Spatial Distribution Trends Research Articles

Long-term changes in Noctiluca scintillans blooms along the Chinese coast from 1933 to 2020.

Noctiluca scintillans is one of the most common harmful algal species and widely known due to its bioluminescence. In this study, the spatial distribution, seasonal variations, and long-term trends of N. scintillans blooms in China and the related drivers were analyzed and discussed. From 1933 to 2020, a total of 265 events of N. scintillans blooms were recorded in Chinese coastal waters, with a total duration of 1052 days. The first N. scintillans bloom occurred in Zhejiang in 1933, and only three events were recorded before 1980. From 1981 to 2020, N. scintillans caused harmful algal blooms (HABs) almost every year, both the average duration and the proportion of multiphase HABs showed an increasing trend. 1986-1992, 2002-2004, and 2009-2016 were the three peak periods with a frequency of no less than five events of N. scintillans blooms per year. In terms of spatial distribution, N. scintillans blooms spread from the Southeast China Sea to the Bohai Sea after 2000, Guangdong, Fujian, and Hebei were the three provinces with the highest numbers of recorded events of N. scintillans blooms. Moreover, 86.8% of the events of N. scintillans blooms occurred in spring (March, April, and May) and summer (June, July, and August). Among environmental factors, the dissolved inorganic phosphate, dissolved silicate and chemical oxygen demand were significantly correlated with the cell density of N. scintillans during N. scintillans blooms, and most of N. scintillans blooms were recorded in the temperature range of 18.0-25.0°C. Precipitation, hydrodynamics, water temperature, and food availability might be the main factors affecting the spatial-temporal distribution of N. scintillans blooms along the Chinese coast.

Spatial distribution and temporal trend of organochlorine pesticides in Chinese surface soil.

Although organochlorine pesticides (OCPs) in the Stockholm Convention List were banned for a period of time, the residue of OCPs in environment was still detected recently. Therefore, the continuous environmental monitoring was necessary and important for the deep understanding on the temporal trend of environmental fate of OCPs. In this study, the national scale surface soil samples in 26 provinces of China in 2012 were collected, and 28 OCPs were analyzed. The mean concentrations (ng/g dw) of Σhexachlorocyclohexanes (HCHs), Σdichlorodiphenyltrichloroethane (DDTs), hexachlorobenzene (HCB), and hexachlorobutadiene (HCBD) were 2.47 ± 5.4, 4.29 ± 8.28, 3.33 ± 7.68, and 0.041 ± 0.097, respectively. The correlations between OCPs concentrations with temperature, latitude, and longitude were conducted for the deep study of the spatial distribution pattern of OCPs. It was found that HCHs, HCB, and HCBD are positively correlated with latitude and longitude; however, the correlations were not significant. HCHs followed the secondary distribution pattern, and DDTs followed both the primary and/or secondary distribution patterns. Except for HCB, other OCPs showed a gradual downward trend from 2005 to 2012, indicating the effectiveness of the phase-out of OCPs. In summary, the results of the study provided new insight into the related studies, which will help us to better understand the long-term environmental fate of OCPs on large scales.

Spatial distribution and historical trend of microplastic pollution in sediments from enclosed bays of South Korea

Seafloor sediments are an important sink for microplastics (MPs), and the vertical profile of MP accumulation in a sediment core represents historical pollution trends. In this study, MP (20–5000 μm) pollution in surface sediments of urban, aquaculture, and environmental preservation sites in South Korea was evaluated, and the historical trend was investigated using age-dated core sediments from the urban and aquaculture sites. The abundance of MPs ranked in the order of urban, aquaculture, and environmental preservation sites. Polymer types were more diverse at the urban site compared to other sites, and expanded polystyrene was dominant in the aquaculture site. An increase in MP pollution and polymer types was observed from bottom to top of cores, and historical trends of MP pollution reflect local influences. Our results indicate that the characteristics of MPs are determined by human activities, and MP pollution should be addressed according to the characteristics of each site.

Drivers of Net Primary Productivity Spatio-Temporal Variation in Ningxia, China

The drivers and spatial distribution trends for net primary productivity (NPP) in Ningxia were studied to determine the priority vegetation restoration areas. NPP data from MOD17 A3 were used to determine the future NPP trends through slope trend analysis and the Hurst index. Spatial drivers were defined by a geographic detector and correlation analysis. Results indicate that NPP positively fluctuated from 2000 to 2020 with an average range between 119.98 and 249.66 gC/m2a, and a multi-year average of 190.15 gC/m2a. The spatial distribution has more obvious divergent characteristics, showing distribution characteristics of low in the central and northern sides and high in the southern and northern middle. Superimposed on the analysis of slope and Hurst indices, the future vegetation NPP in Ningxia will show four scenarios of continuous increase, continuous decrease, change from increase to decrease and change from decrease to increase, accounting for 22.35%, 1.36%, 71.42% and 2.86% of the area of the region, respectively. Driving factor influence can be divided into dominant factors and important factors. The interaction between the two factors is positive, and the maximum q value under the interaction of precipitation and temperature is 0.687. NPP is mainly driven by climatic factors in 50.92% of the area and is mainly distributed in the central, western and southern parts of Ningxia. The non-climatic-factor-driven areas can be used as priority vegetation restoration areas, which accounting for 47.08%, are mainly concentrated in the northern Yellow River irrigation area, the desert steppe in the central and eastern parts, and a small part in the southern Liupan Mountains.

Spatial distribution and secular trend (1991-2014) of small for gestational age infants born in Jujuy.

Introduction. A fetus that does not reach the expected growth potential in utero is considered small for gestational age (SGA). Such restriction depends on genetic and/or environmental factors, being altitude a very relevant factor. This study analyzes the spatial distribution of the prevalence of SGA and its secular trend in Jujuy (1991-2014). Materials and methods. The records of 308 469 live births in Jujuy (Health Statistics and Information Department) were analyzed. The prevalence of SGA (weight/gestational age < P10 and < P3) was estimated for sex according to the INTERGROWTH-21st standard in the ecoregions of Jujuy (Valle and Ramal -less than 2000 MASL-, Puna, and Quebrada) across 3 periods (1991-2000, 2001-2009, 2010-2014) and proportions were compared. The secular trend was assessed using the Joinpoint regression analysis. Results. The overall prevalence of SGA was 2.3% (< P3) and 7% (< P10). Significantly higher values were observed in Puna and Quebrada in both SGA categories and across all periods. Only in Valle, significant differences were observed between sexes across all periods. The prevalence of SGA showed a significant downward secular trend at a provincial and regional level, and this was greater in Quebrada (5.2% < P3 and 3.5% < P10). Conclusions. A consistent and significant decrease in the prevalence of SGA has been observed since the 1990s in Jujuy, where altitude is itself a determining factor of size at birth, since the Puna and Quebrada regions showed the highest prevalence of SGA during the entire period.

Patterns of Forest Species Association in a Broadleaf Forest in Romania

Ecological patterns of species distribution can reveal essential information on the spatial and functional relationship between species or species and their environment. Various approaches can be used to assess species associations, and our study aimed to compare three methods at different scales: the co-occurrence indices for binary presence–absence data, principal component analysis (PCA) on species abundance and point process analysis. Our goal was to gain a deeper understanding of the species’ co-occurrence patterns and notice if the three methods capture roughly the same spatial distribution trends. Our observational study of the analysed sapling community displayed several positive relationships between species (e.g., the association between ash and linden). However, many relationships were inconsistent across different scales. Furthermore, attraction between species was more prevalent than repulsion. Overall, there is a positive association trend, with more relationships being significantly positive across all scales. This trend is consistent with other recent studies of tree–species interaction. Nonetheless, the results suggest that the scale significantly influences spatial patterns of associations. Positive associations tend to be more prevalent on larger scales, while negative associations are more commonly found on smaller scales, regardless of the analysis method used. While the PCA results are less consistent, the point process analysis allowed us to detect more refined patterns of species associations based on the distance of their interaction. In addition, the binary presence–absence analysis provided solid results, with a coarser spatial perspective but with significantly less sampling effort.

Decomposition of drivers and identification of decoupling states for the evolution of carbon emissions from energy consumption in China.

As the largest energy consumer, China's control of carbon emissions from energy consumption plays a pivotal role in world climate governance. However, few studies have been conducted to explore the emission reduction pathways that promote a high level of synergy between China's economic growth and the " carbon peaking and carbon neutrality " goal from the perspective of energy consumption. Based on the measurement of energy consumption carbon emissions, this paper reveals the spatial and temporal distribution and evolution trends of carbon emissions in China at the national-provincial level. The multi-dimensional socio-economic factors such as R&D and urbanization are taken into account, and the LMDI model is used to decompose the driving effects of energy consumption carbon emissions at the national-provincial levels. Further, this paper combines the Tapio decoupling index with the LMDI model to decompose the decoupling states of China year by year and at the provincial level in four periods to explore the reasons for the change of carbon decoupling states. The results show that: (1) China's energy consumption carbon emissions grew at a high rate before 2013, and slowed down after that. There are significant differences in the scale and growth rate of carbon emissions among provinces, which can be classified into four types accordingly. (2) The R&D scale effect, urbanization effect, and population scale effect are the factors driving the growth of China's carbon emissions; while the energy structure effect, energy consumption industry structure effect, energy intensity effect, and R&D efficiency effect inhibit the growth of China's carbon emissions. (3) Weak decoupling is the most dominant decoupling state in China from 2003 to 2020, and the decoupling state varies significantly among provinces. According to the conclusions, this paper proposes targeted policy recommendations based on China's energy endowment.

The Impact of Coordinated Development Policy on the Spatiotemporal Changes of Industrial Structure of Beijing–Tianjin–Hebei Urban Agglomeration

The coordinated development of Beijing–Tianjin–Hebei (BTH) is a major regional strategy in China that aims to alleviate Beijing’s non-capital functions and address the “big city disease”. Understanding the spatial distribution and changing trends of industrial development in BTH is critical for achieving BTH’s coordinated development goals. In particular, it is important to assess the effectiveness of Beijing’s non-capital functions at the industrial level. This study utilized the 2013 and 2018 economic census data and statistical methods such as spatial Gini coefficient, trend analysis, specialization index, and industry similarity. We first characterized the industrial development pattern by analyzing the spatiotemporal changes of the operating income and the number of legal entities in BTH urban agglomeration. Then, we identified the changes in the leading industries and industrial structure of different cities in BTH urban agglomeration from 2013 to 2018. The results indicate that the coordinated development policy has influenced the industrial structure of the BTH urban agglomeration, with an 85.53% increase in the number of legal entities and a 14.61% increase in operating income. Beijing’s non-capital functions have achieved initial results, mainly involving technology-intensive and knowledge-intensive tertiary industries such as information technology, finance, and scientific research. The division of industry and the development positioning of the three regions are gradually becoming clear. Our results show how the economic census data and spatial analysis can support significant advances in evaluating industrial and economic development patterns, and they can be used worldwide in the future.

Toward carbon neutrality: a bibliometric analysis of technological innovation and global emission reductions.

In the context of global carbon neutrality, climate change mitigation and response has become a top priority. Currently, countries around the world are setting emission reduction targets or are already involved in carbon-neutral actions, with technological innovation becoming the key to global emission reduction. Therefore, a systematic review of the literature related to technology innovation and emission reduction in response to carbon-neutral actions for climate change is conducted. A global bibliometric visualization analysis is presented using CiteSpace and VOSviewer software. This study visualizes the basic relationship between global emission reduction and technology-related literature under the carbon neutrality target and analyzes and discusses the spatial distribution and hotspot trends of the co-author network and knowledge base. The results show that (1) the trend of the number of relevant studies can be divided into two phases before and after, and starts to increase gradually after 2020. (2) The structural relationship of the author- and institution-based cooperative networks is relatively loose, and the main cooperative networks, mainly by countries, are initially formed by the key contributions of developed and emerging economies. (3) Relevant research hotspots are reflected in multiple perspectives such as investment, management, and policy, in addition to emission reduction targets and technological innovation itself. The causal relationship between relevant research and economic and political dimensions has become an important driving factor for research development. Especially in the paradigm shift phase, there are research characteristics of human intervention and specific actions. (4) In terms of future trends, research involving policy management, methodological efficiency, and systemic models will become important research paths in the future by matching the supply of actions to real needs.

Spatio-Temporal Patterns of Warm-Season Ground Surface Temperature—Surface Air Temperature Difference over China Mainland

Examining large-scale characteristics of the difference between ground surface temperature (GST) and surface air temperature (SAT) and its long-term trend will help understand land surface energy exchange and the effect of land-atmosphere interaction on climate change and variability. Based on a homogenized monthly dataset of GST and SAT from 1961 to 2018, this study analyzes the spatial distribution and long-term trend of the difference between ground surface temperature and surface air temperature (GST–SAT) in the warm season (April to October) over China mainland. The results show that the warm-season mean GST–SAT in the Qinghai-Tibet Plateau and the northwestern deserts have the largest GST–SAT. On average, the GST–SAT in China is the greatest in summer, with the maximum monthly value occurring in July. During 1961–2018, the warm-season mean GST–SAT undergoes a significant increasing trend (0.04 °C/10yr, p &lt; 0.01), with the largest increase seen in mid-late spring (April and May), and the smallest increase in August. Spatially, the GST–SAT increases significantly in the northern region, decreases slightly in the southern region, and remains unchanged in the Qinghai-Tibet Plateau. The warm-season mean GST–SAT is significantly positively correlated with altitude and sunshine duration (R = 0.50, 0.40; p &lt; 0.05), and significantly negatively correlated with relative humidity and precipitation (R = 0.48, −0.42; p &lt; 0.05), in the country on a whole in the analysis period.

Assessment of soil erosion and its driving factors in the Huaihe region using the InVEST-SDR model

Aiming to provide a scientific basis for the prevention and control of soil erosion in the Huaihe region, this study uses the InVEST-SDR model to estimate the temporal and spatial changes of soil erosion and soil conservation in the Huaihe region in 2010, 2015 and 2020, and the driving factors are evaluated and quantified using Random Forest and Geodetector, respectively. The major findings are as follows: (1) From 2010 to 2020, soil loss and soil retention in the Huaihe region gradually intensified, while the spatial distribution trend was consistent from year to year. (2) The results from Random Forest and Geodetector show that changes in soil loss and soil retention are mainly influenced by slope and rainfall. (3) The steepness and length of slopes are the most influencing factors for soil erosion. Soil loss and soil retention vary widely between different land uses. Forests play an important role in soil conservation.

Mechanisms of propeller jet-induced migration, release, and distribution of perfluoroalkyl acids in sediment–water systems

Perfluoroalkyl acids (PFAAs) are continuously accumulated in surface sediments due to extensive and long-term application. However, the mechanisms through which disturbances induced by ship propeller jets at the riverbed cause secondary release of PFAAs from sediments remain unclear. In this study, the effects of different propeller rotational speeds on PFAA migration, release, and distribution in multiphase media were investigated by performing indoor flume experiments combined with particle tracking velocimetry. Moreover, key factors influencing PFAA migration and distribution were identified, and partial least squares regression (PLS) method was applied to develop quantitative prediction models of relationships among hydrodynamics, physicochemical parameters, and PFAA distribution coefficients. The total PFAA concentrations (ΣPFAAs) in overlying water under propeller jet action exhibited transient characteristics and hysteresis with time after the disturbance. In contrast, the ΣPFAAs in suspended particulate matter (SPM) exhibited an upward trend throughout the process with consistent characteristics. The spatial distribution trends of PFAAs in overlying water and SPM at different propeller rotational speeds featured vertical variability and axial consistency. Furthermore, PFAA release from sediments was driven by axial flow velocity (Vx) and Reynolds normal stress Ryy, while PFAA release from porewater was inextricably linked to Reynolds stresses Rxx, Rxy, and Rzz (p < 0.05). PLS regression models showed that variations in Vorticity, dissolved organic carbon, and pH influenced the decreases in PFAA distribution coefficients between SPM and overlying water (KD-SW) as propeller rotational speed increased, except for very long-chain PFAAs (C > 10). The increases in PFAA distribution coefficients between sediment and porewater (KD-SP) were mainly determined by physicochemical parameters of sediments, and the direct effect of hydrodynamics was relatively weak. Our study provides valuable information regarding the migration and distribution of PFAAs in multiphase media under propeller jet disturbance (both during and after disturbance).

A large-scale assessment on spatial variability of potato yield and soil chemical properties in northern China

Understanding the spatial variability of potato yield and soil chemical properties is critical for designing management strategies and ensuring potato sustainable production. However, there has been no detailed investigation on a large-scale variation in yields and soil nutrients in potato production areas of China. In this study, 938 soil samples and potato production information were collected from the main potato-producing areas in northern China. The results showed that potato yields and selected soil properties varied considerably, with coefficients of variation ranging between 12.2% and 110.8%. Potato yield, pH, soil organic matter (SOM), total nitrogen (TN), available potassium (AK), and electrical conductivity (EC) showed strong spatial correlations, while mineral nitrogen (MN) and available phosphorus (AP) had moderate spatial correlations based on semi-variograms analysis. The spatial distribution of yields indicated that 83.3% of potato yields ranged from 20 to 60 t ha−1. The SOM, TN, AP, and AK showed similar spatial distribution trends with high concentrations in the northeast, while pH showed the opposite trend. EC was found to be highly variable with high values in the west. The high soil pH and low SOM were the most important constraints limiting potato productivity, and the high MN implied excessive nitrogen fertilizer application. The soil quality index (SQI) was calculated using selected soil properties, and a significant correlation between SQI and potato yield was observed. The spatial distribution of SQI showed that 42.2% of the study area was of low soil quality (SQI less than 0.6). A relatively low SQI indicated that there was great potential for increasing potato productivity in northern China. After dividing soil samples into rainfed and irrigated, the effect of soil nutrients on potato yield was found to become weaker at irrigated sites, where there was no correlation between SQI and yield, suggesting that the role of soil moisture overshadowed the role of nutrients. The spatial variability of soil chemical properties provided essential information for developing rational nutrient management strategies and regional planning to achieve sustainable potato production in China.

On the Seasonal and Spatial Dependence of Extreme Warm Days in Antarctica

AbstractThe spatial distribution of trends in temperature extremes over Antarctica remains largely unknown. Here we investigate the seasonal and spatial characteristics of extreme warm occurrence across Antarctica. The Antarctic inland areas show significant positive trends in the number of extreme warm days in austral spring and summer. The trends in the seasonal mean of daily maximum temperature show strong coherence with the trends in extreme warm occurrences. In addition, the long‐term longwave radiation, water vapor flux and regional atmospheric circulation changes are closely connected to the trends of extreme warm days in all seasons outside of summer; the summer longwave radiation and interior wind trends show little coherence with warm extreme trends, indicating other processes at play driving extreme warm days in summer.

Spatio-temporal variability of hydraulic conductivity in the floodplain riverbank of a hyporheic zone

A detailed measurement of floodplain riverbank sediment hydraulic conductivity (K) is the first step in analyzing the hydraulic relationship between streams and aquifers. Poyang Lake is the largest freshwater lake in China and has historically been a flood-prone area. A detailed field experiment was conducted in the Xiushui River, China, before and after the flood season. The grain-size distribution analysis method was used to determine the hydraulic conductivity of the riverbank. A total of 116 sediment samples were collected from the test site. An in situ permeameter test was used to confirm the consistency of the spatial distribution trend of the estimated hydraulic conductivity based on the grain-size distribution analysis. A Kruskal–Wallis test of the riverbank sediment K values obtained before and after the flood season showed that they belong to different populations. The probability distribution illustrated the strong heterogeneity of the riverbank sediments before and after the flood season. Previous studies have confirmed the presence of strong hyporheic exchange and biological processes at this study site. Following the flood season, the K values had a higher mean, median, and coefficient of variation, confirming that the flood process enhanced the heterogeneity of the riverbank sediments. Overall, the hydraulic conductivity of the three areas changed with distance from the river; the closer the area was to the river, the smaller the hydraulic conductivity and weaker the heterogeneity. An experimental framework of spatio-temporal variability in riverbank sediments is proposed, providing recommendations for researchers on conducting an integrated experiment.

The spatial distribution and temporal trends of livestock damages caused by wolves in Europe

Wolf populations are recovering and expanding across Europe, causing conflicts with livestock owners. Here we compiled incident-based livestock damage data across 21 countries for the years 2018, 2019 and 2020, during which 39,262 wolf-caused incidents were reported from 470 administrative regions. We found substantial regional variation in all aspects of the data, including the primary target species, the density of damages, their seasonal distribution, and their temporal trend. More than half of the variation in damage densities across regions was explained by the area of extensively cultivated habitats occupied by wolves, namely natural grasslands and broad-leaved forests. Regional variation in husbandry practices and damage prevention, while difficult to quantify at a continental scale, appear important factors to further modulate these incidents. As illustrated with detailed data from Germany, a relationship between the number of wolf units and damages diminished over time, suggesting some adaptation of livestock owners and local authorities to their presence, for example by increasing prevention efforts. As we argue, temporal trends of damage incidents, which are robust to variation in data collection across regions, are thus informative about the local intensity of the wolf-human conflict. We estimated increasing trends for the majority of regions, reflecting the current expansion of wolves across the continent. Nonetheless, many of these increases were moderate and for more than one third of all regions, trends were negative despite growing wolf populations, thus indicating that wolf-livestock conflicts can be successfully mitigated with proper management.

Spatial distribution and temporal trends of cyclic and linear siloxanes in sediment from semi-enclosed and industrialized bays of Korea, in 2013 and 2021

Although siloxanes are contaminants of emerging concerns, limited studies have been conducted on contamination and time trends in siloxanes from aquatic environments worldwide. To date, most previous studies have focused on the environmental relevance of cyclic siloxanes in coastal environments. In the present study, cyclic and linear siloxanes were measured in sediment collected from semi-enclosed bays in Korea in 2013 and 2021 to assess occurrence, spatial distribution, temporal trends, and ecological risks. Almost all siloxanes were detected in all sediment samples, indicating continuous contamination for the last decade. The concentrations of cyclic siloxanes in sediment were approximately two times higher than those of linear siloxanes. Decamethylcyclopentasiloxane (D5) and dodecamethylcyclohexasiloxane (D6) were predominantly detected in all sediment samples, possibly due to their high consumption and strong resistance. The overall concentrations of siloxanes in sediment gradually decreased from inner to outer parts of the bays, suggesting that industrial activities largely contributed to siloxane contamination. Moreover, the highest concentrations of siloxanes in both sampling years were observed in sediment near the outfall of wastewater treatment plant, implying a potential source in the coastal environment. Siloxane concentrations in sediment were significantly correlated with sedimentary organic carbon. The concentrations of siloxanes in sediment were not significantly different between 2013 and 2021, indicating ongoing contamination. The concentrations of D5 and D6 in our sediment samples showed a limited potential to pose a threat to benthic organisms.

Study on the Spatial and Temporal Evolution of NDVI and Its Driving Mechanism Based on Geodetector and Hurst Indexes: A Case Study of the Tibet Autonomous Region

The Tibet Autonomous Region (TAR) is located in the mid-latitude and high-cold regions, and the ecological environment in most areas is fragile. Studying its surface vegetation coverage can identify the ecosystem’s development trends and provide a specific contribution to global environmental change. The normalized difference vegetation index (NDVI) can better reflect the coverage of surface vegetation. Therefore, based on remote sensing data with a resolution of 1 km2, air temperature, precipitation, and other data in the same period in the study area from 1998 to 2019, this paper uses trend analysis, F-significance tests, the Hurst index, and the Geodetector model to obtain the spatial distribution, change characteristics, and evolution trends of the NDVI in the TAR in the past 22 years. At the same time, the quantitative relationship between natural and human factors and NDVI changes is also obtained. The study results show that the NDVI in the southern and southeastern parts of the TAR is higher, with mean values greater than 0.5 showing that vegetation cover is better. The NDVI in the western and northwestern parts of the TAR is lower, with mean values less than 0.3, indicating vegetation cover is worse. NDVI in the TAR showed an overall increasing trend from 1998 to 2019 but a decreasing trend in ridgelines, snow cover, and glacier-covered areas. The areas where NDVI values show a trend of increasing and then decreasing in the future account for 53.69% of the total area of the TAR. The most crucial factor affecting NDVI changes in the TAR is soil type, followed by influencing factors such as vegetation cover type, average annual air temperature, and average annual precipitation. The influence of natural elements is generally more significant than anthropogenic factors. The influencing factors have synergistic effects, and combining anthropogenic factors and other factors will show mutual enhancement and non-linear enhancement relationships. This study provides a theoretical basis for natural resource conservation, ecosystem restoration, and sustainable human development strategies in the TAR.

A novel spatiotemporal prediction method based on fuzzy Transform: Application to demographic balance data

Many issues require the application of forecasting models applied to spatiotemporal data in Geographic Information Systems (GIS) to predict the spatial distribution and evolution of a specific feature. The use of soft computing techniques in the development of these forecasting models makes it possible to detect non-linear trends but has the disadvantage of increasing the computational complexity of the model. In this paper we present a GIS-based framework in which a fast soft computing forecasting model based on the multidimensional Fuzzy Transform (for short, MF-transform) is applied to evaluate the spatial distribution and the time evolution in a study area of a measurable entity (the feature). The study area is divided into homogeneous zones (the subzones) in which the feature was measured in each time frame. The time series of the feature are analyzed to assess the trend of the feature in subsequent time frames; furthermore, those sub-areas are detected in which the feature is higher than a maximum threshold (hot spots) or lower than a minimum threshold (cold spots) in this time range. A process of fuzzifying the values of the feature is carried out in order to facilitate the interpretation of the results by expert users. The framework was tested on a study area provided by the province of Naples (Italy) to predict and analyze the spatial distribution and temporal trend of the monthly rate of births compared to deaths. Furthermore, the thematic map of the hot and cold spots detected in the three months following the time period of measurements was built. The results show that our method provides reliable results both in terms of forecast error and similarity between the detected hot and cold spots and those who have really formed.

Spatial–temporal pattern of urban ecological construction in the Yellow River basin and its optimization and promotion paths

IntroductionUrban ecological instruction is an important method of sustainable development that couples the needs of the population and the environment, thus facilitating high-quality development. This study aimed to transform existing large-scale considerations of ecological urban construction to provide a more grounded evaluation framework. We constructed an integrated framework that considers economic, environmental, social, cultural, and ecological factors and their contribution to urban ecological construction.MethodsWe used methods of subjective and objective empowerment, exploratory spatial data analysis, and the obstacle degree model to explore spatiotemporal variations in urban ecological construction.ResultsOur results showed that: (1) From 2006 to 2018, urban ecological construction in the Yellow River basin (YRB) exhibited a “polycentric” spatial differentiation pattern and a significant, gradually decreasing “center-periphery” spatial distribution trend. (2) High–high areas (with high agglomeration and high urban ecological construction) in the YRB are mainly distributed in Shandong Province and the adjacent regions, whereas low–low areas are mainly distributed in south–central Ningxia Province and southern Gansu Province. (3) Analysis of urban ecological construction characteristics across different city scales, functional types, spatial carriers, and basin locations shows that the urban ecological construction level is directly proportional to the scale of the city. The level of urban ecological construction is relatively higher in the Shandong Peninsula urban agglomeration, in the priority development area of the North China Plain, and in the downstream and right bank of the YRB. Spatial differences are mainly controlled by the net difference between regions from the upstream and midstream scales, as well as intra-regional differences between the left and right banks. (4) Marked differences can be observed in the obstacles to ecological construction in different types of cities.DiscussionTypical barriers in cities in the YRB include the total water resources per capita, energy consumption per unit of GDP, the proportion of research and development investment in fiscal expenditure, the number of books in public libraries per 10,000 people, and land use efficiency. In the future, urban ecological construction should be based on the development conditions of each individual city, and should be improved according to local conditions to achieve the construction high-quality ecological cities.