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Статті в журналах з теми "Crowdsourced Mapping"

Автор: Grafiati

Опубліковано: 24 лютого 2024

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1

Soney, Johns. "Crowdsourced Pothole Mapping and Route Navigation." International Journal of Wireless Communications and Network Technologies 8, no. 3 (2019): 21–24. http://dx.doi.org/10.30534/ijwcnt/2019/05832019.

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2

Dodge, Martin, and Rob Kitchin. "Crowdsourced Cartography: Mapping Experience and Knowledge." Environment and Planning A: Economy and Space 45, no. 1 (2013): 19–36. http://dx.doi.org/10.1068/a44484.

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3

Jestico, Ben, Trisalyn Nelson, and Meghan Winters. "Mapping ridership using crowdsourced cycling data." Journal of Transport Geography 52 (April 2016): 90–97. http://dx.doi.org/10.1016/j.jtrangeo.2016.03.006.

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4

Rice, Rebecca M., Ahmad O. Aburizaiza, Matthew T. Rice, and Han Qin. "Position Validation in Crowdsourced Accessibility Mapping." Cartographica: The International Journal for Geographic Information and Geovisualization 51, no. 2 (2016): 55–66. http://dx.doi.org/10.3138/cart.51.2.3143.

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5

Gkeli, Maria, and Chryssy Potsiou. "3D crowdsourced parametric cadastral mapping: Pathways integrating BIM/IFC, crowdsourced data and LADM." Land Use Policy 131 (August 2023): 106713. http://dx.doi.org/10.1016/j.landusepol.2023.106713.

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6

Groß, Simon, Benjamin Herfort, Sabrina Marx, and Alexander Zipf. "Exploring MapSwipe as a Crowdsourcing Tool for (Rapid) Damage Assessment: The Case of the 2021 Haiti Earthquake." AGILE: GIScience Series 4 (June 6, 2023): 1–11. http://dx.doi.org/10.5194/agile-giss-4-5-2023.

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Abstract. Fast and reliable geographic information is vital in disaster management. In the late 2000s, crowdsourcing emerged as a powerful method to provide this information. Base mapping through crowdsourcing is already well-established in relief workflows. However, crowdsourced post-disaster damage assessment is researched but not yet institutionalized. Based on MapSwipe, an established mobile application for crowdsourced base mapping, a damage assessment approach was developed and tested for a case study after the 2021 Haiti earthquake. First, MapSwipe’s damage mapping results are assessed

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7

McCullagh, M., and M. Jackson. "CROWDSOURCED MAPPING – LETTING AMATEURS INTO THE TEMPLE?" ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-1/W1 (May 22, 2013): 399–432. http://dx.doi.org/10.5194/isprsarchives-xl-1-w1-399-2013.

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8

Pipelidis, Georgios, Omid Moslehi Rad, Dorota Iwaszczuk, Christian Prehofer, and Urs Hugentobler. "Dynamic Vertical Mapping with Crowdsourced Smartphone Sensor Data." Sensors 18, no. 2 (2018): 480. http://dx.doi.org/10.3390/s18020480.

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9

Branion-Calles, Michael, Trisalyn Nelson, and Meghan Winters. "Comparing Crowdsourced Near-Miss and Collision Cycling Data and Official Bike Safety Reporting." Transportation Research Record: Journal of the Transportation Research Board 2662, no. 1 (2017): 1–11. http://dx.doi.org/10.3141/2662-01.

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Official sources of cyclist safety data suffer from underreporting and bias. Crowdsourced safety data have the potential to supplement official sources and to provide new data on near-miss incidents. BikeMaps.org is a global online mapping tool that allows cyclists to record the location and details of near misses and collisions they experience. However, little is known about how the characteristics of near-miss and collision events compare. Further, the question remains whether the characteristics of crowdsourced collision data are similar to those of collision data captured by official insur

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10

Lingua, Federico, Nicholas C. Coops, Valentine Lafond, Christopher Gaston, and Verena C. Griess. "Characterizing, mapping and valuing the demand for forest recreation using crowdsourced social media data." PLOS ONE 17, no. 8 (2022): e0272406. http://dx.doi.org/10.1371/journal.pone.0272406.

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Mapping and valuing of forest recreation is time-consuming and complex, hampering its inclusion in forest management plans and hence the achievement of a fully sustainable forest management. In this study, we explore the potential of crowdsourced social media data in tackling the mapping and valuing of forest recreation demand. To do so, we assess the relationships between crowdsourced social media data, acquired from over 350,000 Flickr geotagged pictures, and demand for forest recreation in British Columbia (BC) forests. We first identify temporal and spatial trends of forest recreation dema

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11

Xu, Shan, Bin Zou, Yan Lin, Xiuge Zhao, Shenxin Li, and Chenxia Hu. "Strategies of method selection for fine-scale PM<sub>2.5</sub> mapping in an intra-urban area using crowdsourced monitoring." Atmospheric Measurement Techniques 12, no. 5 (2019): 2933–48. http://dx.doi.org/10.5194/amt-12-2933-2019.

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Abstract. Fine particulate matter (PM2.5) is of great concern to the public due to its significant risk to human health. Numerous methods have been developed to estimate spatial PM2.5 concentrations in unobserved locations due to the sparse number of fixed monitoring stations. Due to an increase in low-cost sensing for air pollution monitoring, crowdsourced monitoring of exposure control has been gradually introduced into cities. However, the optimal mapping method for conventional sparse fixed measurements may not be suitable for this new high-density monitoring approach. This study presents

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12

Nelson, Trisalyn, Avipsa Roy, Colin Ferster, et al. "Generalized model for mapping bicycle ridership with crowdsourced data." Transportation Research Part C: Emerging Technologies 125 (April 2021): 102981. http://dx.doi.org/10.1016/j.trc.2021.102981.

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13

Wang, Gang, Bolun Wang, Tianyi Wang, Ana Nika, Haitao Zheng, and Ben Y. Zhao. "Ghost Riders: Sybil Attacks on Crowdsourced Mobile Mapping Services." IEEE/ACM Transactions on Networking 26, no. 3 (2018): 1123–36. http://dx.doi.org/10.1109/tnet.2018.2818073.

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14

Lee, Ju Young, Sherrie Wang, Anjuli Jain Figueroa, et al. "Mapping Sugarcane in Central India with Smartphone Crowdsourcing." Remote Sensing 14, no. 3 (2022): 703. http://dx.doi.org/10.3390/rs14030703.

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In India, the second-largest sugarcane producing country in the world, accurate mapping of sugarcane land is a key to designing targeted agricultural policies. Such a map is not available, however, as it is challenging to reliably identify sugarcane areas using remote sensing due to sugarcane’s phenological characteristics, coupled with a range of cultivation periods for different varieties. To produce a modern sugarcane map for the Bhima Basin in central India, we utilized crowdsourced data and applied supervised machine learning (neural network) and unsupervised classification methods indivi

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15

Cho, Minwoo, Kitae Kim, Soohyun Cho, Seung-Mo Cho, and Woojin Chung. "Frequent and Automatic Update of Lane-Level HD Maps with a Large Amount of Crowdsourced Data Acquired from Buses and Taxis in Seoul." Sensors 23, no. 1 (2022): 438. http://dx.doi.org/10.3390/s23010438.

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Recently, HD maps have become important parts of autonomous driving, from localization to perception and path planning. For the practical application of HD maps, it is significant to regularly update environmental changes in HD maps. Conventional approaches require expensive mobile mapping systems and considerable manual work by experts, making it difficult to achieve frequent map updates. In this paper, we show how frequent and automatic updates of lane marking in HD maps are made possible with enormous crowdsourced data. Crowdsourced data is acquired from onboard low-cost sensing devices ins

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16

Grove, Nicole Sunday. "The cartographic ambiguities of HarassMap: Crowdmapping security and sexual violence in Egypt." Security Dialogue 46, no. 4 (2015): 345–64. http://dx.doi.org/10.1177/0967010615583039.

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In December 2010, HarassMap was launched as a Cairo-based interactive online mapping interface for reporting and mapping incidents of sexual harassment anonymously and in real time, in Egypt. The project’s use of spatial information technologies for crowdmapping sexual harassment raises important questions about the use of crowdsourced mapping as a technique of global human security governance, as well as the techno-politics of interpreting and representing spaces of gendered security and insecurity in Egypt’s urban streetscape. By recoding Egypt’s urban landscape into spaces subordinated to t

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17

Ruggiano, Nicole, Tish Winton, Jane Daquin, Zhe Jiang, Monica Herzog, and Jeff Gray. "THE POTENTIAL OF CROWDSOURCED ASSET MAPPING TECHNOLOGIES FOR SUPPORTING DEMENTIA CAREGIVERS." Innovation in Aging 7, Supplement_1 (2023): 534. http://dx.doi.org/10.1093/geroni/igad104.1753.

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Abstract It is well-established that caregivers of people living with dementia (PLWD) often report having difficulty finding information about education and support that is available to them in their community. Caregiver support groups have demonstrated to be an effective approach to caregiver education through mutual support, though many caregivers are unable to participate in caregiver support groups due to time and geographic constraints. Crowdsourced technologies that rely on volunteered geographic information (VGI) are a viable way of community members to provide mutual support on a varie

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18

Darmody, Aron, Mujde Yuksel, and Meera Venkatraman. "The work of mapping and the mapping of work: prosumer roles in crowdsourced maps." Journal of Marketing Management 33, no. 13-14 (2017): 1093–119. http://dx.doi.org/10.1080/0267257x.2017.1348384.

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19

Nagaraj, Abhishek. "Does Open Data Spur Online Communities? Evidence from Crowdsourced Mapping." Academy of Management Proceedings 2017, no. 1 (2017): 13110. http://dx.doi.org/10.5465/ambpp.2017.13110abstract.

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20

Wijaya, Benny, Kun Jiang, Mengmeng Yang, Tuopu Wen, Xuewei Tang, and Diange Yang. "Crowdsourced Road Semantics Mapping Based on Pixel-Wise Confidence Level." Automotive Innovation 5, no. 1 (2022): 43–56. http://dx.doi.org/10.1007/s42154-021-00173-x.

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21

Potsiou, C., N. Doulamis, N. Bakalos, M. Gkeli, and C. Ioannidis. "INDOOR LOCALIZATION FOR 3D MOBILE CADASTRAL MAPPING USING MACHINE LEARNING TECHNIQUES." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences VI-4/W1-2020 (September 3, 2020): 159–66. http://dx.doi.org/10.5194/isprs-annals-vi-4-w1-2020-159-2020.

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Abstract. With the rapid global urbanization, several multi-dimensional complex infrastructures have emerged, introducing new challenges in the management of the vertically stratified buildings spaces. 3D indoor cadastral spaces consist a zestful research topic as their complexity and geometry alterations during time, prevents the assignment of the corresponding Rights, Restrictions and Responsibilities (RRR). In the absence of the necessary horizontal spatial data infrastructure/floor plans their determination is weak. In this paper a fit-for-purpose technical framework and a crowdsourced met

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22

Cahyono, Ari. "STUDI NAMA GEOGRAFI MELALUI LAYANAN PEMETAAN URUNDAYA DI DESA GIRIPURWO, PURWOSARI, GUNUNGKIDUL D.I. YOGYAKARTA." Jurnal SPATIAL Wahana Komunikasi dan Informasi Geografi 18, no. 2 (2018): 105–14. http://dx.doi.org/10.21009/spatial.182.04.

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A geographical name is a name that identify specific feature on the earth. That features could be a settlement, administrative region, natural feature, artificial feature, unbounded region, or virtual region. Under the Law Number 4 of 2011 concerning Geospatial Information, the geographical name is one of the layer that must appear on the base map. The acquisition of geographical names can be facilitated by crowdsourcing map that are conducted by corporations or the public. The objectives of this study are 1) to carry out an inventory of geographic names through crowdsourced maps, and 2) to ex

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23

Vahidi, Hossein, Brian Klinkenberg, Brian Johnson, L. Moskal, and Wanglin Yan. "Mapping the Individual Trees in Urban Orchards by Incorporating Volunteered Geographic Information and Very High Resolution Optical Remotely Sensed Data: A Template Matching-Based Approach." Remote Sensing 10, no. 7 (2018): 1134. http://dx.doi.org/10.3390/rs10071134.

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This paper presents a collective sensing approach that integrates imperfect Volunteered Geographic Information (VGI) obtained through Citizen Science (CS) tree mapping projects with very high resolution (VHR) optical remotely sensed data for low-cost, fine-scale, and accurate mapping of trees in urban orchards. To this end, an individual tree crown (ITC) detection technique utilizing template matching (TM) was developed for extracting urban orchard trees from VHR optical imagery. To provide the training samples for the TM algorithm, remotely sensed VGI about trees including the crowdsourced da

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24

Pajarito, Diego, and Michael Gould. "Mapping Frictions Inhibiting Bicycle Commuting." ISPRS International Journal of Geo-Information 7, no. 10 (2018): 396. http://dx.doi.org/10.3390/ijgi7100396.

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Urban cycling is a sustainable transport mode that many cities are promoting. However, few cities are taking advantage of geospatial technologies to represent and analyse cycling mobility based on the behavioural patterns and difficulties faced by cyclists. This study analyses a geospatial dataset crowdsourced by urban cyclists using an experimental, mobile geo-game. Fifty-seven participants recorded bicycle trips during one week periods in three cities. By aggregating them, we extracted not only the cyclists’ preferred streets but also the frictions faced during cycling. We successfully ident

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25

Sun, Y., A. Kruspe, L. Meng, et al. "TOWARDS LARGE-SCALE BUILDING ATTRIBUTE MAPPING USING CROWDSOURCED IMAGES: SCENE TEXT RECOGNITION ON FLICKR AND PROBLEMS TO BE SOLVED." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLVIII-1/W2-2023 (December 13, 2023): 225–32. http://dx.doi.org/10.5194/isprs-archives-xlviii-1-w2-2023-225-2023.

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Abstract. Crowdsourced platforms provide huge amounts of street-view images that contain valuable building information. This work addresses the challenges in applying Scene Text Recognition (STR) in crowdsourced street-view images for building attribute mapping. We use Flickr images, particularly examining texts on building facades. A Berlin Flickr dataset is created, and pre-trained STR models are used for text detection and recognition. Manual checking on a subset of STR-recognized images demonstrates high accuracy. We examined the correlation between STR results and building functions, and

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26

Roelandt, N., P. Aumond, and L. Moisan. "CROWDSOURCED ACOUSTIC OPEN DATA ANALYSIS WITH FOSS4G TOOLS." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLVIII-4/W1-2022 (August 6, 2022): 387–93. http://dx.doi.org/10.5194/isprs-archives-xlviii-4-w1-2022-387-2022.

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Abstract. NoiseCapture is an Android application developed by the Gustave Eiffel University and the French National Centre for Scientific Research as central element of a participatory approach to environmental noise mapping. The application is open-source, and all its data are available freely. This study presents the results of the first exploratory analysis of 3 years of data collection through the lens of sound sources. This analysis is only based on the tags given by the users and not on the sound spectrum of the measurement, which will be studied at a later stage. The first results are e

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27

Zhou, Mu, Qiao Zhang, Zengshan Tian, Yiyao Liu, and Zhenyuan Zhang. "Simultaneous pathway mapping and behavior understanding with crowdsourced sensing in WLAN environment." Ad Hoc Networks 58 (April 2017): 160–70. http://dx.doi.org/10.1016/j.adhoc.2016.09.002.

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28

Huynh, Trung Dong, Mark Ebden, Matteo Venanzi, Sarvapali Ramchurn, Stephen Roberts, and Luc Moreau. "Interpretation of Crowdsourced Activities Using Provenance Network Analysis." Proceedings of the AAAI Conference on Human Computation and Crowdsourcing 1 (November 3, 2013): 78–85. http://dx.doi.org/10.1609/hcomp.v1i1.13067.

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Understanding the dynamics of a crowdsourcing application and controlling the quality of the data it generates is challenging, partly due to the lack of tools to do so. Provenance is a domain-independent means to represent what happened in an application, which can help verify data and infer their quality. It can also reveal the processes that led to a data item and the interactions of contributors with it. Provenance patterns can manifest real-world phenomena such as a significant interest in a piece of content, providing an indication of its quality, or even issues such as undesirable intera

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29

Qin, H., A. O. Aburizaiza, R. M. Rice, F. Paez, and M. T. Rice. "OBSTACLE CHARACTERIZATION IN A GEOCROWDSOURCED ACCESSIBILITY SYSTEM." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences II-3/W5 (August 19, 2015): 179–85. http://dx.doi.org/10.5194/isprsannals-ii-3-w5-179-2015.

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Transitory obstacles – random, short-lived and unpredictable objects – are difficult to capture in any traditional mapping system, yet they have significant negative impacts on the accessibility of mobility- and visually-impaired individuals. These transitory obstacles include sidewalk obstructions, construction detours, and poor surface conditions. To identify these obstacles and assist the navigation of mobility- and visually- impaired individuals, crowdsourced mapping applications have been developed to harvest and analyze the volunteered obstacles reports from local students, faculty, staf

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30

Parés, M. E., D. Garcia, and F. Vázquez-Gallego. "MAPPING AIR QUALITY WITH A MOBILE CROWDSOURCED AIR QUALITY MONITORING SYSTEM (C-AQM)." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B4-2020 (August 25, 2020): 685–90. http://dx.doi.org/10.5194/isprs-archives-xliii-b4-2020-685-2020.

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Abstract. World cities are currently facing one of the major crisis of the last century. Some preliminary studies on COVID-19 pandemia have shown that air pollutants may have a strong impact on virus effects. Improved gas sensors and wireless communication systems open the door to the design of new air monitoring systems based on citizen science to better monitor and communicate the air quality levels. In this paper, we present the Crowdsourced Air Quality Monitoring (C-AQM) system, which relies on Air Quality Monitoring reference stations and a cluster of new low-cost and low-energy sensor no

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31

Vaz, Eric, and Jamal Jokar Arsanjani. "Crowdsourced mapping of land use in urban dense environments: An assessment of Toronto." Canadian Geographer / Le Géographe canadien 59, no. 2 (2015): 246–55. http://dx.doi.org/10.1111/cag.12170.

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32

Zhou, Mu, Qiao Zhang, Yu Wang, and Zengshan Tian. "Hotspot Ranking Based Indoor Mapping and Mobility Analysis Using Crowdsourced Wi-Fi Signal." IEEE Access 5 (2017): 3594–602. http://dx.doi.org/10.1109/access.2017.2674798.

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33

Venter, Zander S., Oscar Brousse, Igor Esau, and Fred Meier. "Hyperlocal mapping of urban air temperature using remote sensing and crowdsourced weather data." Remote Sensing of Environment 242 (June 2020): 111791. http://dx.doi.org/10.1016/j.rse.2020.111791.

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34

Créquit, Perrine, Ghizlène Mansouri, Mehdi Benchoufi, Alexandre Vivot, and Philippe Ravaud. "Mapping of Crowdsourcing in Health: Systematic Review." Journal of Medical Internet Research 20, no. 5 (2018): e187. http://dx.doi.org/10.2196/jmir.9330.

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Background Crowdsourcing involves obtaining ideas, needed services, or content by soliciting Web-based contributions from a crowd. The 4 types of crowdsourced tasks (problem solving, data processing, surveillance or monitoring, and surveying) can be applied in the 3 categories of health (promotion, research, and care). Objective This study aimed to map the different applications of crowdsourcing in health to assess the fields of health that are using crowdsourcing and the crowdsourced tasks used. We also describe the logistics of crowdsourcing and the characteristics of crowd workers. Methods

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35

Liu, L., B. Zhou, and X. Yi. "A PILOT STUDY OF URBAN POI MAPPING USING CROWDSOURCED STREET-LEVEL IMAGERY AND DEEP LEARNING." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B4-2022 (June 1, 2022): 261–66. http://dx.doi.org/10.5194/isprs-archives-xliii-b4-2022-261-2022.

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Abstract. Point-of-interest (POI) data contains rich semantic and spatial information, having a wide range of applications including land use, transport planning and driving navigation. However, urban POI mapping traditionally requires a lot of manpower and material resources, which only few institutions or enterprises can afford to. With the increasing amount of street-level imagery, it is possible to directly extract POI-related information from such data and automatically map the distribution of urban POIs. In the pilot study, we mainly focused on extracting POIs from billboards in street-l

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36

Dixon, Barnali, RebeccaA Johns, and Amada Fernandez. "The role of crowdsourced data, participatory decision-making and mapping of flood related events." Applied Geography 128 (March 2021): 102393. http://dx.doi.org/10.1016/j.apgeog.2021.102393.

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37

Brown, Greg, Clive McAlpine, Jonathan Rhodes, et al. "Assessing the validity of crowdsourced wildlife observations for conservation using public participatory mapping methods." Biological Conservation 227 (November 2018): 141–51. http://dx.doi.org/10.1016/j.biocon.2018.09.016.

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38

Lwin, May O., Santosh Vijaykumar, Owen Noel Newton Fernando, et al. "A 21st century approach to tackling dengue: Crowdsourced surveillance, predictive mapping and tailored communication." Acta Tropica 130 (February 2014): 100–107. http://dx.doi.org/10.1016/j.actatropica.2013.09.021.

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39

Huang, Xiao, Di Yang, Yaqian He, et al. "Land cover mapping via crowdsourced multi-directional views: The more directional views, the better." International Journal of Applied Earth Observation and Geoinformation 122 (August 2023): 103382. http://dx.doi.org/10.1016/j.jag.2023.103382.

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40

Cheng, Kai, Yanjun Su, Hongcan Guan, et al. "Mapping China’s planted forests using high resolution imagery and massive amounts of crowdsourced samples." ISPRS Journal of Photogrammetry and Remote Sensing 196 (February 2023): 356–71. http://dx.doi.org/10.1016/j.isprsjprs.2023.01.005.

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41

Schnebele, E., G. Cervone, and N. Waters. "Road assessment after flood events using non-authoritative data." Natural Hazards and Earth System Sciences Discussions 1, no. 4 (2013): 4155–79. http://dx.doi.org/10.5194/nhessd-1-4155-2013.

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Abstract. This research proposes a methodology that leverages non-authoritative data to augment flood extent mapping and the evaluation of transportation infrastructure. The novelty of this approach is the application of freely available, non-authoritative data and its integration with established data and methods. Crowdsourced photos and volunteered geographic data are fused together using a geostatistical interpolation to create an estimation of flood damage in New York City following Hurricane Sandy. This damage assessment is utilized to augment an authoritative storm surge map as well as t

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Schnebele, E., G. Cervone, and N. Waters. "Road assessment after flood events using non-authoritative data." Natural Hazards and Earth System Sciences 14, no. 4 (2014): 1007–15. http://dx.doi.org/10.5194/nhess-14-1007-2014.

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Abstract. This research proposes a methodology that leverages non-authoritative data to augment flood extent mapping and the evaluation of transportation infrastructure. The novelty of this approach is the application of freely available, non-authoritative data and its integration with established data and methods. Crowdsourced photos and volunteered geographic data are fused together using a geostatistical interpolation to create an estimation of flood damage in New York City following Hurricane Sandy. This damage assessment is utilized to augment an authoritative storm surge map as well as t

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Zourlidou, Stefania, Monika Sester, and Shaohan Hu. "Recognition of Intersection Traffic Regulations from Crowdsourced Data." ISPRS International Journal of Geo-Information 12, no. 1 (2022): 4. http://dx.doi.org/10.3390/ijgi12010004.

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In this paper, a new method is proposed to detect traffic regulations at intersections using GPS traces. The knowledge of traffic rules for regulated locations can help various location-based applications in the context of Smart Cities, such as the accurate estimation of travel time and fuel consumption from a starting point to a destination. Traffic regulations as map features, however, are surprisingly still largely absent from maps, although they do affect traffic flow which, in turn, affects vehicle idling time at intersections, fuel consumption, CO2 emissions, and arrival time. In additio

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Wang, Sherrie, Stefania Di Tommaso, Joey Faulkner, et al. "Mapping Crop Types in Southeast India with Smartphone Crowdsourcing and Deep Learning." Remote Sensing 12, no. 18 (2020): 2957. http://dx.doi.org/10.3390/rs12182957.

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High resolution satellite imagery and modern machine learning methods hold the potential to fill existing data gaps in where crops are grown around the world at a sub-field level. However, high resolution crop type maps have remained challenging to create in developing regions due to a lack of ground truth labels for model development. In this work, we explore the use of crowdsourced data, Sentinel-2 and DigitalGlobe imagery, and convolutional neural networks (CNNs) for crop type mapping in India. Plantix, a free app that uses image recognition to help farmers diagnose crop diseases, logged 9

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Gardner, Z., P. Mooney, S. De Sabbata, and L. Dowthwaite. "Quantifying gendered participation in OpenStreetMap: responding to theories of female (under) representation in crowdsourced mapping." GeoJournal 85, no. 6 (2019): 1603–20. http://dx.doi.org/10.1007/s10708-019-10035-z.

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Abstract This paper presents the results of an exploratory quantitative analysis of gendered contributions to the online mapping project OpenStreetMap (OSM), in which previous research has identified a strong male participation bias. On these grounds, theories of representation in volunteered geographic information (VGI) have argued that this kind of crowdsourced data fails to embody the geospatial interests of the wider community. The observed effects of the bias however, remain conspicuously absent from discourses of VGI and gender, which proceed with little sense of impact. This study addre

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Samsonov, Timofey, Anastasia Shurygina, Mikhail Varentsov, Pavel Kargashin, Yulia Yarynich, and Pavel Konstantinov. "Interactive web mapping for urban climate monitoring and research based on reference and crowdsourced observations." Abstracts of the ICA 6 (August 12, 2023): 1–2. http://dx.doi.org/10.5194/ica-abs-6-219-2023.

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Etherington, Thomas. "Mapping uncertain spatial object extents from point samples using fuzzy alpha-shapes." Journal of Spatial Information Science, no. 26 (May 17, 2023): 79–98. http://dx.doi.org/10.5311/josis.2023.26.254.

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Mapping the extent of spatial objects from point samples is a fundamental process in geographical analysis. Computational geometry methods are commonly used, and one method that has been proposed is the alpha-shape as it is insensitive to both bias and errors that are common in crowdsourced geographic data and big geographic data more generally. However, many spatial objects are uncertain in nature, with vague boundaries that are not well represented by the current use of discrete alpha-shapes. Fuzzy alpha-shapes are presented as a highly generic and adaptable methodology that can produce maps

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Karasov, Oleksandr, Stien Heremans, Mart Külvik, Artem Domnich, and Igor Chervanyov. "On How Crowdsourced Data and Landscape Organisation Metrics Can Facilitate the Mapping of Cultural Ecosystem Services: An Estonian Case Study." Land 9, no. 5 (2020): 158. http://dx.doi.org/10.3390/land9050158.

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Social media continues to grow, permanently capturing our digital footprint in the form of texts, photographs, and videos, thereby reflecting our daily lives. Therefore, recent studies are increasingly recognising passively crowdsourced geotagged photographs retrieved from location-based social media as suitable data for quantitative mapping and assessment of cultural ecosystem service (CES) flow. In this study, we attempt to improve CES mapping from geotagged photographs by combining natural language processing, i.e., topic modelling and automated machine learning classification. Our study fo

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Brovelli, M. A., and E. Guilbert. "PREFACE – ISPRS WORKSHOP ON COLLABORATIVE CROWDSOURCED CLOUD MAPPING AND GEOSPATIAL BIG DATA (C3M&GBD 2019)." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W13 (June 5, 2019): 1493–94. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w13-1493-2019.

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Mascitelli, A., M. Ravanelli, S. Mattoccia, C. Berardocco, and A. Mazzoni. "A COMPLETE FOS APPROACH FOR INDOOR CROWDSOURCED MAPPING: CASE STUDY ON SAPIENZA UNIVERSITY OF ROME FACULTIES." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B4-2020 (August 25, 2020): 361–65. http://dx.doi.org/10.5194/isprs-archives-xliii-b4-2020-361-2020.

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Abstract. Indoor mapping is an essential process in several applications such as the visualization of space and its utilization, security and resource planning, emergency planning and location-based alerts and, last but not least, indoor navigation. In this work, a completely free and open-source (FOS) approach to map indoor environments, and to navigate through them, is presented. Our tests were carried out within Sapienza University of Rome public buildings; in detail, Letters and Philosophy faculty and Engineering faculty indoor environments were mapped. To reach this goal, only open source

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