Search Results (4)

The ability to revise texts to meet the needs and expectations of the target audience requires sustained and deliberate practice. Revision becomes more complex when working on somebody’s else text and in a second language. Against this background, we conducted an exploratory and descriptive case study qualitatively shedding light on the characteristics of the processes and the products of revision. We collected data from three graduate students revising a business text in English (their second language) and from an experienced writer/editor, native English speaker, revising the same text in his first language. Using keystroke logging, screen recording, and text analysis, we observed an alternation between revision and rewriting, as well as a combination of expert features (e.g., inclusion of reader-oriented explanations) and less expert features (e.g., fewer rounds of revision) among graduate students. There were also differences between the students and the expert in the way in which they spatially organised their tasks. We interpreted these results within the context of cognitive and sociocultural models of writing, and especially the notion of agency. Full article

Rapid population growth accelerates changes in land use and land cover (LULC), straining natural resource availability. Monitoring LULC changes is essential for managing resources and assessing climate change impacts. This study focused on extracting LULC data from 1993 to 2024 using the classification and regression tree (CART) method on the Google Earth Engine (GEE) platform in Qena Governorate, Egypt. Moreover, the cellular automata (CA) Markov model was used to anticipate the future changes in LULC for the research area in 2040 and 2050. Three multispectral satellite images—Landsat thematic mapper (TM), enhanced thematic mapper (ETM+), and operational land imager (OLI)—were analyzed and verified using the GEE code editor. The CART classifier, integrated into GEE, identified four major LULC categories: urban areas, water bodies, cultivated soils, and bare areas. From 1993 to 2008, urban areas expanded by 57 km², while bare and cultivated soils decreased by 12.4 km² and 42.7 km², respectively. Between 2008 and 2024, water bodies increased by 24.4 km², urban areas gained 24.2 km², and cultivated and bare soils declined by 22.2 km² and 26.4 km², respectively. The CA-Markov model’s thematic maps highlighted the spatial distribution of forecasted LULC changes for 2040 and 2050. The results indicated that the urban areas, agricultural land, and water bodies will all increase. However, as anticipated, the areas of bare lands shrank during the years under study. These findings provide valuable insights for decision makers, aiding in improved land-use management, strategic planning for land reclamation, and sustainable agricultural production programs. Full article

This article presents an evaluation of the ERDAS IMAGINE Spatial Model Editor from the perspective of effective cognition. Workflow models designed in Spatial Model Editor are used for the automatic processing of remote sensing data. The process steps are designed as a chain of operations in the workflow model. The functionalities of the Spatial Model Editor and the visual vocabulary are both important for users. The cognitive quality of the visual vocabulary increases the comprehension of workflows during creation and utilization. The visual vocabulary influences the user’s exploitation of workflow models. The complex Physics of Notations theory was applied to the visual vocabulary on ERDAS IMAGINE Spatial Model Editor. The results were supplemented and verified using the eye-tracking method. The evaluation of user gaze and the movement of the eyes above workflow models brought real insight into the user’s cognition of the model. The main findings are that ERDAS Spatial Model Editor mostly fulfils the requirements for effective cognition of visual vocabulary. Namely, the semantic transparency and dual coding of symbols are very high, according to the Physics of Notations theory. The semantic transparency and perceptual discriminability of the symbols are verified through eye-tracking. The eye-tracking results show that the curved connector lines adversely affect the velocity of reading and produce errors. The application of the Physics of Notations theory and the eye-tracking method provides a useful evaluation of graphical notation as well as recommendations for the user design of workflow models in their practice. Full article

Many of today’s data models for 3D applications, such as City Geography Markup Language (CityGML) or Industry Foundation Classes (IFC) encode rich semantic information in addition to the traditional geometry and materials representation. However, 3D editing techniques fall short of maintaining the semantic information across edit operations if they are not tailored to a specific data model. While semantic information is often lost during edit operations, geometry, UV mappings, and materials are usually maintained. This article presents a data model synchronization method that preserves semantic information across editing operation relying only on geometry, UV mappings, and materials. This enables easy integration of existing and future 3D editing techniques with rich data models. The method links the original data model to the edited geometry using point set registration, recovering the existing information based on spatial and UV search methods, and automatically labels the newly created geometry. An implementation of a Level of Detail 3 (LoD3) building editor for the Virtual Singapore project, based on interactive push-pull and procedural generation of façades, verified the method with 30 common editing tasks. The implementation synchronized changes in the 3D geometry with a CityGML data model and was applied to more than 100 test buildings. Full article