Urban Ecological Environment Research Articles

Research on the Development Path of Agricultural Tourism Based on the Sustainable Development of Regional Economy

The gradual acceleration of urbanization and industrialization in China has led to serious pollution of the urban ecological environment, which has adversely affected the health of urban residents. Rural tourism can help city residents get away from traffic jams and polluted urban environments and breathe more fresh air. In addition, rural tourism has a deeper spiritual pursuit. From the perspective of ecological economy, the development prospect of agricultural tourism is broad, and there are many tourism resources in urgent need of development. Therefore, it is necessary for rural areas to strengthen the research on the development of agricultural tourism from the Angle of ecological economy and provide corresponding help for agricultural development. By studying the current situation of agricultural tourism development in Guizhou, this paper makes the following research on the prospects of sustainable regional economic development in the future.

Evaluation of Sustainable Development of the Urban Ecological Environment and Its Coupling Relationship with Human Activities Based on Multi-Source Data

Combining the travel modes of human activities, fully mining multi-source data, and analyzing the relationship between the urban ecological environment and human activities are important topics in urban ecological environment planning. Human activity indicators were constructed based on the data of POI points, OSM road network, and residential areas. Machine learning models such as support vector regression machine, extreme gradient boosting regression, polynomial regression, and random forest regression were combined with remote sensing images to construct an urban ecological environment indicator system. These models were used to conduct regression analysis of urban ecological environment indicators and human activity indicators in Chengdu, China. The research shows that the three indicators of human activities all show a trend of increasing in the center and gradually decreasing in the surrounding areas, while the sustainable urban ecological environment indicators show the opposite trend. On the relationship between urban ecological environment and human activities, XGB has the best effect; the correlation between the street vitality index and the urban function mixing index and the sustainable urban ecological environment is stronger, and the correlation between the walkability measure index of the residential area and the sustainable urban ecological environment is even worse.

Urban Tree Canopy and Environmental Justice: Examining the Distributional Equity of Urban Tree Canopy in Guangzhou, China.

Rapid urbanization has led to a series of environmental problems that are harmful to the physical and mental health of residents. Not only can increasing urban tree canopy (UTC) improve sustainable city development, but it can also effectively promote the quality of life for residents; however, the uneven spatial distribution of UTC can also bring about social justice problems. Currently, there are few studies related to the justice of UTC distribution in China. Based on this, the paper adopts object-oriented image classification technology to interpret and extract UTC data from satellite images, and it uses house price to explore the justice of the spatial distribution of UTC in the main urban area of Guangzhou from the perspective of environmental justice by ANOVA, Pearson correlation coefficient, and bivariate local spatial autocorrelation. The results show that: (1) There is a significant positive correlation between UTC and house price in the main urban area of Guangzhou, and there are regional differences in the distribution of UTC, with the UTC in the "very high" house price group being significantly higher than that in other groups. (2) The spatial clustering of UTC and house price in the main urban area of Guangzhou is found to be "low-low" and "high-high"; thus, it can be concluded that the spatial distribution of UTC in the main urban area of Guangzhou is uneven. This is an environmental injustice, as the areas with low UTC are spatially clustered in old residential areas, while the areas with high UTC are spatially clustered in commercial housing estates with high house prices. The study shows that urban tree planting should not only focus on quantitative improvement but also on equitable spatial layouts to promote social equity and justice thereby improving the urban ecological environment and promoting healthy urban development.

Urban Ecological Environment Quality Evaluation and Territorial Spatial Planning Response: Application to Changsha, Central China.

Scientific territorial spatial planning is of great significance in the realization of the sustainable development goals in China, especially in the context of China's ecological civilization construction and territorial spatial planning. However, limited research has been carried out to understand the spatio-temporal change in EEQ and territorial spatial planning. In this study, Changsha County and six districts of Changsha City were selected as the research objects. Based on the remote sensing ecological index (RSEI) model, the spatio-temporal changes in the EEQ and spatial planning response in the study area during 2003-2018 were analyzed. The results reveal that (1) the EEQ of Changsha declined and then rose between 2003 and 2018, showing an overall decreasing trend. The average RSEI declined from 0.532 in 2003 to 0.500 in 2014 and then increased to 0.523 in 2018, with an overall decrease of 1.7%. (2) In terms of spatial pattern changes, the Xingma Group, the Airport Group and the Huangli Group in the east of the Xiangjiang River had the most serious EEQ degradation. The EEQ degradation of Changsha showed an expanding and polycentric decentralized grouping pattern. (3) Massive construction land expansion during rapid urbanization caused significant EEQ degradation in Changsha. Particularly, the areas with low EEQ were concentrated in the areas with concentrated industrial land. Scientific territorial spatial planning and strict control were conducive to regional EEQ improvement. (4) The prediction using the urban ecological model demonstrates that every 0.549 unit increase in NDVI or 0.2 unit decrease in NDBSI can improve the RSEI of the study area by 0.1 unit, thus improving EEQ. In the future territorial spatial planning and construction of Changsha, it is necessary to promote the transformation and upgrading of low-end industries into high-end manufacturing industries and control the scale of inefficient industrial land. The EEQ degradation caused by industrial land expansion needs to be noted. All of these findings can provide valuable information for relevant decision-makers to formulate ecological environment protection strategies and conduct future territorial spatial planning.

Calculation model and application of ecological water demand of watercourses in low-carbon sponge urban areas based on DPSA algorithm

Abstract To improve the prediction ability of river ecological water requirement in sponge low-carbon urban areas, a prediction model of it based on big data analysis was proposed. A statistical analysis model of river ecological water requirement in sponge and low-carbon urban areas was established. Differential Particle Swarm Optimization Algorithm (DPSA) was used to calculate the characteristic quantity of river ecological water requirement in sponge and low-carbon urban areas. The detection model of ecosystem hydrothermal balance and lognormal distribution time series of groundwater level were constructed for the prediction of river ecological water requirement in sponge and low-carbon urban areas. Combined with the integrated control method of river ecological environment water demand forecasting and information exchange, a decentralized control model of river ecological water demand in low-carbon sponge urban areas was established. Through applicability analysis and model measurement analysis, combined with comprehensive index measurement, the prediction model of river ecological water requirement in low-carbon sponge urban areas was optimized. The empirical analysis results show that this method has good adaptability and high prediction accuracy for the prediction of river ecological water requirement in sponge low-carbon urban areas and improves the reliability of the prediction of river ecological water requirement and the matching level of urban ecological environment.

UGS-1m: fine-grained urban green space mapping of 31 major cities in China based on the deep learning framework

Abstract. Urban green space (UGS) is an important component in the urban ecosystem and has great significance to the urban ecological environment. Although the development of remote sensing platforms and deep learning technologies have provided opportunities for UGS mapping from high-resolution images (HRIs), challenges still exist in its large-scale and fine-grained application due to insufficient annotated datasets and specially designed methods for UGS. Moreover, the domain shift between images from different regions is also a problem that must be solved. To address these issues, a general deep learning (DL) framework is proposed for UGS mapping in the large scale, and fine-grained UGS maps of 31 major cities in mainland China are generated (UGS-1m). The DL framework consists of a generator and a discriminator. The generator is a fully convolutional network designed for UGS extraction (UGSNet), which integrates attention mechanisms to improve the discrimination to UGS, and employs a point-rending strategy for edge recovery. The discriminator is a fully connected network aiming to deal with the domain shift between images. To support the model training, an urban green space dataset (UGSet) with a total number of 4544 samples of 512×512 in size is provided. The main steps to obtain UGS-1m can be summarized as follows: (a) first, the UGSNet will be pre-trained on the UGSet in order to obtain a good starting training point for the generator. (b) After pre-training on the UGSet, the discriminator is responsible for adapting the pre-trained UGSNet to different cities through adversarial training. (c) Finally, the UGS results of 31 major cities in China (UGS-1m) are obtained using 2179 Google Earth images with a data frame of 7′30′′ in longitude and 5′00′′ in latitude and a spatial resolution of nearly 1.1 m. An evaluation of the performance of the proposed framework by samples from five different cities shows the validity of the UGS-1m products, with an average overall accuracy (OA) of 87.56 % and an F1 score of 74.86 %. Comparative experiments on UGSet with the existing state-of-the-art (SOTA) DL models proves the effectiveness of UGSNet as the generator, with the highest F1 score of 77.30 %. Furthermore, an ablation study on the discriminator fully reveals the necessity and effectiveness of introducing the discriminator into adversarial learning for domain adaptation. Finally, a comparison with existing products further shows the feasibility of the UGS-1m and the great potential of the proposed DL framework. The UGS-1m can be downloaded from https://doi.org/10.57760/sciencedb.07049 (Shi et al., 2023).

Very High Resolution Images and Superpixel-Enhanced Deep Neural Forest Promote Urban Tree Canopy Detection

Urban tree canopy (UTC) area is an important index for evaluating the urban ecological environment; the very high resolution (VHR) images are essential for improving urban tree canopy survey efficiency. However, the traditional image classification methods often show low robustness when extracting complex objects from VHR images, with insufficient feature learning, object edge blur and noise. Our objective was to develop a repeatable method—superpixel-enhanced deep neural forests (SDNF)—to detect the UTC distribution from VHR images. Eight data expansion methods was used to construct the UTC training sample sets, four sample size gradients were set to test the optimal sample size selection of SDNF method, and the best training times with the shortest model convergence and time-consumption was selected. The accuracy performance of SDNF was tested by three indexes: F1 score (F1), intersection over union (IoU) and overall accuracy (OA). To compare the detection accuracy of SDNF, the random forest (RF) was used to conduct a control experiment with synchronization. Compared with the RF model, SDNF always performed better in OA under the same training sample size. SDNF had more epoch times than RF, converged at the 200 and 160 epoch, respectively. When SDNF and RF are kept in a convergence state, the training accuracy is 95.16% and 83.16%, and the verification accuracy is 94.87% and 87.73%, respectively. The OA of SDNF improved 10.00%, reaching 89.00% compared with the RF model. This study proves the effectiveness of SDNF in UTC detection based on VHR images. It can provide a more accurate solution for UTC detection in urban environmental monitoring, urban forest resource survey, and national forest city assessment.

An ecological environment impact assessment of municipal solid waste based on grey prediction model

Aiming at the problem of low accuracy in the impact assessment of urban waste on ecological environment, a method of urban waste ecological environment impact assessment based on grey prediction model is proposed. First, the pollution type of urban waste is determined, and the important pollution data of urban waste is extracted with the help of the calculation of comprehensive water quality identification index. Then, the total ranking of pollution data is determined by the square root method, the judgement matrix is set to calculate the weight of pollution data, and the urban waste ecological environment pollution index system is constructed. Lastly, with the help of grey prediction model, the positive correlation between urban waste and ecological environment is determined, and the urban waste ecological environment impact assessment algorithm is designed to complete the impact assessment. The results show that the evaluation accuracy can be effectively improved by using the evaluation method in this paper.

The impact modelling of urban and rural land planning and development on the ecological environment around the city

In order to effectively explore the impact of urban and rural land planning and development on the environment, there is a need to improve the research accuracy and environmental quality, and summarise the impact of urban and rural land planning and development on the periphery of the city. According to the results of impact analysis, the information of urban and rural land development intensity and the information of ecological environment around the city are counted. The global scheduling method is used to calculate the contribution of promoting factors, so as to construct the impact research model. The urban and rural land development intensity information and ecological environment information are input into the model, and the output of the model is the impact research result. The experimental results show that the accuracy of ecological environmental impact analysis around the city remains above 90% after the application of this method.

Retracted: Temporal and Spatial Differences of Urban Ecological Environment and Economic Development Based on Graph Neural Network.

[This retracts the article DOI: 10.1155/2022/7078671.].

The impact of cultural diversity on urban housing prices in China

<p>Using the commercial housing price data of 254 cities at prefecture level and above in China, this paper measures the cultural diversity by the diversity of Chinese dialects, and studies the impact of regional culture represented by dialects on urban housing prices. The research shows that after controlling the economic development level of the city, the urban ecological environment and other factors, the cultural diversity measured by dialect types has a significant negative impact on the price of urban commercial housing, that is, the more diverse the culture, the lower the house price, and the cultural diversity will restrain the house price by hindering the inflow of local population.</p>

Impacts of trees-grass area ratio on thermal environment, energy saving, and carbon benefits

Rapid urbanization potentially increases the diversity of building morphological characteristics (e.g., heights), causing urban ecological environment problems, such as urban heat islands, energy loss, and carbon emissions. Greenery (e.g., trees and grasses) can alleviate urban environmental problems, further improving the benefits of cooling effect, energy saving, and carbon emission reduction. With limited land resources, it is significant to effectively combine multiple greeneries and quantitatively optimize the greenery design. This paper designed the trees-grass area ratio (TAR) and explored its effect on the benefits at the community scale. The ranges of 0–90% TARs were considered in the communities as well as three building heights. A low-cost computational fluid dynamics (CFD) method of volumetric source term (VST) was proposed to simulate the thermal environment. Energy performance simulation of buildings was performed. Results indicated that the VST method can reduce computing costs by up to 81% compared with the traditional simulation. Air temperature (T), energy consumption (E), and carbon emission (Ce) decreased with increasing TAR in three types of communities. Carbon sequestration (Cs) linearly increased with increasing TAR. When the TAR was 90%, the maximum reduction of T, E, and Ce were 6 °C, 17.3%, and 20%, respectively. Furthermore, the quantified relationships between TAR, building height, and benefits were proposed. This work can serve as a guideline for the optimal design of urban ecological environment.

Evaluation of Urban Ecological Environment Quality Based on Google Earth Engine: A Case Study in Xi’an, China

Evaluation of Urban Ecological Environment Quality Based on Google Earth Engine: A Case Study in Xi’an, China

Multi-temporal evaluation and optimization of ecological network in multi-mountainous city

In karst multi-mountainous areas, there are a large number of urban remnant mountains (URMs) in urban built-up areas, which are an important part of urban green space system and have important and unique ecosystem service functions. However, the densifying development inside the city has been leading to the reduction of the number and area of the URMs and the decrease of the connectivity of the urban green space system, resulting in the fragile urban ecological environment. The construction and optimization of ecological network (EN) is an effective way to protect important urban ecological patches and improve the stability of urban green space ecosystem. Taking the central area of Anshun, a typical multi-mountainous city, as the study area, based on the land use data of 2007, 2012 and 2017, the ecological sources were identified by morphological spatial pattern analysis (MSPA) and the potential ecological corridors were extracted by the minimum cumulative resistance model (MCR), and the ENs of the three periods were identified. 18 ecological sources were selected for each of the three periods, with a total area of 833.67 hm2, 713.25 hm2 and 806.85 hm2, respectively and the intersection area of ecological sources reached 650.58 hm2. The ecological corridors and ecological sources dwindled with time. The Gravity model was used to extract the important EN corridor, the InVEST model was used to quantify the comprehensive habitat quality. The EN was optimized by adding extra ecological sources, mending ecological breakpoints and extracting habitat quality map patches. It is suggested to add 6 ecological sources and 34 ecological corridors, protect ecological nodes and build stepping stone patches. The results of this study could not only provide a scientific and reasonable basis for the ecological protection and the development of ecological protection strategies in the urban central area of Anshun, but also enrich the theoretical research of urban biodiversity conservation planning and ecological restoration practice in multi-mountainous cities.

Does smart city policy improve corporate green technology innovation? Evidence from Chinese listed companies

As a new pattern of urbanization, smart cities offer a set of initiatives to achieve a win-win situation for both environmental protection and economic development. This paper aims to explore the influence of smart city policy (SCP) on green technology innovation (GTI) by Chinese listed enterprises. Employing the difference-in-differences (DID) approach, the results show that SCP promotes enterprises’ GTI. This finding remains valid after various robustness tests, which include the parallel trend test, PSM-DID, placebo test, the substitution of estimation model, replacement of dependent variable, and the exclusion of the impacts of other policies. Additional tests reveal that SCP improves GTI through government environmental subsidy, corporate environmental awareness, and research and development investments. Furthermore, the heterogeneity analysis suggests that our findings are more prominent in subsamples during the growth stage, in high-tech industries, and in eastern regions. Our research is vital to the urban ecological environment and high-quality economic development.

An Evaluation of Factors Influencing Urban Integration and Livelihood of Eco-Migrant Families: Quantitative Evidence from Western China

Background. In China, the policy of ecological migration is a new approach to protect the urban ecological environment. However, the changes in livelihood capital before and after migration and the matching relationship between the livelihood capital and livelihood model of migrants are rarely explored. Our study aims to address these research gaps to determine factors affecting the urban integration of eco-migrant families and their means of sustainable livelihood. Methods. We used the survey data of migrant households in China in 2017 and 2018. Heckman’s two-stage model and the endogenous transformation regression model were applied for data analysis. Results. First, most migrants are willing to integrate into urban life after relocation, but the efficiency of their integration into urban life needs to be improved. Second, differences in demographic background and geographic location significantly affect the decisions of migrants in urban integration. Third, family heterogeneity has the greatest impact on the degree of urban integration, followed by geographical location. Lastly, the high degree of urban integration of migrants has a significant impact on their household income. Conclusions. Local governments and communities should provide immigrant families migrating from rural to urban China with more social and economic resources for their better socioeconomic integration.

GIS-based Ecological Risk Assessment on Land Use In Chongqing City, China

Ecological risk assessment (ERA) is a process of predicting the possibility of harmful effects of environmental pollutants on an entire or part of the ecosystem, which is closely connected with the early human health risk assessment. A rational assessment of ecological risks in an urban area can provide great significance for urban landscape pattern optimization, urban ecological risk warning mechanism establishment, and urban ecological environment risk reduction. This study is based on GIS system to assess the ecological risk of land use in Chongqing in 2020, according to the basic theoretical framework and method system of ecological risk assessment. The main process is using remote sensing image data to construct the Ecological Risk Index (ERI) from the perspective of landscape patterns to reflect the potential impact of resource-based urban land use on the ecological environment. In addition, the ArcGIS spatial analysis method was used to evaluate Chongqing's ecological risk. As a result, high-risk area close to the water body just occupied a small part of Chongqing City (around 5%) and this area should be taken into protective measures urgently.

SPATIOTEMPORAL CHANGES OF THE HABITAT QUALITY AND THE HUMAN ACTIVITY INTENSITY AND THEIR CORRELATION IN MOUNTAINOUS CITIES

As the urbanization is being rapidly boosted, the urban habitat quality has been significantly disturbed by human activities through land use, which highly affects the urban ecological environment and sustainable development of social economy. However, the change characteristics of the habitat quality and human activities in different topographic gradients in rapidly urbanized mountainous cities remain unclear. Accordingly, Guiyang in China, is selected as the representative of typical mountain cities. The change characteristics of the habitat quality, the human activity intensity and their correlation in mountainous cities from 2000 to 2020, are analyzed using the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model, as well as the ArcGIS software based on the remote sensing interpretation data in 2000, 2010 and 2020. The results demonstrate that the overall habitat quality in Guiyang decreased by 0.0304, while the human activity intensity increased by 0.0287 from 2000 to 2020. The amount of changes of the habitat quality and the human activity intensity in Guiyang from 2010 to 2020, are higher than those from 2000 to 2010. The amount of changes of the habitat quality and the human activity intensity in Guiyang decreases with the increase of the slope. The central and southern parts of Guiyang are the highlight areas with a significant decline of habitat quality and significant increase of human activity intensity. The areas with an increased habitat quality and decreased human activity intensity are sporadically distributed. A significant negative correlation is reported between the change of the habitat quality and human activity intensity in Guiyang. In addition, a prominent spatial heterogeneity is identified in the local indicators of the spatial association (LISA) map. The significant increase in the artificial land and the decrease in the natural land as affected by the rapid urbanization, act as crucial factors leading to the decline of the habitat quality and the increase in the human activity intensity in mountainous cities.

Comparative study of domestic and international mandatory policies on three-dimensional greening - Shenzhen as an example

With the accelerated urbanization in China, the phenomenon of insufficient green space in urban built-up areas is becoming increasingly prominent, and the construction of rooftop gardens to increase the green coverage of cities and improve the urban ecological environment has become an important element of urban construction. Taking Shenzhen as an example, this paper studies the current three-dimensional greening policies and regulations of the Shenzhen government, the three-dimensional greening policies and regulations of advanced foreign cities and analyses the problems that exist at the level of urban green space planning and policies and regulations in Shenzhen. In the course of the study, it is found that there are three problems in its, Shenzhen's three-dimensional greening policy planning: small scope of application, lack of planning elements, and low degree of compulsion, By combining the governance experiences of other cities, this paper will propose corresponding improvement solutions and optimization suggestions to address the shortcomings of urban three-dimensional greening policies from the policy level and offer suggestions for the cause of three-dimensional greening in Shenzhen.

The Administrative transformation of the Urban Authority and the Emerging Quarantined Rural Satellite Towns (ERSTs) in Urban Authorities. The Case of Dodoma National Capital City, Tanzania

This study explores how the evolutionary changes in urban administrative status from lowest (Town) to highest (City) ranks resulted in the Re-Emergence of Un – Ecological Quarantined Rural Satellite Towns and Rural Operations in Dodoma Tanzanian National Capital City. Under such circumstances, Un – ecological Rural operations and urbanisms become more prevalent in 28 newly emerged Quarantined Rural Satellite Towns in the City locality which enhances the disappearance and reappearance of Un - Ecological urban environment and land use land cover changes, land degradation in the City locality. The empirical evidence for this study was drawn from interviewing 443 respondents in 13 wards and 53 sub wards and through analyzing Landsat satellite images of 1998, 2008, 2018 and 2022 years by GIS. The study findings revealed that Local people are not relocated out of the city but instead urbanite at a rural scale into the City locality. Objectively, Un -Ecological Rural Operations in 28 Rural Satellite Towns in Dodoma City localities have contributed more to the Urban Ecological Environment degradation to a point that built-up land in the period of 24 years from 1998 to 2022 increased by 2221 ha, bare land by 15,737 ha and vegetation declined by 17,958 ha. If Dodoma City persists in the same way up to 2030 without Green Building Concepts and Design, New Urbanism and Ecological Modernization theories interventions it will lose the potential of being a resilient and habitable City. Sustainable development principles are recommended to be utilized in all the major development projects to be carried out in the city advert the situation.