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Quantifying Ecological Landscape Quality of Urban Street by Open Street View Images: A Case Study of Xiamen Island, China. REMOTE SENSING 2022. [DOI: 10.3390/rs14143360] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
With the unprecedented urbanization processes around the world, cities have become the main areas of political, cultural, and economic creation, but these regions have also caused environmental degradation and even affected public health. Ecological landscape is considered as an important way to mitigate the impact of environmental exposure on urban residents. Therefore, quantifying the quality of urban road landscape and exploring its spatial heterogeneity to obtain basic data on the urban environment and provide ideas for urban residents to improve the environment will be a meaningful preparation for further urban planning. In this study, we proposed a framework to achieve automatic quantifying urban street quality by integrating a mass of street view images based on deep learning and landscape ecology. We conducted a case study in Xiamen Island and mapped a series of spatial distribution for ecological indicators including PLAND, LPI, AI, DIVISION, FRAC_MN, LSI and SHDI. Additionally, we quantified street quality by the entropy weight method. Our results showed the streetscape quality of the roundabout in Xiamen was relatively lower, while the central urban area presented a belt-shaped area with excellent landscape quality. We suggested that managers could build vertical greening on some streets around the Xiamen Island to improve the street quality in order to provide greater well-being for urban residents. In this study, it was found that there were still large uncertainties in the mechanism of environmental impact on human beings. We proposed to strengthen the in-depth understanding of the mechanism of environmental impact on human beings in the process of interaction between environment and human beings, and continue to form general models to enhance the ability of insight into the urban ecosystem.
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The Landscape of the Spa Parks Creation through Components Influencing Environmental Perception Using Multi-Criteria Analysis. SUSTAINABILITY 2022. [DOI: 10.3390/su14095657] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
The improvement of the landscape of spa parks should result from the planned directions of development and the most important tasks of the spatial policy of spa towns. Their proper management significantly impacts the region’s economic growth: the labour market, the size and type of new financial investments, and the natural environment. The basis of activity in the areas of spa parks is the balancing of elements of the natural, cultural and historical background. Parks are health protection zones, health ecosystems—separated from the spa zone to protect healing and environmental values. These areas should be characterized by rational landscaping. The spatial layout of park areas should consider the appropriate zones (healing, silence, recreation). The leading element that allows separating sub-areas in parks is the layout of alleys and greenery. The attractiveness of parks is also influenced by factors related to spa activities. The article aims to indicate the main criteria affecting the perception of the landscape of spa parks. Their meaning was determined by information entropy. A selection of criteria defining the landscape assessment and influencing the perception of spa greenery, which helped determine how to shape and develop the spa park, was presented. Data obtained from actual field measurements on factors influencing the reception and perception of spa parks were considered. The multi-criteria method of comparative analysis allows one to quickly and transparently determine the hierarchy of the most advantageous variables from the adopted criteria. The study confirmed that the smaller the sum of adverse elements affecting the shaping of the park spatial, the better residents’ and patients’ perception of the park.
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Lu Y, Wu B, Yan N, Zeng H, Guo Y, Zhu W, Zhang H. Method for monitoring environmental flows with high spatial and temporal resolution satellite data. ENVIRONMENTAL MONITORING AND ASSESSMENT 2021; 194:13. [PMID: 34877616 DOI: 10.1007/s10661-021-09641-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/29/2021] [Accepted: 11/20/2021] [Indexed: 06/13/2023]
Abstract
Monitoring environmental flows is crucial to maintaining the function and stability of river and lake ecosystems. However, current methods for monitoring environmental flows are expensive and ground based, and the accuracy of the results needs to be verified to evaluate the environmental flows. This evaluation is hampered by the problem of data shortages, such as hydrological and ecological data. In this study, a method for monitoring environmental flows is proposed using multisource high spatial and temporal resolution satellite data. A case study in the Yongding River Basin demonstrates that the method is feasible for monitoring the environmental flows of rivers in semiarid and arid areas. The results show that the environmental flows and months with large water discharges and shortages in the three control sections of the Yongding River Basin were different. Moreover, the downstream river width rarely met the environmental water demand, achieving this only for one period from 2017 to 2019 according to the three typical types of years (an average water year, a dry year, and an extremely dry year). This method and the results have applications in planning environmental flows and could improve the comprehensive management of the ecological environment in river basins.
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Affiliation(s)
- Yuming Lu
- State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100101, China
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Bingfang Wu
- State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100101, China.
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, 100049, China.
| | - Nana Yan
- State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100101, China
| | - Hongwei Zeng
- State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100101, China
| | - Yong Guo
- Haihe River Basin and Beihai Sea Area Ecology and Environment Administration, Tianjin, 300061, China
| | - Weiwei Zhu
- State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100101, China
| | - Hao Zhang
- Haihe River Basin and Beihai Sea Area Ecology and Environment Administration, Tianjin, 300061, China
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Visual Quality Assessment of Urban Scenes with the Contemplative Landscape Model: Evidence from a Compact City Downtown Core. REMOTE SENSING 2020. [DOI: 10.3390/rs12213517] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
In the face of rapid urbanization and the growing burden of mental health disease, there is a need to design cities with consideration for human mental health and well-being. There is an emerging body of evidence on the importance of everyday environmental exposures regarding the mental health of city inhabitants. For example, contemplative landscapes, through a series of neuroscience experiments, were shown to trigger improved mood and restoration of attention. While the Contemplative Landscape Model (CLM) for scoring landscape views was applied to single images, its suitability was never tested for walking paths and areas with a diversity of viewpoints. This study aims to fill this gap using the high-density downtown of Singapore, also known as a “City in a Garden” for its advanced urban greening strategies, as a case study. In this study, 68 360° photos were taken along four popular walking paths every 20 m. A photo set of 204 items was created by extracting three view angles from each photo. Each of them was independently scored by three experts and average CLM scores for each view and path were obtained. The results were then fed into an open-source Quantum Geographic Information System (QGIS) for visualization. Cohen’s kappa agreement between experts’ scores was computed. The outcomes were mapped to facilitate the identification of the most contemplative viewpoints and paths. Moreover, specific contemplative landscape patterns have been distinguished and assessed allowing the recommendation of design strategies to improve the quality of viewpoints and paths. The inter-rater agreement reached substantial to perfect values. CLM is a reliable and suitable tool that enables the fine-grained assessment and improvement of the visual quality of the urban living environments with consideration of the mental health and well-being of urbanites. It can be used at a larger scale owing to 360° photos taken from the pedestrian’s point of view. Utilizing spatially explicit maps in QGIS platforms enables a wider range of visualizations and allows for spatial patterns to be revealed that otherwise would have remained hidden. Our findings demonstrate the usefulness of our semi-automated method. Furthermore, given the high inter-rater agreement observed, we suggest that there is potential in developing fully automated methods.
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