Customizable process design for collaborative geographic analysis

Ma, Zaiyang; Chen, Min; Zheng, Zhong; Yue, Songshan; Zhu, Zuo-Nong; Zhang, Beichen; Wang, Jin; Zhang, Fengyuan; Wen, Yongning; Lv, Guonian

doi:10.1080/15481603.2022.2082751

Cited by 16 publications

(3 citation statements)

References 67 publications

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“…For example, collaborative geographic analysis could be represented via a set of child activities that are split between multiple participants but depend on a parent activity. It has been shown that such hierarchical models are useful for complex applications like real‐time collaboration of experts for designing a geospatial process (Ma et al, 2022). The pattern mining approach evaluated in this article may be a first step toward generating such models and update the WebGIS' objectives, operators, and operands (Table 1).…”

Section: Discussionmentioning

confidence: 99%

Interaction pattern analysis for WebGIS usability evaluation

Unrau

Kudekar

Kray

2022

Transactions in GIS

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Web-based geographic information systems (WebGIS) are increasingly common and accessed by various types of users.However, evaluating their usability is hard, as interactions with the map and provided functionality can be complex.We present a novel approach to remotely assess WebGIS usability and identify design flaws by logging user interface (UI) interactions and applying pattern mining techniques to the resulting datasets. We conducted an online user study with 40 participants in a realistic WebGIS scenario to validate the approach. The results show that applying this concept can provide insights into user strategies and can reveal usability issues, which can help to improve UIs for WebGIS. Designers can use the methods presented here to assess the usability of their WebGIS rapidly and at scale without carrying out expensive and lengthy in-person user studies. This article also contributes to a better understanding of the challenges and limitations of remotely conducted usability evaluations for WebGIS.

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Section: Discussionmentioning

confidence: 99%

Interaction pattern analysis for WebGIS usability evaluation

Unrau

Kudekar

Kray

2022

Transactions in GIS

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“…For this reason, when constructing a collaborative online remote sensing analysis process, it is imperative to take into account the structure of the collaborative process, as well as the activities undertaken by remote sensing analysts and remote sensing image processors during the analysis stage. For the structure of the collaborative process, certain studies have shown that hierarchical and progressive structures are suitable [22]. Furthermore, it has been shown that collaborative geographic analysis activities can be classified into four categories based on their purpose: awareness-related activities, data-related activities, model-related activities, and application-related activities [43,44].…”

Section: A Conceptual Modeling Framework For Collaborative Online Rem...mentioning

confidence: 99%

A Novel Standardized Collaborative Online Model for Processing and Analyzing Remotely Sensed Images in Geographic Problems

Zhang,

Wu,

Zhang

et al. 2023

Electronics

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In recent years, remote sensing image processing technology has developed rapidly, and the variety of remote sensing images has increased. Solving a geographic problem often requires multiple remote sensing images to be used together. For an image processing analyst, it is difficult to become proficient in the image processing of multiple types of remote sensing images. Therefore, it is necessary to have multiple image processing analysts collaborate to solve geographic problems. However, as a result of the naturally large volumes of data and the computer resources they consume for analysis, remote sensing images present a barrier in the collaboration of multidisciplinary remote sensing undertakings and analysts. As a result, during the development of the collaborative analysis process, it is necessary to achieve the online processing and analysis of remote sensing images, as well as to standardize the online remote sensing image collaborative analysis process. To address the above issues, a hierarchical collaborative online processing and analysis framework was developed in this paper. This framework defined a clear collaborative analysis structure, and it identifies what kinds of online image processing and analysis activities participants can engage in to successfully conduct collaborative processes. In addition, a collaborative process construction model and an online remote sensing image processing analysis model were developed to assist participants in creating a standard collaborative online image processing and analysis process. In order to demonstrate the feasibility and effectiveness of the framework and model, this paper developed a collaborative online post-disaster assessment process that utilizes radar images and optical remote sensing images for a real forest fire event. This process was based on the BPMN2.0 and OGC dual standards. Based on the results, the proposed framework provides a hierarchical collaborative remote sensing image processing and analysis process with well-defined stages and activities to guide the participants’ mutual collaboration. Additionally, the proposed model can help participants to develop a standardized collaborative online image processing process in terms of process structure and information interactions.

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“…Geosquare provides a cloud-based framework for building, executing, and sharing collaborative models [20]. Ma et al [21] designed a customizable process expression model and proposed a corresponding process customization method for collaborative geographic analysis. These efforts fully discuss the collaborative patterns for geospatial services and explore novel methods for geospatial applications.…”

Section: Introductionmentioning

confidence: 99%

A Novel and Extensible Remote Sensing Collaboration Platform: Architecture Design and Prototype Implementation

Gao,

Chen,

Chen

et al. 2024

IJGI

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Geospatial data, especially remote sensing (RS) data, are of significant importance for public services and production activities. Expertise is critical in processing raw data, generating geospatial information, and acquiring domain knowledge and other remote sensing applications. However, existing geospatial service platforms are more oriented towards the professional users in the implementation process and final application. Building appropriate geographic applications for non-professionals remains a challenge. In this study, a geospatial data service architecture is designed that links desktop geographic information system (GIS) software and cloud-based platforms to construct an efficient user collaboration platform. Based on the scalability of the platform, four web apps with different themes are developed. Data in the fields of ecology, oceanography, and geology are uploaded to the platform by the users. In this pilot phase, the gap between non-specialized users and experts is successfully bridged, demonstrating the platform’s powerful interactivity and visualization. The paper finally evaluates the capability of building spatial data infrastructures (SDI) based on GeoNode and discusses the current limitations. The support for three-dimensional data, the improvement of metadata creation and management, and the fostering of an open geo-community are the next steps.

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Customizable process design for collaborative geographic analysis

Cited by 16 publications

References 67 publications

Interaction pattern analysis for WebGIS usability evaluation

Interaction pattern analysis for WebGIS usability evaluation

A Novel Standardized Collaborative Online Model for Processing and Analyzing Remotely Sensed Images in Geographic Problems

A Novel and Extensible Remote Sensing Collaboration Platform: Architecture Design and Prototype Implementation

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