An assessment of a collaborative mapping approach for exploring land use patterns for several European metropolises

Until recently, land surveys and digital interpretation of remotely sensed imagery have been used to generate land use inventories. These techniques however, are often cumbersome and costly, allocating large amounts of technical and temporal costs. The technological advances of web 2.0 have brought a wide array of technological achievements, stimulating the participatory role in collaborative and crowd sourced mapping products. This has been fostered by GPS-enabled devices, and accessible tools that enable visual interpretation of high resolution satellite images/air photos provided in collaborative mapping projects. Such technologies offer an integrative approach to geography by means of promoting public participation and allowing accurate assessment and classification of land use as well as geographical features. OpenStreetMap (OSM) has supported the evolution of such techniques, contributing to the existence of a large inventory of spatial land use information. This paper explores the introduction of this novel participatory phenomenon for land use classification in Europe's metropolitan regions. We adopt a positivistic approach to assess comparatively the accuracy of these contributions of OSM for land use classifications in seven large European metropolitan regions. Thematic accuracy and degree of completeness of OSM data was compared to available Global Monitoring for Environment and Security Urban Atlas (GMESUA) datasets for the chosen metropolises. We further extend our findings of land use within a novel framework for geography, justifying that volunteered geographic information (VGI) sources are of great benefit for land use mapping depending on location and degree of VGI dynamism and offer a great alternative to traditional mapping techniques for metropolitan regions throughout Europe. Evaluation of several land use types at the local level suggests that a number of OSM classes (such as anthropogenic land use, agricultural and some natural environment classes) are viable alternatives for land use classification. These classes are highly accurate and can be integrated into planning decisions for stakeholders and policymakers.     

Building a model-based personalised recommendation approach for tourist attractions from geotagged social media data

When travelling, people are accustomed to taking and uploading photos on social media websites, which has led to the accumulation of huge numbers of geotagged photos. Combined with multisource information (e.g. weather, transportation, or textual information), these geotagged photos could help us in constructing user preference profiles at a high level of detail. Therefore, using these geotagged photos, we built a personalised recommendation system to provide attraction recommendations that match a user's preferences. Specifically, we retrieved a geotagged photo collection from the public API for Flickr (Flickr.com) and fetched a large amount of other contextual information to rebuild a user's travel history. We then created a model-based recommendation method with a two-stage architecture that consists of candidate generation (the matching process) and candidate ranking. In the matching process, we used a support vector machine model that was modified for multiclass classification to generate the candidate list. In addition, we used a gradient boosting regression tree to score each candidate and rerank the list. Finally, we evaluated our recommendation results with respect to accuracy and ranking ability. Compared with widely used memory-based methods, our proposed method performs significantly better in the cold-start situation and when mining ‘long-tail’ data.     

互联网众源照片的三维重建定位技术

随着电子产品的普及和互联网发展,人们习惯性地将照片上传到主流图片分享网站和社交媒体。这些照片很多都没有地理坐标或者仅有模糊的位置信息。如果互联网上任意来源的电子照片能被恢复出真实地理位置,它们将可以应用在城市建设、城市景观分析和犯罪追踪等很多方面。本文提出了一种互联网众筹照片的三维重建定位技术,该技术将结构化组织的街景数据作为参考数据集,使用三步走策略：图像检索粗定位、图像匹配细筛选和三维重建精定位,来给不明来源的众筹照片附上精确的地理标签。本文通过摄影测量原理恢复待查询照片周围的三维空间信息,较之前Zamir和Shah的方法,定位精度中值从256.7 m提升到69.0 m,平均值从350.4 m提升到206.0 m,在50 m精度要求下的照片数量占比从17.2%提升到43.2%。另一个发现是在重建误差成因方面,待查询照片的相机距离主拍摄目标越近,定位总误差越小。本文所提出的照片定位技术提供了灵活的参数,使其应用范围不仅仅局限于小区域,也可以扩大至城市、国家尺度。     

Object-based land-cover classification for metropolitan Phoenix,Arizona, using aerial photography

Detailed land-cover mapping is essential for a range of research issues addressed by the sustainability and land system sciences and planning. This study uses an object-based approach to create a 1 m land-cover classification map of the expansive Phoenix metropolitan area through the use of high spatial resolution aerial photography from National Agricultural Imagery Program. It employs an expert knowledge decision rule set and incorporates the cadastral GIS vector layer as auxiliary data. The classification rule was established on a hierarchical image object network, and the properties of parcels in the vector layer were used to establish land cover types. Image segmentations were initially utilized to separate the aerial photos into parcel sized objects, and were further used for detailed land type identification within the parcels. Characteristics of image objects from contextual and geometrical aspects were used in the decision rule set to reduce the spectral limitation of the four-band aerial photography. Classification results include 12 land-cover classes and subclasses that may be assessed from the sub-parcel to the landscape scales, facilitating examination of scale dynamics. The proposed object-based classification method provides robust results, uses minimal and readily available ancillary data, and reduces computational time.     

Automatic Selection of Landmarks for Navigation Guidance

Although current navigation services provide significant benefits to people's mobility, the turn‐by‐turn instructions they provide are sometimes ineffective. These instructions require people to maintain a high level of attention and cognitive workload while performing distance or angle measurements on their own mental map. To overcome this problem, landmarks have been identified as playing a major role in turn‐by‐turn instructions. This requires the availability of landmarks in navigation databases. Landmarks are commonly selected manually, which involves time‐consuming and tedious tasks. Automatic selection of landmarks has recently gained the attention of researchers but currently there are only a few techniques that can select appropriate landmarks. In this article, we present a technique based on a neural network model, where both static and dynamic features are used for selecting landmarks automatically. To train and test this model, two labeling approaches, manual labeling and rule‐based labeling, are also discussed. Experiments on the developed technique were conducted and the results show that rule‐based labeling has a precision of approximately 90%, which makes the technique suitable and reliable for automatic selection of landmarks.     

A Morphological Approach to Predicting Urban Expansion

Many methods for modeling urban expansion are available. Most of these computational models demand a variety of large‐scale environmental and socio‐economic data to investigate the relationship between urban expansion and its driving forces. These requirements are not always fulfilled, particularly in developing countries due to a lack of data availability. This necessitates methods not suffering from data limitations to ease their application. Consequently, this research presents a morphological approach for predicting urban expansion on the basis of spatiotemporal dynamics of urban margins by investigating the interior metropolitan area of Tehran, Iran as a case study. To assess the model's performance, urban expansion is monitored from 1976 to 2012. The proposed model is evaluated to ensure that the prediction performance for the year 2012 is acceptable. For the year 2024, the model predicts Tehran's urban expansion at an overall R² of 88%. Accordingly, it is concluded that: (1) although this approach only inputs urban margins, it represents a suitable and easy‐to‐use urban expansion model; and (2) urban planners are faced with continuing urban expansion.     

Triangulating Social Multimedia Content for Event Localization using Flickr and Twitter

The analysis of social media content for the extraction of geospatial information and event‐related knowledge has recently received substantial attention. In this article we present an approach that leverages the complementary nature of social multimedia content by utilizing heterogeneous sources of social media feeds to assess the impact area of a natural disaster. More specifically, we introduce a novel social multimedia triangulation process that uses both Twitter and Flickr content in an integrated two‐step process: Twitter content is used to identify toponym references associated with a disaster; this information is then used to provide approximate orientation for the associated Flickr imagery, allowing us to delineate the impact area as the overlap of multiple view footprints. In this approach, we practically crowdsource approximate orientations from Twitter content and use this information to orient Flickr imagery accordingly and identify the impact area through viewshed analysis and viewpoint integration. This approach enables us to avoid computationally intensive image analysis tasks associated with traditional image orientation, while allowing us to triangulate numerous images by having them pointed towards the crowdsourced toponym location. The article presents our approach and demonstrates its performance using a real‐world wildfire event as a representative application case study.     

Landmark‐based summarized messages for flood warning

In order to evacuate residents in time, flood warning systems must have rapid data processing algorithms to translate detailed numerical data into simple warnings and navigation aids. Although it is common to display warning messages by directly drawing red circles on a map embedded in a Web page to indicate the regions about to be inundated, such an approach has some drawbacks. We propose an alternative way by summarizing the warning messages based on landmarks, so that the messages can be short and convey even more information. We have designed two approaches to output such messages. They are the nearest landmark approach and the threshold approach, which differ in the way of determining which landmarks will be influenced by a certain flooded region. These two methods are implemented and we compare their performance through real and synthetic datasets. Experimental results show that the threshold approach usually takes less execution time than the nearest landmark approach. Its severity ranking of landmarks is also better suited to human behaviour.     

Relaxation‐Based Point Feature Matching for Vector Map Conflation

With the rapid advance of geospatial technologies, the availability of geospatial data from a wide variety of sources has increased dramatically. It is beneficial to integrate / conflate these multi‐source geospatial datasets, since the integration of multi‐source geospatial data can provide insights and capabilities not possible with individual datasets. However, multi‐source datasets over the same geographical area are often disparate. Accurately integrating geospatial data from different sources is a challenging task. Among the subtasks of integration/conflation, the most crucial one is feature matching, which identifies the features from different datasets as presentations of the same real‐world geographic entity. In this article we present a new relaxation‐based point feature matching approach to match the road intersections from two GIS vector road datasets. The relaxation labeling algorithm utilizes iterated local context updates to achieve a globally consistent result. The contextual constraints (relative distances between points) are incorporated into the compatibility function employed in each iteration's updates. The point‐to‐point matching confidence matrix is initialized using the road connectivity information at each point. Both the traditional proximity‐based approach and our relaxation‐based point matching approach are implemented and experiments are conducted over 18 test sites in rural and suburban areas of Columbia, MO. The test results show that our relaxation labeling approach has much better performance than the proximity matching approach in both simple and complex situations.     

The market value of cultural heritage in urban areas: an application of spatial hedonic pricing

The current literature often values intangible goods like cultural heritage by applying stated preference methods. In recent years, however, the increasing availability of large databases on real estate transactions and listed prices has opened up new research possibilities and has reduced various existing barriers to applications of conventional (spatial) hedonic analysis to the real estate market. The present paper provides one of the first applications using a spatial autoregressive model to investigate the impact of cultural heritage—in particular, listed buildings and historic–cultural sites (or historic landmarks)—on the value of real estate in cities. In addition, this paper suggests a novel way of specifying the spatial weight matrix—only prices of sold houses influence current price—in identifying the spatial dependency effects between sold properties. The empirical application in the present study concerns the Dutch urban area of Zaanstad, a historic area for which over a long period of more than 20 years detailed information on individual dwellings, and their market prices are available in a GIS context. In this paper, the effect of cultural heritage is analysed in three complementary ways. First, we measure the effect of a listed building on its market price in the relevant area concerned. Secondly, we investigate the value that listed heritage has on nearby property. And finally, we estimate the effect of historic–cultural sites on real estate prices. We find that, to purchase a listed building, buyers are willing to pay an additional 26.9 %, while surrounding houses are worth an extra 0.28 % for each additional listed building within a 50-m radius. Houses sold within a conservation area appear to gain a premium of 26.4 % which confirms the existence of a ‘historic ensemble’ effect.     

A Hybrid Approach for Land Use/Land Cover Classification

Atlanta has continuously changed its physical landscape as well as its socioeconomic appearance over the past decades. A hybrid image processing approach, which integrated unsupervised, supervised, and spectral mixture analysis (SMA) classification methods, was used to identify urban land use/land cover changes over a decade (from 1990 to 2000) in the Atlanta metropolitan area. During this process, SMA was proven to be an effective analytical approach for characterizing mixed feature areas, such as a metropolitan area. According to accuracy assessment, the classification results were acceptable.     

Spatial modelling of site suitability assessment for hospitals using geographical information system-based multicriteria approach at Qazvin city,Iran

Due to the population growth and continuous migration of people from rural areas to urban areas, it is important to identify the suitable locations for future development in order to find suitable sites for various kinds of facilities such as schools, hospital and fire stations for new and existing urban areas. Site suitability modelling is a complex process involving various kinds of objectives and issues. Such a complex process includes spatial analysis, use of several decision support tools such as high-spatial resolution remotely sensed data, geographical information system (GIS) and multi criteria analysis (MCA) such as analytical hierarchy process (AHP), and in some cases, prediction techniques like cellular automata (CA) or artificial neural networks (ANN). This paper presents a comparison between the results of AHP and the ordinary least square (OLS) evaluation model, based on various criteria, to select suitable sites for new hospitals in Qazvin city, Iran. Based on the obtained results, proximity to populated areas (0.3) and distance to air polluted areas (0.23–0.26) were the two highest important criteria with high weight value. The results show that these two techniques not only have similarity in size (in m²) for each suitability class but they also have similarity in spatial distribution of each class in the entire study area. Based on calculations of both techniques, 1–2%, 25%, 40–43%, 16–20% and 14% of study areas are assigned as ‘not suitable', ‘less suitable', ‘moderately suitable', ‘suitable' and ‘most suitable' areas for construction of new hospitals. Results revealed that a 75% similarity was found in the distribution of suitability classes in Qazvin city using both techniques. Nineteen per cent (19%) of the study area are assigned as ‘suitable' and ‘most suitable' by both methods, so these areas can be considered as safe or secure areas for clinical purposes. Moreover, almost all (99.8%) suitable areas are located in district 3, because of its higher population, less numbers of existing hospitals and large numbers of barren land plots of acceptable size.     

彩红外航空像片应用于森林灾害调查的方法与结果分析

本文应用联邦德国的一个实例,介绍了大比例尺(1:5000)彩红外航空像片应用于森林灾害调查的程序和方法。总结了彩红外航空像片判读树种和林木受损害等级的标志;并分析了不同树种、年龄和海拔高度等因素对林木受损害程度的影响;最后提出了调查精度。结果表明:利用彩红外航空像片调查林木因大气污染、病虫害、自然灾害等因子影响而受损的程度的方法,可以为合理经营规划森林资源快速提供较精确的信息。     

利用航空遥感象片量算面积的精度分析

直接应用航空遥感象片进行面积量算,必然存在着某些误差。本文首先从理论上分析了这些误差的来源以及它们的计算方法,然后以实例数据对比,分析了这些误差的大小和对面积量算的影响情况,并讨论了应用航片直接进行面积量算的条件和应用范围,为在原航片上量算面积提供了计算数据和理论依据。     

Collaborative personalized multi‐criteria wayfinding for wheelchair users in outdoors

While finding the optimal route for users with physical disabilities and personalizing routes for each user, on the one hand, and collaborative wayfinding, on the other hand, have been addressed in the pedestrian navigation systems literature, there has not been much research on combining the two activities. The problem associated with wayfinding approaches solely based on information about network segments and personal preferences is that the information about segments in the database may not, correctly and/or adequately address user preferences. The problem associated with wayfinding approaches solely based on the ratings given to routes by wheelchair users is the lack of rates (or scores) for all possible routes between all possible origin‐destination pairs in the network. This article discusses an approach to combine these two approaches for wayfinding to augment each other's shortcomings. To evaluate the personalized wayfinding approach, we utilize a route index, called a comparison index. The results show that with a P‐value of 9%, the routes obtained from our approach are more accessible than the routes obtained from another approach developed in another study. To evaluate the collaborative wayfinding approach, a Monte Carlo simulation was conducted which reflects the updates in routes as users' feedbacks become available.     

A global inventory of coral reef stressors based on satellite observed nighttime lights

In this article, we present a satellite-based approach to gather information about the threat to coral reefs worldwide. Three chosen reef stressors – development, gas flaring and heavily lit fishing boat activity – are analysed using nighttime lights data derived from the Defense Meteorological Satellite Program (DMSP) produced at the National Oceanic & Atmospheric Administration, National Geophysical Data Center (NOAA/NGDC). Nighttime lights represent a direct threat to coral reef ecosystems and are an excellent proxy measure for associated human-caused stressors. A lights proximity index (LPI) is calculated, measuring the distance of coral reef sites to each of the stressors and incorporating the stressor's intensity. Colourized maps visualize the results on a global scale. Area rankings clarify the effects of artificial night lighting on coral reefs on a regional scale. The results should be very useful for reef managers and for state administrations to implement coral reef conservation projects and for the scientific world to conduct further research.     

Cartography: A manufacturing industry concerned with the Processing,Transformation, Packaging and Transportation of Spatial Data

Abstract

The communication approach advocated by cartographers during the past decade appears to have provided direction but no route to improvement of the product. Much of the research in this area appears almost aimless and considerable danger is foreseen in that if a path is not quickly established and maintained the purpose of cartographic research will be lost behind ill conceived forays into 'no man's land'. The map is considered within this article as primarily a 'total product' and interdependence between its various elements seen as its strength. The current obsession with component parts detached from their operating environment appears to provide nothing of use to the manufacturer. This paper certainly is not presented as either a research or review article, but rather as a contemplative essay in which the above topics are examined and comparisons made between the cartographic and other manufacturing industries.     

Modeling Use of Space from Social Media Data Using a Biased Random Walker

Individuals and other entities move through space as a function of local characteristics of place, their internal behavioral models, and the topological structure of the underlying space. When a collection of locations (i.e. geotagged photos or other geotagged social media information) from a large number of individuals is assembled, it becomes possible to understand the interrelationship between the individuals and the space they occupy. This research systematically considers this interrelationship through an examination of the effect of the intersection of behavioral and spatial characteristics on individuals moving on street networks. The research illustrates how social media data, in combination with a biased random walker, can be used to understand and model the interaction of spatial structure and social‐environmental factors on influencing individuals' use of their environment. The biased walker offers a flexible approach to incorporate consideration of both social‐environmental and structural factors into a model and we demonstrate this through a case study wherein we are able to use the random walker to model the characteristics of Flickr users in New York City.