Measuring positive public transit accessibility using big transit data

Most of the current existing accessibility measures quantify the potential of reaching desirable opportunities across space and time. Nevertheless, these potent...     

实时交通数据支持下的医疗服务时空可达性分析

针对现有城市医疗服务可达性分析方法未考虑就医偏好,导致测算结果与居民实际感受相差较大的问题,本文提出了一种顾及时间和距离成本偏好的医疗服务时空可达性分析方法,并以武汉市中心城区为例进行了分析。试验结果表明,研究方法充分利用交通路况,兼顾了交通距离和通行时间对就医选择的影响,距离偏好在新方法中作用显著。该方法一方面可以体现不同时刻可达性差异,另一方面又强调了居民就医的时间和距离成本偏好,相比单一的时间或距离成本更具优势,分析结果更符合现实。     

Environmental public health applications using remotely sensed data

We describe a remote sensing and geographic information system (GIS)-based study that has three objectives: (1) characterize fine particulate matter (PM_2.5), insolation and land surface temperature (LST) using NASA satellite observations, Environmental Protection Agency (EPA) ground-level monitor data and North American Land Data Assimilation System (NLDAS) data products on a national scale; (2) link these data with public health data from the REasons for Geographic And Racial Differences in Stroke (REGARDS) national cohort study to determine whether these environmental risk factors are related to cognitive decline, stroke and other health outcomes and (3) disseminate the environmental datasets and public health linkage analyses to end users for decision-making through the Centers for Disease Control and Prevention (CDC) Wide-ranging Online Data for Epidemiologic Research (WONDER) system. This study directly addresses a public health focus of the NASA Applied Sciences Program, utilization of Earth Sciences products, by addressing issues of environmental health to enhance public health decision-making.     

Estimation of transit trip production using Factorial Kriging with External Drift: an aggregated data case study

Studies in transportation planning routinely use data in which location attributes are an important source of information. Thus, using spatial attributes in urban travel forecasting models seems reasonable. The main objective of this paper is to estimate transit trip production using Factorial Kriging with External Drift (FKED) through an aggregated data case study of Traffic Analysis Zones in São Paulo city, Brazil. The method consists of a sequential application of Principal Components Analysis (PCA) and Kriging with External Drift (KED). The traditional Linear Regression (LR) model was adopted with the aim of validating the proposed method. The results show that PCA summarizes and combines 23 socioeconomic variables using 4 components. The first component is introduced in KED, as secondary information, to estimate transit trip production by public transport in geographic coordinates where there is no prior knowledge of the values. Cross-validation for the FKED model presented high values of the correlation coefficient between estimated and observed values. Moreover, low error values were observed. The accuracy of the LR model was similar to FKED. However, the proposed method is able to map the transit trip production in several geographical coordinates of non-sampled values.     

北京地区Landsat 8 OLI高空间分辨率气溶胶光学厚度反演

卫星气溶胶光学厚度(AOD)反演中,传统暗目标方法在反射率较低的水体、浓密植被覆盖区域取得了较好效果,在反射率较高且结构复杂的高反射地表上空目前多采用深蓝算法,但存在空间分辨率较低,对细节分布描述性较差等问题。为解决这一问题,本文首先以5年(2008年—2012年)长时间序列MODIS地表反射率产品为基础,采用最小值合成法建立500 m分辨率逐月地表反射率产品数据集,然后利用地物波谱库中典型地物波谱数据,分析建立MODIS与Landsat 8 OLI传感器蓝光波段反射率转换模型,最后北京地区AERONET地基观测数据确定了气溶胶光学物理参数,并反演获取了北京地区上空500 m分辨率的AOD分布。为验证反演算法的精度,分别将反演结果同AERONET及MODIS/Terra气溶胶产品(MOD04)进行交叉对比,同时利用相关系数R,均方根误差RMSE,平均绝对误差MAE以及MODIS AOD产品预期误差EE共4个指标进行衡量。结果表明:算法反演获取的AOD与AERONET观测值具有较高的一致性,各指标分别为R=0.963,RMSE=0.156,MAE=0.097,EE=85.3%,稍优于MOD04产品(R=0.962,RMSE=0.158,MAE=0.101,EE=75.8%),并且有效的对比点数也高于MOD04。通过与地基观测相比,卫星遥感获取的高分辨率城市地区AOD精度可作为定量评估城市空气质量的有效依据。     

基于高分辨率机载SAR数据的试验研究

主要研究了高分辨率机载SAR数据运用于测绘试验的可行性,提出数据处理的关键流程,诸如数据获取、成像处理、预处理、几何处理、融合处理,以及可供提取的最基本的制图要素,诸如道路、铁路、水系、植被、耕地和居民地,并进行了精度评估,最后对地形图更新,提取变化信息。试验结果初步表明高分辨率、高成像质量的机载SAR影像数据应用于测绘领域是可行的。可以看出高分辨率机载SAR影像的应用得到了比较满意的结果。     

Object-based urban land cover classification using rule inheritance over very high-resolution multisensor and multitemporal data

Very high spatial and temporal resolution remote sensing data facilitate mapping highly complex and diverse urban environments. This study analyzed and demonstrated the usefulness of combined high-resolution aerial digital images and elevation data, and its processing using object-based image analysis for mapping urban land covers and quantifying buildings. It is observed that mapping heterogeneous features across large urban areas is time consuming and challenging. This study presents and demonstrates an approach for formulating an optimal land cover classification rule set over small representative training urban area image, and its subsequent transfer to the multisensor, multitemporal images. The classification results over the training area showed an overall accuracy of 96%, and the application of rule set to different sensor images of other test areas resulted in reduced accuracies of 91% for the same sensor, 90% and 86% for the different sensors temporal data. The comparison of reference and classified buildings showed ±4% detection errors. Classification through a transferred rule set reduced the classification accuracy by about 5%–10%. However, the trade-off for this accuracy drop was about a 75% reduction in processing time for performing classification in the training area. The factors influencing the classification accuracies were mainly the shadow and temporal changes in the class characteristics.     

利用车载激光扫描的城市森林三维绿量估算

针对城市森林绿量估算研究不足的现状,该文提出了结合高分辨率航空遥感影像和车载激光扫描技术估算城市森林三维绿量的方法:首先从车载激光扫描数据中提取道路两侧单株树的生物物理参数,再结合从航空遥感影像中提取的植被分布,对均质城市森林片区进行三维绿量的拟合计算;最后以上海市滨江森林公园为例进行了方法验证。结果表明,该方法能够拓展车载激光扫描系统应用的领域,为城市绿化信息的获取提供参考。     

Mapping the distribution of mangrove species in the Core Zone of Mai Po Marshes Nature Reserve,Hong Kong,using hyperspectral data and high-resolution data

Mangrove species compositions and distributions are essential for conservation and restoration efforts. In this study, hyperspectral data of EO-1 HYPERION sensor and high spatial resolution data of SPOT-5 sensor were used in Mai Po mangrove species mapping. Objected-oriented method was used in mangrove species classification processing. Firstly, mangrove objects were obtained via segmenting high spatial resolution data of SPOT-5. Then the objects were classified into different mangrove species based on the spectral differences of HYPERION image. The classification result showed that in the top canopy, Kandelia obovata and Avicennia marina dominated Mai Po Marshes Natural Reserve, with area of 196.8 ha and 110.8 ha, respectively, Acanthus ilicifolius and Aegiceras corniculatum were mixed together and living at the edge of channels with an area of 11.7 ha. Additionally, mangrove species shows clearly zonations and associations in the Mai Po Core Zone. The overall accuracy of our mangrove map was 88% and the Kappa confidence was 0.83, which indicated great potential of using hyperspectral and high-resolution data for distinguishing and mapping mangrove species.     

Deep neural network for complex open-water wetland mapping using high-resolution WorldView-3 and airborne LiDAR data

Wetland inventory maps are essential information for the conservation and management of natural wetland areas. The classification framework is crucial for successful mapping of complex wetlands, including the model selection, input variables and training procedures. In this context, deep neural network (DNN) is a powerful technique for remote sensing image classification, but this model application for wetland mapping has not been discussed in the previous literature, especially using commercial WorldView-3 data. This study developed a new framework for wetland mapping using DNN algorithm and WorldView-3 image in the Millrace Flats Wildlife Management Area, Iowa, USA. The study area has several wetlands with a variety of shapes and sizes, and the minimum mapping unit was defined as 20 m² (0.002 ha). A set of potential variables was derived from WorldView-3 and auxiliary LiDAR data, and a feature selection procedure using principal components analysis (PCA) was used to identify the most important variables for wetland classification. Furthermore, traditional machine learning methods (support vector machine, random forest and k-nearest neighbor) were also implemented for the comparison of results. In general, the results show that DNN achieved satisfactory results in the study area (overall accuracy = 93.33 %), and we observed a high spatial overlap between reference and classified wetland polygons (Jaccard index ∼0.8). Our results confirm that PCA-based feature selection was effective in the optimization of DNN performance, and vegetation and textural indices were the most informative variables. In addition, the comparison of results indicated that DNN classification achieved relatively similar accuracies to other methods. The total classification errors vary from 0.104 to 0.111 among the methods, and the overlapped areas between reference and classified polygons range between 87.93 and 93.33 %. Finally, the findings of this study have three main implications. First, the integration of DNN model and WorldView-3 image is useful for wetland mapping at 1.2-m, but DNN results did not outperform other methods in this study area. Second, the feature selection was important for model performance, and the combination of most relevant input parameters contributes to the success of all tested models. Third, the spatial resolution of WorldView-3 is appropriate to preserve the shape and extent of small wetlands, while the application of medium resolution image (30-m) has a negative impact on the accurate delineation of these areas. Since commercial satellite data are becoming more affordable for remote sensing users, this study provides a framework that can be utilized to integrate very high-resolution imagery and deep learning in the classification of complex wetland areas.     

Performance of real-time Precise Point Positioning using IGS real-time service

GPS Solutions - Until recently, the real-time IGS precise orbit and clock corrections were only available for the predicted part of the ultra-rapid solution. Whereas the accuracy of the ultra-rapid...     

高分遥感影像与矢量数据结合的变化检测方法

针对高分辨率遥感影像与矢量数据配准套合之后存在的不一致性问题,该文探讨了多尺度分割算法获取同质像斑的方法。在此基础上,发展了一种基于最近邻分类算法的分类后处理变化检测方法。结果表明,通过多尺度分割算法能够获取"类内光谱相同"和"类间光谱相异"的像斑;分类后处理变化检测方法能够正确检测出80%以上的变化区域,在获取变化检测结果的同时能够获取变化像斑的类别,而且检测精度较高,具有较高的应用价值。     

The accessibility analysis of multiple public facilities in the central urban areas based on multi-transportation modes: A study in Chengdu

With the rapid development of social economy in Chengdu, it is of great significance to analyze the accessibility of a public facilities resources, and services in respective regions for the spatial planning of public facilities and the optimization of urban construction in Chengdu. Most existing studies only consider the accessibility of a single public facility under a single transportation mode studying facilities at the same level. In this research, with the consideration of all these factors mentioned above, an improved 3-step floating catchment area (3SFCA) model of multi-transportation modes is introduced to analyze the accessibility and spatial distribution of multiple types of public facilities under multiple traffic modes. The new model classifies the grade of public facilities and calculates the service accessibility of public facilities under the driving, public transport, cycling, and walking modes in the five dimensions of education, medical care, commerce, transportation, and leisure in the central urban areas of Chengdu. Through the comparative analysis of multiple models, we found that the improved 3SFCA can more accurately evaluate the accessibility of all dimensions of public facilities in central urban areas of Chengdu. The accessibility of compound public facilities in the central city is excellent. With the gradual expansion to the outward areas, the diversity and accessibility of compound public facilities gradually decreases. Furthermore, the accessibility distribution of public facilities in the study area is not balanced. The accessibility between the central urban areas and the marginal areas differs greatly and the spatial differentiation is substantial.     

基于公交大数据的满载率推算方法 ——以深圳市为例

城市可持续发展需要提升公共交通的供给能力。公汽满载率是公交规划、调度和服务评价等方面的重要参数。在公交信息化水平不断提升的背景下,由公交IC卡数据和公共汽车GPS数据等构成的公交大数据为获得相对精确的客流提供了可能。虽然已有相对稳定的OD推算方法,但对于公汽满载率的研究尚不够充分。本文提出基于历史公交大数据的大规模公交出行链搜素算法,在此基础上构建公共汽车满载率数据库,并以深圳市为例揭示了高满载率线路段的时空分布特征。本文研究对于揭示公汽服务整体水平和探测关键公交廊道具有较大价值。     

Evaluating the importance of accessibility to congestion response using a GIS-based travel simulator

 This paper examines the effect of accessibility on individual response to unexpected traffic delays and congestion. The dataset used was collected by means of a travel simulator developed within a geographic information system (GIS) environment. The simulator models a commute trip where congestion takes place, and subjects are asked to respond by making a choice among alternative courses of action. Available alternatives for dealing with the unexpected traffic delay include changing the location of the planned activities or changing the activities to be performed. Accessibility to the new locations and to the different activities is computed using a cumulative measure. Analysis using CHAID tree technique found that accessibility is a good predictor of subjects' choice when responding to unexpected traffic delays. Received: September 2002 / Accepted: January 2003 Support for this research by a grant from the Center of Intelligent Transportation Research of the Ohio State University is gratefully acknowledged. The author would also like to thank Joe Weber, Mei-Po Kwan and two anonymous reviewers for their valuable comments.     

Mt. Etna volcano high-resolution topography: airborne LiDAR modelling validated by GPS data

High-resolution digital topography is essential for land management and planning in any type of territory as well as the reproduction of the Earth surface in a geocoded digital format that allows several Digital Earth applications. In a volcanic environment, Digital Elevation Models are a valid reference for multi-temporal analyses aimed to observe frequent changes of a volcano edifice and for the relative detailed morphological and structural analyses. For the first time, a DTM (Digital Terrain Model) and a DSM (Digital Surface Model) covering the entire Mt. Etna volcano (Italy) derived from the same airborne Light Detection and Ranging (LiDAR) are here presented. More than 250 million 3D LiDAR points have been processed to distinguish ground elements from natural and anthropic features. The end product is the highly accurate representation of Mt. Etna landscape (DSM) and ground topography (DTM) dated 2005. Both models have a high spatial resolution of 2?m and cover an area of 620?km². The DTM has been validated by GPS ground control points. The vertical accuracy has been evaluated, resulting in a root-mean-square-error of ±?0.24?m. The DTM is available as electronic supplement and represents a valid support for various scientific studies.     

Individual accessibility and distance from major employment centers: An examination using space-time measures

 Distance has often been assumed to be an influence on intraurban accessibility, whether in traditional proximity-based measures of accessibility, or through expectations about distance-minimizing travel behavior and the logic of the monocentric model. This paper examines the importance of distance from major employment centers to individual accessibility in Portland, Oregon, using space-time accessibility measures computed using GIS. The results of this research indicate that distance from these locations has mixed results on individual accessibility. This appears to reflect the importance of time, both the time of day activities are scheduled as well as time constraints, to individual activity patterns. Received: September 2002 / Accepted: January 2003 The author gratefully acknowledges the contributions of two anonymous reviewers, whose comments greatly improved the content of this paper     

融合高分影像和LiDAR数据的城市道路提取

为避免由于城市道路复杂及树木建筑的阴影遮挡导致从遥感影像中提取道路信息不准确的问题,本文采用高分影像和Li-DAR数据相融合的方法实现城市道路的提取,并使用一种基于最小面积外接矩形(MABR)的后处理改进方法进行完善.首先对试验区进行数据配准;然后应用FNEA算法进行图像分割,并使用随机森林分类法进行分类,将影像融合和...