\"A complete statistical characterization of radar-rainfall uncertainties must include the biases (e.g., [43], [4], [41], [13] and [7]), the error variance (e.g., [11], [3] and [10]), conditional distributions of the errors [16], and a description of the error dependences in space and time. Because correlation functions are simple expressions of these spatiotemporal error dependences, they provide a good starting point.\"
\nClearly the transit people didn't get this memo!
", "tags": [], "relations": {}, "dateAdded": "2016-07-14T22:33:54Z", "dateModified": "2016-07-14T22:34:11Z" } }, { "key": "8T8FM868", "version": 17, "library": { "type": "group", "id": 583331, "name": "Orca-DSSG2016", "links": { "alternate": { "href": "https://www.zotero.org/groups/orca-dssg2016", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/583331/items/8T8FM868", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/orca-dssg2016/items/8T8FM868", "type": "text/html" }, "up": { "href": "https://api.zotero.org/groups/583331/items/PFRMDVXI", "type": "application/json" } }, "meta": { "createdByUser": { "id": 201889, "username": "shwang11", "name": "Sean Wang", "links": { "alternate": { "href": "https://www.zotero.org/shwang11", "type": "text/html" } } }, "numChildren": 0 }, "data": { "key": "8T8FM868", "version": 17, "parentItem": "PFRMDVXI", "itemType": "note", "note": "This one joined boarding card data with APC-VL
\np. 147 - \"Verification of Outputs by Joining AFC with APC-VL Data\"
", "tags": [], "relations": {}, "dateAdded": "2016-07-11T23:56:40Z", "dateModified": "2016-07-11T23:57:11Z" } }, { "key": "PFRMDVXI", "version": 16, "library": { "type": "group", "id": 583331, "name": "Orca-DSSG2016", "links": { "alternate": { "href": "https://www.zotero.org/groups/orca-dssg2016", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/583331/items/PFRMDVXI", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/orca-dssg2016/items/PFRMDVXI", "type": "text/html" } }, "meta": { "createdByUser": { "id": 201889, "username": "shwang11", "name": "Sean Wang", "links": { "alternate": { "href": "https://www.zotero.org/shwang11", "type": "text/html" } } }, "creatorSummary": "Nassir et al.", "parsedDate": "2011-12-01", "numChildren": 1 }, "data": { "key": "PFRMDVXI", "version": 16, "itemType": "journalArticle", "title": "Transit Stop-Level Origin-Destination Estimation Through Use of Transit Schedule and Automated Data Collection System", "creators": [ { "creatorType": "author", "firstName": "Neema", "lastName": "Nassir" }, { "creatorType": "author", "firstName": "Alireza", "lastName": "Khani" }, { "creatorType": "author", "firstName": "Sang", "lastName": "Lee" }, { "creatorType": "author", "firstName": "Hyunsoo", "lastName": "Noh" }, { "creatorType": "author", "firstName": "Mark", "lastName": "Hickman" } ], "abstractNote": "As fare and data collection technology has developed, the resolution of collected data has reached the level of the individual traveler in investigations of transit passenger behavior. This paper investigates the use of these data to estimate passenger origins and destinations at the level of individual stops. Because of a lack of information from the fare collection system, researchers still need some estimate of passengers' alighting stops to complete each passenger trip chain on a specific day. Automated fare collection (AFC) and automated vehicle location (AVL) systems are the inputs to the estimation. Instead of typical AVL data, the paper proposes two models to estimate the alighting stop; both consider passenger trip chaining by using AFC data, transit schedule data (Google's General Transit Feed Specification), and automated passenger counter (APC) data. The paper validates the model by comparing the output to APC data with vehicle location data (APC-VL) and performs sensitivity analyses on several parameters in the models. To detect transfer trips, the new models propose a submodel that takes into account the effect of service headway in addition to some typical transfer time thresholds. Another contribution of this study is the relative relaxation of the search in finding the boarding stops, which enables the alternative algorithm to detect and fix possible errors in identification of the boarding stop for a transaction. As a result, the paper provides algorithms for the proposed models and sensitivity analysis for several predefined scenarios. The results are based on data and observed bus passenger behavior in the Minneapolis-Saint Paul, Minnesota, area.", "publicationTitle": "Transportation Research Record: Journal of the Transportation Research Board", "publisher": "", "place": "", "date": "December 1, 2011", "volume": "2263", "issue": "", "section": "", "partNumber": "", "partTitle": "", "pages": "140-150", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "Transportation Research Record: Journal of the Transportation Research Board", "DOI": "10.3141/2263-16", "citationKey": "", "url": "http://trrjournalonline.trb.org/doi/abs/10.3141/2263-16", "accessDate": "2016-07-11T23:56:34Z", "PMID": "", "PMCID": "", "ISSN": "0361-1981", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "", "libraryCatalog": "trrjournalonline.trb.org (Atypon)", "callNumber": "", "rights": "", "extra": "", "tags": [], "collections": [], "relations": {}, "dateAdded": "2016-07-11T23:56:34Z", "dateModified": "2016-07-11T23:56:34Z" } }, { "key": "3HJBK4ZK", "version": 15, "library": { "type": "group", "id": 583331, "name": "Orca-DSSG2016", "links": { "alternate": { "href": "https://www.zotero.org/groups/orca-dssg2016", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/583331/items/3HJBK4ZK", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/orca-dssg2016/items/3HJBK4ZK", "type": "text/html" }, "up": { "href": "https://api.zotero.org/groups/583331/items/PTZRF9I2", "type": "application/json" } }, "meta": { "createdByUser": { "id": 201889, "username": "shwang11", "name": "Sean Wang", "links": { "alternate": { "href": "https://www.zotero.org/shwang11", "type": "text/html" } } } }, "data": { "key": "3HJBK4ZK", "version": 15, "parentItem": "PTZRF9I2", "itemType": "attachment", "linkMode": "imported_url", "title": "", "accessDate": "2016-07-11T23:55:34Z", "url": "http://trrjournalonline.trb.org/doi/pdf/10.3141/2263-16", "note": "", "contentType": "text/html", "charset": "utf-8", "filename": "2263-16.html", "md5": "99070be59eb665261218aa268d2eb3ec", "mtime": 1468281333000, "tags": [], "relations": {}, "dateAdded": "2016-07-11T23:55:34Z", "dateModified": "2016-07-11T23:55:34Z" } }, { "key": "T2GAAFIM", "version": 13, "library": { "type": "group", "id": 583331, "name": "Orca-DSSG2016", "links": { "alternate": { "href": "https://www.zotero.org/groups/orca-dssg2016", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/583331/items/T2GAAFIM", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/orca-dssg2016/items/T2GAAFIM", "type": "text/html" }, "up": { "href": "https://api.zotero.org/groups/583331/items/4W6JTBXC", "type": "application/json" } }, "meta": { "createdByUser": { "id": 201889, "username": "shwang11", "name": "Sean Wang", "links": { "alternate": { "href": "https://www.zotero.org/shwang11", "type": "text/html" } } }, "numChildren": 0 }, "data": { "key": "T2GAAFIM", "version": 13, "parentItem": "4W6JTBXC", "itemType": "note", "note": "Bias estimates parallel to our project
\nDirect-bias estimates: ORCA boardings := land gauges; APC := satellites
\nIndirect-bias estimates: Since we can analyze the patterns 15% APC deployed by KCM, we can then copy their method (\"... satellites tend to have different biases\")
", "tags": [], "relations": {}, "dateAdded": "2016-06-30T22:15:23Z", "dateModified": "2016-07-07T18:45:56Z" } }, { "key": "Q9E9FR8Z", "version": 12, "library": { "type": "group", "id": 583331, "name": "Orca-DSSG2016", "links": { "alternate": { "href": "https://www.zotero.org/groups/orca-dssg2016", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/583331/items/Q9E9FR8Z", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/orca-dssg2016/items/Q9E9FR8Z", "type": "text/html" } }, "meta": { "createdByUser": { "id": 201889, "username": "shwang11", "name": "Sean Wang", "links": { "alternate": { "href": "https://www.zotero.org/shwang11", "type": "text/html" } } }, "creatorSummary": "Pelletier et al.", "parsedDate": "2011-08", "numChildren": 0 }, "data": { "key": "Q9E9FR8Z", "version": 12, "itemType": "journalArticle", "title": "Smart card data use in public transit: A literature review", "creators": [ { "creatorType": "author", "firstName": "Marie-Pier", "lastName": "Pelletier" }, { "creatorType": "author", "firstName": "Martin", "lastName": "Trépanier" }, { "creatorType": "author", "firstName": "Catherine", "lastName": "Morency" } ], "abstractNote": "Smart card automated fare collection systems are being used more and more by public transit agencies. While their main purpose is to collect revenue, they also produce large quantities of very detailed data on onboard transactions. These data can be very useful to transit planners, from the day-to-day operation of the transit system to the strategic long-term planning of the network. This review covers several aspects of smart card data use in the public transit context. First, the technologies are presented: the hardware and information systems required to operate these tools; and privacy concerns and legal issues related to the dissemination of smart card data, data storage, and encryption are addressed. Then, the various uses of the data at three levels of management are described: strategic (long-term planning), tactical (service adjustments and network development), and operational (ridership statistics and performance indicators). Also reported are smart card commercialization experiments conducted all over the world. Finally, the most promising research avenues for smart card data in this field are presented; for example, comparison of planned and implemented schedules, systematic schedule adjustments, and the survival models applied to ridership.", "publicationTitle": "Transportation Research Part C: Emerging Technologies", "publisher": "", "place": "", "date": "August 2011", "volume": "19", "issue": "4", "section": "", "partNumber": "", "partTitle": "", "pages": "557-568", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "Transportation Research Part C: Emerging Technologies", "DOI": "10.1016/j.trc.2010.12.003", "citationKey": "", "url": "http://www.sciencedirect.com/science/article/pii/S0968090X1000166X", "accessDate": "2016-07-06T21:02:29Z", "PMID": "", "PMCID": "", "ISSN": "0968-090X", "archive": "", "archiveLocation": "", "shortTitle": "Smart card data use in public transit", "language": "", "libraryCatalog": "ScienceDirect", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "Fare collection", "type": 1 }, { "tag": "Intelligent transportation systems", "type": 1 }, { "tag": "Public transportation", "type": 1 }, { "tag": "Smart card", "type": 1 }, { "tag": "Transit planning", "type": 1 }, { "tag": "Transportation demand", "type": 1 } ], "collections": [], "relations": {}, "dateAdded": "2016-07-06T21:02:29Z", "dateModified": "2016-07-06T21:02:29Z" } }, { "key": "PV7XEVE4", "version": 11, "library": { "type": "group", "id": 583331, "name": "Orca-DSSG2016", "links": { "alternate": { "href": "https://www.zotero.org/groups/orca-dssg2016", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/583331/items/PV7XEVE4", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/orca-dssg2016/items/PV7XEVE4", "type": "text/html" } }, "meta": { "createdByUser": { "id": 201889, "username": "shwang11", "name": "Sean Wang", "links": { "alternate": { "href": "https://www.zotero.org/shwang11", "type": "text/html" } } }, "creatorSummary": "Ciach and Krajewski", "parsedDate": "1999-02-24", "numChildren": 0 }, "data": { "key": "PV7XEVE4", "version": 11, "itemType": "journalArticle", "title": "On the estimation of radar rainfall error variance", "creators": [ { "creatorType": "author", "firstName": "Grzegorz J.", "lastName": "Ciach" }, { "creatorType": "author", "firstName": "Witold F.", "lastName": "Krajewski" } ], "abstractNote": "One of the major problems in radar rainfall (RR) estimation is the lack of accurate reference data on area-averaged rainfall. Radar–raingauge (R–G) comparisons are commonly used to assess and to validate the radar algorithms, but large differences of the spatial resolution between raingauge and radar measurements prevent any straightforward interpretation of the results. We assume that the R–G difference variance can be partitioned into the error of the radar area-averaged rainfall estimate, and the area-point background originating from the resolution difference. A robust procedure to decompose these components, named the error separation method (ESM), is proposed, discussed, and demonstrated. If applied to a sufficiently large sample, it allows the estimation of the radar error part and description of the uncertainties of hydrological radar products in rigorous statistical terms. An extensive data set is used to illustrate the ESM application. Proportion of the error components in the R–G difference variance is studied as a function of rainfall accumulation time. The intervals from 5 min through 4 days are considered, and the radar grid resolution of 4 × 4 km is assumed. The results show that the area-point component is a dominant part of the R–G difference at short time scales, and remains significant even for the 4-day accumulations.", "publicationTitle": "Advances in Water Resources", "publisher": "", "place": "", "date": "February 24, 1999", "volume": "22", "issue": "6", "section": "", "partNumber": "", "partTitle": "", "pages": "585-595", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "Advances in Water Resources", "DOI": "10.1016/S0309-1708(98)00043-8", "citationKey": "", "url": "http://www.sciencedirect.com/science/article/pii/S0309170898000438", "accessDate": "2016-06-30T22:21:11Z", "PMID": "", "PMCID": "", "ISSN": "0309-1708", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "", "libraryCatalog": "ScienceDirect", "callNumber": "", "rights": "", "extra": "", "tags": [], "collections": [ "78SIZHUB" ], "relations": {}, "dateAdded": "2016-06-30T22:21:11Z", "dateModified": "2016-06-30T22:21:11Z" } }, { "key": "WC2XPA3Z", "version": 11, "library": { "type": "group", "id": 583331, "name": "Orca-DSSG2016", "links": { "alternate": { "href": "https://www.zotero.org/groups/orca-dssg2016", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/583331/items/WC2XPA3Z", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/orca-dssg2016/items/WC2XPA3Z", "type": "text/html" } }, "meta": { "createdByUser": { "id": 201889, "username": "shwang11", "name": "Sean Wang", "links": { "alternate": { "href": "https://www.zotero.org/shwang11", "type": "text/html" } } }, "creatorSummary": "Mandapaka et al.", "parsedDate": "2009-07", "numChildren": 1 }, "data": { "key": "WC2XPA3Z", "version": 11, "itemType": "journalArticle", "title": "Estimation of radar-rainfall error spatial correlation", "creators": [ { "creatorType": "author", "firstName": "Pradeep V.", "lastName": "Mandapaka" }, { "creatorType": "author", "firstName": "Witold F.", "lastName": "Krajewski" }, { "creatorType": "author", "firstName": "Grzegorz J.", "lastName": "Ciach" }, { "creatorType": "author", "firstName": "Gabriele", "lastName": "Villarini" }, { "creatorType": "author", "firstName": "James A.", "lastName": "Smith" } ], "abstractNote": "The study presents a theoretical framework for estimating the radar-rainfall error spatial correlation (ESC) using data from relatively dense rain gauge networks. The error is defined as the difference between the radar estimate and the corresponding true areal rainfall. The method is analogous to the error variance separation that corrects the error variance of a radar-rainfall product for gauge representativeness errors. The study demonstrates the necessity to consider the area–point uncertainties while estimating the spatial correlation structure in the radar-rainfall errors. To validate the method, the authors conduct a Monte Carlo simulation experiment with synthetic fields with known error spatial correlation structure. These tests reveal that the proposed method, which accounts for the area–point distortions in the estimation of radar-rainfall ESC, performs very effectively. The authors then apply the method to estimate the ESC of the National Weather Service’s standard hourly radar-rainfall products, known as digital precipitation arrays (DPA). Data from the Oklahoma Micronet rain gauge network (with the grid step of about 5 km) are used as the ground reference for the DPAs. This application shows that the radar-rainfall errors are spatially correlated with a correlation distance of about 20 km. The results also demonstrate that the spatial correlations of radar–gauge differences are considerably underestimated, especially at small distances, as the area–point uncertainties are ignored.", "publicationTitle": "Advances in Water Resources", "publisher": "", "place": "", "date": "July 2009", "volume": "32", "issue": "7", "section": "", "partNumber": "", "partTitle": "", "pages": "1020-1030", "series": "Weather Radar and Hydrology", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "Advances in Water Resources", "DOI": "10.1016/j.advwatres.2008.08.014", "citationKey": "", "url": "http://www.sciencedirect.com/science/article/pii/S0309170808001486", "accessDate": "2016-06-30T22:20:58Z", "PMID": "", "PMCID": "", "ISSN": "0309-1708", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "", "libraryCatalog": "ScienceDirect", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "Error structure", "type": 1 }, { "tag": "Oklahoma Micronet", "type": 1 }, { "tag": "Radar-rainfall", "type": 1 } ], "collections": [ "78SIZHUB" ], "relations": {}, "dateAdded": "2016-06-30T22:20:58Z", "dateModified": "2016-06-30T22:20:58Z" } }, { "key": "C9UDP5IU", "version": 9, "library": { "type": "group", "id": 583331, "name": "Orca-DSSG2016", "links": { "alternate": { "href": "https://www.zotero.org/groups/orca-dssg2016", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/583331/items/C9UDP5IU", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/orca-dssg2016/items/C9UDP5IU", "type": "text/html" } }, "meta": { "createdByUser": { "id": 201889, "username": "shwang11", "name": "Sean Wang", "links": { "alternate": { "href": "https://www.zotero.org/shwang11", "type": "text/html" } } }, "creatorSummary": "Chakrabarti", "parsedDate": "2015-10", "numChildren": 0 }, "data": { "key": "C9UDP5IU", "version": 9, "itemType": "journalArticle", "title": "The demand for reliable transit service: New evidence using stop level data from the Los Angeles Metro bus system", "creators": [ { "creatorType": "author", "firstName": "Sandip", "lastName": "Chakrabarti" } ], "abstractNote": "This study explores the role of service reliability in determining bus transit ridership. Using stop level service supply, demand, and performance data from the Los Angeles Metro bus system, I investigate whether reliability of a directional line serving a stop influences the number of passengers boarding the line at that stop, controlling for various other established factors affecting demand. This cross-sectional analysis of the variation in line boardings across about 1300 sample schedule time point bus stops served by about 300 directional bus lines over a six-month period uses a historical archive of real-time geo-referenced vehicle location data, and focuses on five different time periods, peaks and off-peaks, of a typical weekday. By evaluating two measures that capture different dimensions of bus service reliability, and by estimating a series of regression models, I find systematic evidence that higher average service punctuality (or schedule adherence) and lower variation in schedule deviation over time are associated with greater ridership, all else equal, particularly during the peak periods. This study also provides first empirical evidence that the effect of reliability on peak-period ridership is moderated by headway. The demand for reliability seems to be higher for lines with relatively longer headways. The findings indicate that service reliability influences transit mode choice and/or line/route selection, and suggest that system-wide ridership gains can be expected from reliability improvements. From an urban planning perspective, this study provides more evidence that good service quality can effectively compliment transformations in the urban fabric brought about by coordinated land use — transit plans to promote transit use.", "publicationTitle": "Journal of Transport Geography", "publisher": "", "place": "", "date": "October 2015", "volume": "48", "issue": "", "section": "", "partNumber": "", "partTitle": "", "pages": "154-164", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "Journal of Transport Geography", "DOI": "10.1016/j.jtrangeo.2015.09.006", "citationKey": "", "url": "http://www.sciencedirect.com/science/article/pii/S0966692315001696", "accessDate": "2016-06-30T22:19:59Z", "PMID": "", "PMCID": "", "ISSN": "0966-6923", "archive": "", "archiveLocation": "", "shortTitle": "The demand for reliable transit service", "language": "", "libraryCatalog": "ScienceDirect", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "On-time performance", "type": 1 }, { "tag": "Public transit policy", "type": 1 }, { "tag": "Ridership", "type": 1 }, { "tag": "Scheduling", "type": 1 }, { "tag": "Service reliability", "type": 1 } ], "collections": [], "relations": {}, "dateAdded": "2016-06-30T22:19:59Z", "dateModified": "2016-06-30T22:19:59Z" } }, { "key": "XQP8Z6JP", "version": 8, "library": { "type": "group", "id": 583331, "name": "Orca-DSSG2016", "links": { "alternate": { "href": "https://www.zotero.org/groups/orca-dssg2016", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/583331/items/XQP8Z6JP", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/orca-dssg2016/items/XQP8Z6JP", "type": "text/html" }, "up": { "href": "https://api.zotero.org/groups/583331/items/K4739RGN", "type": "application/json" } }, "meta": { "createdByUser": { "id": 201889, "username": "shwang11", "name": "Sean Wang", "links": { "alternate": { "href": "https://www.zotero.org/shwang11", "type": "text/html" } } }, "numChildren": 0 }, "data": { "key": "XQP8Z6JP", "version": 8, "parentItem": "K4739RGN", "itemType": "note", "note": "Lit review section references other studies that joined boarding data with AVL and/or APC. Check those out to see if they include bias estimates.
", "tags": [], "relations": {}, "dateAdded": "2016-06-30T22:18:53Z", "dateModified": "2016-06-30T22:19:37Z" } }, { "key": "K4739RGN", "version": 7, "library": { "type": "group", "id": 583331, "name": "Orca-DSSG2016", "links": { "alternate": { "href": "https://www.zotero.org/groups/orca-dssg2016", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/583331/items/K4739RGN", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/orca-dssg2016/items/K4739RGN", "type": "text/html" } }, "meta": { "createdByUser": { "id": 201889, "username": "shwang11", "name": "Sean Wang", "links": { "alternate": { "href": "https://www.zotero.org/shwang11", "type": "text/html" } } }, "creatorSummary": "Tao et al.", "parsedDate": "2014-12", "numChildren": 1 }, "data": { "key": "K4739RGN", "version": 7, "itemType": "journalArticle", "title": "Examining the spatial–temporal dynamics of bus passenger travel behaviour using smart card data and the flow-comap", "creators": [ { "creatorType": "author", "firstName": "Sui", "lastName": "Tao" }, { "creatorType": "author", "firstName": "David", "lastName": "Rohde" }, { "creatorType": "author", "firstName": "Jonathan", "lastName": "Corcoran" } ], "abstractNote": "Over the past two decades, smart card data have received increasing interest from transport researchers as a new source of data for travel behaviour investigation. Collected by smart card systems, smart card data surpass traditional travel survey data in providing more comprehensive spatial–temporal information about urban public transport-based (UPT) trips. However, the utility of smart card data has arguably yet to be exploited fully in terms of extracting and exploring the spatial–temporal dynamics of UPT passenger travel behaviour. To advance previous work in this area, this paper demonstrates a multi-step methodology in order to render more insightful spatial–temporal patterns of UPT passenger travel behaviour. Drawing on the Brisbane, Australia, bus network as the case study, a smart card dataset was first processed in combination with General Transit Specification Feed (GTFS) data to reconstruct travel trajectories of bus passengers at bus stop level of spatial granularity. By applying geographical information system-based (GIS) techniques, this dataset was used to create flow-comaps to visualise the aggregate flow patterns at a network level. The flow-comaps uncovered the major pathways of bus passengers and its variations over a one-day period. The differences within the flow-comaps were also quantified to produce weighted flow-comaps that highlighted the major temporal changes of passenger flow patterns along a number of stop-to-stop linkages of the bus network. The proposed methodology visually unveiled the spatial–temporal travel behaviour dynamics of UPT passengers and, in doing so, showed the potential to contribute to a new evidence base with the capacity to inform local public transport policy.", "publicationTitle": "Journal of Transport Geography", "publisher": "", "place": "", "date": "December 2014", "volume": "41", "issue": "", "section": "", "partNumber": "", "partTitle": "", "pages": "21-36", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "Journal of Transport Geography", "DOI": "10.1016/j.jtrangeo.2014.08.006", "citationKey": "", "url": "http://www.sciencedirect.com/science/article/pii/S0966692314001689", "accessDate": "2016-06-30T22:18:47Z", "PMID": "", "PMCID": "", "ISSN": "0966-6923", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "", "libraryCatalog": "ScienceDirect", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "Flow-comap", "type": 1 }, { "tag": "Passenger travel behaviour", "type": 1 }, { "tag": "Smart card data", "type": 1 }, { "tag": "Urban public transport system", "type": 1 } ], "collections": [], "relations": {}, "dateAdded": "2016-06-30T22:18:47Z", "dateModified": "2016-06-30T22:18:47Z" } }, { "key": "4W6JTBXC", "version": 2, "library": { "type": "group", "id": 583331, "name": "Orca-DSSG2016", "links": { "alternate": { "href": "https://www.zotero.org/groups/orca-dssg2016", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/583331/items/4W6JTBXC", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/orca-dssg2016/items/4W6JTBXC", "type": "text/html" } }, "meta": { "createdByUser": { "id": 201889, "username": "shwang11", "name": "Sean Wang", "links": { "alternate": { "href": "https://www.zotero.org/shwang11", "type": "text/html" } } }, "creatorSummary": "Smith et al.", "parsedDate": "2006-10-01", "numChildren": 1 }, "data": { "key": "4W6JTBXC", "version": 2, "itemType": "journalArticle", "title": "Estimating Bias of Satellite-Based Precipitation Estimates", "creators": [ { "creatorType": "author", "firstName": "Thomas M.", "lastName": "Smith" }, { "creatorType": "author", "firstName": "Phillip A.", "lastName": "Arkin" }, { "creatorType": "author", "firstName": "John J.", "lastName": "Bates" }, { "creatorType": "author", "firstName": "George J.", "lastName": "Huffman" } ], "abstractNote": "Systematic biases in satellite-based precipitation estimates can be the dominant component of their uncertainty. These biases may not be reduced by averaging, which makes their evaluation particularly important. Described here are several methods of evaluating the biases and their characteristics. Methods are developed and tested using monthly average precipitation estimates from several satellites. Direct estimates of bias are obtained from analysis of satellite–gauge estimates, and they indicate the general bias patterns and magnitudes over land. Direct estimates cannot be computed over the oceans, so indirect-bias estimates based on ensembles of satellite and gauge estimates are also developed. These indirect estimates are consistent with direct estimates in locations where they can be compared, while giving near-global coverage. For both bias estimates computed here, the bias uncertainty is higher than nonsystematic error estimates, caused by random or sampling errors and which have been previously reported by others for satellite estimates. Because of their greater spatial coverage, indirect-bias estimates are preferable for bias adjustment of satellite-based precipitation. The adjustment methods developed reduce the bias associated with each satellite while estimating the remaining bias uncertainty for the satellite. By adjusting all satellites to a consistent base, the bias adjustments also minimize artificial climate-scale variations in analyses that could be caused by the addition or removal of satellite products as their availability changes.", "publicationTitle": "Journal of Hydrometeorology", "publisher": "", "place": "", "date": "October 1, 2006", "volume": "7", "issue": "5", "section": "", "partNumber": "", "partTitle": "", "pages": "841-856", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "J. Hydrometeor", "DOI": "10.1175/JHM524.1", "citationKey": "", "url": "http://journals.ametsoc.org/doi/full/10.1175/JHM524.1", "accessDate": "2016-06-30T22:15:16Z", "PMID": "", "PMCID": "", "ISSN": "1525-755X", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "", "libraryCatalog": "journals.ametsoc.org (Atypon)", "callNumber": "", "rights": "", "extra": "", "tags": [], "collections": [], "relations": {}, "dateAdded": "2016-06-30T22:15:16Z", "dateModified": "2016-06-30T22:15:16Z" } } ]