The Journal of Spatial Science is pleased to announce from January 2023 it will increase publication to four issues per year. Based upon strong submissions and support from the Surveying and Spatial Sciences Institute and Mapping Sciences Institute Australia, and publishers Taylor & Francis, the Journal is now moving to a quarterly publishing schedule. Thank you to all our subscribers and authors for demonstrating strong support for the Journal. Once again, a range of interesting high quality papers appears in this issue.
In order to adapt map tiles to high resolution display devices, some internet map providers pre-generate and store more than two sizes of map tiles. It is inefficient to download larger high-resolution tiles, and they occupy a larger storage space on map servers. Therefore, in this paper, Guo, Wu, Huang and Chen propose a new efficient internet map tile rendering approach on high resolution devices based on bicubic and Laplacian convolution.
Wei and Wang examine the use of navigation and point-of-interest big data in three urban planning tools: community detection, road importance assessment, and urban function pattern recognition. They reveal the community structure for urban spatial organization, followed by identifying major transit corridors and urban function patterns. The detected communities were significantly associated with administrative divisions in the city, and major commercial and residential centres were primarily located across several communities. Spatial mismatch between commercial-residential areas and industrial development areas was also identified and examined for spatial structure optimization in urban development.
Coutry and Elhalafawy examine how urban dispersion can act as a passive thermal comfort method using shrub dispersion patterns to determine the optimum dispersion pattern for urban settlements in hot climates. Shrub self-organised patterns were examined then translated into mathematical equations that formed the basis of an algorithm to guide the redistribution of existing buildings via four proposals. These proposals were examined to compare them to existing urban dispersion patterns, and the proposed dispersion patterns were able to achieve a more comfortable urban microclimate than the existing conditions.
Convergence of flooding and environmental contamination heightens the potential for mobility and transfer of toxic substances. Spatial analytic platforms can help identify the risks of toxic substance release during flooding, but these platforms are not integrated with one another, making data sharing difficult across platforms. Newman, Malecha and Atoba used the Toxics Mobility Inventory for the State of Rhode Island, to present a method that integrates Toxicological Prioritization Index outputs across multiple data visualization platforms. The workflow presented creates an accessible interface for residents and policy makers to monitor spatial conditions related to toxic substances during floods to better target solutions.
Previous studies have neglected the impact of shared spatio-temporal interests in Point of Interest (POI) recommendations. The proposed GHTG-ERWR method by Taheri, Farnaghi, Alimohammadi, Moradi and Khoshahval simultaneously models shared spatio-temporal preferences of users, dynamics of user behaviour, and geographical effects for POI recommendations. The method overcomes shortcomings of prior approaches by employing users’ joint preferences over time and space through information derived from location-session and session-location edges.
Spatial depiction of wheat and predicting yields are crucial for national food security measures. Parida and Singh employed multi-temporal synthetic aperture radar (SAR) data for spatial mapping of winter wheat and estimating its acreage. Results showed that acreage, yield and production of winter wheat based on SAR data was achieved using a polynomial model where VH polarisation was effective in acreage mapping compared to VV. Thereby, the developed framework could support policymakers by giving advanced estimates of area and yield.
Mutowo, Mutanga and Masocha sought to identify an optimal spatial resolution for estimating foliar nitrogen in dry miombo woodlands. The contrast texture measure, calculated at increasing window size on Sentinel-2 imagery, was related to field measured nitrogen via random forest regression models.
Bu, Xu, Zhao and Zhang propose a multi-frame image restoration method to address blur and noise issues caused by airlight and atmospheric scattering in nighttime imaging. The approach for Luojia 1–01 night-light images involved derivation of a degradation model, estimation of the APSF (Atmospheric Point Spread Function) for night-light images, use of improved dark channel prior and sparse constraint models to eliminate effects of airlight and atmospheric scattering, and finally, a multi-frame sparse constraint model to eliminate image noise.
Abe and colleagues examine the accuracy of the Global Positioning System (GPS) within African low-latitudes. The vertical and horizontal accuracy of single-point positioning of GPS was evaluated and the effects of the equatorial ionospheric anomaly over the region of study was critically analysed. The study revealed that 54% of GNSS positioning errors during night-time could be linked to ionospheric plasma irregularities.
Chew presents a framework for spatially interpolating Cyclone Global Navigation Satellite System (CYGNSS) data over land. The method, Previously-Observed Behavior Interpolation (POBI), assumes that reflectivity data can be interpolated at unsampled locations by quantifying how past observations of reflectivity at an unsampled location varied with past observations of reflectivity at nearby locations. This method is useful for applications that necessitate rapidly-updated data but have some tolerance for uncertainty in interpolated points.
Robert Odolinski
University of Otago