New, shared mobility modes, including dockless e-scooters and e-bikes, were recently introduced to many cities around the world. The aim of this article is to determine the differences between the users of e-bike sharing, and e-scooter sharing systems, and the characteristics of their travel behaviour. This study is based on the survey of the citizens of Tricity in northern Poland. We find that e-bicycles are predominantly used as first and last mile transport and to commute directly to various places of interest, whereas e-scooters are more often used for leisure rides. Survey respondents that adopted shared micromobility are generally young, and e-scooter users are on average younger than e-bike users. Although all shared vehicles in Tricity are electrically assisted, this did not allow for the elimination of the gender gap, or help retired and disabled people in the adoption of shared micromobility services. We have also identified factors discouraging people from the usage of e-bike and e-scooter sharing and found them to be different for both types of services. Finally, we investigated the issue of using shared e-bikes for urban logistics.

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Bike-sharing is widely recognized as an eco-friendly mode of transportation and seen as one of the solutions to the problem of air pollution and congestion. As there is little research exploring the performance of bicycle-sharing systems (BSS), many municipal authorities invest in their development without knowledge of their effectiveness. Therefore, the aim of this article is to identify factors that correlate with BSS performance. Data related to BSS and urban characteristics were collected for the 56 cities in Poland, which is the population of BSS systems in this country. The Ordinary Least Square regression model was used to estimate the model. Additionally, to support our findings, a survey of 3631 cyclists was conducted. Our main findings show that BSS performance was positively related to cities’ population, tourism, number of bike stations per capita, congestion, bicycle pathways’ length and higher temperature, and negatively related to precipitation. We have also found that one BSS operator was more effective compared to the others.

Electrically assisted bicycles are anticipated to become an effective tool to limit not only the use of cars in cities but also their negative impact on health, the environment, and passenger transportation in cities. In this paper, we examine the effects of implementing the first fully electric bike (e-bike) sharing system in the Metropolitan Area of Gdańsk–Gdynia–Sopot in Northern Poland, where no other bike sharing system had been introduced before. The aims of this article were to determine the impact of the new e-bike sharing system on the modal choice of citizens, identify barriers to its usage, and find differences between the usage of the system in the core of the metropolitan area and in the suburbs. We used two primary data sets: the survey data collected using the computer-assisted personal interviewing technique (CAPI technique) and the data automatically acquired from the website that monitored the system activities. We performed the analysis by using nonparametric tests and correspondence analysis. We found no evidence suggesting that e-bike sharing can replace large number of private car trips, but we found it likely to be competitive to carsharing, moped, and taxi services. E-bike sharing competes also with public transportation services, but it is also used as the first/last mile of the transportation supplementing public transport system. The major barrier to using this system in central cities of the metropolitan area was the lack of available public bikes, and possession of private bicycles, whereas for residents of the suburbs, the obstacles were the need to transport children, the high price of the bicycle rental/subscription, and the long distance to the docking stations.

The effect of cloud parallax shift occurs in satellite imaging, particularly for high angles of satellite observations. This study demonstrates new methods of parallax effect correction for clouds observed by geostationary satellites. The analytical method that could be found in literature, namely the Vicente et al./Koenig method, is presented at the beginning. It approximates a cloud position using an ellipsoid with semi-axes increased by the cloud height. The error values of this method reach up to 50 meters. The second method, which is proposed by the author, is an augmented version of the Vicente et al./Koenig approach. With this augmentation, the error can be reduced to centimeters. The third method, also proposed by the author, incorporates geodetic coordinates. It is described as a set of equations that are solved with the numerical method, and its error can be driven to near zero by adjusting the count of iterations. A sample numerical solution procedure with application of the Newton method is presented. Also, a simulation experiment that evaluates the proposed methods is described in the paper. The results of an experiment are described and contrasted with current technology. Currently, operating geostationary Earth Observation (EO) satellite resolutions vary from 0.5 km up to 8 km. The pixel sizes of these satellites are much greater than for maximal error of the least precise method presented in this paper. Therefore, the chosen method will be important when the resolution of geostationary EO satellites reaches 50 m. To validate the parallax correction, procedure data from on-ground radars and the Meteosat Second Generation (MSG) satellite, which describes stormy events, was compared before and after correction. Comparison was performed by correlating the logarithm of the cloud optical thickness (COT) with radar reflectance in dBZ (radar reflectance – Z in logarithmic form).