Landscape Photographs Research Articles

Accurate minority Language Representation in the Public Space: the case of Arabic in Israel

ABSTRACT Although Arabic is the native language of a fifth of the Israeli population, its representation in the Israeli linguistic landscape (LL) is problematic. Adopting a sociolinguistic framework that underscores the political nature of language (Ben-Rafael 2009), this study invited Palestinian-Israeli college students to reflect on the linguistic reality in their area through the participatory documentary photography tool ‘PhotoVoice’. The students captured photos of linguistic landscapes, analysed them, and wrote commentaries voicing their reflections. Students ‘PhotoVoices’ shed light on the abundance of mistakes in Arabic words on the signs. Content analysis of the ‘PhotoVoices’ on this issue highlighted students’ cognitive and emotional perceptions and emerging awareness of the explicit and implicit messages delivered through the signage.

Visual Aesthetic Quality of Qianjiangyuan National Park Landscapes and Its Spatial Pattern Characteristics

This paper conducts a scientific assessment of aesthetic quality to provide intuitive and scientific planning strategies for national park construction. Focusing on Qianjiangyuan National Park, the study used the scenic beauty evaluation (SBE) method to subjectively assess landscape photos from 16 sample sites. Objective eye movement indicators describing visual behavior were also analyzed. A national park landscape visual quality assessment model was derived through multiple linear regressions correlating subjective evaluations with objective indicators. Spatial technologies like ArcGIS were used to analyze the visual quality and its spatial distribution. Key findings include (1) subjective evaluations showed higher SBE scores for wetland landscapes, followed by recreational, village, and forest landscapes, (2) eye movement behavior varied across landscape types, with the forest landscape having the shortest first fixation time and the lowest saccade frequency, while recreational landscapes had the lowest average saccade speed, (3) strong correlations were found between SBE and indicators such as average fixation time and saccade frequency, with fixation duration ratio being the leading factor influencing visual aesthetic quality, and (4) visual aesthetic quality was highest in the north and south areas of the park, with significant differences between sample sites in these regions compared to the central area. Among different functional zones, the ecological protection area had the highest quality, while the Suzhuang management area excelled in aesthetic quality compared to the Hetian management area.

Surveillance as a variable explaining why other people’s presence in a park setting affects sense of safety and preferences

Research on preferences towards urban parks very rarely takes into account the impact of other people’s presence in a park setting. We examined how the number of people in the vicinity and their distance affect sense of safety and preferences towards park space, and what role surveillance (being seen or heard) plays in these relationships. We analysed the correlations between the variables and the mediating effects. For this purpose, we employed a within-subjects design in which 194 participants evaluated a set of 112 eye-level photographs of park landscapes with regard to perceived safety, landscape preference and surveillance. We calculated how many people were in the field and determined their distance on the basis of photos. We analysed a number of mediation models testing hypotheses about the mediating role of surveillance and safety in the impact of other people’s presence on safety and preferences. Most of the hypotheses presented, and verified by the analysis of indirect effects, were confirmed. The number of people does not affect preferences, but does affect safety, and this explains why the sense of being monitored (being seen or heard) grows along with the number of people present. On the other hand, the influence of distance on preferences is explained by a sequential model — greater distance is associated with less surveillance; in turn, surveillance increases sense of safety, which also leads to stronger preferences.

Modeling and Locating the Wind Erosion at the Dry Bottom of the Aral Sea Based on an InSAR Temporal Decorrelation Decomposition Model

The dust originating from the extinct lake of the Aral Sea poses a considerable threat to the surrounding communities and ecosystems. The accurate location of these wind erosion areas is an essential prerequisite for controlling sand and dust activity. However, few relevant indicators reported in this current study can accurately describe and measure wind erosion intensity. A novel wind erosion intensity (WEI) of a pixel resolution unit was defined in this paper based on deformation due to the wind erosion in this pixel resolution unit. We also derived the relationship between WEI and soil InSAR temporal decorrelation (ITD). ITD is usually caused by the surface change over time, which is very suitable for describing wind erosion. However, within a pixel resolution unit, the ITD signal usually includes soil and vegetation contributions, and extant studies concerning this issue are considerably limited. Therefore, we proposed an ITD decomposition model (ITDDM) to decompose the ITD signal of a pixel resolution unit. The least-square method (LSM) based on singular value decomposition (SVD) is used to estimate the ITD of soil (SITD) within a pixel resolution unit. We verified the results qualitatively by the landscape photos, which can reflect the actual conditions of the soil. At last, the WEI of the Aral Sea from 23 June 2020, to 5 July 2020 was mapped. The results confirmed that (1) based on the ITDDM model, the SITD can be accurately estimated by the LSM; (2) the Aral Sea is experiencing severe wind erosion; and (3) the middle, northeast, and southeast bare areas of the South Aral Sea are where salt dust storms may occur.

Why Photography Mattered (1847) As Art More Than Ever Before

In the late 20th-century, landscape photographs that were never meant as art come to play a central role in the critique of one notion of what art is. Rosalind Krauss begins her attack on Modernism by mobilizing the indexical qualities of the photograph, holding up Timothy O’Sullivan’s 19th-century landscape photographs as the exemplar. This essay considers Krauss’s model in relation to César Aira’s contemporary revival of the 19th century landscape painter Johann Moritz Rugendas who is conceived, I argue, under the sign of the photograph. Conceptually recasting the landscape— the locus classicus for the crisis of Modernist art— through Rugendas, Aira transforms the painterly genre into an alternative neuro-aesthetically charged “procedure.” Aira’ s landscape painter turned photographer serves, I contend, both as an emblem for Aira’s own relation to writing and as an artifact of Krauss’s post-Art world.

Style transfer for converting images into Chinese landscape painting based on CycleGAN

Chinese landscape painting is a prevalent and unique mode of artistic expression within traditional Chinese art. It boasts intricate techniques and demands a relatively high level of artistic skill. Recent advancements in artificial intelligence have ushered in the era of image style transfer techniques, making it feasible to convert landscape photographs into stunning Chinese landscape paintings. In this study, the author has developed an image translation model that enables mutual transformation between images of landscapes and Chinese landscape paintings. This technology significantly reduces the difficulty of creating Chinese landscape paintings, allowing more ordinary people in China to experience and appreciate the joy brought by traditional Chinese art. Experimental results indicate that the style transfer model based on CycleGAN has achieved significant success in this scenario. The generated artworks successfully integrate the style of Chinese landscape painting into the original images without altering the original composition and details. As a result, the original photos gain a certain level of artistic value. Additionally, this study innovatively explores the goal of reverse restoration of Chinese landscape paintings into images, highlighting both the similarities and differences with the current research, thus laying the foundation for future studies.

Ancient Chinese painting style transfer based on CycleGAN

Style transfer aims to alter the visual aesthetic of images by giving them a different artistic style. With the rapid advancement of deep learning, style transfer tasks have made significant progress, introducing new perspectives and innovative potentials within the realm of image processing. This study seeks to explore style transfer methods based on Cycle-Consistent Adversarial Networks (CycleGAN), enabling contemporary landscape photographs to take on the form of ancient Chinese paintings. This endeavor opens up fresh possibilities for artistic creation, image editing and design applications. The research encompasses an exposition of the process involved in constructing the CycleGAN model, alongside presenting research findings. Furthermore, it delves into the discussion of crucial techniques employed during the model training process, specifically the utilization of cycle consistency loss in configuring the loss functions. Lastly, this study ventures into future research directions, including strategies for further enhancing the performance and expanding the application scope of this style transfer model.

Japanese consumer's visual marketing preferences and willingness to pay for rice produced by biodiversity‐friendly farming

AbstractA market‐based approach for biodiversity conservation can promote sustainable food production, but little is known about how consumers perceive rice and organisms conserved through biodiversity‐friendly farming (BFF). To address this gap, we conducted a web survey of 600 Japanese respondents to investigate their visual preferences for 20 photographs of organisms and landscapes found in paddy field areas and their willingness to pay (WTP) for BFF rice. Our results showed that paddy field landscapes were most preferred, followed by plants and birds, while insects and an endangered frog were the least preferred. Lowland flat and mountainous terraced paddy landscapes were most often selected as package photographs for BFF rice. Most respondents were willing to pay a premium of 0%–30% for BFF rice. Interest in biodiversity conservation was a common respondent characteristic, and it had a relatively strong influence on image preferences and WTP. Presence of children in certain age groups, sex, age, and experience with living near farmlands or conservation activities also affected the image preference or WTP answers, but to a lesser extent. These findings reveal consumer perceptions of BFF and the importance of effective eco‐labeling strategies for communicating conservation activities and improving promotion of sales to consumers.

Paint-CUT: A Generative Model for Chinese Landscape Painting Based on Shuffle Attentional Residual Block and Edge Enhancement

As one of the precious cultural heritages, Chinese landscape painting has developed unique styles and techniques. Researching the intelligent generation of Chinese landscape paintings from photos can benefit the inheritance of traditional Chinese culture. To address detail loss, blurred outlines, and poor style transfer in present generated results, a model for generating Chinese landscape paintings from photos named Paint-CUT is proposed. In order to solve the problem of detail loss, the SA-ResBlock module is proposed by combining shuffle attention with the resblocks in the generator, which is used to enhance the generator’s ability to extract the main scene information and texture features. In order to solve the problem of poor style transfer, perceptual loss is introduced to constrain the model in terms of content and style. The pre-trained VGG is used to extract the content and style features to calculate the perceptual loss and, then, the loss can guide the model to generate landscape paintings with similar content to landscape photos and a similar style to target landscape paintings. In order to solve the problem of blurred outlines in generated landscape paintings, edge loss is proposed to the model. The Canny edge detection is used to generate edge maps and, then, the edge loss between edge maps of landscape photos and generated landscape paintings is calculated. The generated landscape paintings have clear outlines and details by adding edge loss. Comparison experiments and ablation experiments are performed on the proposed model. Experiments show that the proposed model can generate Chinese landscape paintings with clear outlines, rich details, and realistic style. Generated paintings not only retain the details of landscape photos, such as texture and outlines of mountains, but also have similar styles to the target paintings, such as colors and brush strokes. So, the generation quality of Chinese landscape paintings has improved.

Study of the therapeutic effects of Icelandic natural landscape images. A case study of Chinese tourists

The study employs a comprehensive experimental methodology, utilizing a diverse collection of photographs organized into 18 distinct groups. There are three main objectives. First, it explores the cultural and psychological factors that make Icelandic landscapes so therapeutic for the Chinese. Second, it aims to prove how photographs of natural landscapes (two-dimensional images) can have a healing effect on individuals. Third, it strives to create a model for sorting healing photographs and making them useful for selecting images for healing albums.
 A Likert-scale questionnaire was distributed to 1,000 participants from China, 500 individuals who have visited Iceland, and 500 who have not. This diverse pool consists of 500 males and 500 females, spanning ages from 10 to 80.
 The results reveal the top-ranked landscapes and significant improvements in participants’ psychological well-being after viewing the pictures. The findings support the therapeutic nature of the curated collection of forty photographs, providing inspiration and promoting well-being through the beauty and transformative power of nature. This experimental investigation contributes to an understanding of healing landscapes and their potential in assisting psychological therapy and landscape design.

DLP-GAN: learning to draw modern Chinese landscape photos with generative adversarial network

DLP-GAN: learning to draw modern Chinese landscape photos with generative adversarial network

How to light up the night? The impact of city park lighting on visitors’ sense of safety and preferences

This article presents the results of research that seeks to further our understanding of how lighting methods used in city parks impact sense of safety and preferences. We studied how the impact varies according to: (1) the lighting of paths as well as horizontal and vertical space; (2) foreground and background lighting. At the same time, we checked how the impact of these lighting features on sense of safety and preferences may be explained by mystery, legibility and a sense of privacy. We employed a within-subjects design in which 143 participants evaluated a set of 120 eye-level photographs of park landscapes in terms of mystery, legibility, perceived privacy and safety, and preference. We measured the degree of illumination in the photos as a percentage coverage of illuminated landscape forms. We tested the hypotheses by analysing a number of mediation models. The results revealed that the impact of lighting on perceived safety was explained by legibility. Safety (and legibility) increased along with increased lighting of landscape forms, but only in the background. Increased lighting of paths did not affect safety. An increase in path lighting lowered preferences because it deprived the landscape of mystery and privacy. Increasing the lighting around paths raised the assessment of mystery and, therefore, preference, but this only involved the lighting of vertical elements. Background lighting made the landscape more attractive because it became more legible and mysterious, and provided a greater safety and privacy. Foreground lighting had the opposite effect (it lowered the ratings).

Retracted: Color Image Landscape Photo Hand-Painted Effect Evaluation with PFA Algorithm

Retracted: Color Image Landscape Photo Hand-Painted Effect Evaluation with PFA Algorithm

Analisis Nilai Keindahan Wisata Bahari di Pantai Tlangoh Bangkalan Menggunakan Metode Scenic Beauty Estimation (SBE)

The potential for sightseeing in madura is one of the potential for enjoying its natural beauty. The tlangoh village beach Tours are in demand. The purpose of this study is to know the value of beauty on the tlangoh coast. The method of measuring beauty value with scenic beauty colonation (sbe), it is used to assess and analyze the quality of landscapes using the documentaries (location photos) with the presentation of the location (gili labak island). Studies show that 15 landscape photos compared to 4 positive ones and 11 negative ones. Shows there are 4 landscape locations on tlangoh beach better than comparison sites, and 11 landscaping better location Settings. The average score sbe -1.97, suggests that a control site is still better than the tlangoh coast. The lowest score is 82.34 on the 4th landscape photo and 2.11 on the 15th landscape photo. Locations with low value are mostly in natural conditions such as coral reefs, beaches, while the tlangoh beach tourist facilities fare better than comparison points. Improved environmental quality needs to be made to increase the value of beauty at tlangoh beach.

The photographic image of works of art as an instrument of expert appraisal and attribution (on the example of paintings and drawings by V. I. Shukhaev)

The article is based on a study of paintings and drawings by Vasily Ivanovich Shukhaev (1887–1973) from the collections of state museums and private collections, as well as from works available on the antiques market. The study again poses the question of artwork appraisal and attribution and, accordingly, of research methods and tools used by experts. The appraisal and attribution practice of the author of this article has shown the importance of using photographic images of works of art, museum and exhibition displays and interiors of residential premises that captured the works examined, and photographs of natural landscapes taken by artists himself. Of particular value are photographs taken during the author’s lifetime and received in archival storage from his collection. In addition to the above, these include photographs containing inscriptions on the passe-partout or on the back. All this material allows one to imagine what the lost works of art looked like, provides a basis for confirming the authorship and date of creation of the artist’s works, makes it possible to identify variants and copies of paintings, exclude fakes, show stages and peculiarities in the creation of a work of art by the artist, and in some cases witness the repainting of works many years later, which was typical of V.I. Shukhaev. The use of photographic images in expert attribution work can concretize and visualize the creative path and activity of the artist, which is important for objective study of their art and can be used in research, museum exhibition, and educational work by humanities specialists.

Exploring the Psychophysiological Effects of Viewing Urban Nature through Virtual Reality Using Electroencephalography and Perceived Restorativeness Scale Measures

Researchers have long explored how humans respond psychologically and physiologically to distinct landscapes and natural features. Walking in nature and viewing photographs of natural landscapes have been shown to reduce stress measured through the physiological responses of blood pressure, salivary cortisol concentration, and pulse rate. Exposure to natural landscapes has also been shown to improve feelings of relaxation and positive emotion. Little research, however, has focused on the potential impact of visualization through virtual reality (VR). This study explores how brain frequencies and psychological measures test the restorativeness of a virtual place. Utilizing VR, twenty-one participants observed a virtual, vegetated, vacant site as it exists currently and then again as a reimagined greenspace. The psychological responses were analyzed using the Perceived Restorativeness Scale (PRS), and the psychophysiological responses were analyzed using electroencephalography (EEG) with a specific focus on alpha and beta brain frequencies in the frontal and parietal lobes. Findings indicated that the perceived restorativeness of the designed site increased for two of the three determined factors. Alpha brain frequencies were not significantly different when viewing the vacant versus the designed site; however, beta brain frequencies demonstrated a marginally significant effect of sex with male beta power spectral density decreasing when viewing the designed site and female beta brain frequencies increasing. This research suggests that redesigning a vegetated urban vacant site can positively impact perceived restorativeness and unveils a potential gender effect present in beta brain frequencies.

Is there a generational shift in preferences for forest carbon sequestration vs. preservation of agricultural landscapes?

Afforestation and reforestation are considered important measures for climate change mitigation. Because the land area available for tree planting may serve multiple purposes, striking the right balance between climate goals and other objectives is crucial. We conducted a survey of the Norwegian population to investigate potential land-use conflicts that may arise from executing a large-scale afforestation programme. Respondents were presented with three land-use alternatives to replace formerly grazed agricultural land. We used manipulated landscape photos to elicit their underlying value orientations. We combined multiple correspondence analysis with latent class regression models to reveal preference heterogeneity. Our models grouped respondents into three latent classes, with 24%, 24% and 52%, respectively, expressing a preference for forest carbon sequestration, recreation or agriculture as the most crucial land-use function to be retained. Birth year emerged as a strong predictor of class membership. Specifically, generations born before 1970 were more inclined to support the continuation of agricultural landscapes, while those born in 1980 and later showed a stronger inclination towards natural forest succession for carbon sequestration or recreational purposes. Quantitatively, every 10-year reduction in age increased the odds of a respondent belonging to the forestation or recreation class (relative to the agricultural class) by a factor of 2. Interestingly, even among respondents who were classified as most climate concerned, natural forests were 50% more likely to be preferred over monoculture spruce plantation as a policy option. This suggests that there may be public resistance to spruce planting for climate mitigation purposes in Norway.

Image-based Air Quality Prediction using Convolutional Neural Networks and Machine Learning

Air quality has become a major public concern due to the significant threat posed by air pollution to human health, and rapid and efficient monitoring of air quality is crucial for pollution control and human health. In this paper, deep learning and image-based models are proposed to estimate air quality. To evaluate the level of air quality, the model collects feature information from landscape photos taken by mobile cameras. To analyze public perception of air quality, researchers collected questionnaire data from 257 people. The Smartpls method allows for structural analysis to determine the influence of each variable on other variables and the extent of their contribution to the final variable of overall perception of air quality. This study aims to develop a novel approach for air quality prediction using image-based data and machine learning techniques. The research used convolutional neural networks to extract features from images and predict the air quality index. The study was conducted using a dataset obtained from a network of air quality sensors across the city. The results of the study showed that the proposed approach can provide accurate air quality predictions compared to the traditional methods. The developed model was able to capture the complex relationships between air quality and environmental factors, such as temperature and humidity. The implications of the study suggest that image-based air quality prediction can be a powerful tool for improving public health and reducing the impact of air pollution. The study's findings hold promise for a healthier future by facilitating more effective pollution management and improved air quality regulation. The study's primary novelty lies in its approach to air quality prediction by deploying convolutional neural networks to extract image features for predicting air quality indices. This application of advanced machine learning techniques to image-based data for air quality estimation marks a significant advancement.

Alternative methods in contemporary South African landscape photography

This paper examines the work of three contemporary South African photographers whose adaptations of landscape photography support inquiry into themes such as agency, identity, and belonging. None of these artists self-identifies as a landscape photographer, but each has taken up the genre to address topics of social concern such as: colonialism, under-documented histories, and the geographical imagination. Jean Brundrit adapts high-resolution survey technology to chart waves; Cedric Nunn creates extended captions to reorient views of the modern Eastern Cape landscape in relation to Xhosa history; and Francki Burger layers negatives in the darkroom to construct ethereal environments that examine emotive connections to land. These artists draw upon photographic techniques that may be considered ‘alternative’ in relation to traditional modes of landscape photography. In doing so, they challenge, reinterpret, and expand the definition of what constitutes a landscape image and landscape photography. Further, their respective works offer insight into the evolution of the genre from its nineteenth and early twentieth century applications in South Africa, as well as its utility for socially-concerned artists in the post-apartheid era.

Presence of agriculture in photos of Norwegian landscapes uploaded to Flickr

ABSTRACT The aim of the article is to assess whether agricultural landscapes play a role in the perception of Norway held by tourists and residents. An additional aim is to analyse whether information accompanying images on social media indicate that the photographers have acknowledged the agricultural landscape. The authors used geotagged images uploaded to the image-sharing platform Flickr in their analyses. They selected photos from within the agricultural landscapes, inspected them, and categorized them according to extent and content. Additionally, they analysed the accompanying hashtags. The findings revealed that a large proportion of the photos contained agricultural landscapes, and thus confirmed the importance of the agricultural landscape for visual perception of and access to Norwegian landscapes. In addition, the lack of agricultural-related hashtags strengthened the authors’ suspicions that this might not have been widely recognized by the photographers. Thus, while agricultural landscapes commonly are considered primarily as landscapes of food production, the authors conclude that these landscapes also fulfil other functions and that their contribution to the perception of Norway is important. Additionally, many of the landscape elements seen and analysed in the sample of photos are elements that play a role in providing cultural ecosystem services.