Regional Urban Centres Research Articles

Suitability matching evaluation of the low-carbon regional integrated energy system based on the “resource-demand” balance

The integrated energy system (IES) stands out due to its advantages of multi-energy complementarity, green and efficiency. This paper aims to provide a practical model for suitable region site selection of low-carbon regional IES based on the “resource-demand” balance. A “resource-demand” suitability matching analysis indicator system is established. By using prospect theory and variable precision rough set theory, the decision-making preferences and the cognitive fuzziness influence of expert scoring were corrected respectively, and reasonable subjective weights were obtained. Then, the objective weights are obtained using the entropy method, and the optimal combined weights are obtained through the game theory weighting method. Finally, this paper establishes a “resource-demand” suitability matching model consisting of three sub models: similarity matching degree, numerical matching degree, and suitability matching degree. An empirical study is conducted on 16 regions in Beijing, and the results show that the numerical matching degree of “resource-demand” gradually decrease from the central urban regions to the surrounding regions. The similarity matching degree in most regions reaches the highest range (0.776,1.00). There are 4 regions with a suitability matching rating of perfect, 7 regions with a rating of great, 1 region with a rating of good, and 4 regions with a rating of poor. The suitability matching model established in this paper can guide energy project decision-makers to select regions with greater potential for the development of IES. In addition, adjusting the similarity matching coefficient and numerical matching coefficient can meet the diversified needs of decision-makers for the similarity matching degree and numerical matching degree of the “resource-demand” balance, providing support for energy project planning decisions.

Local temperature impact of urban heat mitigation strategy based on WRF integrating urban canopy parameters and local climate zones

Urbanization has led to significant alterations in surface properties, contributing to surging urban heatwave events. The detrimental impact of urban heatwaves on public health highlights the urgency for proactive evaluations of diverse heat mitigation strategies. This study assesses the impacts of cool roof (CR), green roof (GR) and rooftop photovoltaic panel (PV) strategies on urban air temperatures within Guangzhou and Foshan agglomeration, utilizing the Weather Research and Forecasting with Urban Canopy Model (WRF-UCM). A comparative analysis of heat exchanges is conducted between two types of urban morphology datasets: local climate zone maps with categorized urban canopy parameters (LCZ-UCPs) and gridded urban canopy parameters from real building databases (gridded-UCPs). The results indicate that the discrepancies in the average temperature between LCZ-UCP and gridded-UCP is almost negligible, whereas increase to 0.39 °C and 0.54 °C for the daily maximum and minimum temperature, respectively. CR provides the most substantial cooling at an average of 0.44 °C, followed by GR and PV. Scenarios with the two types of morphology datasets reveal varying mitigation efficiencies. CRs with LCZ-UCPs show more pronounced temperature reductions, whereas GRs and PVs with gridded-UCPs in central urban regions demonstrate stronger cooling effects. CRs and PVs cool temperature by decreasing sensible heat flux, whereas GR is largely influenced by enhanced evapotranspiration especially with grass plantation. These findings elucidate the differing efficiencies of the three mitigation strategies and highlight the representation discrepancies in climatic simulations brought by the two urban canopy datasets. This emphasizes the importance of accurate urban morphological datasets in evaluating mitigation strategies in WRF-UCM, thus providing practicable insights for urban planning and climate policy-making.

Research on ecological compensation based on ecosystem service flow: A case study in Guangdong province, China

Ecological compensation (EC) is not only an essential tool for correcting the externalities of ecosystem services (ESs) and fostering sustainable development but also a crucial means to alleviate poverty and promote balanced development across regions. Based on the ecosystem service flow (ESF) theory, this article presents a universal framework for screening ESs in EC research, and employs multiple models and multisource data to measure the supply and demand of five ESs. Moreover, this study examined the transfer values of air-mediated ESs (AMESs) and water-mediated ESs (WMESs) using the field strength model and flow allocation method, respectively, due to their significant differences in flow direction, flow rate and attenuation characteristics. The results indicate that: (1) there is a significant disparity between the supply and demand of the five ESs in Guangdong, with the scope and extent of the mismatch varying among the different ESs. Generally, deficit areas are located in the central urban regions of the Pearl River Delta (PRD) cities and cities in eastern and western Guangdong. (2) The transfer values of all the surplus areas of the AMESs and WMESs to their corresponding deficit areas are 37.02 billion yuan and 37.43 billion yuan, respectively, accounting for 62.9% of the AMESs supply value in the study area and 2.5% of the output value of the WMESs in the surplus areas, indicating that a significant amount of the output value has been transferred to areas outside of the study area. (3) The total transfer in/out value between surplus and deficit areas is 71.83 billion yuan, and is economically acceptable for deficit areas. (4) Compared with the results of this study, some economically developed regions with high ecosystem service value (ESV) outputs in Guangdong have not been compensated, and the current EC standard is relatively low. We suggest that Guangdong pilot horizontal EC, explore various market-oriented trading systems, increase vertical EC standards and enrich EC methods. This study provides a reference for the quantification of ESFs with different transmission carriers and the improvement of EC policy in Guangdong.

Solid waste characterization in the slum areas of Bagmati River—A case of Kathmandu, Nepal

Solid waste management (SWM) is a challenging environmental issue globally, with developing nations experiencing considerable difficulties in its efficient and effective implementation. Urban slum areas within these regions, particularly, have been reported to face unique challenges in SWM due to a combination of factors, including the low socio-economic status of residents, high population density, inadequate infrastructure, and a thriving informal economy. Despite these critical concerns, most SWM research in Nepal has concentrated on major cities and tourist hotspots. As a result, the condition of SWM in urban slum areas, typically found along the banks of major rivers in Nepal, remains a critical yet neglected aspect in research and policy discussions. This study, therefore, aims to evaluate SWM in the densely populated urban slum areas situated along the Bagmati River, a key river system in Kathmandu, the capital of Nepal. Four major slum locations within the central metropolitan area of Kathmandu—Sinamangal, Thapathali, Teku, and Balkhu—were selected for the study, and systematic random sampling and characterization of household solid waste was conducted. The results reveal that the average household solid waste generation rates in the four study sites were 155.32 g capita−1 d−1, 124.69 g capita−1 d−1, 149.9 g capita−1 d−1, and 218.44 g capita−1 d−1, respectively. Organic wastes was the most prevalent type, comprising 63.34% of the total waste, followed by paper and paper products (13.72%), plastics (12.15%), dirt and construction debris (5.57%), glass (4.31%), and other wastes (0.91%). Qualitative data from the survey revealed that although municipal waste management programs exist, awareness and participation among residents were limited. As a result, many households ended up managing their waste on their own, often in an unscientific manner polluting the river water in the vicinity. The study offers critical insights for policymakers, operators, and regulators in addressing the growing challenges of SWM. Findings are expected to aid in the sustainable management of solid waste along the river basin in central urban regions of the capital city. Under Nepal's new federal governance system, provincial and local governments are recommended to collaborate with all stakeholders, including households, to develop comprehensive, multimodal SWM strategies that also address the needs of slum areas.

Dynamics of Heat Island Intensity in a Rapidly Urbanizing Area and the Cooling Effect of Ecological Land: A Case Study in Suzhou, Yangtze River Delta

Ecological land could play an important function in climate regulation to mitigate urban heat islands (UHIs) and enhance the quality of the living environment. In this work, we chose Suzhou as our case study for urban agglomeration in the Yangtze River Delta (YRD), eastern China. In this city, we analyzed the dynamics of heat island intensity from 2000 to 2021 by retrieving land surface temperature (LST). Subsequently, we examined the relationship between the urban thermal environment pattern and land use change, and finally, we explored the cooling effect provided by ecological land. The results indicated that, in 2000, the city’s UHI effect primarily centered around the central urban region as a singular patch; however, since 2014, the patch UHI effect in the central urban region has been mitigated, and the original small hotspots have converged into a large, contiguous expanse spreading outward. As the shift has occurred from low- to high-temperature zones, the proportion of conversion between ecological land has been decreasing, while the opposite trend has been seen for the proportions of ecological land transferred out and for unchanged artificial surfaces. The normalized difference built-up index was found to be the main contributor to the UHI effect, followed by the normalized difference vegetation index. These findings provide novel insights into the regulation of ecosystem services during urban expansion and offer a reference for improving the function of the cooling effect through urban renewal activities and the optimization of spatial planning.

Support for Ukrainian refugees after Russia's invasion of Ukraine: aid structure and resilience factors. Case studies of Lublin and Lutsk

ABSTRACT Russia's invasion of Ukraine in February 2022 triggered forced migration on a scale not seen in Europe since World War II. The city of Lublin (Poland), as the capital of the border region, has become both a destination and transit point for refugees, generating the need for both emergency and long-term assistance. Lublin Voivodeship is adjacent to the Volyn region with its capital in Lutsk, where the situation has also changed rapidly (an influx of internally displaced persons). The purpose of this article is to capture the overall picture of the response to war in regional urban centres with similar demographic, absorption and adaptation potential and to identify social resilience factors. We begin by describing the aid structure based on the concept of multilevel governance. We then identify three groups of social resilience factors in both cities: past experience in emergency response, the diversity of actors involved, and the way the work is managed (with professionalisation of volunteer phenomena). The article is based on data resulting from qualitative research in Lublin and Lutsk with the actors of the humanitarian aid.

The weakening effect of urbanization on tropical cyclone surface winds : An observational study for Shanghai

The observation-reanalysis difference method (OMR) and wind profile fitting method were used to analyze the influence urbanization has on the near-surface wind speed in Shanghai during tropical cyclone events. The data used include daily wind speed data from the Shanghai Meteorological Observatory Station collected from 1991 to 2020, hourly wind speed data from 100 m high wind towers from 2017 to 2019, and reanalysis data that covered the same period. The results indicated that during tropical cyclone occurrence, the wind speed of the OMR in the central urban region was significantly lower than that in the suburban area, and the OMR declined more obviously over the year, down to −8 m/s in 2020. Urbanization leads to the increase of average wind weakening rate to be higher than the maximum wind weakening rate, causing the maximum weakening rate of the central urban region to the average wind over 80%, while maximum wind speed was less than 80%. The weakening rate of both the average and maximum wind speeds during tropical cyclone impacts is greater than the rate that the annual average wind speed was reduced. A logarithmic variation was visible in the wind profile of the island station during tropical cyclone occurrence, with an average friction velocity U∗ of 0.9389 m/s and an average rough length Z0 of 0.4915 m. The wind speed during tropical cyclone events was higher than the three-year average wind speed within each layer. The suburban stations show a linear variation, and every hundred meters of height results in an increase of 5–6 m/s in the wind speed change rate. At 100 m of altitude, the wind speed in the suburban region is reduced by approximately 40%.

Exploring spatial association between residential and commercial urban spaces: A machine learning approach using taxi trajectory data

Human mobility datasets, such as traffic flow data, reveal the connections between urban spaces. A novel framework is proposed to explore the spatial association between urban commercial and residential spaces via consumption travel flows in Shanghai. A social network analysis and a community detection method are employed using taxi trajectory data during the daytime to validate the framework. The machine learning-based approach, such as the community detection method, can overcome the limitation regarding spatial uncertainty and spatial effects. The empirical findings suggest that people's commercial activities are sensitive to the power of accessible commercial centers and travel distances. The high-level commercial centers would contribute to the monocentric structure in the outer urban region based on consumption flows. In the central urban region, increasing the number of high-level commercial centers and making the powers of commercial centers hierarchical can contribute to a polycentric mobility pattern of people's consumption. This research contributes to the literature by providing a novel framework to model, analyze and visualize people's mobility based on the trajectory big data, which is promising in future urban research.

Integrating dual evaluation and FLUS model for land use simulation and urban growth boundary delineation in production-living-ecology spaces: a case study of Central Harbin, China

The delineation of Urban Growth Boundaries (UGBs) has been effective in curbing urban sprawl and facilitating sustainable urban development. This research employs an interdisciplinary framework that combines landscape architecture, landscape ecology, and GIS, focusing on Harbin—a typical cold-region city. The results are as follows: (1) The land use simulation demonstrated high reliability, achieving an average accuracy of 0.955 and Kappa coefficients exceeding 0.8, validating the projected urban growth boundaries for Harbin’s central urban area by 2035. (2) Distinct urban growth boundaries were evident under different development scenarios. (3) Evaluations showed that development scenarios prioritizing living and production spaces had better landscape integration. (4) All development scenarios were proximate to the existing built-up areas of the central urban region. This study not only confirms the utility of the FLUS model in accurately simulating urban land use changes but also provides actionable insights for urban expansion strategies in Northeast China’s cold-region cities.

Internal migration and settlement patterns in Australia's regional urban centres

AbstractThe distribution of population between metropolitan regions and their rural counterparts is a topic of interest, due to the growth pressures in large cities and areas of decline in some, typically remote regions. In Australia, fostering population growth in regional urban centres (RUCs) has been a long‐term goal of government policy. Understanding the different profiles, structures, and population dynamics of Australia's RUCs is critical in informing Australian regional development, as well as factors in regional population dynamics in general. This research is focused on patterns of population change through internal migration across Australian RUCs. In addition to a detailed spatial analysis of patterns of population migration flows, this research offers a comprehensive analysis of a range of regional social, economic and infrastructure development factors and their effects on regional migration and population changes. The outputs of the method are new evidence to inform the future regional plan to increase economic and population growth in RUCs. This research contributes to population research and regional planning and provides a baseline for the prepandemic status of regional population dynamics in Australia.

An investigation on the impact of blue and green spatial pattern alterations on the urban thermal environment: A case study of Shanghai

Consistent urbanization and global warming escalates the summer temperatures of the urban, significantly impacting daily lives and endangering well-being. It is difficult to balance urban construction and increasing the blue-green space. Hence, understanding the impact of changes in the blue-green spatial patterns in different spaces on the urban thermal environment is beneficial to the rational layout of urban patterns. Drawing from the case study of Shanghai, by employing bivariate spatial autocorrelation and multiscale geographically weighted regression, the spatial interplay between changes in the blue-green spatial distribution and modifications in land surface temperature grades is scrutinized, thus unraveling the underlying mechanisms of their mutual influence. The findings reveal the following: (1) The transformation of the blue-green spatial pattern exhibited substantial discrepancies between the northern and southern sectors. (2) The alteration of the thermal environment in Shanghai varies significantly spatially and is characterized by a decrease in temperature grade in the southwestern suburbs, an increase in the east, and almost no change in the central urban region. (3) Furthermore, the correlation between the extent of the change in the blue-green spatial pattern and the change in land surface temperature manifested spatial unevenness. (4) Finally, the mechanism underlying the changes of alterations in the blue-green spatial pattern on the thermal environment of the city emanates primarily from the influence of heat exchange areas. The spatial instability of the influence of blue-green spatial pattern on land surface temperature can provide implications for urban planners.

Spatiotemporal Patterning and Matching of Ecosystem Services’ Supply and Demand in Changchun, China

The process of urbanization has deepened the contradiction between ecosystem services’ supply and demand, resulting in a significant risk to ecological security. Thus, it is imperative to conduct an analysis of the correlation between ecosystem services’ supply and demand to achieve sustainable urban growth. This study evaluated the supply, demand, coordination index, and matching types of ecosystem services’ supply and demand in 2000, 2010, and 2020 based on multisource data in Changchun City. The results showed that ecosystem services’ supply decreased overall, while their demand continued to increase from 2000 to 2020, together with their spatial heterogeneity. The regions characterized by a low supply of and high demand for ecosystem services mostly encompassed central urban regions that have undergone a substantial level of socioeconomic advancement. Conversely, the regions characterized by a high supply and low demand were primarily hilly regions with a sparse population that were situated at higher altitudes. There has been slight incoordination between ecosystem services’ supply and demand in Changchun. In the future, it is imperative for sustainable urban development strategies to protect cultivated and ecological lands, extensively enhance the benefits of the lands, and facilitate the coordinated development of cities, agriculture, and ecology.

Villagers' travel burden and the built environment in rural China: Evidence from a national level survey

Travel burden on rural residents is an important theme in transport geography. However, the empirical evidence for this remains scarce. This paper aims to shed light on rural travel burden by examining the relationship between the rural built environment and villagers' travel burden, as measured by the time and money spent on essential and regional trips. A national survey of rural residents in 287 villages across China is analysed. The results show that residents living in rural areas are more likely to be faced with travel burden than are urban residents when accessing livelihood opportunities in local rural settlements and regional urban centres. The built environment attributes are significantly correlated with residents' travel burden. Specifically, the distance from the village to the destination has the strongest relationship with essential trips compared with other built environment variables. Villagers tend to incur higher time costs for an essential or regional trip when paved roads, bus stations and high-quality roads are less accessible. Bus transfer times from the village to the town centre, the population density, and the accessibility of local facilities also show significantly correlation with villagers' travel cost. Moreover, those residents who are elderly, low-income, or have a physical disability are more likely to suffer from high travel burden. The findings will enhance our understanding of the role of land use and transport policies in releasing villagers' travel burden to achieve sustainable transport development in rural contexts.

Small area estimation of trends in household living standards in Uganda using a GMANOVA-MANOVA model and repeated surveys

Panel survey data from Uganda, as well as data from the 2014 Uganda Population and Housing Census have been analyzed. The Growth Curve model with rank restrictions on parameters was used to estimate the small area means. The aim of the analysis was to assess change over time in household living standards (welfare), i.e., to investigate whether households display growth in living standards? whether households grow at the same rates? and whether households in different geographical areas of the country grow at the same rates? Using a GMANOVA-MANOVA model with rank restrictions on parameters, it was established that growth in household standards of living in Uganda varied across small areas. Sub-regions (small areas) with the highest standards of living in Uganda at the endline were Central Urban region, Kampala Urban region and South Western Urban region, while the sub-regions with the lowest standards of living at the endline were North East Rural region, North East Urban region and Eastern Rural region. The sub-regions with the highest growth rates in standards of living were Mid West Urban region, Mid North Rural region, and South Western Urban region. The sub-regions with the highest decline in standards of living were East Central Rural region, East Rural region and West Nile Urban region.

Spatial-temporal pattern and urban-rural gradient of comprehensive ecological security in urban agglomeration in South China from 2000 to 2020.

The ecological security (ES) of urban agglomeration and surrounding environmental system is related to the sustainable development of cities, which is a hot spot that we must pay attention to. In this study, four subsystems composed of natural base, landscape structure, ecosystem stability, and anthropogenic interference were used to evaluate the comprehensive ecological security (CES) of Guangdong-Hong Kong-Macao Greater Bay Area (GHMGBA) in 2000, 2010 and 2020. The results show that CES of the region was generally well. The central urban region of GHMGBA was unsafety with an area proportion of about 24.5%, the periphery was safety with an area proportion of about 43.5%, and the others are transitional zone. From 2000 to 2020, the CES change first slightly decreases and then relatively stable, and the transfer of different safety levels mainly occurs in the transitional zone. In 2010-2020 the transfer of different levels of CES is more frequent than in 2000-2010, indicating that the spatial-temporal pattern of CES fluctuated sharply during 2010-2020. The urban-rural gradient showed that with the increase of distance, CES fluctuations increase, but decreases at about 20-40km, 60-80km and 120-140km away from the city center, which may be sub-urban regions. The overall CES change range gradually decreases with increasing distance from urban centers. This study helps to understand the temporal and spatial distribution of ecological environment and urban-rural gradient in typical urban regions, and provides a reference for the collaborative planning of urban agglomeration.

The socioeconomic impact of the seafood sector at Ireland’s main ports

The seafood sector in Ireland is an important economic and social driver for communities around the coastline of the island. Many coastal communities in Ireland are situated far from regional urban centres with lower levels of infrastructure making these locations less attractive to industry. In order to capture detailed information on seafood supply chains in Ireland and how these evolve over time, a programme of periodical assessments of the top ten fishing ports was developed. While many studies have assessed the links of seafood sectors with the wider economy at the national level or for a specific port, no studies have been found that assess the sector at numerous ports across multiple regions of a country. The assessment detailed here will be carried out every five years utilizing the same methodology where linkages of the seafood sector with other parts of the local, regional and national economies will be assessed by surveying producers and adapting national input-output tables with the survey results. The survey was carried out in 2019 and the data collected referred to production in 2018. The main findings were that for every four direct employees in the seafood sector, three were employed in the wider economy. Significant variance in multipliers was found across ports and subsectors highlighting the importance of assessing multiple ports and regions when assessing the national seafood sector. In this paper the methodology used to carry out this assessment will be detailed with an overview of the results across the main ports.

Impacts of Emission and Meteorological Conditions on Air Pollutants at Various Sites Around the COVID-19 Lockdown in Wuhan

The random forest algorithm was used to separate the mass concentrations of six air pollutants (SO2, NO2, CO, PM10, PM2.5, and O3) contributed by emissions and meteorological conditions. Their variations for five types of sites including Wuhan's central urban, suburb, industrial, the third ring road traffic, and urban background sites were investigated. The results showed that the values of PM2.5/CO, PM10/CO, and NO2/CO during the lockdown period decreased by 10.8-21.7, 9.34-24.7, and 14.4-22.1 times compared with the period before the lockdown, indicating that the contributions of emissions to PM2.5, PM10, and NO2 were reduced. O3/CO increased by 50.1-61.5 times, implying that the secondary formation increased obviously. The contributions of emissions to various types of pollutants all increased after the lockdown. During the lockdown period, affected by the operation of some uninterrupted industrial processes, PM2.5 concentrations in industrial areas dropped the least (20.5%). Compared with the lockdown period, residential activities, transportation, and industrial production were basically restored after the lockdown, resulting in the alleviation of the reduction in PM2.5 emission-related concentrations. The increase in emission-related O3 concentrations could be associated with the decreased NO and PM2.5 concentrations during the lockdown period. The elevated O3 partially offset the improved air quality brought by the reduced NO2and PM2.5 concentrations. After the lockdown, ρ(O3) related with meteorology at the suburban and urban background sites increased by 16.2 μg·m-3 and 16.1 μg·m-3, respectively, which could be attributed to the increased ambient temperature and decreased relative humidity. The decrease in PM2.5 and increase in O3 concentrations caused by reduced traffic and industrial emissions at the third ring road traffic and central urban regions can provide reference for the current coordinated and precise control of PM2.5 and O3 in subregions.

A Long Short-Term Memory-Based Approach for Detecting Turns and Generating Road Intersections from Vehicle Trajectories.

Owing to the widespread use of GPS-enabled devices, sensing road information from vehicle trajectories is becoming an attractive method for road map construction and update. Although the detection of intersections is critical for generating road networks, it is still a challenging task. Traditional approaches detect intersections by identifying turning points based on the heading changes. As the intersections vary greatly in pattern and size, the appropriate threshold for heading change varies from area to area, which leads to the difficulty of accurate detection. To overcome this shortcoming, we propose a deep learning-based approach to detect turns and generate intersections. First, we convert each trajectory into a feature sequence that stores multiple motion attributes of the vehicle along the trajectory. Next, a supervised method uses these feature sequences and labeled trajectories to train a long short-term memory (LSTM) model that detects turning trajectory segments (TTSs), each of which indicates a turn occurring at an intersection. Finally, the detected TTSs are clustered to obtain the intersection coverages and internal structures. The proposed approach was tested using vehicle trajectories collected in Wuhan, China. The intersection detection precision and recall were 94.0% and 91.9% in a central urban region and 94.1% and 86.7% in a semi-urban region, respectively, which were significantly higher than those of the previously established local G* statistic-based approaches. In addition to the applications for road map development, the newly developed approach may have broad implications for the analysis of spatiotemporal trajectory data.

Family Environment and Coping Strategies as Mediators of School Bullying Involvement

ABSTRACT This study examined whether family environment and coping strategies mediate the relationship between adolescents’ bullying involvement (being a bully or victim) and severity of depression. The study utilized a nationally representative school survey and gathered data from 1083 school adolescents (mean age 15.0 ± 1.4 years; 66% females; 46% from the central urban region; 71% had very good to excellent school GPA). The relationship between bullying involvement and depression was partially mediated by family environment and emotion-focused coping. No mediating effect was revealed for problem-focused coping in this relationship. Findings from this study might help understand how the effect of bullying transmits on adolescents’ psychological health, allowing us to supply more in-depth information about the bullying phenomenon than what can be explained by direct effects alone. Family environment and coping strategies used by adolescents seemed to play a critical role in shaping their bullying experience and thus, incorporating these factors into available effective anti-bullying programs can be promising.

Monitoring of urban ecological environment including air quality using satellite imagery.

Rapid urbanisation has highlighted problems in the urban ecological environment and stimulated research on the evaluation of urban environments. In previous studies, key factors such as greenness, wetness, and temperature were extracted from satellite images to assess the urban ecological environment. Although air pollution has become increasingly serious as urbanisation proceeds, information on air pollution is not included in existing models. The Sentinel-5P satellite launched by the European Space Agency in 2017 is a reliable data source for monitoring air quality. By making full use of images from Landsat 8, Sentinel-2A, and Sentinel-5P, this work attempts to construct a new remote sensing monitoring index for urban ecology by adding air quality information to the existing remote sensing ecological index. The proposed index was tested in the Beijing metropolitan area using satellite data from 2020. The results obtained using the proposed index differ greatly in the central urban region and near large bodies of water from those obtained using the existing remote sensing monitoring model, indicating that air quality plays a significant role in evaluating the urban ecological environment. Because the model constructed in this study integrates information on vegetation, soil, humidity, heat, and air quality, it can comprehensively and objectively reflect the quality of the urban ecological environment. Consequently, the proposed remote sensing index provides a new approach to effectively monitoring the urban ecological environment.