ISPRS Int. J. Geo-Inf.2016, 5(9), 154; doi:10.3390/ijgi5090154 (registering DOI) - published 26 August 2016 Show/Hide Abstract
Abstract: Land-cover datasets are crucial for earth system modeling and human-nature interaction research at local, regional and global scales. They can be obtained from remotely sensed data using image classification methods. However, in processes of image classification, spectral values have received considerable attention for most classification methods, while the spectral curve shape has seldom been used because it is difficult to be quantified. This study presents a classification method based on the observation that the spectral curve is composed of segments and certain extreme values. The presented classification method quantifies the spectral curve shape and takes full use of the spectral shape differences among land covers to classify remotely sensed images. Using this method, classification maps from TM (Thematic mapper) data were obtained with an overall accuracy of 0.834 and 0.854 for two respective test areas. The approach presented in this paper, which differs from previous image classification methods that were mostly concerned with spectral “value” similarity characteristics, emphasizes the "shape" similarity characteristics of the spectral curve. Moreover, this study will be helpful for classification research on hyperspectral and multi-temporal images.
ISPRS Int. J. Geo-Inf.2016, 5(9), 150; doi:10.3390/ijgi5090150 - published 25 August 2016 Show/Hide Abstract
Abstract: With the development of service industry and cultural industry, urban leisure and entertainment services have become an important symbol of the city and the driving force of economic and social development. Karaoke, a typical form of urban entertainment, is immensely popular throughout China, and the number of karaoke bars is expected to keep growing in the future. However, little is known about their spatial distribution in the urban space and their association with other location-specific factors. Based on the geospatial entity data and business statistics data, we demonstrate a clustered pattern of 530 karaoke bars in Nanjing by means of point pattern analysis and cluster analysis in GIS. Furthermore, we identify the distribution of population, transportation network, and commercial centers as the three determinants underlying the formation of the pattern.
ISPRS Int. J. Geo-Inf.2016, 5(9), 151; doi:10.3390/ijgi5090151 - published 25 August 2016 Show/Hide Abstract
Abstract: Large quantities of location-sensing data are generated from location-based social network services. These data are provided as point properties with location coordinates acquired from a global positioning system or Wi-Fi signal. To show the point data on multi-scale map services, the data should be represented by clusters following a grid-based clustering method, in which an appropriate grid size should be determined. Currently, there are no criteria for determining the proper grid size, and the modifiable areal unit problem has been formulated for the purpose of addressing this issue. The method proposed in this paper is applies a hexagonal grid to geotagged Twitter point data, considering the grid size in terms of both quantity and quality to minimize the limitations associated with the modifiable areal unit problem. Quantitatively, we reduced the original Twitter point data by an appropriate amount using Töpfer’s radical law. Qualitatively, we maintained the original distribution characteristics using Moran’s I. Finally, we determined the appropriate sizes of clusters from zoom levels 9–13 by analyzing the distribution of data on the graphs. Based on the visualized clustering results, we confirm that the original distribution pattern is effectively maintained using the proposed method.
ISPRS Int. J. Geo-Inf.2016, 5(9), 148; doi:10.3390/ijgi5090148 - published 25 August 2016 Show/Hide Abstract
Abstract: Law enforcement agencies, as well as researchers rely on temporal analysis methods in many crime analyses, e.g., spatio-temporal analyses. A number of temporal analysis methods are being used, but a structured comparison in different configurations is yet to be done. This study aims to fill this research gap by comparing the accuracy of five existing, and one novel, temporal analysis methods in approximating offense times for residential burglaries that often lack precise time information. The temporal analysis methods are evaluated in eight different configurations with varying temporal resolution, as well as the amount of data (number of crimes) available during analysis. A dataset of all Swedish residential burglaries reported between 2010 and 2014 is used (N = 103,029). From that dataset, a subset of burglaries with known precise offense times is used for evaluation. The accuracy of the temporal analysis methods in approximating the distribution of burglaries with known precise offense times is investigated. The aoristic and the novel aoristic method perform significantly better than three of the traditional methods. Experiments show that the novel aoristic method was most suitable for estimating crime frequencies in the day-of-the-year temporal resolution when reduced numbers of crimes were available during analysis. In the other configurations investigated, the aoristic method showed the best results. The results also show the potential from temporal analysis methods in approximating the temporal distributions of residential burglaries in situations when limited data are available.
ISPRS Int. J. Geo-Inf.2016, 5(9), 149; doi:10.3390/ijgi5090149 - published 24 August 2016 Show/Hide Abstract
Abstract: (1) Background: Due to the advent of Volunteered Geographic Information (VGI), large datasets of user-generated Points of Interest (POI) are now available. As with all VGI, however, there is uncertainty concerning data quality and fitness-for-use. Currently, the task of evaluating fitness-for-use of POI is left to the data user, with no guidance framework being available which is why this research proposes a generic approach to choose appropriate measures for assessing fitness-for-use of crowdsourced POI for different tasks. (2) Methods: POI are related to the higher-level concept of geo-atoms in order to identify and distinguish their two basic functions, geo-referencing and object-referencing. Then, for each of these functions, suitable measures of positional and thematic quality are developed based on existing quality indicators. (3) Results: Typical use cases of POI are evaluated with regards to their use of the two basic functions of POI, and allocated appropriate measures for fitness-for-use. The general procedure is illustrated on a brief practical example. (4) Conclusion: This research addresses the issue of fitness-for-use of POI on a higher conceptual level by relating it to more fundamental notions of geographical information representation. The results are expected to assist users of crowdsourced POI datasets in determining an appropriate method to evaluate fitness-for-use.
ISPRS Int. J. Geo-Inf.2016, 5(8), 147; doi:10.3390/ijgi5080147 - published 22 August 2016 Show/Hide Abstract
Abstract: Geomatics as a geospatial science, including technologies and processes, has experienced a boost in recent years with the development of Unmanned Aerial Vehicles (UAVs) equipped with sensing instruments .[...]