Building a Low-Cost Geographic Website for Collecting Citizen Science Contributions

Parr, David A.; Scholz, Michael

doi:10.1080/23754931.2015.1014263

Cited by 4 publications

(3 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Section: Citizen Science and Flood Hazard Assessmentmentioning

confidence: 99%

“…Other aspects to consider when citizen science projects involve contributions through dedicated websites are related to its design and usability. As contributors have different levels of expertise (Newman et al, 2010), websites should be designed to ensure the ease of use to be successful (Parr & Scholz, 2015), a fact even more so for EVOs as discussed by Karpouzoglou et al, 2016. Another crucial challenge is the commitment of people to the project and over time. Studies demonstrate that engagement and motivation of contributors are necessary elements for success of citizen science projects (Eveleigh, Jennett, Blandford, Brohan, & Cox, 2014).…”

Section: Some Issues To Considermentioning

confidence: 99%

See 1 more Smart Citation

Flood hazard assessment and the role of citizen science

Frischknecht

Dao

et al. 2019

J Flood Risk Management

View full text Add to dashboard Cite

Flood hazard assessment is at the core of flood risk management. In order to develop an efficient flood hazard assessment, it is of primary importance to have a well‐defined flood scenario encompassing all processes that could occur during an event. Understanding and assessing these processes requires meteorological, topographical and land‐use data as well as historical observations. Nowadays, flood delineation is based upon hydrological and hydraulic modelling, ground data collection, and remote sensing. Despite the advantages of these tools, they also present some specific limitations, either intrinsic to the approaches or linked with constraints of the local context. With the rapid advancement of web 2.0 technologies (e.g., Flickr and Wikimapia) and the increase of the use of participatory research, citizen science has the potential to provide valuable and complementary information at all levels of flood risk management and in particular for flood hazard assessment. After reviewing the capabilities and limitations of the current tools used in flood hazard assessment, this paper demonstrates the role that citizen science can play in providing key information on factors leading to flooding and on flood hazard parameters.

show abstract

Section: Citizen Science and Flood Hazard Assessmentmentioning

confidence: 99%

Section: Some Issues To Considermentioning

confidence: 99%

Flood hazard assessment and the role of citizen science

Frischknecht

Dao

et al. 2019

J Flood Risk Management

View full text Add to dashboard Cite

show abstract

“…As shown in Table 2, the first JavaScript invocation rule is derived from the OpenLayers [52], ArcGIS API for JavaScript [53], Leaflet [54] and Mapbox.js [55], all of which are JavaScript libraries that provide support for OGC's web mapping standards [58]. The listed total of seven common functions are often directly used to invoke WMSs in a large number of geospatial web applications.…”

Section: Understanding Of Javascript Code Using Invocation Rulesmentioning

confidence: 99%

Discovering Land Cover Web Map Services from the Deep Web with JavaScript Invocation Rules

Hou

Chen

2016

IJGI

View full text Add to dashboard Cite

Automatic discovery of isolated land cover web map services (LCWMSs) can potentially help in sharing land cover data. Currently, various search engine-based and crawler-based approaches have been developed for finding services dispersed throughout the surface web. In fact, with the prevalence of geospatial web applications, a considerable number of LCWMSs are hidden in JavaScript code, which belongs to the deep web. However, discovering LCWMSs from JavaScript code remains an open challenge. This paper aims to solve this challenge by proposing a focused deep web crawler for finding more LCWMSs from deep web JavaScript code and the surface web. First, the names of a group of JavaScript links are abstracted as initial judgements. Through name matching, these judgements are utilized to judge whether or not the fetched webpages contain predefined JavaScript links that may prompt JavaScript code to invoke WMSs. Secondly, some JavaScript invocation functions and URL formats for WMS are summarized as JavaScript invocation rules from prior knowledge of how WMSs are employed and coded in JavaScript. These invocation rules are used to identify the JavaScript code for extracting candidate WMSs through rule matching. The above two operations are incorporated into a traditional focused crawling strategy situated between the tasks of fetching webpages and parsing webpages. Thirdly, LCWMSs are selected by matching services with a set of land cover keywords. Moreover, a search engine for LCWMSs is implemented that uses the focused deep web crawler to retrieve and integrate the LCWMSs it discovers. In the first experiment, eight online geospatial web applications serve as seed URLs (Uniform Resource Locators) and crawling scopes; the proposed crawler addresses only the JavaScript code in these eight applications. All 32 available WMSs hidden in JavaScript code were found using the proposed crawler, while not one WMS was discovered through the focused crawler-based approach. This result shows that the proposed crawler has the ability to discover WMSs hidden in JavaScript code. The second experiment uses 4842 seed URLs updated daily. The crawler found a total of 17,874 available WMSs, of which 11,901 were LCWMSs. Our approach discovered a greater number of services than those found using previous approaches. It indicates that the proposed crawler has a large advantage in discovering LCWMSs from the surface web and from JavaScript code. Furthermore, a simple case study demonstrates that the designed LCWMS search engine represents an important step towards realizing land cover information integration for global mapping and monitoring purposes.

show abstract

Automatic detection of urban vacant land: An open-source approach for sustainable cities

Ehlers

2022

Computers, Environment and Urban Systems

View full text Add to dashboard Cite

Building a Low-Cost Geographic Website for Collecting Citizen Science Contributions

Cited by 4 publications

References 8 publications

Flood hazard assessment and the role of citizen science

Flood hazard assessment and the role of citizen science

Discovering Land Cover Web Map Services from the Deep Web with JavaScript Invocation Rules

Automatic detection of urban vacant land: An open-source approach for sustainable cities

Contact Info

Product

Resources

About