Modeling thermal comfort in different condition of mind using satellite images: An Ordered Weighted Averaging approach and a case study

Mijani, Naeim; Alavipanah, Seyed Kazem; Hamzeh, Saeid; Firozjaei, Mohammad Karimi; Arsanjani, Jamal Jokar

doi:10.1016/j.ecolind.2019.04.069

Cited by 49 publications

(28 citation statements)

References 58 publications

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“…The study site is located in the capital of Iran, Tehran, for the longitude 51_19′, E and latitude of 35_41′ N Geographic location has largely affected Tehran's climate (Crosbie et al, 2014). it is located in the north of Iran on the southern slope of the Alborz Mountain and the northern edge of the central desert of Iran, which suggests a heterogeneous weather condition across the city (Mijani et al, 2019). Based on Köppen climate classi cation, Tehran features a cold semi-arid climate (Delfani, Karami and Pasdarshahri, 2010) that can be de ned as mild in the spring and autumn, hot and dry in the summer (Keyhani et al, 2010), and cold in the winter (Amindeldar, Heidari and Khalili, 2017).…”

Section: Selected Areamentioning

confidence: 99%

Assessing the Impact of Vegetation in the Visibility Connection and Thermal Comfort in the Urban Outdoors (Case Study: Shafagh Park)

Karimi

Gachkar

et al. 2021

Preprint

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Regarding the significant impact of visibility, landscape, and thermal comfort on the presence of users’ attendance in urban parks, there is a severe interest in studies on the amount of visibility and the outdoor thermal comfort especially in a district with hot summers. this research, after investigating the shafagh park based on space laws and the relationship between park spaces with each other in terms of accessibility and visibility to achieve the effect of plants, then, based on the obtained data, the role of plants in evaluating thermal comfort conditions in the park space was investigated and finally, their relationship with each other has been examined. results have revealed that, plants have an undeniable role in improving the conditions of thermal comfort and visual visibility and user movement in spaces, so that, the best points in terms of thermal comfort, had a favorable view and perspective, while, areas of the park that did not have good visibility and landscape did not experience favorable conditions in terms of thermal comfort. Therefore, architects, landscape architects, and urban designers who research the problem of thermal comfort and landscape analysis in urban parks can use the findings of this article for effective outcomes, especially in parks with climatic conditions use similar in Tehran.

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Section: Selected Areamentioning

confidence: 99%

Assessing the Impact of Vegetation in the Visibility Connection and Thermal Comfort in the Urban Outdoors (Case Study: Shafagh Park)

Karimi

Gachkar

et al. 2021

Preprint

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“…TCT is a method based on the linear combination of different spectral bands to extract information about the main surface characteristics. Equations (2)-(4) were, respectively, used to extract surface brightness, greenness, and wetness information based on Landsat 8 image bands [69].…”

Section: Modelling Lst and Siiscmentioning

confidence: 99%

Evaluating the Spectral Indices Efficiency to Quantify Daytime Surface Anthropogenic Heat Island Intensity: An Intercontinental Methodology

et al. 2020

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The surface anthropogenic heat island (SAHI) phenomenon is one of the most important environmental concerns in urban areas. SAHIs play a significant role in quality of urban life. Hence, the quantification of SAHI intensity (SAHII) is of great importance. The impervious surface cover (ISC) can well reflect the degree and extent of anthropogenic activities in an area. Various actual ISC (AISC) datasets are available for different regions of the world. However, the temporal and spatial coverage of available and accessible AISC datasets is limited. This study was aimed to evaluate the spectral indices efficiency to daytime SAHII (DSAHII) quantification. Consequently, 14 cities including Budapest, Bucharest, Ciechanow, Hamburg, Lyon, Madrid, Porto, and Rome in Europe and Dallas, Seattle, Minneapolis, Los Angeles, Chicago, and Phoenix in the USA, were selected. A set of 91 Landsat 8 images, the Landsat provisional surface temperature product, the High Resolution Imperviousness Layer (HRIL), and the National Land Cover Database (NLCD) imperviousness data were used as the AISC datasets for the selected cities. The spectral index-based ISC (SIISC) and land surface temperature (LST) were modelled from the Landsat 8 images. Then, a linear least square model (LLSM) obtained from the LST-AISC feature space was applied to quantify the actual SAHII of the selected cities. Finally, the SAHII of the selected cities was modelled based on the LST-SIISC feature space-derived LLSM. Finally, the values of the coefficient of determination (R2) and the root mean square error (RMSE) between the actual and modelled SAHII were calculated to evaluate and compare the performance of different spectral indices in SAHII quantification. The performance of the spectral indices used in the built LST-SIISC feature space for SAHII quantification differed. The index-based built-up index (IBI) (R2 = 0.98, RMSE = 0.34 °C) and albedo (0.76, 1.39 °C) performed the best and worst performance in SAHII quantification, respectively. Our results indicate that the LST-SIISC feature space is very useful and effective for SAHII quantification. The advantages of the spectral indices used in SAHII quantification include (1) synchronization with the recording of thermal data, (2) simplicity, (3) low cost, (4) accessibility under different spatial and temporal conditions, and (5) scalability.

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“…The MLC method has been applied to classify the land uses in the image using the training dataset (Otukei & Blaschke, 2010). The method is the widely used supervised classification in a variety of applications (Firozjaei, Fathololoumi, Kiavarz, Arsanjani, & Alavipanah, 2020;Mijani, Alavipanah, Hamzeh, Firozjaei, & Arsanjani, 2019;Sisodia, Tiwari, & Kumar, 2014). The MLC method assigns each pixel in the image to a particular class, depending on the likelihood of occurrence of the class in the pixel (i.e., a pixel with the highest likelihood) according to the Bayes probability theory (Otukei & Blaschke, 2010).…”

Section: Image Preprocessing and Classificationmentioning

confidence: 99%

An urban growth simulation model based on integration of local weights and decision risk values

Firozjaei

Seddighi

Jelokhani‐Niaraki

2020

Transactions in GIS

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Monitoring and managing the rapid growth of cities, especially in developing countries, highlights the need for appropriate spatio‐temporal models to predict urban growth. The parameters affecting the spatio‐temporal analysis of urban growth play a key role in the prediction results. This study proposes an urban growth simulation model by integrating local subjective–objective weights and decision risk values (ORness) into a CA–Markov model. This involves the use of ordered weighting averaging as one of the multicriteria decision analysis methods to combine the weights and degree of risk for generating a variety of risk‐averse and/or risk‐taking urban growth prediction scenarios. The proposed model has been applied to predict the physical growth of Babol city, located in Mazandaran, Iran. The results indicate that the degrees of ORness = 0.3 and ORness = 0.9 yield better prediction results in the case of using the local and global weighting strategies, respectively. Furthermore, the overall accuracy of local and global weighting strategies at different degrees of risk was 87.6 and 86.8, respectively. This implies that the use of local subjective–objective weights leads to more accurate results than the global weights for simulating urban growth.

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Modeling thermal comfort in different condition of mind using satellite images: An Ordered Weighted Averaging approach and a case study

Cited by 49 publications

References 58 publications

Assessing the Impact of Vegetation in the Visibility Connection and Thermal Comfort in the Urban Outdoors (Case Study: Shafagh Park)

Assessing the Impact of Vegetation in the Visibility Connection and Thermal Comfort in the Urban Outdoors (Case Study: Shafagh Park)

Evaluating the Spectral Indices Efficiency to Quantify Daytime Surface Anthropogenic Heat Island Intensity: An Intercontinental Methodology

An urban growth simulation model based on integration of local weights and decision risk values

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