This is issue Number 3 for 2019, the first time the Journal of Spatial Science has been published three times in a year. Impact factors for 2018 were released in late June with the Journal achieving an Impact Factor of 1.711, a substantial increase from the 2017 Impact Factor of 1.071.
I would also like to welcome a new member to our editorial team, Dr Amy Griffin from RMIT University in Melbourne. Amy will be an asset to the Editorial Board and will contribute in areas including cartography, interactive mapping, UX, reasoning with uncertainty, historical GIS, time geography and health geography.
Featherstone, McCubbine, Claessens, Belton and Brown present an important paper on using AUSGeoid2020 and its error grids in surveying computations. Summarised formulas and worked examples for the propagation of geoid and vertical deflection errors through some common geodetic surveying computations, as well as a demonstration of their effects on least squares adjustments of small simulated geodetic networks are presented.
A comparison of advanced troposphere models for aiding reduction of PPP convergence time in Australia is provided by Deo and El-Mowafy. The paper analyses the precision of tropospheric zenith total delay values obtained from the empirical models GPT2 and GPT2w, and numerical weather models from Australian Bureau of Meteorology, and European Centre for Medium-Range Weather Forecasts, and makes comparisons at four sites.
The development of local spatial data infrastructures in Croatia was examined by Marasović, Crompvoets and Poslončec-Petrić. This nation-wide evaluation is an important assessment of LSDI progress in Croatia.
Assessment of the accuracy of kernel smoothing population surface models for Northern Ireland using geographically weighted regression was undertaken by Nejad and Lloyd making use of two sets of census outputs for Northern Ireland. This paper pulls together the benefits of a gridded population data source with local regression procedures to provide a more detailed assessment of surface modelling accuracy than was possible from any previous studies.
A paper led by Heng Zhang presents a knowledge reuse framework to solve the problem that modelling knowledge cannot be reused effectively in the process of generating multi-type railway scenes. The experimental results show the method is applicable to unified modelling of different types of 3D railway scenes on the same platform, enabling reuse of primitive models, 3D scenes and modelling knowledge.
Cegielska, Kukulska-Kozieł, Salata, Piotrowski and Szylar assessed spatial concentration and quantitative spatial density of anthropogenic elements in their research using Shannon entropy as a peri-urban landscape metric.
A research paper led by Arnab Sengupta was used to identify and map high-potential iron ore indicative alteration zones related to new prospects using ASTER and Hyperion data by considering in-situ and reported spectral signatures and band ratio techniques.
Combining Landsat and landscape metrics to analyse large-scale urban land cover change was investigated by Wahyudi, Liu and Corcoran using a case study in the Jakarta Metropolitan Area. This study tested the capacity of Landsat imagery and landscape metrics to explore spatial and temporal dynamics of urban expansion over a 23-year period (1994–2017).
Peerbhay, Germishuizen and Ismail evaluated the potential of remote sensing to detect, monitor and track baboon-damaged Pinus plantations in South Africa due to the increasing number of biotic stressors on the plantations. Overall, this research developed an operational framework that supports forest protection using a space-borne satellite platform.