Spatial Coupling Relationship Research Articles

Multivariate statistical analysis and bespoke deviation network modeling for geochemical anomaly detection of rare earth elements

Rare earth elements (REEs), a significant subset of critical minerals, play an indispensable role in modern society and are regarded as “industrial vitamins,” making them crucial for global sustainability. Geochemical survey data proves highly effective in delineating metallic mineral prospects. Separating geochemical anomalies associated with specific types of mineralization from the background reflecting geological processes has long been a significant subject in exploration geochemistry. The processing of high-dimensional, non-linear geochemical survey data necessitates a systematic framework to address common issues, including missing values, the closure effect, the selection of appropriate multivariate analysis methods, and anomaly detection techniques in order to detect geochemical anomalies associated with mineral occurrences. The Curnamona Province in South Australia is considered an emerging REE province with significant REE mineralization potential. In this study, we use data from this region to evaluate the performance of a novel machine learning-based framework that incorporates data pre-processing, multivariate statistical analysis, and anomaly recognition to address challenges such as missing data, noise interference, data imbalance and high non-linearity. We utilize lithogeochemical data to map potential greenfield regions of REE mineralization. The primary advantages of our framework lie in its provision of an effective random forest-based data imputation method, utilization of isometric log-ratio transformation to eliminate the closure effect, and reduction of the impact of outliers on data interpretation through robust principal component analysis. Additionally, the framework utilizes a deviation network to learn anomaly scores from complex, non-linear data under imbalanced data conditions, identifying geochemical anomalies associated with REE occurrences by leveraging prior knowledge rather than those caused by data noise or anthropogenic factors. The anomalous areas identified by this framework delineate all known REE deposits and extend to the surrounding regions. Furthermore, a close spatial coupling relationship exists between these strongly anomalous areas and the felsic granite intrusions. The comprehensive workflow for processing geochemical data proposed in this study can effectively address common challenges in the geochemical exploration of critical minerals. The identified geochemical anomalies can provide important clues for subsequent exploration.

A semantic segmentation model for road cracks combining channel-space convolution and frequency feature aggregation

In transportation, roads sometimes have cracks due to overloading and other reasons, which seriously affect driving safety, and it is crucial to identify and fill road cracks in time. Aiming at the defects of existing semantic segmentation models that have degraded the segmentation performance of road crack images and the standard convolution makes it challenging to capture the spatial and channel coupling relationship between pixels. It is difficult to differentiate crack pixels from background pixels in complex backgrounds; this paper proposes a semantic segmentation model for road cracks that combines channel-spatial convolution with the aggregation of frequency features. A new convolutional block is proposed to accurately identify cracked pixels by grouping spatial displacements and convolutional kernel weight dynamization while modeling pixel spatial relationships linked to channel features. To enhance the contrast of crack edges, a frequency domain feature aggregation module is proposed, which uses a simple windowing strategy to solve the problem of mismatch of frequency domain inputs and, at the same time, takes into account the effect of the frequency imaginary part on the features to model the deep frequency features effectively. Finally, a feature refinement module is designed to refine the semantic features to improve the segmentation accuracy. Many experiments have proved that the model proposed in this paper has better performance and more application potential than the current popular general model.

Coupling and interaction mechanism between green urbanization and tourism competitiveness based an empirical study in the Yellow River Basin of China

Exploring the spatial coupling relationship and interaction mechanism between green urbanization (GU) and tourism competitiveness (TC) is of great significance for promoting urban sustainable development. However, the lack of research on the interaction mechanism between GU and TC limits the formulation of effective environmental management policy and urban planning. Taking 734 counties in the Yellow River Basin (YRB) as the study area, this paper analyzes the spatial coupling relationship between GU and TC on the basis of comprehensive evaluation of GU and TC. Then, the interactive mechanism between GU and TC is systematically discussed, and the synergistic development strategy of the two is proposed. The results show that the GU level presents a multicore circle structure, with provincial capitals, prefecture-level urban districts and economically developed counties in east-central regions as high-value centers. The TC at county scale presents a multi-center spatial structure. Additionally, there is a significant positive spatial coupling between GU and TC in the YRB. The analysis further reveals that green urbanization level, social progress, population development, infrastructure construction, economic development quality, and eco-environmental protection has a observably influence on TC. Tourism competitiveness, service competitiveness, location competitiveness, resource competitiveness, market competitiveness, environmental influence, and talent competitiveness has a observably influence on GU. TC can promote GU, and the improvement of green urbanization level can support the development of tourism competitiveness. According to the spatial zoning method, 734 counties are divided into 6 categories, and the coordinated development strategy of GU and TC for each type of district is proposed.

Does ecological network affect the construction land spatial development intensity? -An empirical study based on the main urban area of Jinan, China

The ecological network as the cornerstone of urban ecological security protection, understanding the interaction between ecological network and construction land spatial development intensity (CLSDI), which is crucial for guiding the orderly utilization of territorial space and promoting regional sustainable development. However, the information on the complex spatial and temporal interactions between ecological networks and CLSDI has not yet been adequately studied. This study takes the main urban area of Jinan City as an example, and explores the spatial and temporal coupling relationship and change rule of ecological network and CLSDI during 2006–2018 through spatial multiple buffer analysis tools, and proposes the optimization path of construction land spatial development under the perspective of ecological network. The results showed that: from 2006 to 2018, there is a significant spatial effect between CLSDI and ecological network elements; within the buffer zone of 300–3000 m for ecological sources and nodes, CLSDI rises with the increase of buffer zone distance; while the ecological corridor exhibits decreased CLSDI within the 500-m buffer zone, the 500–3000-m CLSDI tends to increase. Based on the empirical analysis, the optimization path of construction land spatial development is proposed from three aspects: ecological source, corridor and node. The 300 m control range of the ecological source is designated as a “specific protection zone”, and strictly control the increase of the CLSDI within the zone; the ecological corridor is set up with differential protection and utilization zoning, and CLSDI and activity types are controlled in a hierarchical and classified manner; the CLDSI around the ecological nodes is strictly controlled in order to prevent encroachment of construction activities on the nodes. This study provides a reference value for constructing a territorial spatial pattern coordinated with ecological protection and development of construction.

Spatial coupling relationship between architectural landscape characteristics and urban heat island in different urban functional zones

The process of urbanization exacerbates the urban heat island phenomenon. In order to reasonably identify urban functional zones, and reveal the influence of buildings on land surface temperature (LST). Guiyang, a multi-mountainous city in China, was taken as the research area, Open Street Map (OSM) and land use type data were used to identify urban functional zones. Subsequently, the correlation between urban building morphology metrics and LST was analyzed using Pearson correlation and boosted regression tree (BRT) model. The results showed that: (1) There were significant differences in LST among different urban functional zones. (2) The relative contribution value of building density (BD) to land surface temperature was high, and it significantly exacerbated the urban heat island effect across all urban functional zones, with the maximum impact on LST reaching 2.5 °C in Utility zone. (3) Mean building height (MBH), Southerly wind speed (S_Wind speed) and Landscape shape index of building (LSI_Building) had the effect of alleviating thermal environment, and the mitigation degree of land surface temperature was the highest in Residential zone and Ecological zone, reaching 0.6 °C, 0.8 °C and 2.0 °C, respectively. This study enhances our understanding of the relationship between urban functions and LST, providing valuable insights for mitigating the urban thermal environment and promoting sustainable development.

Spatial coupling relationship between metamorphic core complex and gold deposits: Constraints from geophysical electromagnetics

Spatial coupling relationship between metamorphic core complex and gold deposits: Constraints from geophysical electromagnetics

Spatiotemporal variation pattern and spatial coupling relationship between NDVI and LST in Mu Us Sandy Land

Spatiotemporal variation pattern and spatial coupling relationship between NDVI and LST in Mu Us Sandy Land

Propagation thresholds and driving mechanism detection of karst meteorological- agricultural drought: A case study in Guizhou Province.

It is significant to systematically quantify the propagation thresholds of meteorological drought to different levels of agricultural drought in karst areas, and revealit's the propagation driving mechanisms. This can guide early warning and fine management of agricultural drought. In this study,we selected Guizhou Province as an example. The standardized precipitation evapotranspiration index (SPEI) and standardized soil moisture index (SSI) were used to characterize meteorological and agricultural drought. The run theory was used to identify, merge and eliminate drought events. The maximum correlation coefficient was used to capture the propagation time of meteorological-agricultural drought. The regression models were used to quantify the propagation intensity threshold from meteorological drought to different levels of agricultural drought. Finally, the propagation threshold driving mechanism was explored using geographical detectors. The results show that: (1) in terms of temporal variations during the past 21 years, regional meteorological drought had a shorter duration and a higher intensity than agricultural drought, Particularly, 2011 was a year of severe drought, and agricultural drought was significantly alleviated after 2014. (2) In terms of spatial variations, the "long duration area" of meteorological drought duration showed an "S" shaped distribution in the northeast, and the "short duration area" showed a point-like distribution. The overall duration of agricultural drought showed a spatial distribution of northeast to "medium-high in the northeast and low in the southwest. (3) The drought propagation time showed an alternating distribution of "valley-peak-valley-peak" from southeast to northwest. In terms of propagation intensity thresholds, light drought showed an overall spatial distribution of high in the east and low in the west. Moderate, severe, and extreme droughts showed a spatial distribution of low in the center north of southern Guizhou) and high in the borders. (4) There was a strong spatial coupling relationship between karst development intensity, altitude and meteorological-agricultural drought propagation thresholds. The interaction of different factors exhibited a two-factor enhancement and nonlinear enhancement on the propagation threshold. This indicates that synergistic effects of different factors on the propagation threshold were larger than single-factor effects.

Identifying Urban Built-Up Areas Based on Spatial Coupling between Nighttime Light Data and POI: A Case Study of Changchun

Nighttime light (NTL) data and points of interest (POI) data offer precise visual indications of the distributional characteristics of urban spatial structures. This study employed nighttime light data and point of interest data to investigate spatial distribution patterns in Changchun, a selected study area. The built-up area was extracted from the nighttime light data, while kernel density analysis was utilized to examine the distribution of point of interest data. The processing outcomes of both datasets were gridded with spatially resolved resolution. Afterward, the fishnet tool was employed to conduct two-factor integrated mapping and visual analysis, which helped identify shared or divergent spatial coupling relationships. The results indicated a high degree of consistency in the distribution of both NTL and POI across Changchun, with 84.58% of the coupling demonstrating a concordant pattern. The spatial analysis conducted in this study showed that the heterogeneities of the coupling relationship within each administrative borough expanded outward from the center of the borough. POI provided a more accurate depiction of the spatial distribution of urban built-up areas compared to NTL, leading to a more precise representation of spatial patterns of human activity intensity. Changchun has undergone zoning adjustments, resulting in the emergence of multiple urban centers in both the central city and the surrounding administrative districts. These urban centers are gradually merging into each other. The study found that the level of spatial coupling was much higher in the central area compared to the surrounding administrative districts. This has contributed to the formation of multiple urban centers and the gradual expansion of the urban built-up area beyond the main city, indicating a trend towards regional integration and development. This study provides a more detailed and accurate description of the current distribution of urbanization and spatial structural characteristics of Changchun by investigating the spatial coupling between POI and NTL. The findings contribute to a better understanding of the urban development patterns in the region and provide insights for future urban planning and management.

Towards carbon neutrality in China: A systematic identification of China's sustainable land-use pathways across multiple scales

Sustainable land use is crucial for achieving Carbon Neutrality goals, which requires a scientific identification of optimized pathways for land use patterns across multiple scales. Yet, current land use studies predominantly focus on single scales but lack system thinking and fail to establish complementary cross-regional carbon neutrality collaboration schemes. Applying life-cycle thinking to analyze land use sustainability and carbon neutrality potential at multiple scales could address this challenge. This study aims to present China's first multi-scale spatiotemporal optimization pathway for sustainable land use to improve carbon neutrality potential. It systematically integrates the complex spatial coupling relationships between land use intensity and efficiency. We integrate multi-scale sustainable land use pathways, spanning grid, basin, and administrative levels, and unveil significant variations in land use sustainability and carbon neutrality potential across China. Sixty-three percent of China's land is in low sustainability, and the overall carbon neutrality potential in China is relatively low, with regions accounting for <30 % facing more carbon neutrality missions. Implementing sequential and partitioned governance modes can effectively support China in achieving sustainable land use and advancing Carbon Neutrality goals. Our sustainable land use pathways for China provide valuable insights for systematically undertaking carbon neutrality actions across different scales.

Spatial coupling relationship between older adults and elderly care resources in the Yangtze River Delta.

The imbalance between supply and demand of elderly care resources in the Yangtze River Delta is increasing. By the older adult agglomeration, spatial cluster analysis, hotspot analysis, and coupling coordination model, this study explores the spatial coupling relationship between older adults and elderly care resources in the Yangtze River Delta in 2020 from the perspective of a supply-and-demand balance. The results demonstrate that: (1) population aging is mainly in the moderate aging stage, followed by the primary aging stage; (2) there are significant spatial differences in elderly care resources on the urban scale in the Yangtze River Delta; and (3) elderly care resources and the older adults in the Yangtze River Delta are mostly highly coupled. However, Nantong, with the highest degree of aging, has a serious mismatch in life service resources and ecological environment resources. The social security resources and medical resources of provincial capital cities with low aging are mismatched. Medical and health resources in underdeveloped areas are seriously mismatched. The social security resources are barely matched in Shanghai. A path for optimizing the spatial allocation of elderly care resources is proposed. This research offers a decision-making reference for coordinating elderly care resources distribution.

Domain adaptation graph convolution network for quality inferring of batch processes

Developing a reliable quality inference model in batch processes remains a challenge. The performance of the model tends to decline due to batch-to-batch variations. Additionally, the spatial coupling relationships among multiple variables need to be mined to explain the model behavior. To this end, a domain adaptation graph convolution network is developed for quality prediction of batch processes. Under the constraint of the structural loss function, the model is firstly encoded to capture the topological correlations between variables. Moreover, the production time information is added into input variables to track the process temporal characteristics. Subsequently, the cross-batch characteristics are explored by the finetune technology to transfer the source knowledge and enlarge the prediction domain. Compared with several popular data-driven candidates, the proposed model shows its superiority in two batch processes. Remarkably, the variable relationships self-captured by the source model are visualized, which are consistent with the process prior knowledge to verify the model interpretability.

Correlation between fractal characteristics of fault structures and metallogenic density in the Nanling area, South China

As fault structures exert a significant effect on metallogenic processes and mineralization, their proper characterization can assist in the determination of target areas for exploration. In this study, we apply the fractal theory on the interpretation of remote sensing images of the Nanling area, South China, to determine the relationship between fault structures and regional mineralization. Our results show that the fractal dimension (D) of fault structures in the Nanling area is 1.72, which is much higher than the regional average (1.35) for southern China. This difference reflects a strong geological tectonic activity in this region. Besides, we find that well-developed faults have a complex spatial distribution, and therefore this region is characterized by favorable metallogenic conditions with good prospecting prospects. Our results indicate the presence of a close relationship between the fractal dimension (D) and the spatial distribution of mineral deposits. Specifically, a higher D value generally corresponds to a dense distribution of ore deposits. Finally, based on regional structural and metallogenic characteristics as well as spatial coupling relationships, two target mineralization areas are identified as potential candidates for further exploration.

Spatial Coupling Relationship and Driving Mechanism of Population and Economy in Rural Areas in Qinling-Daba Mountains, China

Spatial Coupling Relationship and Driving Mechanism of Population and Economy in Rural Areas in Qinling-Daba Mountains, China

Analysis of Spatial and Temporal Variability and Coupling Relationship of Soil Water and Salt in Cultivated and Wasteland at Branch Canal Scale in the Hetao Irrigation District

The Hetao Irrigation District is a typical salinized irrigation district in China, and soil salinization restricts agricultural development. To explore the spatial and temporal variability of soil water and salt and the coupling relationship in the Hetao Irrigation District, a field experiment was carried out at the scale of the Yichang Irrigation District branch canal in the downstream of the Hetao Irrigation District. Fifty-three soil sampling points were established to analyze the spatial and temporal variability of soil water content and total salt content and the coupling relationship using geostatistics and the coupling degree model. The results showed that soil water content in the study area belonged to medium variability and weak variability, and soil total salt content belonged to strong variability and medium variability. The theoretical models of soil water content and total salt content semi-variance function in the study area following the Gaussian model, with the block-base ratio less than 25%, with strong spatial autocorrelation, and the spatial correlation gradually increased with the increase of soil depth. The total salt content of the soil in the study area was interpolated with higher accuracy using radial basis functions as compared to ordinary kriging interpolation. In terms of temporal changes in salinity, the average salt accumulation rate of the 0–100 cm soil layer in the study area was 20.17% when salinity increased from May to June; the average desalination rate was 16.37% when salinity decreased from June to August. The main factors affecting soil salinity in cultivated land during the growing period were irrigation, precipitation, and planting crops, and the main factors affecting soil salinity in wasteland were precipitation and topography. The average coupling degree of soil water and salt in wasteland in the study area was lower than that of cultivated land, ranging from 65.15% to 86.59% of that of cultivated land. The level of coordination is marginal coordination for cultivated land and marginal disorder for wasteland. The study provides a theoretical basis for the prevention and control of soil salinization in arid areas.

Spatial distribution and ecological risk assessment of heavy metal elements in rock‐soil in the mountainous areas of Southwest China: A case study of Xichang

This study employs the Muller geological accumulation index method and the Hakanson risk assessment method in combination with ArcGIS technology to assess the potential heavy metal pollution in soil. The study aims to investigate the geochemical characteristics, pollution degree, and potential ecological risks associated with soil heavy metal element content and distribution across various geological formations. The concentrations of eight heavy metals, namely Cu, Cd, Ni, Pb, Zn, Hg, As, and Cr, were analysed by collecting samples of the soil layer, parent material layer, and parent rock layer. The proportions of samples with different risk levels are accurately calculated to locate areas with high pollution risks. The findings are as follows: Firstly, the soil pH value in the study area is low, and the Cd and Cr concentrations are 1.38 and 1.20 times the background concentrations in soil in Sichuan Province, respectively. Moreover, Cu, Cd, Ni, Zn, and Cr concentrations are 1.23, 1.10, 1.20, 1.10, and 1.55 times the background concentrations in soil in China. Secondly, the distribution of heavy metal elements varies across different geological formation units, and the heavy metal contents of different samples from the same formation also varies significantly. The concentrations of heavy metal elements are influenced by different geological formations, with the pedogenic parent rock in the soil determining the initial concentrations of heavy metal elements. Thirdly, the spatial distribution of heavy metal elements indicates a good spatial distribution coupling relationship among the soil layer, parent material layer, and rock layer. The study suggests that the contents of the eight heavy metal elements in the soil inherited the characteristics of the parent material to a large extent and are influenced and controlled by the pedogenic parent rock (geological formation). Finally, the evaluation results reveal that all eight heavy metal elements exhibit moderate pollution, with a relatively large distribution area exhibiting moderate Cd, Hg, and As pollution and above. The overall study area exhibits a mild potential ecological risk level, with some areas at a moderate potential ecological risk level, distributed in patches across the study area. Cd and Hg exhibit relatively high potential ecological risks. The potential ecological risks of heavy metals are relatively high in the JKms and Tss units. While the overall quality of the soil in the study area is good, heavy metal pollution and potential ecological risks of some elements are still above ideal levels.

Spatial Coupling Pattern and Driving Forces of Rural Settlements and Arable Land in Alpine Canyon Region of the Maoxian County, China.

For mountainous areas in different regions, the study of the spatial coupling relationship between rural settlements and arable land resources is a key aspect of coordinated rural development. In this study, a spatial coupling relationship model and a Geodetector are introduced to explore the spatial coupling relationship and driving factors of rural settlements and arable land in the alpine canyon region. The nearest neighbor index, Voronoi diagram, and landscape pattern index system based on the geographic grid are used to analyze the spatial differentiation characteristics of rural settlements in the alpine canyon region, and the spatial coupling relationship model is introduced to explore the spatial coupling relationship between rural settlements and arable land. Finally, the driving factors of the coupling relationship are detected based on Geodetector. The results show that (1) the spatial distribution of rural settlements in the study area is "T-shaped" with a relatively regular settlement shape; (2) the population in the alpine canyon region is relatively small, and the conflict between people and land is not prominent in most areas, so the overall coupling situation between rural settlements and farming land is dominated by fewer people and more land; and (3) the spatial coupling between rural settlements and arable land in the alpine canyon region is mainly affected by four types of factors: terrain topography, meteorology, soil and population, and economy. The interaction between the factors has a synergistic enhancement effect. The results of the study provide theoretical support for the development of rural settlements in the alpine canyon region.

Spatial coupling relationship between multidimensional poverty and the risk of geological disaster

ABSTRACT Objective: Studying the coupling relationship between multidimensional poverty and geological disaster risk is a beneficial exploration for the collaborative promotion of disaster and poverty reduction. Methods: Taking Sichuan province as the research area, this study adopted the multidimensional poverty index and the information content model to quantitatively evaluate the multidimensional poverty and geological disaster risk in 2019, and uses the coupling coordination degree model to explore their coupling relationship and coordinated development. Results: The development level of high-altitude areas and remote mountainous areas was lower than that of plain and hilly areas, and the spatial difference of multidimensional poverty is obvious. The risk of geological disaster is relatively high overall in the alpine valley regions of Western, Southern and Northern Sichuan. The coupling level of multidimensional poverty and geological disasters is comparatively prominent. The overall coordination degree is relatively high. There existed obvious gathering areas in places of disorder of both poverty and disaster, disaster risk lag, poverty lag and synchronous development. In contrast, the coordinated-disaster risk and the poverty lags were relatively scattered. The unbalanced development between eastern and western Sichuan is comparatively prominent. More efforts will be paid to pursue poverty and disaster reduction in a highly collaborative way. Conclusion: This study gives data support for the long-term mechanism established in Sichuan province for forestalling and defusing the risk of returning to poverty caused by disease so that the international community can learn from China’s experience through observation and collaboration in terms of poverty and disaster reduction.

Research progress on calculation method and impact factors of carbon sequestration capacity in urban ecosystems

Achieving carbon neutrality is an urgent, complex and arduous task in China. How to effectively exert carbon sequestration and improve carbon sequestration capacity of urban ecosystems should be solved. Compared with other terrestrial ecosystem types, frequent anthropogenic activities lead to more abundant carbon sink elements of urban ecosystems and more complex factors affecting their carbon sequestration capacity. Based on researches at multiple spatial and temporal scales, we analyzed key factors affecting the carbon sequestration capacity of urban ecosystems from different perspectives. We illuminated the composition and characteristics of carbon sinks of urban ecosystems, summarized the methods and characteristics of carbon sequestration capacity of urban ecosystems, and revealed the impact factors of carbon sequestration capacity of different carbon sink elements and the comprehensive impact factors of carbon sinks of urban ecosystems under the influence of human activities. With the continuous improved understanding of carbon sinks of urban ecosystems, it is necessary to further improve the accounting method of carbon sequestration capacity of artificial carbon sink systems, explore the key impact factors of comprehensive carbon sequestration capacity, change the research method from global to spatially weighted, discover the spatial coupling relationship between artificial and natural carbon sink systems, find out the optimal artificial-natural spatial configuration to achieve carbon sequestration capacity enhancement, break the limitations of increasing carbon sink of urban ecosystems, and finally contribute to the achievement of the urban carbon neutrality goal.

Study on Spatial Pattern and Spatial Coupling with Geographical Environment of Key Villages for Rural Revitalization in Hunan Province

After China's comprehensive poverty alleviation in 2020, key villages for rural revitalization have become key areas of follow-up rural revitalization work. Objective analysis of KAVRR (Key Assistance Villages for Rural Revitalization) poverty geographical pattern, and verify whether there is a spatial coupling relationship between poverty pattern and geographical environment, so as to further consolidate the space coupling connection between targeted poverty alleviation and rural revitalization. In this paper, 2307 KAVRRs published by Hunan Provincial Poverty Alleviation Office were selected as the research objects. The spatial distribution of key KAVRR was quantitatively analyzed from three aspects. The coupling relationship between KAVRR spatial pattern and geographical environment was verified from six aspects. Draw the following conclusions: 1) The nearest neighbor index of KAVRR in Hunan province is 0.82, indicating obvious spatial aggregation. At the municipal level, changsha-Zhuzhou-Xiangtan tended to be uniformly distributed, while other cities tended to be agglomerated. 2) The spatial distribution of KAVRR varies in different urban areas. More than 60% of KAVRR is concentrated in Shaoyang, Huaihua, Xiangxi Tujia Autonomous Prefecture, Yongzhou and Loudi. 3) In the analysis of influencing factors, the geographical location characteristics of KAVRR, hydrological conditions, geographical location characteristics, accessibility of public service facilities, such as education and medical resources, are highly coupled with the spatial distribution of assistance. Different influencing factors have different influencing mechanisms, but the final spatial layout is the result of interaction and coupling of geographical environment elements.