Area Of Beijing Research Articles

Quantifying and assessing nitrogen sources and transport in a megacity water supply watershed: Insights for effective non-point source pollution management with mixSIAR and SWAT models

The expansion and intensification of human activities have resulted in excessive nitrogen (N) in rivers, causing worldwide concern. To effectively manage agricultural non-point source pollution and ensure a safe drinking water supply in watersheds, it is crucial to trace and quantify the primary sources and spatial distribution patterns of N. In response to the challenge of unclear sources and agricultural non-point source pollution, this study utilised the Bayesian isotope mixing model and Soil and Water Assessment Toolmodel to identify the dominant nitrate sources and transformation processes. These models were employed to quantify N retention by the mainstream and tributaries in the Bai River Basin, which directly impacts the safety of drinking water in Beijing. Total N (TN) concentrations in the Yunzhou Reservoir (4.22 ± 0.04 mg.L˗1) and Miyun Reservoir (2.88 ± 0.62 mg.L˗1) inlets in autumn and winter were V class (2 mg.L˗1) category as per GB 3838–2002 standards. This implies higher risks of eutrophication and algal blooms exceeding the standards at individual points and seasons in the Bai River. Fertilisers were the main nitrate source in the Bai River Basin, contributing 44.6% during the dry season and 62.9% during the wet season, suggesting that nitrate is more susceptible to leaching and runoff during rainy periods. Rainfall was not a major contributor, with only 3.2% and 2.9% originating from the Hebei and Beijing areas of the Bai River, respectively. Annually, the Bai River Basin exports loads of approximately 629.3 t.a˗1 of TN and 433.7 t.a˗1 of organic N (Org-N) from the Bai River Basin land to the river. The TN and Org-N loads at the final destination in the Miyun Reservoir were 521.3 t.a˗1 and 100.3 t.a˗1, respectively. Of the exported TN and Org-N, 17.16% and 76.87%, respectively, were retained in the river network. Consequently, N transformation occurred in the Bai River, with nitrification–denitrification being particularly dominant. Nitrification was more evident in the nitrate-enriched river.

A DEEP LEARNING APPROACH USING VERY-HIGH SPATIAL RESOLUTION GAOFEN-2 IMAGES TO SUPPORT THE UNITED NATIONS SUSTAINABLE DEVELOPMENT GOAL INDICATOR 11.7.1 ASSESSMENT

Abstract. Since the proposal of the "2030 Agenda", the United Nations Sustainable Development Goal indicator 11.7.1 aims to calculate the accessibility and quality of urban open spaces(UOS). An accurate and rapid assessment framework of UOS is of great significance for urban sustainable development. Previous research on UOS has mainly focused on the evolution patterns of UOS, with little research on assessments of their accessibility for different population structures (i.e., men vs. women, young vs. older). In this study, a U-Net deep learning network was used for training from 3072 annotated samples of urban green spaces(UGS) which was created based on Gaofen-2 remote sensing images. The trained model was used to identify UGS within five districts of Beijing at sub-meter level, incorporated with Open Street Map and area of interest data. A spatial analysis was conducted for accessibility of UOS, finding that most of the UOS in the central urban area of Beijing can be reached within 10 minutes, but access to the eastern and western edges is poorer (more than 30 minutes). Finally, using Worldpop data, the accessibility of UOS was statistically analyzed for different ages and genders. The results show that UOS accessibility rate for the elderly and children reaches over 90% (10 minutes accessibility).

The Effect of Different Vegetation Restoration Types on Soil Quality in Mountainous Areas of Beijing

Soil quality is a very important indicator used to assess ecosystem restoration states in terms of vegetation recovery and establishment. Evaluating the soil quality of different vegetation restoration types in mountainous areas of Beijing and identifying their influencing factors would provide a scientific basis and be helpful for vegetation restoration in the future. Six vegetation types (or communities), including Platycladus orientalis (L.) Franco pure forest (POP), Pinus tabulaeformis Carr. pure forest (PTP), Platycladus orientalis–Pinus tabulaeformis mixed forest (PPM), Platycladus orientalis coniferous and broadleaved mixed forest (POCB), Pinus tabulaeformis coniferous and broadleaved mixed forest (PTCB), deciduous broadleaved mixed forest (DBMF), and one area of non-afforested land (NF), with similar stand conditions were selected and fourteen factors of soil physical and chemical characteristics were measured and used to establish a total data set (TDS), while a minimum data set (MDS) was obtained by using the principal component analysis (PCA) and Pearson correlation analysis methods. Two scoring methods, linear (L) and non-linear (NL), were used to calculate the soil quality index (SQI), and the key factors influencing soil quality by vegetation were identified by a general linear model (GLM), PCA, and correlation analysis. The results showed that: (1) The screened MDS indicators which showed good relationships with the SQIs in the study areas were total nitrogen (TN), sand content, total potassium (TK), pH, and available water capacity (AWC). The SQI–NLM method has better applicability. (2) The contribution rates of vegetation to different soil factors accounted for 28.644% (TN), 21.398% (sand content), 24.551% (TK), 16.075% (pH), and 9.332% (AWC). (3) TN showed a positive relationship with all vegetation types; the content of TN in PTCB and DBMF was obviously larger than in the other types in the 0–10 cm layer; PPM, PTCB, and POCB affected the sand content, which showed negative correlativity; and DBMF showed positive correlativity with AWC. The mechanism of how different species affect TN, sand content, and AWC should be focused on and taken into consideration in further studies.

Examining spatial coordination of human-land-industry-service system from a regionalization approach: A case study of Beijing

Sustainable development requires a better understanding of the coupling relationship among population, urban land use, industry, and city services since they are closely related to the benefits of human beings. However, previous studies tend to focus on population and land use for urbanization-targeted insights without considering city services and industry development from a people-centered on the fine scale. This research aims to fill this gap by examining the spatial coordination of the human-land-industry-service system combining the coupling coordinated degree model and a regionalization approach with Beijing as a case study. Results show that about 3% area of Beijing is enjoying favorable coordination along with over 6% having moderate coordination, and sub-systems like human-land are experiencing better-coordinated development. Though the well-known monocentric structure of Beijing dominated by built-up expansion exists, sub-centers represented by Tongzhou and Changping rise to possibly alleviate the non-capital functions. In addition, Gini coefficients at 200-, 500-, 1000-, and 2000-meter scales decrease, and coarser resolutions present more continuous and smoother patterns. Three points concerning the unbalanced development, the scale effect, and the urbanization pattern of Beijing are further discussed. Our framework could be easily extended to explore interactions in other systems with the ability to consider both the fine details and the general spatial regionalization patterns.

Space, people, activity and time: A theoretical model for understanding children's outdoor play with specific reference to the historical protected central areas of Beijing, China

AbstractAiming to document children's daily outdoor play experiences in a rapidly developing urban environment, this research is based on a case study involving children living in the central Shichahai area in Beijing to provide an understanding from the scarce Chinese perspective. Based on the development of the SPIT model, this study proposes the SPAT model and investigates its subject from dimensions of space, people, activities and time. This study employs a qualitative triangulation approach to investigating childhood experience, using data collection methods including interviews, observations and diaries. This data record the children's outdoor play experience and its analysis addresses the lack of knowledge and understanding of childhood play experience in Chinese cities. The factors which have a profound influence on children's play experience in a developing urban contexts are discussed and interpreted in terms of a range of factors which have influenced the transformation of the urban environment, including economic development, policy implications and cultural traditions. Based on the insights from this evidence, this study offers recommendations that the SPAT model provides a mechanism for exploring children and their experiences of outdoor environments in different contexts which has a strong adaptation to various contexts.

The Effect of Meteorological Features on Pollution Characteristics of PM2.5 in the South Area of Beijing, China

Based on the air quality monitoring data and meteorological data, the pollution characteristics of PM2.5 in southern Beijing and relationships between PM2.5 levels and meteorological features were analyzed. The results showed that during the investigation period, daily air quality was characterized as “excellent” and “favorable” (<75 µg m−3) on 77% of days in southern Beijing, and there were only two days with serious air pollution (>250 µg m−3). The PM2.5 concentration displayed obvious monthly variations with the highest concentration in November and the lowest concentration in August. When PM2.5 pollution episodes occurred (>75 µg m−3) in this area, the wind direction was often south and southeast with low wind speed (<3 m∙s−1), followed by southwest wind; in addition, the air temperature was low (<10 °C) and the relative humidity was high (>75%). The air quality of the study area was affected by the pollution transmission form the surrounding areas, especially the southeastern and the southern transmission paths. The PM2.5 concentration was positively correlated with SO2, NO2 and CO, and negatively correlated with O3. Therefore, to further improve the air quality in the study area, it is necessary to coordinate the control of PM2.5 and O3.

Knee Point‐Based Multiobjective Optimization for the Numerical Weather Prediction Model in the Greater Beijing Area

AbstractDetermination of the optimal parameter values in numerical weather prediction (NWP) models has a significant impact on predictions. Here, we propose a knee point‐based multiobjective optimization (KMO) method to find an optimal solution of the NWP model parameters. We apply it to optimize the Weather Research and Forecasting (WRF) model's summer precipitation and temperature simulations for the Greater Beijing area. The results showed that it required fewer than 125 samples (i.e., 25 times the number of dimensions of the parameter space) to obtain the WRF model's optimal parameter values. The optimal parameters determined by KMO outperform the default parameters in WRF simulations for summer precipitation and temperature prediction in the Greater Beijing area, across all periods (calibration, validation, and testing). Additionally, clear physical interpretations are provided to explain why the optimal parameters lead to improved precipitation and temperature forecasting. Overall, the proposed method is effective and efficient to improve NWP.

Typical Plantation Water Use Strategies Are Determined by Environmental Conditions and Plant Eco-Physiology in Beijing, China

The forest ecosystem of Beijing is an important barrier that preserves the ecological environment in the capital city of China. Therefore, the study of plant water utilization techniques in Beijing holds considerable importance in establishing a theoretical framework for the rehabilitation, administration, and preservation of forest ecosystem structures and functions. Here, the samples of precipitation, xylem water, and soil water were collected during the months of August and December 2021 from both mountainous and plains areas of Beijing. We measured the hydrogen and oxygen stable isotope values (δ2H and δ18O, respectively) and demonstrated the water use strategies of two typical tree species (Pinus tabuliformis Carr. and Acer truncatum Bunge) using the MixSIAR model. Divergent water use strategies were found in the mountainous and plains areas of Beijing. In the mountainous area, the two tree species exhibited seasonal differences in water use strategies. The xylem water of P. tabuliformis was mainly derived from the surface soil water (0~20 cm). In contrast, the xylem water of A. truncatum mainly originated from the surface soil water during the growing season, and it mainly originated from the deep soil water (60~100 cm) during the nongrowing season. However, in the plains area, the water sources of P. tabuliformis and A. truncatum did not show seasonal differences and originated mainly from the deep soil water. The findings of our study emphasize the notable disparity in water utilization strategies among tree species in the mountainous and plains areas. Consequently, it is imperative to formulate sustainable forestry management approaches that align with the water use efficiency of trees in various locations of Beijing.

Geological Hazard Identification and Susceptibility Assessment Based on MT-InSAR

Geological hazards often occur in mountainous areas and are sudden and hidden, so it is important to identify and assess geological hazards. In this paper, the western mountainous area of Beijing was selected as the study area. We conducted research on landslides, collapses, and unstable slopes in the study area. The surface deformation of the study area was monitored by multi-temporal interferometric synthetic aperture radar (MT-InSAR), using a combination of multi-looking point selection and permanent scatterer (PS) point selection methods. Random forest (RF), support vector machine (SVM), convolutional neural network (CNN), and recurrent neural network (RNN) models were selected for the assessment of geological hazard susceptibility. Sixteen geological hazard-influencing factors were collected, and their information values were calculated using their features. Multicollinearity analysis with the relief-F method was used to calculate the correlation and importance of the factors for factor selection. The results show that the deformation rate along the line-of-sight (LOS) direction is between −44 mm/year and 28 mm/year. A total of 60 geological hazards were identified by combining surface deformation with optical imagery and other data, including 7 collapses, 25 unstable slopes, and 28 landslides. Forty-eight of the identified geological hazards are not recorded in the Beijing geological hazards list. The most effective model in the study area was RF. The percentage of geological hazard susceptibility zoning in the study area is as follows: very low susceptibility 27.40%, low susceptibility 28.06%, moderate susceptibility 21.19%, high susceptibility 13.80%, very high susceptibility 9.57%.

Identifying Major Diurnal Patterns and Drivers of Surface Urban Heat Island Intensities across Local Climate Zones

Deepening the understanding of diurnal characteristics and driving mechanisms of surface urban heat islands (SUHIs) across different local climate zones (LCZs) and time scales is of great significance for guiding urban surface heat mitigation. However, a comprehensive investigation of SUHIs from the diurnal, local, multi-seasonal, and interactive perspectives remains a large gap. Here, we generalized major diurnal patterns of LCZ-based SUHI intensities (SUHIIs) throughout 2020 over the urban area of Beijing, China, based on diurnal temperature cycle modeling, block-level LCZ mapping, and hierarchical clustering. A geographical detector was then employed to explore the individual and interactive impacts of 10 morphological, socioeconomic, and meteorological factors on the multi-temporal spatial differentiations of SUHIIs. Results indicate six prevalent diurnal SUHII patterns with distinct features among built LCZ types. LCZs 4 and 5 (open high- and mid-rise buildings) predominantly display patterns one, two, and five, characterized by an afternoon increase and persistently higher values during the night. Conversely, LCZs 6, 8, and 9 (open, large, and sparsely built low-rise buildings) mainly exhibit patterns three, four, and six, with a decrease in SUHII during the afternoon and lower intensities at night. The maximum/minimum SUHIIs occur in the afternoon–evening/morning for patterns 1–3 but in the morning/afternoon for patterns 5–6. In all four seasons, the enhanced vegetation index (EVI) and gross domestic product (GDP) have the top two individual effects for daytime spatial differentiations of SUHIIs, while the air temperature (TEM) has the largest explanatory power for nighttime differentiations of SUHIIs. All factor interactions are categorized as two-factor or nonlinear enhancements, where nighttime interactions exhibit notably greater explanatory powers than daytime ones. The strongest interactions are EVI ∩ GDP (q = 0.80) during the day and TEM ∩ EVI (q = 0.86) at night. The findings of this study contribute to an improved interpretation of the diurnal continuous dynamics of local SUHIIs in response to various environmental conditions.

Surface energy balance fluxes in a suburban area of Beijing: energy partitioning variability

Abstract. Measurements of radiative and turbulent heat fluxes for 16 months in suburban Miyun with a mix of buildings and agriculture allows the changing role of these fluxes to be assessed. Daytime turbulent latent heat fluxes (QE) are largest in summer and smaller in winter, consistent with the net all-wave radiation (Q*), whereas the daytime sensible heat flux (QH) is greatest in spring but smallest in summer rather than in winter, as commonly observed in suburban areas. The results have larger seasonal variability in energy partitioning compared to previous suburban studies. Daytime energy partitioning is between 0.15–0.57 for QH/Q* (mean summer = 0.16; winter = 0.46), 0.06–0.56 for QE/Q* (mean summer = 0.52; winter = 0.10), and 0.26–7.40 for QH/QE (mean summer = 0.32; winter = 4.60). Compared to the literature for suburban areas, these are amongst the lowest and highest values. Results indicate that precipitation, irrigation, vegetation growth activity, and land use and land cover all play critical roles in the energy partitioning. These results will help to enhance our understanding of surface–atmosphere energy exchanges over cities and are critical to improving and evaluating urban canopy models needed to support integrated urban services that include urban planning to mitigate the adverse effects of urban climate change.

Analysis of urban water dissipation characteristics considering anthropogenic impacts: a case study in Beijing

Abstract Urban water dissipation is a significant part of the urban hydrologic cycle and has a typical natural–social dualistic attribute. Besides natural evaporation, the water dissipation in people's daily life and production process cannot be ignored. This study developed an urban water dissipation model based on different land uses and applied it in urban-built areas in Beijing. The results showed that the water dissipation of buildings and green spaces occupied the dominant position, and the water dissipation intensity of each district exceeded 500 mm, among which the six core districts were 700–1,100 mm. Comparing the water dissipation contribution rate and area rate of each underlying surface, it showed that the water dissipation intensity from strong to weak was building, water surface, green spaces, and hardened ground. According to the dualistic analysis of urban water dissipation, the contribution rates of social water dissipation in the six core districts were 45.3–69.1%, which was higher than the 17.8–36.1% of other suburbs obviously. This study reflected that the higher the degree of regional urbanization, the greater the water dissipation intensity, and artificial water dissipation was the main influencing factor.

Application research of comprehensive geophysical prospecting in a typical slope of abandoned open-pit in Beijing, China

New government policy in China has facilitated research on the hazards in open-pit mine slopes. Remote sensing, geological, geophysical, and computer simulation techniques have been applied to obtain better information in slope investigation. In this study, we investigated the slope of the Qianlingshan open-pit mine area in Beijing, China. Electrical resistivity tomography and ground-penetrating radar were used, and the results were compared with borehole data to ascertain the slope structure, potential slip surface, and deformation zone. A geological model of the slope was established, and the slope stability was analyzed by numerical simulation. The results showed that the slope had an unstable surface layer over bedrock, and probable creep sliding-tension deformation. In addition, the slope would become less stable in wet conditions. The geological methods used in this study will provide a useful reference for further slope stability analysis and prevention. We took the Qianlingshan open-pit slope in Beijing, China, as the research object, by comprehensive application of historical remote sensing images analysis, field investigation, electrical resistivity tomography (ERT) and ground penetrating radar (GPR), and comparative analysis with borehole data, to obtain the slope parameter such as resistivity and velocity of electromagnetic wave, and to ascertain the slope structure, potential slip surface and deformation zone. On this basis, the geological generalisation model of slope was established, and the failure mechanism and stability of slope were analyzed by numerical simulation.

Optimization algorithms for light pollution management based on TOPSIS-non-linear regularization model

Rapid urbanization and economic development have inevitably led to light pollution. However, currently the world has not yet formed a unified technical standard for light pollution, and light pollution cannot be effectively controlled when the environmental protection department is unable to operate. To effectively solve this problem, this paper establishes a combined weight ideal point method evaluation model based on TOPSIS evaluation method to obtain comprehensive index weights to evaluate the light pollution risk levels of four different land types in urban, suburban, rural and nature reserve areas in Beijing, China, and uses one-way ANOVA to test the differences among the four regions. Based on the Random Forest algorithm to determine the three variables with the top three feature importance weights, and based on the nonlinear optimization algorithm, using the SLSQP method, the optimal parameter combinations with the smallest cost are obtained after iteration, so as to put forward three feasible intervention strategies such as adjusting the design of the nightscape lighting, reducing the time of nonessential lighting, and rationally planning the layout of the city’s lighting, etc., to solve the light pollution problem, which effectively promote the urban nightscape lighting’s it effectively promotes the healthy and sustainable development of urban nightscape lighting.

Research on the Light Pollution Risk Index Model Based on Entropy Weight Method and TOPSIS

This paper applies entropy weight method and TOPSIS ideal solution method, multiple linear and linear regression, the least squares method and sensitivity analysis to the light pollution problem, and firstly, it discusses how to measure light pollution risk levels using multiple factors, and then explores different influencing factors for specific areas by controlling for variables and conducting a regional analysis of four urban areas in Beijing, while verifying the validity of the indicator model in an example. Next, this paper develops and tests three intervention strategies for light pollution risk levels, establishes a correlation model, and uses case studies to analyze what reasonable and effective interventions people should take. Finally, the successful implementation of this strategy may increase people's knowledge and environmental awareness of light pollution through leaflets to educate the population and thus reduce the possibility of light pollution flooding, in order to construct light pollution risk indicators, the evaluation criteria were determined based on the TOPSIS method combined with urban light pollution, normalized matrices, and a normalization method was used to standardize the score of each indicator into a relative score with weighted weights.

The Social Equity of Urban Parks in High-Density Urban Areas: A Case Study in the Core Area of Beijing

Urban parks beautify the environment and promote urban public health, and their spatial allocation is significant in maintaining environmental justice. However, the current allocation of urban parks focuses on quantity fairness and pays insufficient attention to accessibility and quality fairness. This study investigated the core area of Beijing and analyzed the fairness of urban park allocation based on park accessibility, area, and quality. We used big data crawling, the two-step floating catchment area method, comprehensive equity evaluation of parks, spatial autocorrelation, and non-parametric tests. The results showed inequality in terms of accessibility, area, and quality, with high spatial distribution in the north and low spatial distribution in the south. The accessibility, shortest distance, and total area of urban parks in high-income residential areas were 3.0, 2.1, and 1.8 times higher, respectively, than those of the low-income residential areas. This indicates that high-income groups have better accessibility, live closer to, and have access to larger urban parks. Middle-income and above groups had access to green space, whereas medium-to-low-income residential areas had poor access to parks, particularly high-quality parks. These findings provide decision-making and planning references for the optimal allocation and rational planning of urban parks.

Coordination of Public Service Facilities and Greening in Residential Communities in Beijing

The coordination of green space and public service facilities is of great importance in improving the spatial quality of existing residential districts. This paper adopts the method of a questionnaire survey to investigate the current cooperation between green space and service facilities in residential communities in urban areas in Beijing, China, explores the possibility of their coordinated development in residential areas, and puts forward countermeasures and suggestions for their collaborative transformation. The results show that the three types of facilities that residents thought should be coordinated most with green space were cultural and sports, educational, and social welfare facilities, while commercial service facilities were the most frequently used. Based on the survey results and considering the difficult degree of collaborative transformation of different service facilities and practical problems in implementation, three suggestions were put forward: (a) Differentiated hierarchical control strategies should be put forward for the collaborative transformation of service facilities and green space for different types of communities. (b) Urban planners should optimize the spatial layout relationship between green space and service facility land and pay attention to their functional combination, considering both spatial and functional coordination. (c) In the actual reconstruction, the residents' willingness to transform different public service facilities, the frequency of use, and the objective economic conditions of the community should be comprehensively considered, and the reconstruction should be carried out in stages according to the order of priority.

Benefit Analysis and Comparison of Electric Heating System for Municipal Central Heating

Electric heating can not only relieve the pressure of municipal central heating but also help to solve the problem of wind and light abandonment, which is an important direction for the future development of central heating. To maximize the comprehensive benefits, this paper constructs three kinds of electric heating systems. According to the comprehensive benefit evaluation of technical, economic, and environmental aspects, the comprehensive optimal scheme is selected. An office area in Beijing is taken as an example to determine the optimal scheme of electric heating and heating supplement. The results show that the comprehensive benefit of the heat pump + phase change accumulator system is the best, but the environmental benefit needs to be further improved. To promote the pace of electric heating and heating supplement, the government should increase the subsidies for electric boiler technology. At the same time, clean energy power supply enterprises should improve the trading mechanism of the electric heating market and reduce the price of clean energy heating.

An Automatic Method for Delimiting Deformation Area in InSAR Based on HNSW-DBSCAN Clustering Algorithm

InSAR (Interferometric Synthetic Aperture Radar) is widely recognized as a crucial remote sensing tool for monitoring various geological disasters because it provides all-day and all-weather monitoring. Nevertheless, the current interpretation methods for InSAR heavily depend on the interpreter’s experience, which hinders efficiency and fails to meet the requirements for the timely detection of geologic hazards. Furthermore, the results obtained through current InSAR processing carry inherent noise interference, further complicating the interpretation process. To address those issues, this paper proposes an approach that enables automatic and rapid identification of deformation zones. The proposed method leverages IPTA (Interferometric Point Target Analysis) technology for SAR data processing. It combines the power of HNSW (Hierarchical Navigable Small Word) and DBSCAN (Density-Based Spatial Clustering of Applications with Noise) algorithms to cluster deformation results. Compared with traditional methods, the computational efficiency of the proposed method is improved by 11.26 times, and spatial noise is suppressed. Additionally, the clustering results are fused with slope units determined using DEM (Digital Elevation Model), which facilitates the automatic identification of slopes experiencing deformation. The experimental verification in the western mountainous area of Beijing has identified 716 hidden danger areas, and this method is superior to the traditional technology in speed and automation.

Impact of Land Cover Changes on Soil Type Mapping in Plain Areas: Evidence from Tongzhou District of Beijing, China

The flat terrain in the plain areas of Beijing, China makes the land easily accessible for cultivation and farming, providing vast opportunities for agricultural development. Meanwhile, these areas are also crucial for urban construction and economic growth. Soil type mapping plays a key role in understanding soil characteristics and guiding land management practices. However, accurately mapping soil types in plain regions can be challenging due to their low spatial variability and diverse land use types. Although land cover changes due to phenomena such as urbanization, agricultural expansion, and conversion of natural vegetation can significantly affect soil properties and distribution patterns, their impacts on soil type mapping remain unclear. This study investigated the impacts of land cover changes in plain areas on the accuracy of soil type mapping, hoping to provide effective assistance for soil type mapping in plain areas by analyzing their coupling relationship. Focusing on the 20 year land cover changes in Tongzhou District, this study utilizes a unified approach that combines expert knowledge, mixed sampling methods, and RF mapping techniques, while incorporating environmental covariates that have minimal period influence and synergistically using NDVI and land cover data from the same year. Transition matrices are used to reveal land cover changes, confusion matrices, and their derived indicators to analyze changes in soil type mapping accuracy, and coupling analysis is conducted between soil type change areas and land cover change areas. The results show that Tongzhou District has experienced rapid development over the past 20 years, with the area of construction land nearly doubling. Additionally, 29% of arable land has been converted into construction land, resulting in an increase in the accuracy of the soil map from 58.99% to 66.91% over the 20 year period. The soil type change area during this period accounts for 16.5% of the total area, with 51.9% of the changed areas overlapping with land cover change areas. These overlapping regions are predominantly influenced by human activities. In terms of cultivated land types in the study area, the quantity of arable land has decreased by approximately 29% over 20 years, while the proportion of Sandy loam calcareous fluvo-aquic soil and Light loam calcareous fluvo-aquic soil, which constitute nearly half of the soil type, has increased. These data demonstrate the coupling relationship between land cover changes and soil type variations. It is evident that improving the extent of land use in plain areas enhances the credibility of soil type mapping. Meanwhile, human activities impact land cover, which, in turn, affects and reflects changes in the soil type.