Spatial Distribution Characteristics Research Articles

Data-driven insights into age-friendly smart community development in China: A case study of Beijing

The aging society has prompted a re-evaluation of community development strategies to better accommodate the needs of older populations. In this context, the concept of age-friendly smart communities has gained prominence, aiming to leverage technologies to enhance the quality of life for older residents. This article summarizes a general concept of an age-friendly community within the framework of smart city development in China. It then explores residential compounds in Beijing to investigate their potential for implementing age-friendly smart communities. Through data description and classification, the spatial distribution and local characteristics of residential compounds were examined. The results highlight housing compounds with the potential to become age-friendly smart communities, based on factors such as building age, population demographics, and typological differences reflecting community conditions and surrounding resources. Overall, by examining the intersection of the aging population, urban regeneration, and technology integration, this article contributes to understanding how data-driven insights can shape the evolution of smart communities in an aging society.

Spatial Distribution Characteristics and Sustainable Inheritance Strategies of National Traditional Fine Arts Intangible Cultural Heritage in China

Spatial Distribution Characteristics and Sustainable Inheritance Strategies of National Traditional Fine Arts Intangible Cultural Heritage in China

Spatial distribution characteristics and influencing factors of traditional villages based on geodetector: Jiarong Tibetan in Western Sichuan, China.

Jiarong Tibetan is a regional group with distinctive regional characteristics and possess precious traditional village resources. Studying the spatial distribution and influencing factors of traditional villages is of vital significance for the protection and renewal of villages and the revitalization of cultural heritage. Nevertheless, due to the fact that the Jiarong Tibetan inhabited area has not been clearly defined for a long time, there is a lack of holistic discussion on the distribution features and driving mechanisms of traditional villages in this region. In order to fill this research gap, the paper is the first to break away from the existing county administrative divisions to define the study area. Moreover, the analysis is carried out by using the nearest neighbor index, kernel density, GoeDa and Geodetector, etc. for traditional villages at national-level and provincial-level. The results show that the spatial distribution of the traditional villages of Jiarong Tibetan is characterized by typical aggregation, with the core intensive area in Danba County and the sub-core intensive area in the central and northern parts. The results of factor detection show that the spatial distribution pattern of the traditional villages is the consequence of the synergistic effect of multiple factors, and the interaction effect is significantly enhanced. The economic level and climatic conditions play a controlling role, and population, elevation, intangible cultural heritage and rivers also have notable effects. The findings of study can offer scientific guidance and suggestions for the inheritance and development of traditional villages in Jiarong Tibetan settlement area.

Spatial Distribution Characteristics and Source Analysis of Ions in Lancang River and Yangtze River Source Region During Wet Period

Spatial Distribution Characteristics and Source Analysis of Ions in Lancang River and Yangtze River Source Region During Wet Period

Constrained Iterative Adaptive Algorithm for the Detection and Localization of RFI Sources Based on the SMAP L-Band Microwave Radiometer

The Soil Moisture Active Passive (SMAP) satellite carries an L-band microwave radiometer. This sensor can be used to observe global soil moisture (SM) and sea surface salinity (SSS) within the protected L-band spectrum (1400–1427 MHz). Owing to the complex effects of radio frequency interference (RFI), the SM and SSS data are missing or have low accuracy. In this paper, a constrained iterative adaptive algorithm for the detection, identification, and localization of RFI sources is designed, named MICA-BEID. The algorithm synthesizes antenna temperatures for the third and fourth Stokes parameters before RFI filtering, creating a new polarization parameter called WSPDA, designed to approximate the level of RFI interference on the L-band microwave radiometer. The algorithm then utilizes the WSPDA intensity and distribution density of RFI detection samples to enhance the identification and classification of RFI sources across various intensity levels. By utilizing statistical methods such as the probability density function (PDF) and the cumulative distribution function (CDF), the algorithm dynamically adjusts adaptive parameters, including the RFI detection threshold and the maximum effective radius of RFI sources. Through the application of multiple iterative clustering methods, the algorithm can adaptively detect and identify RFI sources at various satellite orbits and intensity levels. Through extensive comparative analysis with other localization results and known RFI sources, the MICA-BEID algorithm can achieve optimal localization accuracy of approximately 1.2 km. The localization of RFI sources provides important guidance for identifying and turning off illegal RFI sources. Moreover, the localization and long-time-series characteristic analysis of RFI sources that cannot be turned off is of significant value for simulating the spatial distribution characteristics of localized RFI source intensity in local areas.

Spatial distribution, influencing factors and innovative development countermeasures of farmer cooperatives in Hunan Province, China

China’s rural reform is reliant on farmers' cooperatives as a key organization vehicle. It plays an important role in promoting rural revitalization. Such as, realizing the organic connection between small farmers and agricultural modernization. This study used the nearest neighbor index and kernel density estimation to analyze the spatial distribution and structural characteristics of farmer cooperatives in Hunan Province. It revealed the spatial differentiation law of cooperatives. Also using geographical detectors to figure out the main factors that affect the spatial distribution. The results show that: ① Hunan Farmers Cooperatives show significant spatial agglomeration. The overall spatial distribution shows the spatial characteristics of "one core, one circle, and multiple points". And the spatial distribution pattern of "large agglomeration, finger-shaped radiation distribution". Among them, the distribution of provincial demonstration cooperatives is relatively balanced. ② Cooperatives in six types of industries, such as planting, forestry, and feeding, showed agglomeration distribution. Different industrial cooperatives spread out in different ways, such as in an anti-"L" shape, a dual-core shape, or a one-center area. ③ The 24 influence factors selected from the five dimensions of the natural environment, social economic basis, production basis, output capacity, and facility basis have high, general, and weak influence on cooperatives' spatial distribution. The development and distribution of cooperatives mainly depend on resource endowment, social and economic development level, and market dependence. The spatial distribution heterogeneity of different professional cooperatives is mainly affected by slope, per capita disposable income of rural residents, road density, and other factors. ④ The progression of farmer cooperatives in Hunan Province should prioritize high-quality development, emphasizing the need for innovative approaches and transformative strategies within rural industrial organizations. It is imperative to optimize the spatial distribution of cooperatives, strategically contributing to the establishment of a novel framework for modern agricultural development in Hunan Province. Additionally, there is a critical emphasis on spearheading collaborative initiatives among cooperatives of varied industrial types, aimed at fostering the integrated development of rural primary, secondary, and tertiary industries.

The Influence of Spatial Heterogeneity of Urban Green Space on Surface Temperature

Urban green space (UGS) has been recognized as a key factor in enhancing the urban ecosystem balance, particularly in arid areas. It is often considered an effective means to mitigate the urban heat island (UHI) effect. In this study, the reference comparison method was utilized to optimize the process of nighttime lighting data; the random forest classification method was employed to extract UGS data; and the radiative transfer method was applied in land surface temperature (LST) inversion. Additionally, moving window analysis was conducted to assess the robustness of the results. The objective of this research was to analyze the spatial distribution characteristics of UGS and LST and to explore their bivariate local spatial autocorrelations by calculating four landscape metrics, including the aggregation index (AI), edge density (ED), patch density (PD), and area-weighted mean shape index (Shape_am). It was found that the distribution of UGS in the study area was uneven, with higher temperatures in the eastern and western regions and lower temperatures in the central and southern regions. The results also revealed that ED, PD, and Shape_am were negatively correlated with LST, with correlation coefficients being −0.469, −0.388, and −0.411, respectively, indicating that UGS in these regions were more effective in terms of cooling effect. Conversely, AI was found to be positively correlated with LST (Moran’ I index of 0.449), indicating that surface temperatures were relatively higher in regions of high aggregation. In essence, the fragmented, complex, and evenly distributed green patches in the study area provided a better cooling effect. These findings should persuade decision makers and municipal planners to allocate more UGS in cities for UHI alleviation to improve quality of life and enhance recreational opportunities.

Critical Threshold-Based Heat Damage Evolution Monitoring to Tea Plants with Remotely Sensed LST over Mainland China

Tea plants (Camellia sinensis (L.) Kuntze) are a cash crop that thrive under warm and moist conditions. However, tea plants are becoming increasingly vulnerable to heat damage (HD) during summer growing seasons due to global climate warming. Because China ranks first in the world in both harvested tea area and total tea production, monitoring and tracking HD to tea plants in a timely manner has become a significant and urgent task for scientists and tea producers in China. In this study, the spatiotemporal characteristics of HD evolution were analyzed, and a tracking method using HD LST-weighted geographical centroids was constructed based on HD pixels identified by the critical LST threshold and daytime MYD11A1 products over the major tea planting regions of mainland China from two typical HD years (2013 and 2022). Results showed that the average number of HD days in 2022 was five more than in 2013. Daily HD extent increased at a rate of 0.66% per day in 2022, which was faster than that in 2013 with a rate of 0.21% per day. In two typical HD years, the tea regions with the greatest HD extent were concentrated south of the Yangtze River (SYR), with average HD pixel ratios of greater than 50%, then north of the Yangtze River (NYR) and southwest China (SWC), with average HD pixel ratios of around 40%. The regions with the least HD extent were in South China (SC), where the HD ratios were less than 40%. The HD LST-weighted geographical centroid trajectories showed that HD to tea plants in 2013 initially moved from southwest to northeast, and then moved west. In 2022, HD moved from northeast to west and south. Daily HD centroids were mainly concentrated at the conjunction of SYR, SWC, and SC in 2013, and in northern SWC in 2022, where they were near to the centroid of the tea planting gardens. The findings in this study confirmed that monitoring HD evolution of tea plants over a large spatial extent based on reconstructed remotely sensed LST values and critical threshold was an effective method benefiting from available MODIS LST products. Moreover, this method can identify and track the spatial distribution characteristics of HD to tea plants in a timely manner, and it will therefore be helpful for taking effective preventative measures to mitigate economic losses resulting from HD.

Examining the complex relationship between Urbanization and ecological environment in ecologically fragile areas: a case study in Southwest China

The sustainable development of ecologically fragile areas and the implementation of regional coordinated development strategies cannot be separated from the coordinated development and common progress of urbanization and the ecological environment, and this is particularly the case in Southwest China. This study examines the interplay between urbanization and the ecological environment across 26 cities in Southwest China from 2009 to 2019, utilizing 30 statistical indicators to analyze their coupling coordination relationship and its spatiotemporal evolution. The Entropy TOPSIS method, the coupling coordination degree model, and the obstacle factors model were used to calculate the subsystem score, coupling coordination degree, and obstacle factors, respectively. Our findings reveal an upward trajectory in urbanization scores across the 26 cities, juxtaposed with a fluctuating downward trend in ecological environment scores. The coupling coordination degree of urbanization and ecological environment in most cities maintained a rapid upward trend and showed spatial distribution characteristics of “strong core, weak middle, and edge.” Moreover, our analysis identified public transport facilities, aggregate purchasing power, and cultural supply service services as primary obstacle factors impeding the development of coupling coordination degrees. These research results offer valuable insights for informing future endeavors in achieving high-quality development and fostering ecological civilization.

Spatiotemporal Variation, Meteorological Driving Factors, and Statistical Models Study of Lake Surface Area in the Yellow River Basin

The surface area changes of 151 natural lakes over 37 months in the Yellow River Basin, based on remote sensing data and 21 meteorological indicators, employing spatial distribution feature analysis, principal component analysis (PCA), correlation analysis, and multiple regression analysis, identify key meteorological factors influencing these variations and their interrelationships. During the study period, lake area averages were from 0.009 km2 to 506.497 km2, with standard deviations ranging from 0.003 km2 to 184.372 km2. The coefficient of variation spans from 3.043 to 217.436, indicating considerable variability in lake area stability. Six primary meteorological factors were determined to have a significant impact on lake surface area fluctuations: 24 h precipitation, maximum daily precipitation, hours of sunshine, maximum wind speed, minimum relative humidity, and lakes in the source region of the Yellow River generally showed a significant positive correlation. For maximum wind speed (m/s), 28 lakes showed significant correlations, with five positive and twenty-three negative correlations, correlation coefficients ranging from −0.34 to −0.63, average −0.47, indicating an overall negative correlation between lake surface area and maximum wind speed. For maximum daily precipitation (mm), 36 lakes had 21 showing a positive correlation, indicating a positive correlation between lake surface area and daily precipitation in larger lakes. Furthermore, of the 117 lakes with sufficient data to model, the predictive capabilities of various models for lake surface area changes showcased distinct advantages, with the random forest model outperforming others in a dataset of 65 lakes, Ridge regression is best for 28 lakes, Lasso regression performs best for 20 lakes, Linear model is only best for 4 cases. The random forest model provides the best fit due to its ability to handle a large number of feature variables and consider their interactions, thereby offering the best fitting effect. These insights are crucial for understanding the influence of meteorological factors on lake surface area changes within the Yellow River Basin and are instrumental in developing predictive models based on meteorological data.

Source Analysis and Bioavailability of Soil Cadmium in Poyang Lake Plain of China Based on Principal Component Analysis and Positive Definite Matrix Factor

In order to identify the source and bioavailability of soil Cd in the alluvial geological high background area, 3799 topsoil samples and 140 root soil samples were collected from the Jiulong area on the south bank of Poyang Lake, Jiangxi Province. The results confidently indicate that the range of topsoil Cd content is 0.02~8.12 ppm, with an exceedance rate of 14.6%. It is noteworthy that exceedance points were mostly distributed in quaternary sediments. The geostatistical analysis clearly shows that the spatial distribution characteristic of topsoil Cd is higher in the north and lower in the south. The area with extremely high values (>90% quantile) is predominantly located in the tidal flat and low-lying areas of the mainstream of the Xinjiang River. The PCA analysis confirms that the main source of topsoil Cd is man-made activities related to industry and mining. Soil Cd is primarily derived from upstream industrial and mining discharge (58.5%), as revealed by the PMF model analysis. The active Cd content in root soil is 77 ppb, with higher levels observed in the north and lower levels in the south. These findings suggest a significant risk of Cd diffusion along the upstream stream and deposition in the low-lying parts of the north. It is worth noting that Cd’s bioavailability and active forms in paddy fields are the highest, which can have a detrimental effect on food security. The correlation analysis suggests that genetic sources primarily control the bioavailability of soil Cd, followed by soil physicochemical properties such as SOC, Fe-Al oxides, and soil texture. Preventing source pollution and cutting off water system transmission are effective methods for preventing and controlling soil Cd pollution. These methods ensure the safety of cultivated land in the lakeside area of Poyang Lake Plain.

Identification of Critical Areas of Openness–Vitality Intensity Imbalance in Waterfront Spaces and Prioritization of Interventions: A Case Study of Xiangjiang River in Changsha, China

To alleviate the contradiction between high-density urban spatial environments and high-frequency citizens’ activities, it is vital to determine the degree of openness of waterfront space, figure out the matching relationship between spatial openness and vitality intensity, identify imbalanced spatial zones and divide the order of intervention, and compensate for the limitations of subjective judgment in traditional planning decisions. This paper uses the Changsha Xiangjiang River waterfront space as a research sample based on multi-source data. It constructs the evaluation indicators system and research framework for the degree of openness of waterfront space. Then, by evaluating the openness and vitality intensity of the waterfront space and adopting the quadrant division method, waterfront space zones with a mismatched openness and vitality intensity were identified. Finally, planning interventions are prioritized based on a priority index. The results show the following: (1) The openness and vitality of the waterfront space of Xiangjiang River show the spatial distribution characteristics of “high in the middle and low in the north and south” and “high on the east bank and low on the west bank”. (2) Fifteen low-quality waterfront spatial zones with “low vitality intensity and low openness” and one with a severe imbalance of “low openness–high vitality intensity” were identified. These waterfront spatial zones cannot meet the requirements for the high-quality development of waterfront space. (3) The study delineates five priority levels for planning interventions. Among them, three waterfront space zones belong to priority V, mainly distributed north and south of the Xiangjiang River. Five waterfront spatial zones belonging to priority IV are concentrated in the middle of the Xiangjiang River. The above areas need to be prioritized for improvement to accurately promote the overall balanced development of the waterfront space.

Spatial Distribution and Variation Characteristics of Saturated Hydrologic Conductivity on the Chinese Loess Plateau

Spatial Distribution and Variation Characteristics of Saturated Hydrologic Conductivity on the Chinese Loess Plateau

Global Atlas of Methane Metabolism Marker Genes in Soil.

Methane, a greenhouse gas, plays a pivotal role in the global carbon cycle, influencing the Earth's climate. Only a limited number of microorganisms control the flux of biologically produced methane in nature, including methane-oxidizing bacteria, anaerobic methanotrophic archaea, and methanogenic archaea. Although previous studies have revealed the spatial and temporal distribution characteristics of methane-metabolizing microorganisms in local regions by using the marker genes pmoA or mcrA, their biogeographical patterns and environmental drivers remain largely unknown at a global scale. Here, we used 3419 metagenomes generated from georeferenced soil samples to examine the global patterns of methane metabolism marker gene abundances in soil, which generally represent the global distribution of methane-metabolizing microorganisms. The resulting maps revealed notable latitudinal trends in the abundances of methane-metabolizing microorganisms across global soils, with higher abundances in the sub-Arctic, sub-Antarctic, and tropical rainforest regions than in temperate regions. The variations in global abundances of methane-metabolizing microorganisms were primarily governed by vegetation cover. Our high-resolution global maps of methane-metabolizing microorganisms will provide valuable information for the prediction of biogenic methane emissions under current and future climate scenarios.

A Gaussian Function Model of Mesoscale Eddy Temperature Anomalies and Research of Spatial Distribution Characteristics

Mesoscale eddies are ubiquitous oceanic phenomena and play an important role in ocean circulation, ocean dynamics, and the transport of material energy. Temperature anomalies are a crucial parameter that reflects the state of mesoscale eddies. This study proposes a Gaussian function model to fit the vertical temperature anomaly (TA) profile to facilitate the analysis of variations, and the principle of the model is based on the fact that each TA profile tends to fluctuate around one or more peaks. The model is extracted and validated using Argo profiles within cyclonic and anticyclonic eddies in the Northwest Pacific Ocean spanning over the period from 2002 to 2021. The validation demonstrates that the model can accurately recover the vertical TA profiles with a limited number of parameters. This makes it suitable for analysing the spatial distribution patterns that require a large sample count. The analysis indicates that eddies with different TA profiles have a spatial aggregation effect in geographic distribution. Eddies with lower extreme temperature anomalies, at depths of 200–300 m, are mainly distributed along two bands on the north side of the Kuroshio Extension (KE) and the North Equatorial Current. Eddies with extreme TAs at the deepest depth (500–600 m) are distributed along the KE.

An efficient method for modeling and evaluating the bench terrain of open-pit mines

In order to quantitatively analyze the roughness of the bench floor during open-pit mine blasting, this study proposes a real-time measuring method for the three-dimensional terrain of the bench floor during the excavation process. Real-time monitoring is conducted at the boundary and discrete internal points of the workbench floor during electric shovel operation, utilizing real-time kinematic global navigation satellite system (RTK-GNSS) positioning technology. An improved convex hull algorithm is introduced to automatically extract the optimal boundary of discrete point clouds based on their spatial distribution characteristics. This study establishes a digital elevation model (DEM) using five interpolation algorithms for 3D terrain visualization simulation. Through cross-validation, a comparative analysis of the DEM accuracy, the simulation results of the ordinary kriging interpolation algorithm were found to be optimized. The optimized interpolation algorithm is applied to simulate the 3D terrain in the Dexing open-pit copper mine, and the relevant terrain parameters were calculated. This dataset can serve as a precise foundation for the real-time path planning of elevation blasting design and ground leveling operations.

Spatial and Temporal Distribution Characteristics of Ozone Concentration and Health Benefit Assessment in the Beijing-Tianjin-Hebei Region from 2015 to 2020

To evaluate the spatial and temporal distribution characteristics of ambient ozone (O3) in the Beijing-Tianjin-Hebei (BTH) Region, the land use regression (LUR) model and random forest (RF) model were used to simulate the ambient O3 concentration from 2015 to 2020. Meanwhile, all-cause, cardiovascular, and respiratory mortalities as well as economic losses attributed to O3 were also estimated. The results showed that upward trends with fluctuation were observed for ambient O3 concentration, mortalities, and economic losses attributable to O3 exposure in the BTH Region from 2015 to 2020. The areas with high O3 concentration and great changes were concentrated in the central and southwestern regions, whereas the concentration in the northern region was low, and the change degree was small. The spatial distribution of the mortalities was also consistent with the spatial distribution of O3 concentration. From 2015 to 2020, the economic losses regarding all-cause mortality and cardiovascular mortality increased in 13 cities of the BTH Region, whereas the economic losses of respiratory mortality decreased in 4 cities in the BTH Region. The results indicated that the priority areas for O3 control were not uniform. Specifically, Beijing, Tianjin, Hengshui, and Xingtai were vital areas for O3 pollution control in the BTH Region. Differentiated control measures should be adopted based on the characteristics of these target areas to decline O3 concentration and reduce health impacts and economic losses associated with O3 exposure.

Health Risk Assessment of Heavy Metals in Soils of a City in Guangdong Province Based on Source Oriented and Monte Carlo Models

Taking a city in Guangdong Province as the research area, the concentration and spatial distribution characteristics of heavy metals in the surface soil were studied to clarify the situation of soil heavy metal pollution and priority control factors, providing basic data for the prevention and control of soil heavy metal pollution in the city. The content characteristics of heavy metals in 221 soil samples in the city were analyzed, and the potential health risk assessment and source analysis were carried out through the Monte Carlo model, the potential health risk assessment (HRA) model, and the PMF receptor model. It was found that heavy metals ω(As), ω(Hg), ω(Cd), ω(Pb), ω(Cr), ω(Cu), ω(Ni), and ω(Zn) in the soil of the city were 18.16, 0.43, 1.46, 68.57, 98.34, 64.19, 26.53, and 257.32 mg·kg-1, respectively, with a moderate to high degree of variation. Except for Ni concentration, the soil concentrations of other heavy metal elements exceeded the background values of soil in Guangdong Province to a certain extent, and the concentrations of Cd and Zn exceeded the national secondary standards, resulting in severe heavy metal pollution; the main sources of heavy metals were industrial sources, and natural parent materials, lead battery manufacturing, transportation, artificial cultivation, and pesticide and fertilizer inputs also had an undeniable impact on the accumulation of heavy metals in the soil. Heavy metals in the soil had a certain degree of tolerable carcinogenic health risk for both children and adults, whereas non-carcinogenic risks could be ignored. The potential health risk of children was greater than that of adults, and the main exposure route was through oral intake. The input sources of pesticides and fertilizers and As should be the main controlling factors for the health risks of heavy metals in the city's soil, followed by mixed sources and Cr. There were differences in the spatial distribution characteristics and relative pollution levels of heavy metals, and it is necessary to deepen zoning monitoring and control, strengthen soil pollution prevention and control, and reduce human input of heavy metals in soil.

Seasonal and Spatial Distribution Characteristics of Sepia esculenta in the East China Sea Region: Transfer of the Central Distribution from 29° N to 28° N.

The golden cuttlefish (Sepia esculenta) is an important cephalopod species with a lifespan of approximately one year. The species plays a crucial role in marine ecological support services and is commercially valuable in fisheries. In the seas around China, this species has emerged as the main target for cuttlefish fisheries, replacing Sepiella maindroni since the 1990s. Variations in oceanographic conditions associated with global warming could significantly impact the temporal-spatial distribution of the species. In this study, we performed bottom trawling surveys with four cruises during 2018-2019 in the East China Sea region to determine the current resource status and seasonal-spatial variations in S. esculenta. We found that the average individual weight (AIW) values were 4.87 and 519.00 g/ind at stations located at 30.50° N, 124.00° E and 30.50° N, 124.50° E, respectively, with the aggregation of larvae and parent groups in spring. The species was not distributed north of 32.00° N in summer. The catch per unit effort by weight (CPUEw) value decreased in the order of 2772.50→2575.20→503.29→124.36 g/h, corresponding to latitudes of 34.50° N→34.00° N→33.50° N→32.50° N 121.50° E in autumn. The most suitable fishing areas were the south of the East China Sea region in spring; the south of the East China Sea region extending to the center and outer parts of the East China Sea region in summer; the south of the Yellow Sea close to the Haizhou Bay fishing ground and the forbidden fishing line region of the Lusi and Dasha fishing grounds in autumn; and the south and center of the East China Sea region in winter. The most suitable sea bottom temperature (SBT) values from spring to winter were 14.76-20.53 °C, 19.54-22.98 °C, 11.79-17.64 °C, and 16.94-20.36 °C, respectively. The most suitable sea bottom salinity (SBS) values were 31.53-34.80‱ in spring, 32.95-34.68‱ in summer, 31.51-34.77‱ in autumn, and 33.82-34.51‱ in winter. We concluded the following: (1) the southern and northern areas of the East China Sea region are spawning and nursery grounds, respectively, in spring; (2) the central distribution is located at a latitude of 28.00° N in autumn and winter; and (3) the southern area of the Yangtze River to the north is a spawning ground in spring, and the areas located at 29.00-34.50° N, 124.00-124.50° E, and 28.00-30.50° N, 125.50-126.50° E are nursery grounds. The results of this study provide useful guidance for appropriate fisheries management, thereby avoiding a collapse in the S. esculenta population, which has been experienced in other species in this area.

Land use transition and its effect on ecosystem service value with introducing "three wastes" factor in the industrial county, China.

Land use transition and its impact on ecosystem service value (ESV) are the foundation for optimizing the layout of territorial space and ecological civilization construction. With the acceleration of industrialization and urbanization, the area of construction land expands in China. To accurately estimate the ESV in industrial counties, the impact of construction land on the ecological environment should be fully considered. This paper took Gangcheng District, Jinan City, a steel base in the Shandong Province of China as an example, then the value coefficients of "three wastes" factors (waste gas, wastewater, and waste) were introduced, and an improved calculation method of ESV was put forward for industrial counties in combination with remote sensing and land use data. Finally, the land use transition and its ESV effect in typical industrial counties were analyzed using geo-informatic Tupu and grid method. The results showed that the most important land use transitions were from grassland and forestland to cultivated land, from cultivated land and forestland to construction land in 1990-2010, and from cultivated land transformed to forestland in 2010-2021. The types of land use transition were mainly repetitive and continuous. The ESV first decreased and then increased, with a slight overall decline for more than 30years, showing a spatial distribution characteristic of "low in the south-central and high around." Land use transition had the impact on ESV with the negative contribution rate of 68.28% in 1990-2000 and 73.16% in 2000-2010, mainly caused by the transition from forestland and grassland to cultivated land and construction land, and the positive contribution rate of 81.72% in 2010-2021, mainly caused by the transition from cultivated land to forestland. Compared with the ESV calculation method without introducing the "three wastes" factor and Xie Gaodi's method, the improved method in this paper considered the inevitable impact of construction land on ESV in industrial counties and made the ESV calculated more accurate according to the regional nature. This paper cannot only enrich the theories and technical methods of land use transition and its effects, and provide a case reference for similar industrial counties, but also provide data and decision-making support for the spatial layout and ecological protection in the study area.