Measuring place-based accessibility under travel time uncertainty

Travel time uncertainty has significant impacts on individual activity-travel scheduling, but at present these impacts have not been considered in most accessibility studies. In this paper, an accessibility evaluation framework is proposed for urban areas with uncertain travel times. A reliable space-time service region (RSTR) model is introduced to represent the space-time service region of a facility under travel time uncertainty. Based on the RSTR model, four reliable place-based accessibility measures are proposed to evaluate accessibility to urban services by incorporating the effects of travel time reliability. To demonstrate the applicability of the proposed framework, a case study using large-scale taxi tracking data is carried out. The results of the case study indicate that the proposed accessibility measures can evaluate large-scale place-based accessibility well in urban areas with uncertain travel times. Conventional place-based accessibility indicators ignoring travel time reliability can significantly overestimate the accessibility to urban services.     

地统计学方法在土壤学中的应用

地统计学目前在土壤科学中得到广泛的应用和发展,成为认识土壤特征的一个重要工具.地统计学的空间变异函数和克里格插值等方法是土壤性状分析的主要手段,空间变异函数主要用于描述土壤理化性状空间变异特性,不同的插值方法可优化田间试验设计和田间采样方案,克里格插值方法则特别适用于未测量点土壤属性值的估测等.近年插值方法又被广泛应用于确定区域土壤环境容量和土壤质量标准,随机模拟则用于对土壤特性进行不确定性估计等.因而,地统计学方法对我国大量土壤学资料的整合与分析具有极大的应用前景.     

广域差分GPS系统完备性监测

广域差分 GPS系统完备性监测技术是广域差分的关键和核心。本文全面介绍了完备性监测技术的定义 ,完备性监测系统的构成 ,以及各个部分的监测方法 ,包括监测站和用户站的监测技术 ,最后给出了完备性监测的一般步骤。     

不动产地籍和产权登记信息系统

介绍了一种涵盖地籍管理过程且在实施过程中简单易行而有效的信息系统,为土地资源的合理开发利用和地籍信息的动态管理了新的途径。     

科研思维融入教学过程的教学方法探讨

创新能力培养依赖于科研思维和创新思维的训练.本研究以"遥感导论"课程为例,探讨将科研思维融入教学过程,并引导学生归纳和总结,提升科研思维和创新能力.对教学效果的分析表明,将科研思维融入教学过程能够更好地引导学生主动学习和主动思考,有效提高了他们的动手能力和解决问题能力.     

Improved Priority‐Flood method for depression filling by redundant calculation optimization in local micro‐relief areas

Depression filling is a critical step in distributed hydrological modeling using digital elevation models (DEMs). The traditional Priority‐Flood (PF) approach is widely used due to its relatively high efficiency when dealing with a small‐sized DEM. However, it seems inadequate and inefficient when dealing with large high‐resolution DEMs. In this work, we examined the relationship between the PF algorithm calculation process and the topographical characteristics of depressions, and found significant redundant calculations in the local micro‐relief areas in the conventional PF algorithm. As such calculations require more time when dealing with large DEMs, we thus propose a new variant of the PF algorithm, wherein redundant points and calculations are recognized and eliminated based on the local micro‐relief water‐flow characteristics of the depression‐filling process. In addition, depressions and flatlands were optimally processed by a quick queue to improve the efficiency of the process. The proposed method was applied and validated in eight case areas using the Shuttle Radar Topography Mission digital elevation model (SRTM‐DEM) with 1 arc‐second resolution. These selected areas have different data sizes. A comparative analysis among the proposed method, the Wang and Liu‐based PF, the improved Barnes‐based PF, the improved Zhou‐based PF, and the Planchon and Darboux (P&D) algorithms was conducted to evaluate the accuracy and efficiency of the proposed algorithm. The results showed that the proposed algorithm is 43.2% (maximum) faster than Wang and Liu's variant of the PF method, with an average of 31.8%. In addition, the proposed algorithm achieved similar performance to the improved Zhou‐based PF algorithm, though our algorithm has the advantage of being simpler. The optimal strategies using the proposed algorithm can be employed in various landforms with high efficiency. The proposed method can also achieve good depression filling, even with large amounts of DEM data.     

Solar abundance of praseodymium

16 lines of Pr ii possibly present in the solar photospheric spectrum have been studied. When including hyperfine structure in synthetic calculations, investigations of 9 lines result in an abundance A _Pr = 0.71 ± 0.08 in the log A _H = 12.00 scale.     

A Voronoi neighborhood-based search heuristic for distance/capacity constrained very large vehicle routing problems

Local search heuristics for very large-scale vehicle routing problems (VRPs) have made remarkable advances in recent years. However, few local search heuristics have focused on the use of the spatial neighborhood in Voronoi diagrams to improve local searches. Based on the concept of a k-ring shaped Voronoi neighbor, we propose a Voronoi spatial neighborhood-based search heuristic and algorithm to solve very large-scale VRPs. In this algorithm, k-ring Voronoi neighbors of a customer are limited to building and updating local routings, and rearranging local routings with improper links. This algorithm was evaluated using four sets of benchmark tests for 200–8683 customers. Solutions were compared with specific examples in the literature, such as the one-depot VRP. This algorithm produced better solutions than some of the best-known benchmark VRP solutions and requires less computational time. The algorithm outperformed previous methods used to solve very large-scale, real-world distance constrained capacitated VRP.