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This study explores the effects that the weather has on people's everyday activity patterns. Temperature, rainfall, and wind speed were used as weather parameters. People's daily activity patterns were inferred, such as place visited, the time this took place, the duration of the visit, based on the GPS location traces of their mobile phones overlaid upon Yellow Pages information. Our analysis of 31,855 mobile phone users allowed us to infer that people were more likely to stay longer at eateries or food outlets, and (to a lesser degree) at retail or shopping areas when the weather is very cold or when conditions are calm (non-windy). When compared to people's regular activity patterns, certain weather conditions affected people's movements and activities noticeably at different times of the day. On cold days, people's activities were found to be more diverse especially after 10AM, showing greatest variations between 2PM and 6PM. A similar trend is observed between 10AM and midnight on rainy days, with people's activities found to be most diverse on days with heaviest rainfalls or on days when the wind speed was stronger than 4 km/h, especially between 10AM-1AM. Finally, we observed that different geographical areas of a large metropolis were impacted differently by the weather. Using data of urban infrastructure to characterize areas, we found strong correlations between weather conditions upon people's accessibility to trains. This study sheds new light on the influence of weather conditions on human behavior, in particular the choice of daily activities and how mobile phone data can be used to investigate the influence of environmental factors on urban dynamics.

To represent 3-D space in detail, it is necessary to( acquire 3-D shapes and textures simultaneously and efficiently through the use of precise trajectories of sensors. However, there is no reliable, quick, cheap, and handy method for acquiring accurate high-resolution 3-D data on objects in outdoor and moving environments. In this paper, we propose a combination of charge-coupled device cameras, a small and inexpensive laser scanner, an inexpensive inertial measurement unit, and Global Positioning System for a UAV-borne 3-D mapping system. Direct georeferencing is achieved automatically using all of the sensors without any ground control points. A new method of direct georeferencing by the combination of bundle block adjustment and Kalman filtering is proposed. This allows objects to be rendered richly in shape and detailed texture automatically via a UAV from low altitude. This mapping system has been experimentally used in recovery efforts after natural disasters such as landslides, as well as in applications such as river monitoring. [ABSTRACT FROM AUTHOR]

The Vehicle-borne Laser Measurement System (VLMS) is a mobile mapping system where three single-row laser range scanners, six line CCD cameras, and a GPS/INS-based navigation unit are mounted on a van to measure object geometry and texture along a street. This paper contributes to a method of fusing the data output of VLMS with existing geographic data sources where the focus is on the rectification of the vehicle's motion data derived from GPS/INS, which may be quite erroneous in an urban area. An algorithm is developed to correct the four variables of the vehicle's motion data, i.e., x, y, and z coordinates of the vehicle position and yaw angle of orientation by registering the laser points of the VLMS with an existing data source, e.g., a DSM. The algorithm was examined using the VLMS data that were taken in the Ginza District, Tokyo. By manually assigning 18 sets of tiepoints, the vehicle's motion data were corrected automatically and efficiently, such that the laser points of VLMS were matched to a DSM. In data fusion, a set of objects, which contained commercial signboards, traffic signs and signals, road boundaries, and road lights were extracted from the corrected VLMS data using an interface described in a previous paper. They were integrated with a 1:2500 3D map that consists of only building frames. In addition, line images from the VLMS were projected onto the building facades of the 3D map, and textures were generated automatically. [ABSTRACT FROM AUTHOR]

In this paper, a new methodology for global estimation of crop productivity is proposed. This methodology integrates Erosion Productivity Impact Calculator (EPIC) model with Geographic Information System (GIS) and Inference Engine (IE) technique. EPIC was developed by USDA to analyze the relationship between soil erosion and agricultural productivity just at field level. With the integration of GIS, EPIC can be extended to the application of global or regional level. In this integration, IE is developed to determine possible crop combinations, the optimum starting and ending dates of growth cycle for each crop type and grid cell, in order to ensure best possible crop yields for both rain-fed and irrigated conditions. A case of global crop productivity estimation is tested with GIS-based EPIC in 2000. National averages are computed to be comparable to yields in FAO statistics. The comparison indicates that the GIS-based EPIC is able to simulate crop productivity at global level. In addition, with the global climate change data provided by the Intergovernment Panel on Climate Change (IPCC) from the first version of the Canadian Global Coupled Model (CGCM1), GIS-based EPIC is run for scenarios of future climate in the year of 2010, 2020, 2030, 2040, and 2050 to predict the effects of global warming on main crop yields. Results show the global warming will be harmful for most of the countries, and an efficient adaptation to alternative climates tends to reduce the damages. [Copyright &y& Elsevier]

Abstract. In this paper, a novel method is presented for generating a textured CAD model of an outdoor urban environment using a vehicle-borne sensor system. In data measurement, three single-row laser range scanners and six line cameras are mounted on a measurement vehicle, which has been equipped with a GPS/INS/Odometer-based navigation system. Laser range and line images are measured as the vehicle moves forward. They are synchronized with the navigation system so they can be geo-referenced to a world coordinate system. Generation of the CAD model is conducted in two steps. A geometric model is first generated using the geo-referenced laser range data, where urban features, such as buildings, ground surfaces, and trees are extracted in a hierarchical way. Different urban features are represented using different geometric primitives, such as a planar face, a triangulated irregular network (TIN), and a triangle. The texture of the urban features is generated by projecting and resampling line images onto the geometric model. An outdoor experiment is conducted, and a textured CAD model of a real urban environment is reconstructed in a full automatic mode. [ABSTRACT FROM AUTHOR]

Many LBS applications provide automatic audio playing functions for introducing POI's. Appropriate automatic audio playing can improve users' expressions during traveling with LBS and in some degree prevent walking-smartphone. However, the problem of discontinuity of audio playing on the contrary affects users' expressions. One main reason that cause the discontinuity of audio playing is the sudden switch of audios, usually caused by a user entering the geofence of another POI while the audio of current POI is under playing. This paper proposed a preliminary approach to prevent the sudden switch of the audio instruction of POI's by making adjustments on the POI's audios and geofences. Current main approach for automatic POI audio playing is using a geofence of the POI as a spatial trigger to control the audio playing. This simple approach may cause sudden switch of audio playing, which causes negative users' expressions. As shown in Figure 1, a user's moving trajectory frequently crosses geofences of two POI's, which will result in a frequent switch of POI's audios with neither completely played. The inflexible audio files and geofences are the main reasons causes the sharp audio switches and we are going to solve the problem by making the audio files and geofences flexible. Conventional POI audio is made of one integrated file. As shown in Figure 2, we separate the POI audio content into several audio files, with each file consists one sentence or one short paragraph, and we call it composed audio. The files of a composed audio will be played in sequence, and the basic rule of playing a composed audio is not stopping until one file is completely played, which ensures that the composed audio will stop naturally after a complete sentence or paragraph. We define four important events for automatic playing composed audios. Start playing means start to play a composed audio from the beginning. It usually happens when a user enters a geofence of a POI. Stop playing means to stop a composed audio when finishing playing the current audio file. It usually happens when a user enters the geofence of another POI. Prepare playing means to start playing a composed audio when finishing playing the composed audio that is under playing. It usually happens when enters the geofence of a second POI. Cancel playing means to cancel the prepare playing status of a composed audio. It happens when a composed audio of a POI is in prepare playing status but the user leaves the geofence of the current POI or enters the geofence of another POI before the composed audio starting playing. By introducing buffers to a geofence (Tokita, Arikawa, Si et al, 2018), it makes a geofence flexible, and we note the geofences with buffers as the buffered geofences. As shown in Figure 3, here we add an outer buffer to the geofence in Figure 1 to improve stability of POI's audio play. An object has two status related to the buffered geofence: out and in, and it has two events related to the buffered geofence: enter and leave. The enter event occurs when the object is out of the buffered geofence and crosses the geofence's boundary; the leave event occurs when the object is in the buffered geofence and crosses the geofence's outer buffer. The result is that even though the user is frequently crossing the boundaries of the buffered geofences, he/she only enters each buffered geofences once, thus the audios of each POI will play once and will not be frequently switched. In this paper we introduced an approach to prevent discontinuous POI's audio playing by composed audios and buffered geofences. This research is still preliminary, and it needs more researches on how to separate POI audios: too fragmented separation of POI audio may still make users feel an unnatural finish of an audio, and too generalized separation may result in more time costed before stopping a composed audio. Also, the current rules for playing composed audios based on the buffered geofences are relatively simple, which may cause unbalanced audio play. For example, when a user enters the buffered geofence of POI_A and soon enters the buffered geofence of POI_B, the time for playing composed audio of POI_A will be short. In the future, we plan to estimate the overall time for candidate audios to be played and balance the time for each of them. [ABSTRACT FROM AUTHOR]

Abstract: Multipath is one of the main causes of degraded position accuracy in the Global Navigation Satellite System (GNSS) because portions of the signals can be reflected by high buildings in dense urban areas. Multipath mitigation techniques based on hardware enhancement or signal processing help to improve GNSS accuracy for high-precision surveying. A Geographic Information System (GIS) is also used in the signal propagation model to predict multipath effects. In addition to these existing approaches, we found that spatial statistical methods are useful in multipath mitigation because the multipath produces a unique spatial distribution of user positions. In this paper, we present a spatial statistics-based simulation system for mitigating multipath and improving the accuracy in GNSS positioning. Multipath tends to be associated with spatial outliers in simulated user positions (SUPs) and contributes little to the spatial clustering of SUPs. Using these spatial characteristics, we developed a method called the “satellite participation ratio in outliers versus cluster” (SPROC) to identify multipath satellites. Once the identified multipath satellites are excluded, a user position is determined using a mean spatial center of the SUPs from the remaining satellites. The effects of such multipath mitigation were validated by examining whether the SPROC method correctly identified multipath satellites and by comparing the position errors with and without SPROC. We demonstrated the applicability of our system with a simulation experiment using a precise ephemeris for the Global Positioning System (GPS) and the orbital parameters for the proposed constellations of the GALILEO and the Quasi-Zenith Satellite System (QZSS). In our simulation of Shinjuku ward in Tokyo, the user-equivalent range error (UERE) other than multipath was virtually generated and added to the multipath delay. The pattern of position errors with and without SPROC showed that the improvements in accuracy were considerable at locations close to buildings. [Copyright &y& Elsevier]

Offshore wind farms are increasingly becoming the focus of clean sources market because of the huge energy potential and fast-maturing technology. The existing researches normally optimize the wind turbine layout and two-dimensional cable routing independently. This work focuses on the synchronization optimization of site selection of the offshore wind farm, three-dimensional wind turbine layout and three-dimensional cable network routing based on meta-heuristic algorithms and geographic information systems. Several practical issues, i.e., restricted areas, power generation, cable network and energy loss, are taken into consideration. A two-layer model is proposed. The outer layer model is for the site selection and the wind turbine layout optimization. The inner layer model is for the obstacle-avoiding cable routing optimization. In this stage, the seabed terrain is considered for the first time. The proposed integrated model is complex and non-convex. Thus, a hybrid method including an improved ant colony optimization combined with genetic algorithm, dual-simplex method and Kruskal algorithm is proposed to search the solution more efficiently. The initialization stage of the hybrid method is improved from random assignment to directional assignment. The directional solution is obtained by the widely used genetic algorithm. A case study based on a real offshore wind farm is established to prove the effectiveness of the proposed methodology. The results show an over one million dollars increase in annual benefit compared with conventional methods. [ABSTRACT FROM AUTHOR]

Despite a growing body of evidence indicating increasing health impacts from heat exposure secondary to climate change, previous studies have assessed heat exposure based only on the residential locations of individuals. Such assessments may be imprecise as they do not reflect the impact of people's daily mobility patterns. Furthermore, most studies have focused on urban areas in developed countries, whilst relatively little is known about the situation in developing nations, particularly a tropical climate region where heat exposure is severe for residents. As a case study in Dhaka, Bangladesh, we conducted a heat exposure assessment by integrating individual mobility data which was obtained from a questionnaire survey. Estimates of heat exposure were made using remotely sensed land surface temperature data. Population exposures based on residential locations were compared to a dynamic exposure model that incorporated mobility. Especially for people in suburban areas, we found the traditional assessment method based on the static residential model underestimated exposure compared to the dynamic model owing to the fact that some residents migrate into the city center each day where they tend to experience higher temperatures. We found small differences in heat exposure levels between social groups stratified by gender, age, and income based on the dynamic and static models. These results demonstrate that integration of mobility patterns may be important when comparing exposure levels between urban and suburban populations. Our findings may raise issues regarding new remediation measures against urban heat islands, such as reviewing the distribution of health resources or generating a risk map. • This is a new application of GIS-based mobility data for a dynamic heat exposure assessment in Dhaka, Bangladesh. • Population exposure based on a static residential model was compared to a dynamic exposure model that incorporated mobility. • We found the static assessment underestimated heat exposure compared to the dynamic assessment for some suburb populations. • Mobility data have the potential for a more precise exposure assessment of adverse environmental risks. [ABSTRACT FROM AUTHOR]