• Rural Digital Europe
• 0211 other engineering and technologies close

It is very likely that the post-Covid-19 world will be significantly different from today. From the experience in fighting the pandemic we can identify lessons on the vulnerability of humans, logistics, and supply chain of vital strategic assets (e.g. medical equipment). This require to think about how to conduct operations in the future, investigate robotics and autonomous systems (RAS) to reduce the exposure while achieving operational improvement, and to assess if current doctrines need to undergo a review. Modelling and simulation play a significant role in analysis and training for scenarios that might include reacting and anticipating the unexpected, challenging our agility and resilience. Available constructive simulations have been designed primarily for training commanders and staff but often lack the ability to exploit the outcomes from predictive systems. The authors propose a novel approach considering the Spatiotemporal Epidemiological Modeler (STEM) for computing the epidemic trend. This tool has been linked with the MASA SWORD constructive simulation. STEM computed data enable the creation in SWORD of highly realistic scenarios in the context of infectious diseases, outbreaks, bioterrorism and biological defence where to model RAS, run the simulation, and analyse doctrine and courses of actions.

A prominent question in transportation planning is how cities should regulate emerging modes, such as shared bikes and e-scooters. This pertains to a range of attributes, including pricing, use of the public right of way, number of vehicles in a fleet, and vehicle speeds. However, less attention has been paid to the way private operators spatially constrain access to their fleets, such as via the use of virtual geographic boundaries (hereafter “geofences”), or how municipalities have regulated these features. San Francisco, given it is home to a number of these schemes, presents a compelling case for studying geofences, and how regulators have sought to influence them to further public policy goals, including spatial equity. This study analyzes each bike and e-scooter geofence in San Francisco longitudinally from 2017 to 2019 via manual digitization of all geofences. This reveals high levels of overlap in the city’s dense northeast quadrant, with limited to no coverage in western neighborhoods. Each operator’s geofence expanded over this period, filling in gaps in the northeast quadrant and expanding outward in each direction. Review of permit guidelines and applications submitted by operators indicate that San Francisco’s regulations for geofences have been limited and inconsistent, which may have contributed to the concentration of services in one section of the city, as well as disconnected geofence “islands.” Together, these observations demonstrate that if broad geofence coverage (i.e., spatial equity) is an explicit municipal goal, such an aim must prominently feature into the regulatory process. This is particularly important given that operators, if left with freedom over geofence design, are likely to emphasize only a city’s densest areas, especially if tight caps are set on the allowed number of vehicles. Finally, this case also exemplifies that geofences are not drawn in a vacuum but instead relate to other permit conditions as well as pressure from community organizations.

To avoid using a large 4D-Hough counting space (HCS) and complex invariant features of generalized Hough transform (GHT) or its extensions when detecting objects in remote sensing image (RSI), a tensored GHT (TGHT) is proposed to extract object contour by simple gradient angle feature in a 2D-HCS using a single training sample. Considering that tensor can record the structure relationship of object contour, tensor representation R-table is constructed to record the contour information of template. For slice centered at each position of RSI, the tensor-space-based voting mechanism is presented to use the tensor that records the contour information of slice to gather votes at the same entry of 2D-HCS. Furthermore, a multiorder binary-tree-based searching method is presented to accelerate voting by searching the index numbers of elements in tensors. In addition, by solving the tensor-space-based optimization problem that is used to determine the candidates objects, the cause of false alarms (FAs) caused by interferences with complex contour and FAs caused by interferences that are partial-similar to objects is revealed, and the matching rate and matching sparsity-based strategies are then proposed to remove these FAs. Using public RSI datasets with different scenes, experimental results demonstrate that TGHT reduces nearly 99% storage requirement compared with GHT for RSI with size exceeding 1000 × 1000 under small time consumption, and outperforms the well-known contour extraction methods and state-of-the-art deep-learning-based methods in terms of precision and recall.

Abstract Effective urban planning, and urban green space management in particular, require proper data on urban green spaces. The potential of urban green spaces to provide benefits to urban inhabitants (ecosystem services) depends on whether they are managed as a comprehensive system of urban green infrastructure, or as isolated islands falling under the responsibility of different stakeholders. Meanwhile, different urban green space datasets are based on different definitions, data sources, sampling techniques, time periods and scales, which poses important challenges to urban green infrastructure planning, management and research. Using the case study of Lodz, the third largest city in Poland, and an additional analysis of 17 other Polish cities, we compare data from five publicly available sources: 1) public statistics, 2) the national land surveying agency, 3) satellite imagery (Landsat data), 4) the Urban Atlas, 5) the Open Street Map. The results reveal large differences in the total amount of urban green spaces in the cities as depicted in different datasets. In Lodz, the narrowly interpreted public statistics data, which are aspatial, suggest that green spaces account for only 12.8% of city area, while the most comprehensive dataset from the national land surveying agency reveals the figure of 61.2%. The former dataset, which excludes many types of green spaces (such as arable land, private and informal green spaces), is still the most commonly used. The analysis of the 17 other cities confirms the same pattern. This results in broader institutional failures related to urban green infrastructure planning, management, and research, including a lack of awareness of green space quality (e.g. connectivity) and benefits (ecosystem services), and the related political disregard for urban green spaces. Our comparison suggests that a better understanding of green space data sources is necessary in urban planning, and especially when planning urban green infrastructure.

The High-speed Railway (HSR) network in China is the largest in the world, competing intensively with airlines for inter-city travel. Panel data from 2007 to 2013 for 138 routes with HSR-air competition were used to identify the ex-post impacts of the entry of HSR services, the duration of operating HSR services since entry, and the specific impacts of HSR transportation variables such as travel time, frequency, and ticket fares on air passenger flows in China. The findings show that the entry of new HSR services in general leads to a 27% reduction in air travel demand. After two years of operating HSR services, however, the negative impact of HSR services on air passenger flows tends to further increase. The variations of the frequency in the temporal dimension and the travel time in the spatial dimension significantly affect air passenger flows. Neither in the temporal nor spatial dimensions are HSR fares strongly related to air passenger flows in China, due to the government regulation of HSR ticket prices during the period of analysis. The impacts of different transportation variables found in this paper are valuable to consider by operational HSR companies in terms of scheduling and planning of new routes to increase their competitiveness relative to airlines. Highlights • The paper is the first to identify the ex-post impacts of HSR on air transport in such a large scale and a long period. • The paper employs within-between models to specify how HSR transportation are interacted with air travel demand in temporal and spatial dimensions. • Impacts of different transportation variables found here are valuable to HSR companies and airlines.

Several non-governmental initiatives have emerged in the Czech Republic in recent years with the aim to organise the provision of public goods or ecosystem services from agriculture and forestry. These initiatives are usually started by activists (elites) and take forms such as foundations or trust funds, but often present themselves as collective actions of communal interests. This paper sets out to present four cases of such efforts and to show their common and contrasting features in light of their relevance to local needs and possible integration in the future CAP framework. A particular focus is on the community-based character of these initiatives for the provision of public goods. This is done by examining the necessary conditions for the success of collectively managed common pool resources. The research shows that elite-driven non-governmental organisations often emerge because of a lack of interest on the part of public bodies and because local communities do not have the capacity to set up a collective action for the provision of environmentally and socially “beneficial outcomes” (ESBO). The investigated NGOs, however, soon came into conflict with non-involved actors. To improve the governance mechanism, an extension towards a community-based collective action is proposed. However, each step of such a transition is a challenge for the initiatives of the presented case studies. The first critical issue is to find a common interest among actors. Similarly, “sharing power” represents a struggle which consequently delays progress in creating effective internal governance. The difficulty in progressing towards community-based collective action is amplified by the uncertainty concerning property rights induced by the activities of the NGOs and unfavourable socioeconomic and institutional conditions. Finding that the private initiatives are far from being able to transform into community-based collective action, we propose to launch a measure of institutional funding for the coordination and management of their projects – similar to LEADER but more concentrated in scope.

In Jiangsu province of China, many farmers have changed their planting method from puddled transplanted rice (PTR) to direct seeded rice (DSR), which was not suggested by the local government. Compared with PTR, DSR increases the use of weedicide. Farmer’s characteristics and planting methods play a crucial role in pesticide use for rice production, but little is known on the inter-relationships among these variables and their impact on weedicide, germicide, and insecticide use. This study examined socioeconomic characteristics, the planting method, and use of the three kinds of pesticides among rice farmers. The research population consisted of 117 households randomly in the study area. We found that the land size and household’s farming days had significant relationships with rice planting method and pesticide use. Farmers with more farmlands or farming days were prefer to choose DSR. Changing from PTR to DSR increased weedicide use (P = 0.006) and decreased germicide use (P = 0.007). Meanwhile, the total input of pesticide would be decreased if more farmers were using DSR (P = 0.022). If farmers could apply the new knowledge of DSR correctly, changing from PTR to DSR showed significance on the decrease in pesticide use.

Abstract Lakes provide significant ecological and economic benefits to society. However, they are prone to over-exploitation and degradation. In this paper, we address the challenge of protecting Chilika Lake in India from heavy siltation caused by land degradation in its catchment areas. Community led afforestation is explored as a management tool for reducing soil erosion and improving fish yields in the lake. Optimal afforestation by a forestry-dependent community is compared to that from the perspective of a manager who maximizes the joint utility of the forestry and fishery-based communities. Additionally, a payment for ecosystem services (PES) mechanism is designed, which pays the forest community on the basis of reduced siltation loading in the lake while also allowing it to benefit from fuelwood harvesting in the newly restored forests. Through relating the impact of fuelwood harvesting by the forestry-based communities on fish yields of the fishing community, a dynamic optimization model evaluates the various trade-offs between environmental services provided by the forest and lake ecosystems. Findings indicate that paying the forestry-based communities for restoration can help improve the lake's lifespan in absence of other interventions. Increasing afforestation levels in the lake's catchment region to 1000 km2 can result in additional fish yield of half a million tonnes over the next hundred years, generating more than a billion dollars in revenues for the fishing communities.

Abstract We propose a method for region-specific budgeting of European Union rural development funds, based on objectively measured indexes of rural development. The indexes are calculated based on statistical data with the use of factor analysis. Next, they are implemented in a linear programming model in order to allocate the given rural development budget. The results demonstrate that the proposed approach allocates the funds according to an assumed logic that supports the weaker and underdeveloped regions and features of agriculture. However, it can be also used as a discussion tool for allocation taking into account different assumptions.