Spatial Dissimilarity Research Articles

Plant size inequality: How to analyse competing spatial dissimilarity Indices?

Worldwide biodiversity loss is perceived as a major threat and is likely to be enforced by ongoing climate change. Continued monitoring of biodiversity can assist in compensating for decreasing biodiversity by goal-oriented conservation management. Plant size diversity, also termed size inequality and size hierarchy, has often been neglected in studies of biodiversity, but plays a crucial role in many ecosystems, e.g. in forests. Several competing diversity indices and other characteristics of spatial plant size inequality have been proposed but to date no protocols or guidelines exist for evaluating their relative merits. In our study, we proposed a broad framework for such an analysis. In order to put this framework to a test, we revisited the dissimilarity coefficient, a somewhat ignored but promising spatial size inequality index published at the end of the 1990s, identified its nearest index competitors and analysed their performances in different mathematical-statistical contexts. We learned that the dissimilarity coefficient is more sensitive in statistical significance tests relating to three very different summary characteristics than its closest competitor, the size differentiation index. In addition the dissimilarity coefficient has a more solid foundation than the differentiation index, since it is based on the well-known coefficient of variation. The dissimilarity coefficient can be recommended in a wide range of plant diversity applications. The principle of the dissimilarity coefficient can also be used to define an effective mark correlation function. We recommend our evaluation framework for use in similar analyses of competing diversity characteristics.

Changes in soil bacterial community diversity and its network stability under different grazing intensities in plateau rangelands

Grassland degradation is a significant ecological challenge, it changes the grassland environment, including the structure of soil microbial communities. Grazing is a critical factor in this process, yet the impact of different grazing intensities on soil bacterial communities, particularly in unique environments like the Qinghai-Tibet Plateau, remains poorly understood. This study utilized a full-length 16 S rRNA gene sequencing technology combined with environmental factors to assess the impacts of the Holba sheep grazing on soil bacterial community diversity in Zhongba County, Shigatse City, Qinghai-Tibet Plateau. The specific aim was to explore the changes in soil bacterial community diversity and stability under contrasting grazing intensities: prohibited grazing, light grazing, moderate grazing, and heavy grazing. The results showed that grazing activities significantly altered the diversity of bacterial communities, particularly under light and heavy grazing. The spatial dissimilarity in soil bacterial communities was mainly driven by species turnover (i.e., species replacement), which was more pronounced under heavy grazing. The number of keystone species increased with the grazing intensity of the bacterial co-occurrence network. Under heavy grazing, bacterial communities showed the highest number of keystone species and the community stability. Environmental factors such as exchangeable magnesium (EM), soil available kalium (SAK), and soil pH were the most important environmental variables impacting changes in bacterial community structure by influencing community α-diversity and stability. This study enhances our understanding of the response mechanisms of soil microbial communities to grazing intensities and other environmental stresses in grassland ecosystems. In addition, this study also provides important references and guidance for microbial diversity research in extreme environments. These findings are crucial for promoting the sustainable management and conservation of grassland ecosystems in climatically harsh areas such as the Qinghai-Tibet Plateau.

Inequality and spatial mismatch in the urban labor market: Evidence for the Curitiba metropolitan region, Brazil

Accessibility plays a fundamental role in improving urban economic equity, especially for disadvantaged communities. In many metropolitan areas of Brazil, accessibility relies on infrastructure unequally distributed, creating barriers to access opportunities in the urban labor market. This paper aims to identify sources of spatial mismatch and measure its effects on the labor market of the Curitiba Metropolitan Region (CMR), in Brazil. First, we measured the spatial imbalances of households and jobs by income classes and their effects on the spatial dissimilarity of accessibility to job opportunities. Second, we use econometric tools to evaluate how accessibility to the formal job sector affects individual earnings in the CMR labor market by wage quartile. We find evidence of strong spatial segregation for the poorest individuals from public transit network and from the formal job sector. The econometric results show there was roughly no accessibility premium for individual earnings for the poorest workers and positive effects for the richest workers in the CMR labor market. This set of empirical evidence suggest a spatial concentration of urban amenities that enhance economic inequality for the CMR.

Earth Mover's Charge Transfer Distance: A General and Robust Approach for Describing Excited State Locality.

A novel approach for assessing the extent of electron displacement in optical transitions is proposed by implementing the Earth Mover's Distance (EMD) method, which quantifies the spatial dissimilarity between ground and excited state electron density distributions. In contrast to previous descriptors, this index provides a representative and intuitively understandable distance under a robust and computationally efficient scheme for all possible forms of locality, even in the most difficult to dissect topological cases. The theoretical differences among the existing indices and our method are first illustrated with the help of a simplified model system, followed by a benchmarking of several partial atomic charge models using experimentally relevant push-pull compounds with diverse symmetries. These same molecules are finally employed to further demonstrate the principal advantages of the EMD index and its capabilities in rationalizing charge transfer phenomena.

Development of Soil-Suppressed Impervious Surface Area Index for Automatic Urban Mapping

Expanding urban impervious surface area (ISA) mapping is crucial to sustainable development, urban planning, and environmental studies. Multispectral ISA mapping is challenging because of the mixed-pixel problems with bare soil. This study presents a novel approach using spectral and temporal information to develop a Soil-Suppressed Impervious Surface Area Index (SISAI) using the Landsat Operational Land Imager (OLI) data set, which reduces the soil but enhances the ISA signature. This study mapped the top 12 populated megacities using SISAI and achieved an over-all accuracy of 0.87 with an F1-score of 0.85. It also achieved a higher Spatial Dissimilarity Index between the ISA and bare soil. However, it is limited by bare gray soil and shadows of clouds and hills. SISAI encourages urban dynamics and inter-urban compari- son studies owing to its automatic and unsupervised methodology.

Spatial and temporal variation in lake macroinvertebrate communities is decreased by eutrophication

Eutrophication impacts freshwater ecosystems and biodiversity across the world. While temporal monitoring has shown changes in the nutrient inputs in many areas, how spatial and temporal beta diversity change along the eutrophication gradient under a changing context remains unclear. In this regard, analyses based on time series spanning multiple years are particularly scarce. We sampled benthic macroinvertebrates in 32 sites across three lake habitat types (MACROPHYTE, OPEN WATER, PHYTOPLANKTON) along the eutrophication gradient of Lake Taihu in four seasons from 2007 to 2019. Our purpose was to identify the relative contributions of spatial and temporal dissimilarity (i.e., inter-annual dissimilarity and seasonal dissimilarity) to overall benthic biodiversity. We also examined spatio-temporal patterns in community assembly mechanisms and how associated variation in benthic macroinvertebrate communities responded to nutrient indicators. Results showed that eutrophication caused macroinvertebrate community homogenization both along spatial and temporal gradients. Though spatial variability dominated the variation of species richness, abundance and community dissimilarity, seasons within years dissimilarity, inter-annual dissimilarity and seasonal dissimilarity were much more sensitive to eutrophication. Moreover, eutrophication inhibited a strong environmental control in benthic macroinvertebrate community assembly, including a dominant role of deterministic process in the spatial variation of macroinvertebrate communities and transition from stochastic to deterministic process in the temporal assembly of macroinvertebrate communities along the eutrophication gradient. In addition, some sites in PHYTOPLANKTON habitats showed similar spatial dissimilarity and spatial SES as sites in MACROPHYTE habitats, and the decreased spatial dissimilarity of three habitats implying that lake ecosystem recovery projects have achieved their goal at least to a certain degree.

Studies on plankton community and physico-chemical parameters of Elechi Creek, Eagle Island, Port Harcourt

Studies on the plankton communities and physico-chemical characteristics of Elechi Creek were carried out for six months, from January to June. Fourteen physico-chemical parameters were evaluated, and monthly plankton alteration was investigated. Water quality samples and plankton analyses were obtained simultaneously. Water temperature was in the range of (29.4–35.5⁰C) across the (3) study locations. The results revealed no spatial dissimilarity (P˃0.05) of all physicochemical factors while results of the monthly variations test showed significant elevations (P˂0.05) for some parameters between (April and June), except for Turbidity, Nitrate, pH, Sulphate and Chloride. The mean concentration levels in total hardness (1600 mg/L), chloride (1075.8 mg/L) and sulphate (621.6 mg/L), were found considerably above the acceptable levels. Most plankton showed negative changes subsequent to these elevations. Phytoplankton identified comprised two families, of which Bacillariophyceae (diatoms) were higher followed by Cyanophyceae. Bacillariophyceae, cell density (46 cells L-1) contributed the highest (80.7%) sum phytoplankton cell–density while Cyanophyceae had (11 cells L-1) contributing (19.3%). The zooplankton density was from (17 L-1 - 1190 L-1). Copepoda recorded the utmost percentage population, contributing (91%) zooplankton, followed by Cladocera (4.8%), Crustaceae (2.9%) and most reduced (1.3%) contribution by Rotifera. Monthly variations of Plankton density showed that most families recorded higher density during the wet months (April–June). The occurrence of these factors and conditions in Elechi Creek underscore pollution therefore, aquatic organisms from such water are almost unsafe for food. Hence, standard checking of the creek is advocated to ensure seafood safety.

Drivers of decadal-scale temporal change in epibenthic megafaunal assemblages on scallop fishing grounds in the Bay of Fundy

The Bay of Fundy presents a unique environment with extreme tidal range, strong currents, fresh-water river discharge, and diverse habitats that are also experiencing temperature increase at a faster rate than most of the world ocean. There is extensive commercial fishing, valuable beds of sea scallop (Placopecten magellanicus) being found in several areas, some of which have been fished for over a century. Previously, comparative analyses of data collected in 1967 and 1997 found that the epibenthic assemblage on the Digby scallop ground had become more homogenous over the 30 year interval, while species composition had changed significantly. Attached, fragile, epifaunal taxa declined, whereas scavengers and robust burrowing filter-feeders increased in frequency of occurrence, consistent with the physical impacts of fishing gears as a primary driver. The Digby ground along with the commercial scallop grounds around Grand Manan Island and on Lurcher Shoal were resampled in 2007–08 to determine whether the changes off Digby had continued and if they were also occurring in other parts of the Bay. Significant spatial differences among the three scallop grounds were observed. The leafy bryozoan, Flustra foliacea, which was expanding its local range through time, was the leading contributor to the spatial dissimilarity. Depth and mean tidal current speed were the most important environmental variables influencing species composition. Significantly more taxa were recorded per station in 1997 than in 2007–08, while assemblage compositions were significantly different between the two periods. Decadal-scale declines in the frequencies of occurrence of attached, epibenthic filter-feeders, including the polychaete Filograna implexa, were observed, continuing the trend previously reported and consistent with on-going impacts of bottom-contact fishing gears, despite decades of trawling and dredging. However, other and unknown drivers were also implicated in the observed changes.

Multi-scaled attentive style transfer based on dilated convolution

Image style transfer aims to apply artists painting styles to various images. Many approaches seek different purposes, but a general tendency is to increase efficiency and enable arbitrary style inputs. The state-of-art method is the adaptive convolutional network which expands the process of feature mixture into a layer-wise adjustment that superior previous work by presenting results that is more aware of detailed structures. However, the encoding process that guides the entire stylized revision is unaware of multi-scaled information. We designed an improved version of the style feature encoding procedure in our work. With the introduction of dilated convolution with a different rate, the output stylized image is better at spatial texture migration and color distribution determination. We also come up with a hybrid objective that better measures the spatial dissimilarity between content and style features.

Global beta-diversity of angiosperm trees is shaped by Quaternary climate change.

As Earth's climate has varied strongly through geological time, studying the impacts of past climate change on biodiversity helps to understand the risks from future climate change. However, it remains unclear how paleoclimate shapes spatial variation in biodiversity. Here, we assessed the influence of Quaternary climate change on spatial dissimilarity in taxonomic, phylogenetic, and functional composition among neighboring 200-kilometer cells (beta-diversity) for angiosperm trees worldwide. We found that larger glacial-interglacial temperature change was strongly associated with lower spatial turnover (species replacements) and higher nestedness (richness changes) components of beta-diversity across all three biodiversity facets. Moreover, phylogenetic and functional turnover was lower and nestedness higher than random expectations based on taxonomic beta-diversity in regions that experienced large temperature change, reflecting phylogenetically and functionally selective processes in species replacement, extinction, and colonization during glacial-interglacial oscillations. Our results suggest that future human-driven climate change could cause local homogenization and reduction in taxonomic, phylogenetic, and functional diversity of angiosperm trees worldwide.

What is redundant and what is not? Computational trade-offs in modelling to generate alternatives for energy infrastructure deployment

Given the urgent need to devise credible, deep strategies for carbon neutrality, approaches for ‘modelling to generate alternatives’ (MGA) are gaining popularity in the energy sector. Yet, MGA faces limitations when applied to state-of-the-art energy system models: the number of alternatives that can be generated is virtually infinite; no realistic computational effort can discover the complete technology and spatial option space. Here, based on our own SPORES method, a highly customisable and spatially-explicit advancement of MGA, we empirically test different search strategies – including some adapted from other MGA approaches – with the aim of identifying how to minimise redundant computation. With application to a model of the European power system, we show that, for a fixed number of generated alternatives, there is a clear trade-off in making use of the available computational power to unveil technology versus spatial dissimilarity across alternative system configurations. Moreover, we show that focussing on technology dissimilarity may fail to identify system configurations that appeal to real-world stakeholders, such as those in which capacity is more spread out at the local scale. Based on this evidence that no feasible alternative can be deemed redundant a priori, we propose to initially search for options in a way that balances spatial and technology dissimilarity; this can be achieved by combining the strengths of two different strategies. The resulting solution space can then be refined based on the feedback of stakeholders. More generally, we propose the adoption of ad-hoc MGA sensitivity analyses, targeted at testing a study’s central claims, as a computationally inexpensive standard to improve the quality of energy modelling analyses.

A PMF-SSD based approach for the source apportionment and source-specific ecological risk assessment of Le'an river in Jiangxi Province, China

Identifying the contamination characteristics of trace metals in river and targeting their corresponding potential contamination sources and source-specific ecological risk are of very importance for putting forward effective river environment protection strategies. Here, a detailed investigation was conducted to recognize the contamination and ecological risk characteristics of trace metals in Le'an River. To attain this objective, a PMF-SSD model (Positive Matrix Factorization-Species Sensitivity Distribution) was proposed to evaluate the ecological risk of trace metals in Le'an River. The positive matrix factorization (PMF) was employed to identify the potential source of trace metals in surface water and their corresponding contributions. The ecological risks of the sources were quantitatively calculated by PMF-SSD. In addition, the spatial dissimilarity analysis of the source contribution distributions was also conducted in this study. Results showed that the water environment in Jiangxi were considerably contaminated by trace metals (Cd, Cr, Co, Al, Mn, Cu, Zn and Ni). The concentrations of these trace metals in surface water demonstrated significant spatial variations and the ecological risk lay in high level. Mining activities were identified as the main anthropogenic sources, which should to be strictly regulated.

Weighted Local Ratio-Difference Contrast Method for Detecting an Infrared Small Target against Ground–Sky Background

Fast and robust detection of infrared small targets in a single image has always been challenging. The background residue in complex ground–sky background images leads to high false alarm rates when traditional local contrast methods are used because of the complexity and variability of the ground–sky background imaging environment. A weighted local ratio-difference contrast (WLRDC) method is proposed in this paper to address this problem and detect infrared small targets in the ground–sky background. First, target candidate pixels are obtained using a simple facet kernel filter. Second, local contrast saliency maps and weighted mappings are calculated on the basis of the local ratio-difference contrast and the spatial dissimilarity of the target, respectively. Third, the final weighted mapping can be obtained through the multiplication fusion strategy. Finally, a simple threshold segmentation method is employed to extract the target. Experimental results on six real ground–sky infrared scenes showed that the proposed method outperforms existing state-of-the-art methods.

Spatial dissimilarity of zooplankton and hydrodynamic conditions in a Patagonian channel used intensely by aquaculture: the influence of a geomorphological constriction

BackgroundMarine aquaculture is a very important economic and food production activity in Patagonian channels. The biophysical mechanisms through which farms interact with surrounding areas is poorly understood. A better understanding of the relationship between zooplankton distribution, hydrodynamics and aquaculture farms in Patagonian channels can contribute to the environmental sustainability of this activity.MethodsThe study was conducted in winter in the Caucahué Channel (Chiloé Island, southern Chile), which is composed of two asymmetric northern and southern sections separated by a geomorphological constriction (a narrows) and hosts 55 aquaculture farms. Intensive zooplankton and water column sampling (time scale: 12 h) was carried out, together with current measurements as a background of the channel hydrodynamics (time scale: 30 days).ResultsSpatial dissimilarities in composition and abundances of zooplankton communities and in water column variables were identified between the two sections of the channel in this short-term time scale. In the southern section we found higher abundances of holo- and meroplankton and higher species richness. No differences in zooplankton community were found between sampling sites near and far from aquaculture farms. Southward asymmetrical residual flow and semidiurnal tidal excursion were verified in the central part of the channel during two tidal fortnightly time periods.Conclusions(i) Clear dissimilarity in zooplankton composition were found between the two sections of Caucahué Channel in the time scale studied; and (ii) Quemchi geomorphological constriction and the asymmetrical southward residual flow could act as a physical barrier favoring the spatial dissimilarities found in biotic and abiotic variables between the two sections of the channel.

A Hybrid-Clustering Model of Ship Trajectories for Maritime Traffic Patterns Analysis in Port Area

A hybrid-clustering model is presented for the probabilistic characterization of ship traffic and anomaly detection. A hybrid clustering model was proposed to increase the efficiency of trajectory clustering in the port area and analyze the maritime traffic patterns in port. The model identified dissimilarities between trajectories based on characteristics, using K-Means and the density-based spatial clustering of applications with noise algorithm (DBSCAN). Firstly, the ship’s trajectory characteristics are constructed based on real ship trajectories considering static characteristics and dynamic characteristics of ship trajectories to calculate the characteristic dissimilarity between trajectories. Simultaneously, the spatial dissimilarity could be quantified using the Hausdorff algorithm. Then, the ship trajectory is clustered initially based on the departure and destination characteristics using K-Means algorithms to obtain various sub-trajectories. However, there are still different types of trajectories in each sub-trajectory. Thus, the DBSCAN algorithm is adopted to cluster the sub-trajectory based on the analysis of the different trajectory characteristics. Finally, the proposed model is applied to the characterization of the Zhanjiang Port, and the results show that the hybrid-clustering method can effectively cluster ship trajectory and present probabilistic characterization of ship traffic and anomaly detection. This lays a solid theoretical foundation for the supervision and risk control of intelligent ships.

Reforestation improves vegetation coverage and biomass, but not spatial structure, on semi-arid mine dumps

Modern mine rehabilitation aims at thorough restoration of an ecosystem with emphasis on not only land area covered by vegetation but also the structure and function of that vegetation. However, assessment of current restoration success reveals a lack of attention to the spatial structure and its relationships with vegetation coverage and biomass. A forest's spatial structure is an important attribute of structural diversity. Complex spatial structures mean diverse species composition and spatial dissimilarity, which can provide a base for self-sustaining and regeneration. This study uses WorldView-2 images and field data to train the mind evolutionary algorithm-back propagation neural network (MEA-BP) model for the purpose of mapping three parameters (coverage, biomass, and spatial structure) across mine dumps. The results show that the spectral and textural features could effectively assess the coverage, biomass, and spatial structure, with an R2 of 0.91, 0.86, and 0.62, respectively. The coverage is positively correlated with biomass, while the spatial structure is negatively correlated with coverage and biomass. Pure Hippophae rhamnoides L. had high coverage but very low spatial structure, while the mixed community dominated by Populus L. and Pinus tabulaeformis Carr had high coverage, high biomass, and medium structure at around 10 years. The results suggested that the artificial reforestation improves vegetation coverage and biomass but did not synchronously increase spatial structure. The initially planted species composition, substrates, and succession process have a significant influence on the forest parameter relationships. The future reforestation and optimization of community assemblages should take the relationships and their influence factors and effects on ecosystem services into account. The remote sensing-based data and model has potential and advantages in dynamically guiding the rehabilitation and monitoring of the restored ecosystem.

Infrared small target detection algorithm based on spatial dissimilarity weighted local contrast

To solve the problem that the local contrast algorithm is easily influenced by the heavy clutter background or strong noise and does not fully consider the spatial neighbourhood characteristics of the small target, a spatial dissimilarity weighted local contrast-based method (SDWLCM) for infrared small target detection is proposed in this paper. Firstly, the two-dimensional difference of the Gaussian filter with central excitation and lateral suppression characteristics is chosen to preprocess the original infrared image for removing the flat background and improving the signal-to-noise ratio (SNR) of the small target. Secondly, the spatial dissimilarity between the target and its surrounding backgrounds is designed for local contrast weighting to generate the contrast saliency map so that the heavy clutter background is greatly suppressed and the small target is further highlighted. Thirdly, the saliency map is segmented by the adaptive threshold to get the real targets. Experimental results show that, compared with other methods, the SDWLCM, which owns not only a higher SNR gain and a larger background suppression factor but also a higher detection rate and a lower false alarm rate, is confirmed to be an effective method to detect the small targets.

On the efficacy of restoration in stream networks: comments, critiques, and prospective recommendations

Swan and Brown (2017) recently addressed the effects of restoration on stream communities under the meta-community framework. Using a combination of headwater and mainstem streams, Swan and Brown (2017) evaluated how position within a stream network affected the outcome of restoration on invertebrate communities. Ostensibly, their hypotheses were partially supported as restoration had stronger effects in headwater streams: invertebrate taxonomic richness was increased and temporal variability decreased in restored reaches; however, these results were not consistent upon closer scrutiny for both the original paper (Swan and Brown 2017) and the later erratum (Swan and Brown 2018). Here, I provide a secondary analysis of the data, with hypotheses and interpretations in the context of stream, meta-community, and restoration ecology. Swan and Brown (2017, 2018) evaluated the effect of restoration on sites receiving various combinations of in-channel manipulation and riparian reforestation treatments. Given the difference in the relative importance of environmental filtering and dispersal between headwaters and mainstems and the structure of river networks, I contend that different restoration treatments have differential effects between headwaters and mainstems. I hypothesized in-channel manipulations would have more consistent effects between headwaters and mainstems compared to riparian reforestation, and I used this hypothesis to guide site selection in the re-analysis. I then compared results from the re-analysis to those presented by Swan and Brown (2017, 2018). I did not find any effects of restoration on local diversity, spatial dissimilarity, or temporal variability, let alone differential effects of restoration between headwaters and mainstems; these results are contrary Swan and Brown (2017, 2018), who reported that restoration increased taxonomic richness, increased spatial dissimilarity, and decreased temporal variability in restored headwater streams. I demonstrate further that the statistical tests conducted by Swan and Brown (2017, 2018) were invalid and, therefore, recommend the use of the results presented here. More broadly, I suggest, in agreement with Swan and Brown (2017, 2018) and a growing body of research, that river and stream restoration will likely have greater success if a regional approach is taken to designing and implementing restoration projects.

Joint model of gradient magnitude and Gabor features via Spatio-Temporal slice

To form a high-performance video quality predictor, we developed a framework for full-reference (FR) video quality assessment that integrates Spatio-temporal slice analysis (STS) to create a high-performance predictor of video quality. However, both gradient and Gabor are spatial–temporal structural capturers used for the simultaneous extraction of both spatial and temporal features. In this paper, we proposed a novel VQA algorithm via a joint model of gradient magnitude and Gabor features (JMG) between the STS images of the reference videos and their distorted counterparts to assess the degradation of video quality effectively. Firstly, gradient magnitude and the Gabor filter were constructed to extract the spatiotemporal features of the video sequence. However, the two-feature model combined to predict the perceptual quality of frames. This new proposed VQA model is known as the horizontal and time STS (HT-JMG) model. To further investigate the influence of spatial dissimilarity, we combined the frame-by-frame spatial T-JMG(S) factor with the HT-JMG and propose another VQA model, called the time, horizontal, and vertical STS (THV-JMG) model. Finally, the results of the experiment showed that the proposed method has a strong correlation with subjective perception and is competitive with state-of-the-art full reference VQA models.

Spatial patterns and influencing factors of sewage treatment plants in the Guangdong-Hong Kong-Macau Greater Bay Area, China

Over the past few years the discharge of waste and sewage in the Guangdong-Hong Kong-Macau Greater Bay Area (GHMB) of China has increased, exerting a great amount of pressure on ecological protection. In this study, we focus on achieving a balanced spatial layout of sewage treatment plants in order to reveal the regional differences and spatial patterns of sewage treatment plants in the GHMB and identify the key factors influencing the spatial patterns. In particular, we employ POI (point of interest) geographical data to evaluate the spatial patterns and agglomeration status of sewage treatment plants in the GHMB using Exploratory Spatial Data Analysis (ESDA). We then explore the principle influencing factors of the determined spatial patterns using the geographical weighted regression model (GWR). Results demonstrate that: (1) the absolute number of sewage treatment plants is highest in the central and western regions, while the per capita of sewage treatment plants is clearly clustered in the northwest and southwest regions; (2) the absolute number of sewage treatment plants exhibits larger spatial dissimilarity than that of the per capita values, with High-High cluster types principally distributed in the conjunction areas of Jiangmen, Foshan and Zhaoqing in western GHMB and Low-Low clusters in the western Pearl River Delta (PRD) estuary; and (3) the key influencing factors are identified as GDP per capita, the output value of the primary and secondary industries and industrial water consumption. Regions with high regression coefficient fluctuations of the four influencing factors are centralized within the PRD estuary and adjacent regions. Policy recommendations including optimizing the sewage treatment plant layout, enhancing the service capacity potential of the existing sewage treatment plants and upgrading the industrial structure are proposed to promote a spatial equilibrium configuration of sewage treatment plants in the GHMB.