanism and was tested by modeling the principal buildings included in the Palace Museum. Full article
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8620 KiB  
Article
Detecting Damaged Building Regions Based on Semantic Scene Change from Multi-Temporal High-Resolution Remote Sensing Images
by Jihui Tu, Deren Li, Wenqing Feng, Qinhu Han and Haigang Sui
ISPRS Int. J. Geo-Inf. 2017, 6(5), 131; https://doi.org/10.3390/ijgi6050131 - 27 Apr 2017
Cited by 35 | Viewed by 5638
Abstract
The detection of damaged building regions is crucial to emergency response actions and rescue work after a disaster. Change detection methods using multi-temporal remote sensing images are widely used for this purpose. Differing from traditional methods based on change detection for damaged building [...] Read more.
The detection of damaged building regions is crucial to emergency response actions and rescue work after a disaster. Change detection methods using multi-temporal remote sensing images are widely used for this purpose. Differing from traditional methods based on change detection for damaged building regions, semantic scene change can provide a new point of view since it can indicate the land-use variation at the semantic level. In this paper, a novel method is proposed for detecting damaged building regions based on semantic scene change in a visual Bag-of-Words model. Pre- and post-disaster scene change in building regions are represented by a uniform visual codebook frequency. The scene change of damaged and non-damaged building regions is discriminated using the Support Vector Machine (SVM) classifier. An evaluation of experimental results, for a selected study site of the Longtou hill town of Yunnan, China, which was heavily damaged in the Ludian earthquake of 14 March 2013, shows that this method is feasible and effective for detecting damaged building regions. For the experiments, WorldView-2 optical imagery and aerial imagery is used. Full article
(This article belongs to the Special Issue Smart Solutions for Disaster Risk Reduction: Big Data Concepts for Disaster Risk Reduction (DRR))
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15087 KiB  
Article
Upscaling of Surface Soil Moisture Using a Deep Learning Model with VIIRS RDR
by Dongying Zhang, Wen Zhang, Wei Huang, Zhiming Hong and Lingkui Meng
ISPRS Int. J. Geo-Inf. 2017, 6(5), 130; https://doi.org/10.3390/ijgi6050130 - 27 Apr 2017
Cited by 42 | Viewed by 6625
Abstract
In current upscaling of in situ surface soil moisture practices, commonly used novel statistical or machine learning-based regression models combined with remote sensing data show some advantages in accurately capturing the satellite footprint scale of specific local or regional surface soil moisture. However, [...] Read more.
In current upscaling of in situ surface soil moisture practices, commonly used novel statistical or machine learning-based regression models combined with remote sensing data show some advantages in accurately capturing the satellite footprint scale of specific local or regional surface soil moisture. However, the performance of most models is largely determined by the size of the training data and the limited generalization ability to accomplish correlation extraction in regression models, which are unsuitable for larger scale practices. In this paper, a deep learning model was proposed to estimate soil moisture on a national scale. The deep learning model has the advantage of representing nonlinearities and modeling complex relationships from large-scale data. To illustrate the deep learning model for soil moisture estimation, the croplands of China were selected as the study area, and four years of Visible Infrared Imaging Radiometer Suite (VIIRS) raw data records (RDR) were used as input parameters, then the models were trained and soil moisture estimates were obtained. Results demonstrate that the estimated models captured the complex relationship between the remote sensing variables and in situ surface soil moisture with an adjusted coefficient of determination of R ¯ 2 = 0.9875 and a root mean square error (RMSE) of 0.0084 in China. These results were more accurate than the Soil Moisture Active Passive (SMAP) active radar soil moisture products and the Global Land data assimilation system (GLDAS) 0–10 cm depth soil moisture data. Our study suggests that deep learning model have potential for operational applications of upscaling in situ surface soil moisture data at the national scale. Full article
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5327 KiB  
Article
Modeling the Hourly Distribution of Population at a High Spatiotemporal Resolution Using Subway Smart Card Data: A Case Study in the Central Area of Beijing
by Yunjia Ma, Wei Xu, Xiujuan Zhao and Ying Li
ISPRS Int. J. Geo-Inf. 2017, 6(5), 128; https://doi.org/10.3390/ijgi6050128 - 26 Apr 2017
Cited by 40 | Viewed by 8128
Abstract
The accurate estimation of the dynamic changes in population is a key component in effective urban planning and emergency management. We developed a model to estimate hourly dynamic changes in population at the community level based on subway smart card data. The hourly [...] Read more.
The accurate estimation of the dynamic changes in population is a key component in effective urban planning and emergency management. We developed a model to estimate hourly dynamic changes in population at the community level based on subway smart card data. The hourly population of each community in six central districts of Beijing was calculated, followed by a study of the spatiotemporal patterns and diurnal dynamic changes of population and an exploration of the main sources and sinks of the observed human mobility. The maximum daytime population of the six central districts of Beijing was approximately 0.7 million larger than the night-time population. The administrative and commercial districts of Dongcheng and Xicheng had high values of population ratio of day to night of 1.35 and 1.22, respectively, whereas Shijingshan, a residential district, had the lowest value of 0.84. Areas with a high population ratio were mainly concentrated in Dongcheng, Xicheng, West Chaoyang, and Southeast Haidian. The daytime population distribution showed a hierarchical spatial pattern of planar centers and second scattered centers as opposed to multiple scattered centers during the night-time. This was because most people moved inward from the areas with a low–high to high–low population ratio of day to night from night-time to daytime, which can be explained by the process of commuting between residential areas and workplaces. Several distinctive phenomena (e.g., the distribution of new industrial parks, the so-called old residential areas, and colleges and universities) in the development of China are reflected by the spatiotemporal pattern of the distribution of population. The general consistency of the population ratios of day to night, population distribution, population variation of typical communities, and population mobility pattern with previous research suggests that the subway smart card data has potential in analyzing dynamic diurnal variations of urban population. This method can be easily duplicated to calculate hourly dynamic changes in population at the community level. These results can be used to estimate the potential hourly number of evacuees under different temporal scenarios of disasters and to support future urban planning in Beijing. Full article
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4312 KiB  
Article
Reducing Building Conflicts in Map Generalization with an Improved PSO Algorithm
by Hesheng Huang, Qingsheng Guo, Yageng Sun and Yuangang Liu
ISPRS Int. J. Geo-Inf. 2017, 6(5), 127; https://doi.org/10.3390/ijgi6050127 - 26 Apr 2017
Cited by 13 | Viewed by 4764
Abstract
In map generalization, road symbolization and map scale reduction may create spatial conflicts between roads and neighboring buildings. To resolve these conflicts, cartographers often displace the buildings. However, because such displacement sometimes produces secondary spatial conflicts, it is necessary to solve the spatial [...] Read more.
In map generalization, road symbolization and map scale reduction may create spatial conflicts between roads and neighboring buildings. To resolve these conflicts, cartographers often displace the buildings. However, because such displacement sometimes produces secondary spatial conflicts, it is necessary to solve the spatial conflicts iteratively. In this paper, we apply the immune genetic algorithm (IGA) and improved particle swarm optimization (PSO) to building displacement to solve conflicts. The dual-inheritance framework from the cultural algorithm is adopted in the PSO algorithm to optimize the topologic structure of particles. We generate Pareto optimal displacement solutions using the niche Pareto competition mechanism. The results of experiments comparing IGA and the improved PSO show that the improved PSO outperforms IGA; the improved PSO results in fewer graphic conflicts and smaller movements that better satisfy the movement precision requirements. Full article
(This article belongs to the Special Issue Intelligent Spatial Decision Support)
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1014 KiB  
Article
Approach to Facilitating Geospatial Data and Metadata Publication Using a Standard Geoservice
by Sergio Trilles, Laura Díaz and Joaquín Huerta
ISPRS Int. J. Geo-Inf. 2017, 6(5), 126; https://doi.org/10.3390/ijgi6050126 - 25 Apr 2017
Cited by 9 | Viewed by 5730
Abstract
Nowadays, the existence of metadata is one of the most important aspects of effective discovery of geospatial data published in Spatial Data Infrastructures (SDIs). However, due to lack of efficient mechanisms integrated in the data workflow, to assist users in metadata generation, a [...] Read more.
Nowadays, the existence of metadata is one of the most important aspects of effective discovery of geospatial data published in Spatial Data Infrastructures (SDIs). However, due to lack of efficient mechanisms integrated in the data workflow, to assist users in metadata generation, a lot of low quality and outdated metadata are stored in the catalogues. This paper presents a mechanism for generating and publishing metadata through a publication service. This mechanism is provided as a web service implemented with a standard interface called a web processing service, which improves interoperability between other SDI components. This work extends previous research, in which a publication service has been designed in the framework of the European Directive Infrastructure for Spatial Information in Europe (INSPIRE) as a solution to assist users in automatically publishing geospatial data and metadata in order to improve, among other aspects, SDI maintenance and usability. Also, this work adds more extra features in order to support more geospatial formats, such as sensor data. Full article
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