A method of linking functional and structural connectivity analysis in urban green infrastructure network construction

Accelerated urbanization and population growth lead to the fragmentation of urban green space and loss of biodiversity. There are few studies on the integration of structural and functional connectivity to solve this problem. Our study aims to draw up a methodology to synthesize two methods of connectivity evaluation, accordingly, to construct an urban green infrastructure (UGI) network which is of great significance to maintain the stability of the urban ecosystem. Taking Beijing as a study area, we first used Morphological Spatial Pattern Analysis (MSPA) to identify the source patches, then combined with the graph theory-based landscape metrics to discuss the effect of different diffusion distances on the regional landscape connectivity and classify the importance level of the source patches. Finally, we used both least-cost path (LCP) and circuit theory to construct network and identify pinch areas in corridors for network optimization. The results show that (1) the landscape connectivity of the study area is obviously polarized. Source patches in mountain and hilly areas have good ecological bases and large areas, and the density of corridors is relatively high, which makes a large contribution to the overall landscape connectivity; Source patches in plain areas are severely fragmented, and there are only a small number of potential corridors connecting urban areas and suburban areas. (2) The UGI network is composed of 70 source patches and 148 potential corridors. The diffusion distance that is most beneficial to improve landscape connectivity is 20–25 km. (3) 6 pinch areas that are of great significance for improving the connectivity of the landscape present the coexistence of high migration resistance and large optimization potential, and urgently need to be restored first. This study provides a method to combine the structural and the functional analysis to construct a UGI network and formulate more scientifical protection strategies for planning departments.

Control of mobile robot formations using A-star algorithm and artificial potential fields

Formations or groups of robots become essential in cases where a single robot is insufficient to satisfy a given task. With an increasingly automated world, studies on various topics related to robotics have been carried out in both the industrial and academic arenas. In this paper, the control of the formation of differential mobile robots based on the leader-follower approach is presented. The leader's movement is based on the least cost path obtained by the A-star algorithm, thus ensuring a safe and shortest possible route for the leader. Follower robots track the leader's position in real time. Based on this information and the desired distance and angle values, the leader robot is followed. To ensure that the followers do not collide with each other and with the obstacles in the environment, a controller based on Artificial Potential Fields is designed. Stability analysis using Lyapunov theory is performed on the linearized model of the system. To verify the implemented technique, a simulator was designed using the MATLAB programming language. Seven experiments are conducted under different conditions to show the performance of the approach. The distance and orientation errors are less than 0.1 meters and 0.1 radians, respectively. Overall, mobile robots are able to reach the goal position, maintaining the desired formation, in finite time.

Sequential Least-Cost Path Sailing Model for Early 17th Century South China Sea: Digitally Navigating the Selden Map of China

During the 17th century, Southeast Asia was a bustling hub of maritime commerce. The Selden Map of China depicts some of the trade routes in the area and is drawn in a way which allows their sailing durations to be measured. This information is used in the development of a sequential least-cost path sailing model that utilizes deterministic timeseries wind data. The model can be used to simulate the optimized routes and durations between any points A and B in the South China Sea. With minor modifications, the method is applicable to other time periods and geographical settings.

Protohistoric Landscapes in Sardinia (Italy): Territorial Control and Exploitation of Natural Resources in the Middle and Late Bronze Ages

During the Bronze Age, in many Western Mediterranean areas (Spain, France, Italian peninsula, islands), we can observe the development of a series of fortified centers and structures, often on high places, aimed to the defense of strategic locations and resources. These fortifications, which began to be built from the Copper Age, are the answer to a need for possession and control of the territory linked to a greater degree of social complexity, with an ever-increasing hierarchy and the rise to power of persons or groups who very often show the possession of weapons and, consequently, can be related to warlike activities. In Sardinia, Nuragic phenomenon developed during Protohistoy: an extraordinary culture ranging from the Middle to Late Bronze Age (XVIII-XII centuries BC), some of whose features could last from Final Bronze Age until the beginnings of Iron Age (XI-VIII centuries BC), characterized by the building of great monuments, especially nuraghi, cyclopean-type constructions similar to towers. These great buildings have multiple functions, but in particular were used to surveil the whole island territory. We have mainly carried out different GIS analyzes on different sample areas with the aim to reading the visual-perceptive aspects and to try to research about the relationship between settlements and territory and the mobility systems across different territories through the applying of the least-cost path analysis. Reconstruction of certain characteristics of Sardinian Protohistoric Landscape in these areas is achieved. GIS-based analysis show how these territorial control systems, consisting of several nuraghi and settlements, were intended to control the most important natural and economic resources and transit routes.

Route planning on orienteering maps with least-cost path analysis

The feature categories of an orienteering map are prepared to allow the map reader to estimate the travel time between any two points on the map with a good approximation. This requires not only an accurate map, but also a key that adapts to the speed of travel. Such map key is developed and maintained by the IOF (International Orienteering Federation), and technically all the orienteering maps are compiled by using it. Estimated time also plays an important role in planning the courses of orienteering races. The course setter estimates time based on a route he thinks is ideal, but the speed of travel is basically a non-linear function of terrain, road network and land cover. Because of this, the easiest (ideal) route between the two points and its time cost can be calculated using the least-cost path (LCP) GIS method, which can be prepared to take into account these three map feature categories. This method is based on the calculation of a cost surface, then the analysis of the ideal path from a given point to the destination. The automation can be adapted to any orienteering map due to the similarities of the map keys. This study shows that if the weight corresponding to the different feature categories is given properly, the ideal path between two points on orienteering maps can be calculated. The ideal path, however is still a subjective category, which may depend on the capabilities and preferences of the orienteer. In this study the routes calculated with the LCP method were compared with the suggestions of the ideal routes by orienteering runners of different ages. The results show that the routes given by sportsmen can be simulated with the LCP method and even the time cost of the calculated routes can be calculated. This study can lay the groundwork for a GIS tool helping the course setting process on standard orienteering maps.

The Green Paths route planning software for exposure-optimised travel

Green Paths is a prototype of route planning software for finding exposure-optimised routes for active travel. It incorporates external data on environmental exposures, including traffic noise levels, air quality, and street-level greenery into the street and paths network produced by the OpenStreetMap project. Written in the Python programming language, the software applies a novel environmental impedance function in the least cost path routing to find exposure-optimised routes. Routes for externally defined origin-destination pairs can be queried via a RESTful API. The API returns alternative routes equipped with rich exposure data. The published version of the software has been applied in population level environmental exposure assessment and in an end-user-oriented web-based route planner application designed for use in the Helsinki Metropolitan Area.

Transboundary spread of peste des petits ruminants virus in western China: A prediction model

In pan Pamir Plateau countries, Peste des petits ruminants (PPR) has brought huge losses to the livestock industry and threaten the endangered wildlife. In unknown regions, revealing PPRV transmission among countries is the premise of effective prevention and control, therefore calls for quantified monitoring on disease communication among countries. In this paper, a MaxEnt model was built for the first time to predict the PPR risk within the research area. The least cost path (LCP) for PPR transboundary communication were calculated and referred to as the maximum available paths (MAP). The results show that there are many places with high-risk in the research area, and the domestic risk in China is lower than that in foreign countries and is mainly determined by human activities. Five LCPs representing corridors among Kazakhstan, Tajikistan, Pakistan, India and China were obtained. This study proves for the first time that there is the possibility of cross-border transmission of diseases by wild and domestic animals. In the future, it will play an important role in monitoring the PPR epidemic and blocking-up its cross-border transmission.

An Investigation of Non-Coplanar Volumetric Modulated Radiation Therapy for Locally Advanced Unresectable Pancreatic Cancer Using a Trajectory Optimization Method

PurposeThis study was conducted in order to develop a trajectory optimization algorithm for non-coplanar volumetric modulated arc therapy (VMAT) and investigate the potential of organs at risk (OARs) sparing in locally advanced pancreatic cancer patients using non-coplanar VMAT.Methods and MaterialsFirstly, a cost map that represents the ray–OAR voxel intersections at each source position was generated using a ray-tracing algorithm. A graph search algorithm was then used to determine the least-cost path from the cost map. Lastly, full arcs or partial arcs were selected based on the least-cost path to generate the non-coplanar VMAT (ncVMAT) trajectories. Clinical coplanar VMAT (coVMAT) plans for 11 patients diagnosed with locally advanced unresectable pancreatic cancer (LAPC) receiving 45 to 70 Gy in 25 fractions were replanned using non-coplanar VMAT trajectories. Both coplanar and non-coplanar plans were normalized to cover 95% of the PTV45 Gy volume with a prescription dose of 45 Gy. The conformity index (CI), homogeneity index (HI), PTV coverage, and dose to the OARs were compared between coVMAT and ncVMAT plans.ResultsWith ncVMAT, the mean coverage of PTV50 Gy, PTV54 Gy, PTV60 Gy, and PTV70 Gy increased significantly. The mean conformity index of PTV45 Gy, PTV54 Gy, and PTV70 Gy was also improved in the ncVMAT plans. Compared with coVMAT plans, the ncVMAT plans resulted in significantly lower doses to the spinal cord, bilateral kidneys, stomach, and duodenum. The maximum dose to the spinal cord decreased by 6.11%. The mean dose to the left and right kidneys decreased by an average of 5.52% and 11.71%, respectively. The Dmax, Dmean, and D15% of the stomach were reduced by an average of 7.45%, 15.82%, and 16.79%, separately. The D15% and Dmean of the duodenum decreased 6.38% and 5.64%, respectively.ConclusionA trajectory optimization algorithm was developed for non-coplanar VMAT. Compared with conventional coplanar VMAT, non-coplanar VMAT resulted in improved coverage and conformity to the targets. The sparing of OARs was significantly improved in non-coplanar VMAT compared with coVMAT plans for locally advanced pancreatic cancer.