The rapid increase in infrastructural development in populated areas has had numerous adverse impacts. The rise in land surface temperature (LST) and its associated damage to urban ecological systems result from urban development. Understanding the current and future LST phenomenon and its relationship to landscape composition and land use/cover (LUC) changes is critical to developing policies to mitigate the disastrous impacts of urban heat islands (UHIs) on urban ecosystems. Using remote sensing and GIS data, this study assessed the multi-scale relationship of LUCC and LST of the cosmopolitan exponentially growing area of Beijing, China. We investigated the impacts of LUC on LST in urban agglomeration for a time series (2004–2019) of Landsat data using Classification and Regression Trees (CART) and a single channel algorithm (SCA), respectively. We built a CA–Markov model to forecast future (2025 and 2050) LUCC and LST spatial patterns. Our results indicate that the cumulative changes in an urban area (UA) increased by about 908.15 km² (5%), and 11% of vegetation area (VA) decreased from 2004 to 2019. The correlation coefficient of LUCC including vegetation, water bodies, and built-up areas with LST had values of r = −0.155 (p > 0.419), −0.809 (p = 0.000), and 0.526 (p = 0.003), respectively. The results surrounding future forecasts revealed an estimated 2309.55 km² (14%) decrease in vegetation (urban and forest), while an expansion of 1194.78 km² (8%) was predicted for a built-up area from 2019 to 2050. This decrease in vegetation cover and expansion of settlements would likely cause a rise of about ~5.74 °C to ~9.66 °C in temperature. These findings strongly support the hypothesis that LST is directly related to the vegetation index. In conclusion, the estimated overall increase of 7.5 °C in LST was predicted from 2019–2050, which is alarming for the urban community’s environmental health. The present results provide insight into sustainable environmental development through effective urban planning of Beijing and other urban hotspots.

Urbanization has adverse environmental effects, such as rising surface temperatures. This study analyzes the relationship between the urban heat island (UHI) intensity and Tianjin city’s land cover characteristics. The land use cover change (LUCC) effects on the green areas and the land surface temperature (LST) were also studied. The land cover characteristics were divided into five categories: a built-up area, an agricultural area, a bare area, a forest, and water. The LST was calculated using the thermal bands of spatial images taken from 2005 to 2020. The increase in the built-up area was mainly caused by the agricultural area decreasing by 11.90%. The average land surface temperature of the study area increased from 23.50 to 36.51 °C, and the region moved to a high temperature that the built-up area’s temperature increased by 1.5%. Still, the increase in vegetation cover was negative. From 2020 to 2050, the land surface temperature is expected to increase by 9.5 °C. The high-temperature areas moved into an aerial distribution, and the direction of urbanization determined their path. Urban heat island mitigation is best achieved through forests and water, and managers of urban areas should avoid developing bare land since they may suffer from degradation. The increase in the land surface temperature caused by the land cover change proves that the site is becoming more urbanized. The findings of this study provide valuable information on the various aspects of urbanization in Tianjin and other regions. In addition, future research should look into the public health issues associated with rapid urbanization.

Gastronomic tourism is becoming an essential consideration among tourists when choosing a tourist destination. One of the main reasons for visiting a specific destination for almost 15% of tourists is “gastronomy”. This has led to the development of a new kind of tourism called “Gastronomic Tourism”. However, there has been minimal research on gastronomy tourism, specifically in Pakistan. The primary purpose of this study is to measure the level of satisfaction in a tourist destination and furthermore consider gastronomy as a component of visitor motivation. A survey of 307 tourists who had recently visited Pakistan’s northern areas was undertaken to conduct the study. This has enabled us to better understand the variables that influence the behaviors and attitudes of tourists toward this popular tourist attraction. Gastronomy motivation impacts tourism location selection, and gastronomic experience influences satisfaction, according to the research. Specifically, tourists show a keen interest in gastronomic experiences after feeling satisfied with the destination and local foods, developing loyalty toward the destination.

The rapid infrastructure development in densely populated areas has had several negative impacts. Increases in urbanization have led to increased LST, and urban ecological systems have been negatively affected. Urban heat islands (UHIs) can be mitigated by understanding how current and future LST phenomena are linked to changes in landscape composition and land use cover (LUC). This study investigated the multi-scale spatial analysis of LUC and LST in Tianjin using remote sensing and GIS data. We used Landsat data from 2005 to 2020 to examine the effects of LUC on LST in urban agglomeration. According to the Urban Thermal Field Variance Index (UTFVI), the city’s ecological evaluation was carried out. Results show that changes in LUC and other anthropogenic activities affect the spatial distribution of LST. For the study years (2004–2009), the estimated mean LST in Tianjin was 25.32 °C, 26.73 °C, 27.62 °C, and 27.93 °C. Between LST and urban areas with other infrastructures, and NDBI, significant positive correlation values were found about 0.53, 0.48, and 0.76 (p < 0.05), respectively. Temperatures would almost certainly increase by 3.87 °C to 7.26 °C as a result of decreased plant cover and increased settlements. These findings strongly imply a correlation between LST and the vegetation index. Between 2005 and 2020, the anticipated increase in LST of 3.39 °C is expected to harm urban environmental health. This study demonstrates how Tianjin and other cities can achieve ecological sustainability.

In the recent years, the health and wellness tourism industry has become one of the new emerging industries in Pakistan. In terms of the sharing economy, the driving mechanism of the health and wellness tourism industry has undergone significant changes. Based on a combination of theoretical and practical research, the paper explores the dynamic system and mechanism of innovation development of health and wellness in the tourism industry in Pakistan. Firstly, it theoretically constructs the driving factors in four aspects, which include market demand, industrial supply, infrastructure, and external environment. Secondly, taking Khyber Pakhtunkhwa province (KPK) as an example, it uses the entropy method and Grey relational analysis to test the driving factors system. The empirical results show that four aspects jointly influence the innovation of the health and wellness tourism industry in Pakistan. Finally, this study discusses several practical implications for the development of the health and wellness tourism industry of KPK for academics, policymakers, business owners, and scholars, with recommendations for future research.

The COVID-19 pandemic has led to a significant increase in e-commerce, which has prompted residents to shift their purchasing habits from offline to online. As a result, Smart Parcel Lockers (SPLs) have emerged as an accessible end-to-end delivery service that fits into the pandemic strategy of maintaining social distance and no-contact protocols. Although numerous studies have examined SPLs from various perspectives, few have analyzed their spatial distribution from an urban planning perspective, which could enhance the development of other disciplines in this field. To address this gap, we investigate the distribution of SPLs in Tianjin’s central urban area before and after the pandemic (i.e., 2019 and 2022) using kernel density estimation, average nearest neighbor analysis, standard deviation elliptic, and geographical detector. Our results show that, in three years, the number of SPLs has increased from 51 to 479, and a majority were installed in residential communities (i.e., 92.2% in 2019, and 97.7% in 2022). We find that SPLs were distributed randomly before the pandemic, but after the pandemic, SPLs agglomerated and followed Tianjin’s development pattern. We identify eight influential factors on the spatial distribution of SPLs and discuss their individual and compound effects. Our discussion highlights potential spatial distribution analysis, such as dynamic layout planning, to improve the allocation of SPLs in city planning and city logistics.