Landscape Scenes Research Articles

Eye-Tracking and Visual Preference: Maybe Beauty Is in the Eye of the Beholder?

The “Content-Identifying Methodology”, or CIM, is an approach developed by environmental psychologists Rachel and Stephen Kaplan to understand the landscape characteristics that people find visually attractive. The Kaplans did this by surveying people’s landscape preferences and then analyzing the preferences to develop sets of landscape scenes to which people reacted in a similar pattern. The underlying assumption is that a common stimulus or content exists in the photographs of a set responsible for the preference. However, identifying the common stimulus or content in each set or grouping of scenes and how it affects preference can still be challenging. Eye-tracking is a tool that can identify what the survey participants were looking at when indicating their preference for a landscape. This paper demonstrates how eye-tracking was used in two different landscape preference studies to identify the content important to people’s preferences and provide insights into how the content affected preference. Eye-tracking can help identify a common stimulus, help determine if the stimulus is a physical or spatial characteristic of the landscape, and show how the stimulus varies in different landscape contexts.

Robust sound-guided image manipulation

Recent successes suggest that an image can be manipulated by a text prompt, e.g., a landscape scene on a sunny day is manipulated into the same scene on a rainy day driven by a text input “raining”. These approaches often utilize a StyleCLIP-based image generator, which leverages multi-modal (text and image) embedding space. However, we observe that such text inputs are often bottlenecked in providing and synthesizing rich semantic cues, e.g., differentiating heavy rain from rain with thunderstorms. To address this issue, we advocate leveraging an additional modality, sound, which has notable advantages in image manipulation as it can convey more diverse semantic cues (vivid emotions or dynamic expressions of the natural world) than texts. In this paper, we propose a novel approach that first extends the image–text joint embedding space with sound and applies a direct latent optimization method to manipulate a given image based on audio input, e.g., the sound of rain. Our extensive experiments show that our sound-guided image manipulation approach produces semantically and visually more plausible manipulation results than the state-of-the-art text and sound-guided image manipulation methods, which are further confirmed by our human evaluations. Our downstream task evaluations also show that our learned image–text-sound joint embedding space effectively encodes sound inputs. Examples are provided in our project page: https://kuai-lab.github.io/robust-demo/.

Beyond just green: Explaining and predicting restorative potential of urban landscapes using panorama-based metrics

Amidst the growing concerns about mental health issues among urban dwellers, there has been increased attention to the restorative potential (RP) of urban landscapes. However, research into the relevant landscape features tends to lack the integration of quantifiable methodologies, which are essential for practical implementation in urban planning and management. To address this gap, our study employed panorama-based metrics relying on computer vision to quantify the features of urban landscapes. We established an explanatory (generalized linear mixed model, GLMM) and a predictive (Random Forest) model to comprehensively elucidate the relationship between these landscape features and RP. The RP outcome was derived from an online survey of respondents (n = 1500) with diverse socio-demographic characteristics, where each respondent was randomly assigned panoramic images from a pool of a hundred landscape scenes taken across the city of Singapore. The GLMM regression identified sky, tree, water, and depth as the primary influences of RP. Furthermore, the Random Forest model demonstrated commendable predictive performance and was used to visually showcase the scenes within the testing dataset with corresponding RP outcomes. To illustrate the potential application of this predictive tool, we also performed spatial mapping for RP prediction, taking the Singapore Botanic Gardens as an example. The subsequent discussion underscored the simultaneous effect of tree, sky, and depth on RP from a quantitative perspective using LOWESS curves. By employing metrics and models that explain and predict the RP, this study contributes evidence-based insights that underscore the pivotal role of trees and openness (sky and depth) in enhancing the psychological benefits of urban landscapes and provides an effective predictive tool that contributes to urban landscape planning and management.

Multiscale Deep - CNN Based Target Prediction in Hyperspectral Image with Transfer Learning

Abstract: There are different types of landscape throughout the world which is not readily or directly approachable for human being but their analysis to uncover factual information has become necessary for forming important decision when developing any fresh project. The geographical and landscape scenes can be adequately represented through hyperspectral images captured using remote sensors. The data in the images can potentially be both vast and intricate to analyze and it is essential to consistently perform adequate pre-processing. In this work, we have put up the use of deep learning and transfer learning for object prediction in hyperspectral data. There are mainly two algorithms that have been implemented in this research. The first method is based on Multi-Scale Deep CNN (Convolutional Neural Network) which takes hyperspectral data with varying sizes as the input to detect pixels whose intensity spreads uniformly over many wavelengths or may vary rapidly. Secondly, hyperspectral image sources are not readily available and can be expensive and there are also possibilities for high analysis complexity in the research, so a Transfer Learning based algorithm is applied to the DCNN model. Superior performance in accuracy was noted in the evaluation with respect to the F1 score and recall values for different objects fluctuate between 0.8 to 1.0. Further, we conducted a comparative study, pitting the proposed method against other state-of-the-art target prediction methodologies

Speaking Back to the Landscape Canon: Cultural Translation in Phumulani Ntuli’s Cloud Migration and the Liewe Land! Exhibition

ABSTRACTIn this article I argue that contemporary artists in post-and decolonial contexts are adopting deliberate approaches to respond to and revise canonical art, in what I interpret as acts of cultural translation. Seeing representational practices through this linguistic lens, with concomitant grammars and vocabularies, sheds light on how established conventions may now be challenged through translation—filtering and transforming them. I am particularly interested in the historical South African landscape canon and in how Phumulani Ntuli and several other artists employ different strategies to contest and reimagine the erasures and biases enacted in the canon in their work for the exhibition Liewe Land!. The exhibition was held at the Voortrekker Monument in 2021, and included various artists who all responded to printed reproductions of landscape paintings by historical South African artists. The strategies used by artists that I investigate here include: the reinscribing of people into portrayals of empty colonial landscape scenes, the subversion of pictorial unity and the naturalistic style solidified in the canon through western conventions, and lastly, the use of pre-colonial iconography, grammar, vocabulary and registers of representation that evoke historical relationships between land and people.

Unraveling the mediating role of plant color and familiarity on children’s mood in urban landscape

ABSTRACT An important element of urban landscapes is various plants, and contact with urban landscapes can promote children’s positive mood and mental health. However, few studies focus on Asian school-aged children’s mood for different urban landscapes and the factors shaping them. This study attempted to understand the variables, including plant color, familiarity, and viewing distances (setting 0 m and 2 m), using 150 landscape scenes (68 flowering plants, 50 exotic plants, and 32 foliage plants), on the effects of the landscape preferences and mood states of 119 school-aged children (55 boys and 64 girls). Then, using partial least squares path modelling analysis to display the gender difference in children’s color perception, landscape preferences, and mood states. The results show that: (1) Plant color richness, familiarity, and the proportion of non-green parts of scenes positively affected children’s mood states. (2) Flowering plants are more likely to produce positive moods than those of exotic plants and foliage plants. (3) Plant color richness and familiarity significantly and positively correlated with children’s mood states and landscape preferences. (4) Notably, gender differences exist in children’s landscape preferences and mood states. This study underscores the importance of plant color collocation in child-friendly landscapes and considers the gender differences in urban landscape policy decisions. Besides, adding flowering plants and native plants in urban landscapes may potentially enhance children’s mood state and urban green space utilization rate.

Landscape architecture as means of forming national identity in public spaces in buffer zones of Ukrainian cultural heritage objects

The article presents the results of the author's study of the formation of national identity in public spaces by means of landscape architecture. It has been presented that public spaces are separated on democratic and totalitarian by the socio-political factor. The most expressive about the manifestation or change of national identity is the urban environment of important public spaces, that are centers of popular assemblies, demonstrations and other collective events. Based on the theoretical analysis of the development of the Ukrainians, the main aspects of the manifestation of national identity in the public spaces are democracy and sacredness. It means giving democratic features to public spaces and creation memorable places. The key symbol of Ukrainian identification – is vegetation as an image of the infinity of life, the strength of the spirit and love for the Motherland. Additionally, in the article, is analyzed intercultural and instinctive perception of landscape scenes. These features correspond to the deep foundations of human perception of the environment: natural forms; zoning; semi-closed space; the presence of greenery and water. The internal filling of space should be carried out taking into account comfort and safety, but with a bias towards national motives. In particular, we have identified such features of the Ukrainian landscape style as: zoning and monoculture; the presence of a stalls and front gardens; abundant autochthonous gardening; and sacred elements of improvement. The newly created concept of an identical space device should be fixed in a special document - the design code of the buffer zone. The design code should contain detailed characteristics regarding the improvement of the buffer zone. The formation of national identity in the public spaces of buffer zones of cultural heritage monuments will contribute to the implementation of safety and security functions without violating the traditional nature of the historical environment.

Exploring Landscape Design Intensity Effects on Visual Preferences and Eye Fixations in Urban Forests: Insights from Eye Tracking Technology

Individuals’ preferences for urban forest scenes are an essential factor in the design process. This study explores the connection between landscape design intensity, visual preferences, and eye fixations in urban forest scenes. Five pictures representing different urban forest scenes (plaza, lawn, garden path, pond, and rockery) were selected as stimuli, representing the original landscape design intensity. Three additional levels of design intensity (low, moderate, and high) were created by modifying the landscape elements of the original picture. A group of 50 participants was randomly assigned to observe the four levels of design intensity pictures within each type of landscape using eye-tracking technology. They also rated their preferences for each scene. In total, 250 participants took part in the study, with five groups observing five types of urban forest scenes. The results indicate that landscape design intensity has a positive impact on visual preferences, with moderate design intensity showing the strongest effect. However, the influence of design intensity and preferences also depends on the specific landscape scene. The fixation data did not show a significant relationship with design intensity but were associated with the type of landscape scene. In conclusion, this study suggests that moderate design intensity is recommended for urban forest design. However, it also highlights the importance of considering the specific landscape scene type. The research provides valuable insights into urban forest design and contributes to the understanding of eye-tracking technology in landscape perception studies.

Design of Urban Public Landscape Lighting Control System Based on Dmx512 Protoco

Design an urban public landscape lighting control system based on DMX512 protocol to improve the lighting effect of urban public landscapes. The system uses the upper computer urban public landscape scene transformation software to edit the colour change data of urban public landscape lamps, set a reasonable number of sub-controllers according to the actual needs of urban public landscape scenes, and store relevant data in the SD card of the data storage layer. The Ethernet transmits the data in the SD card to the lighting control module, the main controller transmits the data in the SD card to the sub-controller, and the ARM of the sub-controller decodes the urban public landscape scene data, and uses the fireworks algorithm-fuzzy adaptive PID. The control algorithm solves the control data of urban public landscape lighting lamps, and the data that meets the DMX512 protocol is edited by FPGA and transmitted to the DMX512 controller. Through the DMX512 controller, the control data of urban public landscape lighting lamps is transmitted to the equipment module realize the control of LED lamps for urban public landscape lighting. The experimental results show that the response speed of the system is fast, at 0.60s it can quickly reach the illuminance value of the park landscape lighting LED light 7.5 lx set in the experiment, and its control ability is strong. At the same time, the system has high software and hardware compatibility and system stability. Better, in multiple operating systems, there will be no problems such as flashback, blue screen, crash, etc., ensuring the safe operation of the PC and improving the effect of park landscape lighting control.

Research on Landscape Architecture Modeling Simulation System Based on Computer Virtual Reality Technology

This paper develops a three-dimensional garden landscape design simulation system based on virtual reality technology. The landscape design data collection module uses files to read and write landscape design data. Use the resource library to store the basic materials required for 3D landscape design. The system realizes the functions of 3D solid modeling, 3D real-time virtual presentation of design scenes, rendering and animation production, and construction drawing. After the landscape architecture simulation system generates construction drawings, it uses the coordinate matrix method of three-dimensional graphics processing technology to render the three-dimensional texture of the model. The system realizes three-dimensional landscape design through the statistical budget and engineering data of the data statistics module. The system simulation results show that the system can effectively realize the garden landscape design of the community, and the visual effect of obtaining the garden landscape scene is better.

Bunny & Tree by Balint Zsako

Reviewed by: Bunny & Tree by Balint Zsako Kara Forde Zsako, Balint Bunny & Tree; written and illus. by Balint Zsako. Enchanted Lion, 2023 [184p] Trade ed. ISBN 9781592703937 $29.95 Reviewed from digital galleys R* Gr. 3-6 This exquisite wordless book in nine acts visually conveys the story of a friendship between the titular characters Bunny and Tree. A prologue establishes a peaceful and contemplative tone with depictions of Tree’s germination and growth throughout the seasons. Act 1 opens dramatically, as fearful-eyed Bunny flees from a terrifying sharp-toothed monster, thankfully finding refuge with Tree, who bends and morphs to mirror the intimidating form of the monster, scaring it away. In safety, Bunny and Tree regard one another (Tree through the binocular holes in its leaf canopy), and Bunny gently digs through the soil to uproot and deposit Tree into a small red wagon. The two embark (pun intended) on an epic journey across railroads, seas, and mountain peaks to search for the other bunnies that were scared off by the monster. Devotion exudes from Tree’s being, as Tree’s transformations into various shapes (a train, a sailboat, a plane, etc.) enable their shared expedition spurred by Bunny’s longing. Sweeping full-bleed illustrations rely on color to guide the tenor [End Page 345] of this tale, with consistent landscape scenes that have the fluid pigment layering of watercolor and the bold saturation of gouache. Zsako brilliantly utilizes speech bubbles containing visually symbolic messages to relay the conversations between Bunny and Tree. The denouement of an emotionally charged climax provides comfort and includes a surprising moment of humor relating to bunny droppings that still suits the story’s philosophical tone. Readers with a romantic worldview and keen attentiveness to visual information will find deep solace in this picture book. [End Page 346] Copyright © 2023 The Board of Trustees of the University of Illinois

In the Presence of "Gypsiness": Dvořák, Ecocriticism, Stimmung

This article is about Stimmung and "Gypsiness" (two aesthetic tropes of nineteenth-century culture) in the music of Antonín Dvořák. In visual art and music, Stimmung has long been associated with idyllic landscape scenes. Yet in Dvořák's music, its usage is more fraught. In his Gypsy Songs, Stimmung demands unmediated contact with "Gypsiness," an imagined amalgamation of alterity that is more often kept at arm's length. Insofar as it makes "Gypsiness" affectively proximate, this music is more ideologically challenging than other cultural products in the Stimmung tradition, and it prompts larger questions about the politicization of affect in the imperial creative imagination.

Interval type-2 fuzzy set based block-SBU for image fusion technique

Image fusion is the process of examining one or more obscure images, combining only the critical information in those images to make them a good quality image. Due to the large gap between the high dynamic range of landscape scenes and the low quality of consumer quality cameras, a single-shot image cannot record the information of a single set. A part of image processing called image fusion is used to overcome the above problem. In this method, authors propose a new technology for image fusion with intuitionistic fuzzy sets. During the processing, the given images are converted into fuzzy images and then intuitionistic fuzzy images (IFIs). Thus, a significant change occurs between the given image and IFIs. The resulting IFIs are converted into interval type-2 fuzzy images (IT2FIs) to overcome this problem. The proposed technique is compared to other procedures such as discrete cosine harmonic wavelet transform (DCHWT), multi-resolution single value decay (MSVD), primary component analysis (PCA), standard wavelet transform (SWT), two scale image fusion (TSIF), and wavelet transform (WT). The proposed method gives the best results based on performance analysis such as Entropy, standard deviation (STD), average gradient (AG), mutual information (MIF), and blind referenceless image spatial quality evaluator (BRISQUE). Using the proposed technique, one can obtain the best results for entropy, STD, AG, MIF, and BRISQUE respectively as 7.6241, 49.6745, 69.2100, 5.7276, and 3.3091. Hence it reveals that the proposed method performs better than other methods regarding overall visual quality and performance measurements.

Quantitative evaluation of attraction intensity of highway landscape visual elements based on dynamic perception

In order to quantify the aesthetic attraction of visual elements of highway landscape space, the concept of visual attraction intensity of highway landscape space is proposed, and the factors and indicators of visual attraction elements are clarified. Based on the perspective of human factors, taking passengers as the main attraction, taking 30 landscape elements from three typical highway landscape scenes, namely mountain highway landscape, plain highway landscape and elevated highway landscape, as the research object. The real-time evaluation and data processing system of subjective landscape preference has been independently developed, and combined with the processing and analysis of human-machine-environment synchronous quantitative analysis technology and in-depth learning, a “subjective+objective” quantitative evaluation model of highway landscape visual element attraction intensity based on dynamic perception has been constructed, revealing the quantitative relationship between highway landscape visual attraction elements and attraction intensity, The quantitative method and action law of the attraction intensity of highway landscape and the dynamic aesthetic perception of the attraction subject is clarified. It is found that the change of highway planning alignment, high green view rate and low enclosure have positive effects on the subjective preference score of the landscape (0.690), and there is a significant positive correlation between green view rate and enclosure; the richer the landscape elements such as mountains, trees and water bodies, the stronger the visual attraction, but the complexity of the landscape elements increases the cognitive load of the area of interest. Among the physiological indicators, there are significant correlations between EEG and ECG (0.790), EDA and ECG (0.632), and subjective preference and passengers' eye-movement behavior and EDA; as well as the change pattern of attraction intensity based on the dynamic perception of tunnel area. The results show that the attraction intensity of visual elements of highway landscape space based on dynamic perception is consistent with human aesthetic preference, visual perception and physiological response, which verifies the scientificity, appropriateness and accuracy of eye-movement analysis method and physiological analysis method for quantitative evaluation of aesthetic preference of highway landscape.

Research on Ecological Landscape Design and Healing Effect Based on 3D Roaming Technology.

Impacted by the COVID-19 epidemic, the human sub-health in national high-tech zones (hereinafter referred to as high-tech zones) has become more prominent. It is critical for the mental sub-health group in the high-tech zone to relieve the anxiety and tension caused by the pressure of life and work. This paper uses SketchUp virtual engine (Unity 2019) software, and 3D roaming technology to carry out the ecological landscape transformation design of the Baotzixi ecological corridor in the East Lake High-tech Zone, to construct a 3D roaming landscape scene and measure its therapeutic effect by inviting subjects to participate in an interactive experience experiment on the ErgoLAB platform. The results illustrate that: (1) the thermogram trend shows that the more attractive the 3D roaming landscape scene is, the stronger the subjects’ interest is; (2) the participants have a positive emotional arousal state in the immersive experience of the 3D roaming landscape scene after the modification design; and (3) the mean skin conductance (SC) fluctuation variance of the subjects is 5.819%, indicating that the healing effect is significant in the state of positive emotional arousal. The research results show that there is a connection between the subjects and the 3D roaming landscape scene after the transformation design of “high interest, emotional arousal and significant healing”.

Computer 3D Scene Simulation of Ecological Landscape Layout Planning

There are some problems in traditional 3D landscape construction and virtual display, such as inflexible landscape spatial organization and limitations of virtual garden simulation in reality. Virtual reality, virtual plants and geographic information systems, and other technologies are used. Based on parameterized method in constructing 3D landscape scene, the main elements of the landscape were, respectively, constructed and rendered in 3D model, and a complete 3D landscape scene construction model was formed. OpenGL shader language was used for rendering, improved NSGA-II algorithm was used with the help of bionic logic of the genetic evolution process to achieve landscape land allocation optimization. The experimental result shows: through 3D scene view clipping hierarchical detail model and other techniques, the frame rate of 3D landscape vegetation scene drawing was improved. The interactive 3D scene browsing is realized, and the six-degree-of-freedom omni-directional display of the whole landscape is provided.

Colour Preference and Healing in Digital Roaming Landscape: A Case Study of Mental Subhealth Populations.

From the perspective of emotional preference, studies have been conducted about landscape healing for subhealth people in the National High-Tech Zone (the study area). Combined with a preliminary practice investigation, Unity 2019 was used to make a digital roaming landscape, and 91 subjects with a history of mental subhealth diseases were randomly invited to participate in the immersive experimentation of the Human–Machine Environment Synchronisation (ErgoLAB) platform. After the experiment, the subjects were invited to fill in a Likert scale as the control group. The interest preference, emotion fluctuation, and healing effect of landscape colour were verified. The results show that: (1) The variation trend of interest reflected the concentration of interest in landscape, and the order of degree of interest, ranging from high to low, went Green > Yellow > Blue > Red > Orange > Purple > Cyan. (2) The subjects’ interest in landscape colour was correlated with the arousal of positive emotions. The correlation between interest in landscape colour and positive emotions, from high to low, went Blue > Green > Yellow, while the correlation between red, cyan, orange, and purple was not significant. (3) The mean skin conductance (SC) fluctuation variance of subjects was 5.594%, which confirmed that the healing effect of digital roaming landscape scenes was significant under the state of low arousal. According to the Likert scale data, subjects’ scores of the healing effect of landscapes, from high to low, went as follows: Green > Yellow > Red > Blue > Cyan > Orange > Purple. The results provide a new method for demonstrating the logical relationship between the digital landscape interest experience–emotional awakening–healing effect and providing a theoretical method and construction scheme for landscape colour configuration in the implementation of landscape healing projects.

Research on Digital Experience and Satisfaction Preference of Plant Community Design in Urban Green Space

In the context of carbon neutrality, it is increasingly important to reduce carbon and increase sinks, and urban green spaces play an important role in carbon sinks. In this paper, we used virtual reality (VR) and photoplethysmographic (PPG) technology to evaluate subject satisfaction regarding urban green space plant community landscape scenes using physiological eye movement and heart rate variability (HRV) data and psychological data obtained according to positive and negative emotional adjectives (PANA). The results of the study showed the following. (1) The physiological data showed the highest visual interest in single-layer grassland. The compound layer of tree-shrub-grass composite woodland communities resulted in the strongest comfort level. (2) The psychological subjective satisfaction evaluation scores were, in descending order: tree-shrub-grass composite woodland (T-S-G) > single-layer grassland (G) > tree-grass composite woodland (T-G) > single-layer woodland (T). (3) The correlation between interest, comfort, and subjective satisfaction was significant, which verified the feasibility of the model of “interest + comfort + subjective evaluation = comprehensive satisfaction”. The results of the study provide theoretical guidance for landscape design based on human perception preferences in the context of carbon neutrality as well as for the implementation of sustainable landscapes to achieve a win–win situation in which carbon sequestration and oxygen release benefits and aesthetics can coexist. The combined physiological and psychological evaluation model can also be applied to other landscapes.

Effects of Visual Environment on Students Adjustment to Stress

The impact of stress on visual landscape perception was assessed in a photo-based survey. The survey was first performed when the student participants were expected to be stressed just prior to an important examination. The same students were asked to respond to the same questionnaire a month after the examination when they were expected to have a lower level of stress. Then respondents answered some daily activities, personal study habits, and feelings before an exam. They also provided ratings of how much a selection of environmental factors generally influence their ability to study and their academic success. In the main perceptual survey reactions to a selection of 22 landscape scenes photos were reported by ratings (1–5) of the extent to which each of six emotions was associated with each scene. Differences in emotions ratings for the represented landscapes during high-stress and low-stress periods were analyzed by multiple comparison and Pearson correlational methods using the SPSS 17.00 package. Stress tests confirmed higher stress in the first versus second survey and perceptual ratings showed significant statistical differences in emotion ratings between landscape scenes, as well as both main effects and interactions between high stress and low stress conditions. Scene ratings for each emotion were strongly positively correlated between high stress and lower stress conditions. At the same time, respondents generally gave slightly higher ratings for positive emotions -excited, relaxing, happiness-when in the high stress condition and moderately higher ratings for negative emotions -stressed, irritating, scary-, compared to their ratings when tested later under lower stress conditions. This study indicated that stress conditions affect perception, and stressed conditions gave higher emotionality overall than the unstressed condition. In general, in both stressed and unstressed conditions, the students gave the highest scores (>3.4) to convenience and the lowest score (<2) to scary. The main limitations of this study are the large number of environmental factors that influence people's perception. The strongest determiner of emotion ratings was the landscape scenes themselves. Inspection of outliers in the scatter plots and multiple comparisons articulating higher order interactions with stress conditions revealed clear differences in the patterns of emotions ratings, especially for scenes representing water surfaces, open green spaces, and seasonal plant scenes.

Analysis of Forest Landscape Preferences and Emotional Features of Chinese Forest Recreationists Based on Deep Learning of Geotagged Photos

Forest landscape preference studies have an important role and significance for forest landscape conservation, quality improvement and utilization. However, there are few studies on objective forest landscape preferences from the perspective of plants and using photos. This study relies on Deep Learning technology to select six case sites in China and uses geotagged photos of forest landscapes posted by the forest recreationists on the “2BULU” app as research objects. The preferences of eight forest landscape scenes, including look down landscape, look forward landscape, look up landscape, single-tree-composed landscape, detailed landscape, overall landscape, forest trail landscape and intra-forest landscape, were explored. It also uses Deepsentibank to perform sentiment analysis on forest landscape photos to better understand Chinese forest recreationists’ forest landscape preferences. The research results show that: (1) From the aesthetic spatial angle, people prefer the flat view, while the attention of the elevated view is relatively low. (2) From the perspective of forest scale and level, forest trail landscape has a high preference, implying that trail landscape plays an important role in forest landscape recreation. The landscape within the forest has a certain preference, while the preference of individual, detailed and overall landscape is low. (3) Although forest landscape photographs are extremely high in positive emotions and emotional states, there are also negative emotions, thus, illustrating that people’s preferences can be both positive and negative.