Determination of waterscape beauties through visual quality assessment method

Bulut, Zöhre; Yılmaz, Hasan

doi:10.1007/s10661-008-0412-5

Cited by 72 publications

(40 citation statements)

References 36 publications

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“…It is also worth mentioning that this article compared the two data sources based on a population aged [19][20][21][22][23][24][25][26][27][28][29][30][31][32][33][34][35]. This group constitutes the major users of social media in China.…”

Section: A Combined Evaluation Methodsmentioning

confidence: 99%

Comparing Social Media Data and Survey Data in Assessing the Attractiveness of Beijing Olympic Forest Park

Wang

Liu

et al. 2018

Sustainability

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Abstract:Together with the emerging popularity of big data in numerous studies, increasing theoretical discussions of the challenges and limitations of such data sources exist. However, there is a clear research gap in the empirical comparison studies on different data sources. The goal of this paper is to use "attractiveness" as a medium to examine the similarity and differences of Social media data (SMD) and survey data in academic research, based on a case study of the Beijing Olympic Forest Park, in Beijing, China. SMD was extracted from two social media platforms and two surveys were conducted to assess the attractiveness of various locations and landscape elements. Data collection, keyword extraction and keyword prioritization were used and compared in the data gathering and analysis process. The findings revealed that SMD and survey data share many similarities. Both data sources confirm that natural ambience is more appreciated than cultural elements, particularly the naturalness of the park. Spaces of practical utility are more appreciated than facilities designed to have cultural meanings and iconic significance. Despite perceived similarities, this study concludes that SMD exhibits exaggerated and aggregated bias. This resulted from the intrinsic character of SMD as volunteered and unstructured data selected through an emotional process rather than from a rational synthesis. Exciting events were reported more often than daily experiences. Reflecting upon the strength and weakness of SMD and survey data, this study would recommend a combined landscape assessment process, which first utilizes SMD to build up an assessment framework, then applies conventional surveys for supplementary and detailed information. This would ultimately result in comprehensive understanding.

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Section: A Combined Evaluation Methodsmentioning

confidence: 99%

Comparing Social Media Data and Survey Data in Assessing the Attractiveness of Beijing Olympic Forest Park

Wang

Liu

et al. 2018

Sustainability

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“…The visual landscape is an important part of humanity's everyday life experience (Bulut and Yilmaz, 2009). Visual preference for landscapes has received a lot of attention for the past half century and a number of theories explaining landscape *Corresponding author.…”

Section: Introductionmentioning

confidence: 99%

Determining the visual preference of urban landscapes

Abkar¹,

Kamal²,

Maulan³

et al. 2011

Sci. Res. Essays

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This study attempted to determine people's visual preference for urban landscapes in Malaysia. In an experimental study, 120 students from three departments in Universiti Putra Malaysia rated 4 predictors of preference (Coherence, complexity, legibility and mystery) and a criterion variable (preference) of 24 color slides depicting urban built landscape (UBL) and urban natural landscape (UNL) scenes. The results of this study showed that the mean preference and the four predictor ratings were significantly higher for UNL than UBL and it confirmed the role of urban nature in urban landscapes. Also, the results showed that all the predictors of preference could explain a large amount of variance in preference, except for "legibility" in UBL. "Mystery" and "complexity" are found to be the most influential predictors of preference in both categories. Furthermore, "coherence" in UNL notably predicts more preference than in UBL. However, knowledge about preferences and the characteristics of urban landscapes contributes to the designing of an enjoyable environment by designers or planners, and to the decision makers who manage the landscape settings for their users.

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“…Water is one of the most indispensable elements in different landscapes; it has a visual reverse value in scenery and provides users with recreational opportunities [1]. Landscapes with large water bodies (i.e., oceans) tend to be among the most preferred landscapes [2], and water bodies are in fact also positive factors in landscape perception [3]- [5].…”

Section: Introductionmentioning

confidence: 99%

“…Furthermore, Ryan [18], Pfluger et al [19], and Vesterinen et al [20] have shown that water clarity is an important determinant of public perception of water quality. A water surface with a good visual quality can attract more tourists [1] [21] and the visual satisfaction of people observing a water body is thus very important.…”

Section: Introductionmentioning

confidence: 99%

The Relationship between Visual Satisfaction and Water Clarity and Quality Management in Tourism Fishing Ports

Lee¹

2016

JWARP

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Visual satisfaction of the tourists with a water body is strongly influenced by water clarity, which is in turn influenced by a number of water quality parameters. Visual satisfaction thus stands to benefit from having a water quality management tool that results in better water clarity. A Clarity Suitability Index of Water Quality (CSIWQ), derived from clarity suitability curves of selected water quality parameters, can allow estimation of optimal values for these parameters, while ensuring high visual satisfaction among tourists. The present study used sampling and survey methodologies to investigate water clarity and quality at five tourism fishing ports; simultaneously, tourists' visual satisfaction with a water body was assessed through a questionnaire based on their perceptions. The relationship between tourists' visual satisfaction and water clarity was found to be positive and strong, with water clarity having predictive power of 74.2%. The study showed that DO, BOD, TP, and SS were the most critical parameters for water clarity. A continued product approach of CSIWQ was found to be most appropriate for describing the relationship between water clarity and these four parameters. This enabled a CSIWQ Index value to be calculated. With a CSIWQ value of 0.6, water clarity would be more than 2.08 m, and tourists would experience very high satisfaction. CSI curves showed that DO would preferably be 9.0 mg/L, and BOD, TP, and SS less than 0.5 mg/L, 0.12 mg/L, and 45.0 mg/L, respectively. The model thus produced valuable insights for assessing and improving water quality and ensuring high levels of visual satisfaction among tourists in tourism fishing ports. This model identified only four parameters but could be improved by ensuring that other water quality parameters were included, to encourage an increase in the number of tourists and to include monitoring of more pollutant sources.

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Determination of waterscape beauties through visual quality assessment method

Cited by 72 publications

References 36 publications

Comparing Social Media Data and Survey Data in Assessing the Attractiveness of Beijing Olympic Forest Park

Comparing Social Media Data and Survey Data in Assessing the Attractiveness of Beijing Olympic Forest Park

Determining the visual preference of urban landscapes

The Relationship between Visual Satisfaction and Water Clarity and Quality Management in Tourism Fishing Ports

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