Sketch Map Research Articles

Recall of nature hiking landmarks on account of sketch maps

Recall of nature hiking landmarks on account of sketch maps

PRN: progressive reasoning network and its image completion applications

Ancient murals embody profound historical, cultural, scientific, and artistic values, yet many are afflicted with challenges such as pigment shedding or missing parts. While deep learning-based completion techniques have yielded remarkable results in restoring natural images, their application to damaged murals has been unsatisfactory due to data shifts and limited modeling efficacy. This paper proposes a novel progressive reasoning network designed specifically for mural image completion, inspired by the mural painting process. The proposed network comprises three key modules: a luminance reasoning module, a sketch reasoning module, and a color fusion module. The first two modules are based on the double-codec framework, designed to infer missing areas’ luminance and sketch information. The final module then utilizes a paired-associate learning approach to reconstruct the color image. This network utilizes two parallel, complementary pathways to estimate the luminance and sketch maps of a damaged mural. Subsequently, these two maps are combined to synthesize a complete color image. Experimental results indicate that the proposed network excels in restoring clearer structures and more vivid colors, surpassing current state-of-the-art methods in both quantitative and qualitative assessments for repairing damaged images. Our code and results will be publicly accessible at https://github.com/albestobe/PRN.

Exploring Personalized Tornado Risk with a Sketch Map Activity

Our study sought to understand how individuals think about their home location and county, including their geospatial awareness, and how they conceive of risk from a tornado geospatially. We conducted interviews and a sketch mapping activity with sixty-five individuals from Mississippi and Alabama. Our results indicated that participants could name and correctly locate only a few neighboring counties and that there was a difference of 4.7 miles on average between their perceived home location and their actual address. Participants labeled on average 9.1 features. Some maps displayed common heuristics or biases, but none was present in a majority of the sketch maps. Regarding geospatial risk personalization, participants’ drawings indicated that many inferred a tornado approaching from the southwest, and that they would take protective action when a tornado was within an average of fifteen miles of their home. Human landmarks and point locations were the features most frequently mentioned that would let participants know a tornado was coming close and participants estimated these features were on average 9.7 miles. Both distances showed a great deal of variation. The results have implications not only for tornado warning communication but also for understanding how individuals might think about a “close call.”

Gathering a multicultural ontology of outdoor and hiking landmarks from direct terrain observations and sketch maps

Gathering a multicultural ontology of outdoor and hiking landmarks from direct terrain observations and sketch maps

A sketch map tool for geography education

A sketch map tool for geography education

SketchMetaFace: A Learning-Based Sketching Interface for High-Fidelity 3D Character Face Modeling.

Modeling 3D avatars benefits various application scenarios such as AR/VR, gaming, and filming. Character faces contribute significant diversity and vividity as a vital component of avatars. However, building 3D character face models usually requires a heavy workload with commercial tools, even for experienced artists. Various existing sketch-based tools fail to support amateurs in modeling diverse facial shapes and rich geometric details. In this article, we present SketchMetaFace - a sketching system targeting amateur users to model high-fidelity 3D faces in minutes. We carefully design both the user interface and the underlying algorithm. First, curvature-aware strokes are adopted to better support the controllability of carving facial details. Second, considering the key problem of mapping a 2D sketch map to a 3D model, we develop a novel learning-based method termed "Implicit and Depth Guided Mesh Modeling" (IDGMM). It fuses the advantages of mesh, implicit, and depth representations to achieve high-quality results with high efficiency. In addition, to further support usability, we present a coarse-to-fine 2D sketching interface design and a data-driven stroke suggestion tool. User studies demonstrate the superiority of our system over existing modeling tools in terms of the ease to use and visual quality of results. Experimental analyses also show that IDGMM reaches a better trade-off between accuracy and efficiency.

An algorithmic approach to detect generalization in sketch maps from sketch map alignment.

Sketch maps are valuable tools used across various disciplines including spatial cognition, environmental psychology, and spatial reasoning. A common approach to evaluate sketch maps in research is to align and compare them with metric maps. However, sketch maps are highly abstract and contain generalized information causing difficulty in their alignment. Current approaches to study sketch maps cannot handle generalized information. They require a one-on-one correspondence between features in the metric map and features in the sketch map. But memory is often generalized. This paper makes two contributions to the research on sketch maps: (i) we present an algorithmic approach to detect generalization in sketch maps (ii) we present an online tool that creates a generalized metric map corresponding to features in sketch maps. Previously, we identified nine types of generalization in sketch maps. In this paper, we develop formal operators to detect these generalizations and implement them as an online tool. We evaluated our algorithm with a set of 11 sketch maps containing 84 instances of generalization. The results indicated that our algorithm consistently detects instances of generalization in sketch maps.

VResin: Externalizing spatial memory into 3D sketch maps

An intuitive way to externalize spatial memory is to sketch it. Compared to traditional paper-based sketches, virtual reality (VR) creates new opportunities to investigate the 3D aspect of spatial memory as it empowers users to express 3D information on a 3D interface directly. The goal of this study is to design a 3D sketch mapping tool for researchers and non-expert users without sketching expertise that enables externalizing memories of spatial information after some 3D-critical tasks. There exist 3D sketching tools using VR, but there are two issues with the current mid-air 3D sketching approach: (1) distortion of sketches due to depth perception errors and (2) increased cognitive and sensorimotor demands due to an increased degree of freedom and absence of physical support. To address these problems, we implemented VResin, a novel sketching interface that synergizes 3D mid-air sketching with 2D surface sketching to scaffold 3D sketching into a layer-by-layer process. An experimental study with 48 participants on multi-layer building scenarios showed that VResin supports users in creating less distorted sketches while maintaining the level of completeness and generalization compared to mid-air sketching in VR. We also demonstrate the potential applications that can benefit from 3D sketch maps and the suitability of VResin for a variety of building shapes.

Geoenvironmetal assessment of different types of cryolithic soils in Western Yakutia under the conditions of diamond-mining operations

The problems of geoenvironmental consequences of mining operations are especially acute in the arctic and subarctic regions, where the spread of permafrost significantly reduces the buffering capacity of landscapes. The article presents data on the content of heavy metals in the soil cover of the transient zone between the middle taiga and north taiga landscapes of Western Yakutia under the conditions of mining operations and assesses the resistance of different types of soils to heavy metals pollution. Field and laboratory works were carried out in August 2022. The heavy metals content was determined by atomic absorption spectrometry. Specialized software was used for analysis, such as MS Excel 2013, Statistica 12.0, and QGis 3.26.1. Calculation of organic forms of heavy metals in soil solutions was performed using the NICA-Donnan model. In the course of studies, the structure of the soil cover in the Nakyn kimberlite field in the conditions of the mining industrial complex operation was determined and a sketch map of the soil cover of the territory was compiled. The geochemical series of the studied heavy metals is as follows according to the degree of concentration of heavy metals in cryolithic soils: Pb > Zn > Ni > Cu > Cd > As > Hg. Positive correlations between humus and Cd, Pb, Zn, as well as the occurrence of synergism in the Pb–Cd, Zn–Pb, Zn–Cu pairs were revealed. The soils organic matter enhances migration of heavy metals. The man-made input of Ni and Zn in cryolithic soils will lead to increase of mobile fraction. Cd is more mobile in pale-yellow carbonate and cryogenic soils. The regional background level of heavy metals for these types of soils was calculated, which can be used in future works when the intensity of mining operations increases.

Thinking. Speaking. Producing. Maps: linking cartographic concepts and cartography-specific language use

Maps are spatial representations of environments and are thus inherently geographical. As such, attaining map skills necessitates fostering students’ cartographic- and language-related abilities when using maps, which represent a characteristic role in geography education. However, to our knowledge, there is no empirical research on the cartographic- and language-related abilities required when using maps in geography education classrooms. To gain more profound insights into the linkages between cartographic concept knowledge and language skills regarding maps, a qualitative study among students is conducted. Upper secondary students drew a sketch map using a digital pen of a familiar route in the school area, while simultaneously being recorded thinking aloud. Students’ representations of the cartographic concept in their sketch maps and their cartography-specific/-unspecific language use in think-aloud protocols were analyzed qualitatively. Despite the high heterogeneity within the sample, results show linkages between the cartographic concept representation and cartography-specific language use among the participants. In addition, students who use cartography-specific language at a medium or high level paraphrased less and represented cartographic concepts more appropriately.

A machine learning based approach for generating point sketch maps from qualitative directional information

People often use qualitative relations to describe locations or directional information, especially in written communication, such as ‘the restaurant is located at the southeast corner of the square’. However, when a large number of spatial entities are involved, qualitative relations alone are not intuitive enough for people to understand a spatial configuration. In fact, many applications, e.g. pertaining to sharing travel experiences, use sketch maps, i.e. maps focusing on the main features of an area whilst abstracting exact scale measurements, to help demonstrate abstract qualitative relations with more intuitive geometric points. Current approaches for generating point sketch maps from qualitative spatial relations require a high level of expertise, face inherent difficulties with efficiently processing large-scale data in bulk, and are vulnerable to inaccurate or conflicting information contained in qualitative data. To address these limitations, by incorporating machine learning techniques, we propose to translate the problem into an optimization problem of data reconstruction, enabling a novel end-to-end approach for generating point sketch maps from qualitative directional relations in bulk. Experiments on real-world datasets show that the proposed approach has very high accuracy and is robust even with a large portion of inaccurate or incomplete information.

Deriving requirements for integrated and standardised cadastre profile from the legacy Board of Revenue and the contemporary land administration systems

Modernising the paper-based manual Land Administration System (LAS) benefits society at large. This study examines the integration and standardisation requirements of LASs in Islamabad, Pakistan, using the Land Administration Domain Model (LADM). The exploratory case study approach assesses land tenure, value, use and development aspects. The existing LASs satisfy LADM requirements for a unified LAS. Systematic transformations are required to upgrade revenue sketch maps and drawings into accurate geospatial data in 2D and above and below-ground infrastructure into 3D. Developing a LADM edition I & II country profile is recommended for land tenure security, socioeconomic development and sustainable urban growth.

Towards Personally Relevant Navigation: The Differential Effects of Cognitive Style and Map Orientation on Spatial Knowledge Development

Under emergencies such as floods and fires or during indoor navigation where cues from local landmarks and a Global Positioning System (GPS) are no longer available, the acquisition of comprehensive environmental representation becomes particularly important. Several studies demonstrated that individual differences in cognitive style might play an important role in creating a complete environmental representation and spatial navigation. However, this relationship between cognitive style and spatial navigation is not well researched. This study hypothesized that a specific type of map orientation (north-up vs. forward-up) might be more efficient for individuals with different cognitive styles. Forty participants were recruited to perform spatial tasks in a virtual maze environment to understand how cognitive style may relate to spatial navigation abilities, particularly the acquisition of survey and route knowledge. To measure survey knowledge, pointing direction tests and sketch map tests were employed, whereas, for route knowledge, the landmark sequencing test and route retracing test were employed. The results showed that both field-dependent and field-independent participants showed more accurate canonical organization in their sketch map task with a north-up map than with a forward-up map, with field-independent participants outperforming field-dependent participants in canonical organization scores. The map orientation did not influence the performance of Field-Independent participants on the pointing direct test, with field-dependent participants showing higher angular error with north-up maps. Regarding route knowledge, field-independent participants had more accurate responses in the landmark sequencing tests with a north-up map than with a forward-up map. On the other hand, field-dependent participants had higher accuracy in landmark sequencing tests in the forward-up map condition than in the north-up map condition. In the route retracing test, however, the map orientation had no statistically significant effect on different cognitive style groups. The results indicate that cognitive style may affect the relationship between map orientation and spatial knowledge acquisition.

Do urban renewal programs make suburbs safer? A fine-grained GIS and space syntax study of an urban renewal project in the city of Toulouse

ABSTRACT This paper evaluates the impact of urban renewal programs (PRU) on creating a safe environment. People’s perceptions of PRU and its impact on security were collected through questionnaires and sketch maps. This study applies a space syntax approach to analyse the spatial and structural properties of successive urban space evolutions and compare them with people’s perceptions of security. The findings reveal a strong correlation between areas with high levels of social housing concentration, poverty rates and insecurity. Surprisingly, visually controlled areas are vulnerable and attractive locations for drug trafficking. Density indicators have a minor influence on the perception of insecurity.

Multi3D: 3D-aware multimodal image synthesis

3D-aware image synthesis has attained high quality and robust 3D consistency. Existing 3D controllable generative models are designed to synthesize 3D-aware images through a single modality, such as 2D segmentation or sketches, but lack the ability to finely control generated content, such as texture and age. In pursuit of enhancing user-guided controllability, we propose Multi3D, a 3D-aware controllable image synthesis model that supports multi-modal input. Our model can govern the geometry of the generated image using a 2D label map, such as a segmentation or sketch map, while concurrently regulating the appearance of the generated image through a textual description. To demonstrate the effectiveness of our method, we have conducted experiments on multiple datasets, including CelebAMask-HQ, AFHQ-cat, and shapenet-car. Qualitative and quantitative evaluations show that our method outperforms existing state-of-the-art methods.

Automatic sketch map creation from labeled planar graph

Maps constructed in Euclidean space are commonly used to visually present information about the real world. However, their creation is resource intensive, be it financial, technical, human, or time-consuming, which can limit their timeliness and detail. A simpler form of visualization of data about the real world is represented by sketch maps, which mainly capture the topology and mutual features’ spatial location. By default, they are drawn by hand. This presupposes that the creator has a good knowledge of the depicted territory, can create a cognitive map, and is skilled in transforming it into a graphical form. Sketch maps can be detailed and up-to-date if these prerequisites are met. Our question was whether it is possible to meet these assumptions in another way: acquire knowledge of the territory by processing narratives related to the area of interest, create a suitable computer representation for further processing, and automatically generate the resulting sketch map. This article presents the last step – creating a sketch map based on spatial data acquired from narratives. The results show that even without metric data, it is possible to automatically generate a sketch map visually close to the actual situation.

Transport makes cities: transit maps as major cognitive frames of metropolitan areas.

Spatial representations play a fundamental role in navigation, decision-making, and overall interaction with our environments. Understanding how individuals construct and use them holds significant importance in spatial cognition research, and even bears practical implications for urban planning as it can explain how we interact with the spaces we inhabit. In large urban areas, transit maps stand as prominent visual aids, guiding people through public transportation systems. These maps, while designed for navigational purposes, may influence how individuals perceive and represent their cities. For instance, Vertesi (Social Studies of Science 38:09-35, 2008) showed through a series of interviews including a "sketch mapping" phase, that London Tube Map seems to structure residents' spatial representation of their city. However, thorough quantitative research on this subject have not been carried out yet. Two experimental studies have been conducted to demonstrate how residents' representations of metropolitan areas closely resemble the schematic representations of their public transport networks. First, we show that residents of Greater Paris-public and private transport users alike-plot city landmarks in a layout more closely resembling that of the Parisian transit map than the geographical map. Next, we asked Greater Berlin, London and Paris residents to place landmarks of their cities on different map backgrounds. A similar procedure was followed for landmarks from an unknown city, after a dedicated learning phase. For known cities, the sketch maps produced were closer to transit maps than to the geographical ones, although less so if the test map background presented topographical elements (e.g., rivers, etc.). For learnt cities, participants' sketch maps were almost exclusively dependent on the map provided during the learning phase. These results suggest that familiarity with transit maps has a direct impact on the metric properties of spatial representation in memory, a phenomenon we propose to call the 'schema effect'.

Understanding Everyday Mobility of Skilled U.S. Migrants in the Pearl River Delta Region of China

Everyday mobility is critical to understand migrants’ accessibility and inclusions to the destination cities. Existing research was insufficient to explain the everyday movement of relatively privileged skilled migrants from the Global North to the Global South, nor did it distinguish the role of one’s capability and intentionality in shaping mobility. To fill in the research gap, we employ the capital-mobility framework to investigate how skilled U.S. migrants’ capital accumulation and intentionality jointly affect their everyday mobility in Chinese cities, and the implications for their social inclusion in the local society. We use sketch mapping with semistructured interviews to conduct this study in the Pearl River Delta region, a pioneer of economic development in China. We find that although migrants’ capital accumulation facilitated their everyday movement, COVID-19 disrupted such mobility. Whether migrants had intentions to move varied, shaped by geopolitical relations, urban environment, and migrants’ own capital. The voluntary or involuntary nature of their everyday mobility also suggests whether their social inclusion or exclusion in the local society is by choice or constraint. Our study integrates geographic information systems visualization with qualitative data to highlight the spatial mobility and immobility at the individual level and generates policy implications for retaining global talent at the city level.

Spatial learning using Google Streetview in an online wayfinding task

The use of navigation applications changed the way people find their way in an unfamiliar environment. A combination of maps, images and textual route instructions shown (or with audio) on one screen guides the user to the destination but may sometimes be overwhelming. This article investigated the spatial knowledge participants acquired after being presented with different types of route instructions, human and computer-generated, in an online wayfinding task using Google Streetview (without the 2D map) of an unfamiliar environment. The results showed a significant difference in the wayfinding performance for deviations from computer-generated instructions, whilst there was no difference in the time spent and the scene recall. Sketch maps revealed both route-like and survey-like characteristics. But most sketch maps are characterised by high route-likeness. Furthermore, this study showed a significant effect of the environmental layout on the participant’s performance based on deviations incurred during wayfinding. The results of this study have implications for improving navigation system instructions and design as well as for learning with geospatial technologies.

Spatial Relationship Analysis of Geographic Elements in Sketch Maps at the Meso and Micro Spatial Scales

Sketch maps are an abstract and conceptual expression of humans’ cognition of geographic space. Humans perceive geographical space at different spatial scales. However, few researchers have considered the spatial relationships of geographic elements in sketch maps at multiple spatial scales. Considering the meso and micro spatial scales, this study analyses the accuracy of the spatial relationships depicted in 52 sketch maps of urban areas, including qualitative orientation, order, qualitative distance, and topological relationships. We utilized OpenStreetMap (OSM) to assess the accuracy of the four spatial relationship representations in the sketch maps. This study evaluates the reliability of spatial relationships in capturing the invariant spatial information of geographic elements in sketch maps. It helps to understand the differences in human cognition of multi-scale space.