Spatial Analysis Techniques Research Articles

Impact of Local Government Competition and Land Finance on Haze Pollution: Empirical Evidence from China

ABSTRACT Taking 269 prefecture-level cities in China from 2004 to 2017 as the sample dataset, this research employs spatial analysis techniques to investigate the roles of local government competition and land finance on haze pollution. The paper concludes that a significant spatial spillover and time lag are associated with haze pollution. Local government competition and land finance positively relate to haze pollution in the local area, but also produce the same effect on neighboring areas. Local government competition positively moderates the contribution of land finance to haze pollution both locally and in neighboring areas. Moreover, the role of local government competition on haze pollution is significantly negative in the east region, while significantly positive in the central-west region. The impact of land finance on haze pollution in the east region is negative but insignificant, while significantly positive in the central-west region. Local government competition positively and negatively moderates the role of land finance in the east region on haze pollution, while in the central-west region the role is significantly positive. This study provides new research ideas and empirical reference evidence for alleviating haze pollution, which is valuable for accelerating the improvement of China’s environmental quality.

Reviewing the willingness of the community to implement absorption wells and biopore in disaster mitigation management of Semarang City

Semarang city is growing larger, with a population of more than 1.5 million. As one of Indonesia’s important cities, Semarang faces water management and disaster problems. The city faces various problems such as groundwater scarcity, land subsidence, flood, and drought. In order to maintain the ecological function of Semarang, water management by applying rainwater management through rainwater harvesting and by making absorption and biopore wells have become necessary. Community as a subject needs to be involved in this effort, but this effort is often less successful in Indonesia. This study aims to evaluate the willingness and constraints of the community to apply absorption wells and biopores to maintain the ecological urban areas’ functions. This study utilizes remote sensing data to identify community groups and questionnaires to assess community willingness. The primary methods are spatial analysis and non-parametric statistical techniques based on questionnaires. Social variables involve aspects of community attitudes, gender, education, and income. Landscape variables involve aspects of altitude and type of settlement. At the same time, this study’s results show that the community’s willingness is very diverse in every social group and different landscape.

SpatialEpi'2022 Workshop Report: The 3rd ACM SIGSPATIAL International Workshop on Spatial Computing for Epidemiology

Since the onset of the COVID-19 pandemic, researchers in the SIGSPATIAL community have utilized computational solutions to better explain, predict, and respond to infectious disease outbreaks. Using spatial computing for pandemic preparedness has also been highlighted as a major application of mobility data science [16]. At the beginning of the COVID-19 pandemic, the SIGSPATIAL community rapidly published ideas to improve our understanding of the spread of the virus in two SIGSPATIAL Special Newsletter Issues in March and July 2020 [28, 29]. These efforts led to the 1st and 2nd ACM SIGSPATIAL International Workshop on Spatial Computing for Epidemiology [5, 4] (formerly called Workshop on Modeling and Understanding the Spread of COVID-19 in 2020) which has provided authors of these newsletter articles a forum to present and discuss their solutions. Including both work published at the SIGSPATIAL Special Newsletter and regular peer-reviewed submissions, this workshop included topics such as the collection of large spatiotemporal datasets [20], leveraging data mining and spatial analysis techniques to analyze and visualize such data [2, 12, 25, 21, 11, 9, 8, 3], developing predictive spatial models and simulations [6, 1, 19, 13, 24, 10, 23, 14], and employing novel technologies towards contact tracing and surveillance [17, 26].

Identifying the Spatiotemporal Differences and Driving Forces of Residents’ Consumption at the Provincial Level in the Context of the Digital Economy

The digital economy has become a new form of the economy. Based on data from the China Year Book from 2012 to 2020, this paper characterizes China’s spatial differences in regional consumption expenditure in the context of the digital economy. We utilize the GIS spatial analysis technique, ESDA, Geodetector, and other spatial econometric tools to reveal the spatiotemporal evolution patterns and driving mechanism of residents’ consumption development in the context of the digital economy for 31 provinces in China and propose differentiated policy suggestions for residents’ consumption development against the background of the digital economy in China, creating a reference for decision making on residents’ consumption in China. The findings show that, first, provincial residents’ consumption expenditures appear to decrease on a gradient from eastern to central and western China, showing extreme polarization and spatial aggregation. Second, the power of the seven driving factors of residents’ consumption varies widely across time; the driving factors representing the digital economy can reduce the regional differences in residents’ consumption. On the other hand, non-digital economic factors increase the spatial difference. Third, two digital economic factors play the most important roles in the interaction effect in most years.

Exploring spatial variations in level and predictors of unskilled birth attendant delivery in Bangladesh using spatial analysis techniques: Findings from nationally representative survey data.

BackgroundBangladesh has failed to meet the United Nations goal for reducing maternal mortality in the last decade. The high prevalence of unskilled birth attendant (UBA) delivery (47%) has resulted in negative consequences for the health of mothers and newborn babies in the country. Spatial variations in UBA delivery and its predictors are yet to be explored in Bangladesh, which could be very helpful in formulating cost-effective policies for reducing that. This study examines the spatial variations in UBA delivery and its predictors in Bangladesh.MethodsThis study analyzed the characteristics of 672 clusters extracted from the 2017/18 Bangladesh Demographic and Health Survey, and healthcare facility data from the 2017 Bangladesh Health Facility Survey. These data were analyzed using descriptive and spatial analyses (hot spot analysis, Ordinary Least Squares Regression, and Geographically Weighted Regression) techniques.ResultsStatistically significant hot spots of UBA delivery were concentrated in parts of the Mymensingh, Sylhet, Barishal, and Rangpur regions, while Khulna was the safest region. Predictive strengths of the statistically significant predictors of spatial variation in UBA delivery were observed to vary considerably across the regions. Poorest household wealth status and less than four antenatal care contacts emerged as strong predictors of UBA delivery in all the aforementioned hot spot-stricken regions, except Barisal. Additionally, primiparity and all secondary education or higher were strong predictors of lower UBA delivery rates in Mymensingh and Sylhet, while poorer household wealth status was also a strong predictor of UBA delivery in Sylhet. Multiparity was an additional strong predictor of UBA delivery in Rangpur. In Barisal, only poorer household wealth status exerted a strong positive influence on UBA delivery.ConclusionsThe remarkable spatial variations in UBA delivery and its predictors’ strengths indicate that geographically-targeted interventions could be a cost-effective method for reducing the UBA delivery prevalence in Bangladesh, thereby improve maternal and child health.

Exploratory Analysis of Regional Disparities in Human Development in Cameroon

The objective of this paper is to analyze the link between geographic location and the level of human development in Cameroon. To achieve that objective, we use Exploratory Spatial Data Analysis (ESDA) techniques on regional human development indices (HDI) in Cameroon from 2001 to 2014. The Moran test confirms the presence of a positive and significant global spatial autocorrelation of the regional human development indices. Thus, the values of the regional human development index in Cameroon are not randomly distributed. There is thus spatial clustering of regions with similar HDI levels. The spatial dependence of the regional HDI in Cameroon suggests cooperation and synergy of action by the regions within the framework of their competences resulting from decentralization, in order to take advantage of the spatial diffusion effects of human development. The Cameroonian government could pursue geo-targeting policies in the implementation of development programs, focusing on regions where spatial externalities would have a greater impact.

Identifying groundwater resilience zones in an arid inland basin using GIS-based Dempster-Shafer theory

Study regionHotan River Basin, an arid inland river basin, Northwest China. Study focusA method for assessing the spatial distribution of groundwater resilience is constructed by combining the Dempster-Shafer theory model and spatial analysis techniques. The groundwater performance indicator CRS and resilience indicator pi are calculated to present groundwater resilience. Using the Dempster-Shafer theory model to mine the data, nine groundwater conditioning factors are selected as evidential layers of the model, and the mathematical relationships between the resilience indicators and groundwater conditioning factors are established through evidence integration; Ultimately, a groundwater resilience spatial distribution map is generated, and the performance of the map is explored based on the CRS and pi values. New hydrological insights for the regionThe constructed assessment method based on this study reliably and effectively predicts the regional groundwater resilience. Validation of the groundwater resilience prediction map with pi indicates that this indicator outperforms the CRS. The areas with high groundwater resilience are mainly concentrated in the upstream oasis irrigation area and the downstream river channel. The groundwater resilience (pi) zonation map is divided into five categories: very low (Bel of 0–0.072), low (0.072–0.171), moderate (0.171–0.458), moderate high (0.458–0.786), and high (>0.786). The results can provide a scientific basis for groundwater safety and management in the Hotan River Basin.

GEOSCIENCES, SPATIAL ANALYSIS AND COLLECTIVE HEALTH

This article aims to describe experiences from research projects entitled “Children’s calendar incompleteness and racial inequality: birth cohorts (BRISA) in northeastern and southeastern Brazil and“ Spatial analysis of the children’s calendar in São Luís ”that took place from 2016 to 2019 in the Graduate Program in Public Health (PPGSC) of the Federal University of Maranhão. This report consists of the perceptions of the scholarship holders involved and the techniques produced by them that aimed to apply spatial analysis techniques in GIS and geoprocessing to analyze variables that influence childhood vaccination, while maps were produced to discuss the themes covered. Therefore, these experiences are fundamental in educational institutions, especially to broaden the horizons of future specialists in geosciences and geotechnologies, as it allows to take from theory to future technical praxis concomitant with their professions.

Identification and evaluation of the risk induced by landslides based on G.I.S. models of spatial analysis. Case study: Bicazu Ardelean, Romania

Having a strong impact on human activities, landslides represent one of the most frequent hazards encountered throughout the world, but also in Romania. As a result, various exhaustive scientific approaches try to identify the areas affected by this phenomenon or at risk, among the proposed methods being those offered by G.I.S. techniques of spatial analysis in tandem with statistical methods. In the present study, G.I.S. methods of spatial analysis were used, with a focus on methodologies capable of determining the probability of occurrence of landslides, possible and viable within any territory. The analysis was carried out in the area of the commune of Bicazu Ardelean, Neamț County, Romania, where multiple areas with a medium-high and high probability of vulnerability were identified, by means of a deterministic “white-box” type model, followed by an evaluation from the point of view of the risk induced on the territorial infrastructures. Both the model and the evaluation generated suitable results, validated in G.I.S. and in the field. The obtained results attested the viability of the working method, as well as the potential of its application in any other areas with similar morphometric characteristics.

Tourism circular economy: Identification and measurement of tourism industry ecologization

Environmental problems caused by excessively pursuing tourism economic activities have become increasingly prominent. The circular economy theory is one of the essential tools to solving tourism environmental problems. However, the sustainable process of the tourism industry, which is a linear process, usually leads to a particular gap between the sustainability assessment of tourism industry and the reality. This study points out this research gap, refines the concept of tourism industry ecologization through the circular economy theory, and proposes an assessment index system of tourism industry ecologization based on the Driver-Pressure-State- Impact-Response model (DPSIR). The level of tourism industry ecologization in China from 2011 to 2019 is assessed. The development characteristics of tourism industry ecologization are analyzed by the Thiel index and spatial correlation analysis techniques. The research results show that the proposed system can better evaluate the dynamic process of tourism industry ecologization and explain the evolution of tourism industry ecologization level to a certain extent. Finally, put forward relevant policy suggestions to improve the development of the tourism industry ecologization from micro, medium, and macro perspectives.

Applying spatio-chemical analysis to grassland ecosystems for the illustration of chemoscapes and creation of healthscapes

Grasslands are heterogeneous landscapes composed of a diversity of herbaceous and shrub vegetation that varies not only taxonomically, but biochemically in terms of primary and secondary compounds. Plant Secondary Compounds (PSC) have specific nutritional, medicinal, and prophylactic properties, to which benefits depend upon dosage, type, arrangements, and concentration that changes between and within plants across time and space. The knowledge of the plant content of PSC and their distribution in grazing environments would therefore contribute to the design and creation of healthier foodscapes for ruminants; in other words, healthscapes. Geographic information systems (GIS) have been used extensively for landscape visualization and assessment, through several spatial analysis techniques applied for the creation of virtual maps to add valuable information to a particular environment. Given the knowledge of plants and their composition, GIS emerges as a readily available and low-cost tool to assess and evaluate the distribution of plants with beneficial PSC in large and heterogeneous foodscapes. We present and propose for the very first time, the application and use of GIS to determine the spatial distribution of PSC rich plants with nutraceutical properties to illustrate, visualize, and generate healthscapes for grazing ruminants. We present healthscape maps created using botanical composition analyses and advanced image classification methods to illustrate the distribution of plants regarding their PSC and nutraceutical properties. Such maps add an extra dimension and perspective to plant chemical composition, enabling graziers to visualize in space and time centers of nutrition and prophylactics or medicines, contributing to advanced grazing management decisions toward more productive, sustainable, and healthy grazing systems. The valuable information behind the mapped PSC advances the understanding of the nutritional ecology of grazing environments and foodscapes, introducing a new dimension to the holistic management of pastoral livestock production systems.

How Neighborhood Characteristics Influence Neighborhood Crimes: A Bayesian Hierarchical Spatial Analysis.

Urban crimes are a severe threat to livable and sustainable urban environments. Many studies have investigated the patterns, causes, and strategies for curbing the occurrence of urban crimes. It is found that neighborhood socioeconomic status, physical environment, and ethnic composition all might play a role in the occurrence of urban crimes. Inspired by the recent interest in exploring urban crime patterns with spatial data analysis techniques and the development of Bayesian hierarchical analytical approaches, we attempt to explore the inherently intricate relationships between urban assaultive violent crimes and the neighborhood socioeconomic status, physical environment, and ethnic composition in Paterson, NJ, using census data of the American Community Survey, alcohol and tobacco sales outlet data, and abandoned property listing data from 2013. Analyses are set at the census block group level. Urban crime data are obtained from the Paterson Police Department. Instead of examining relationships at a global level with both non-spatial and spatial analyses, we examine in depth the potential locally varying relationships at the local level through a Bayesian hierarchical spatially varying coefficient model. At both the global and local analysis levels, it is found that median household income is decisively negatively related to urban crime occurrence. Percentage of African Americans and Hispanics, number of tobacco sales outlets, and number of abandoned properties are all positively related with urban crimes. At the local level of analysis, however, the different factors have varying influence on crime occurrence throughout the city of Paterson, with median household income having the broadest influence across the city. The practice of applying a Bayesian hierarchical spatial analysis framework to understand urban crime occurrence and urban neighborhood characteristics enables urban planners, stakeholders, and public safety officials to engage in more active and targeted crime-reduction strategies.

Spatial analysis techniques for tsunami vulnerability and inundation mapping of Andaman region using remote sensing, GIS, AHP, and Fuzzy logic methods

Spatial analysis techniques for tsunami vulnerability and inundation mapping of Andaman region using remote sensing, GIS, AHP, and Fuzzy logic methods

PENGARUH PERUBAHAN TATA GUNA LAHAN TERHADAP DISPARITAS REGIONAL ANTARKECAMATAN DI KOTA TANGERANG SELATAN

Regional disparity is a phenomenon of economic differences between regions (Bakri, et.al 2016). The Bappeda of Banten Province stated that South Tangerang City experienced a relatively high regional disparity level (Noviar, 2021). Triyanto, et.al (2019) stated that land use changes influenced regional disparity. However, this influence has not been identified in South Tangerang City. This study aims to identify the influence of land use change on regional disparity between sub-districts in South Tangerang City in 2015 and 2019. The data collection technique uses secondary data from related agencies with regional disparity, spatial and multiple linear regression statistical analysis techniques. The results of the analysis show that regional disparity consist of low, medium and high levels. Then, land use changes in 2019 are built-up land use change with an area of ​​493.29 ha (84.75%) and non-built-up land use change with an area of ​​88.73 ha (15.25%) out of a total of 582, 02 ha (100%). Furthermore, the influence of built-up land use change (X1) and non-built-up land use change (X2) simultaneously or partially has a significant influence on regional disparity (Y) which is 86%, while the remaining 14% is influenced by other independent not examined variables.

Spatio-temporal evolution of landscape patterns in an oasis city.

Studying the spatial-temporal evolution of oasis urban landscape patterns can provide a unique reference for future sustainable development. This study aimed to characterize the spatio-temporal evolution of landscape patterns in the past 20years. The remote sensing and spatial analysis techniques included land transfer matrix, orientation evolution combined with landscape index, natural driving factor, and mass center migration model. The results showed that (1) two decades of urbanization brought prominent LULC changes. An increase of 464.8 km2 in the building area denoted the dominant change. (2) Changes in building, bare land, and green space occurred mainly in the northwest orientation. The patch Aggregation Index (AI) increased continually during building expansion. Meanwhile, the Landscape Division Index (DIVISION) experienced a progressive and complementary decline. (3) Increase in building land was associated with topography (DEM) and vegetation cover (NDVI). A lower elevation induced a larger building increment. Around NDVI average value for bare land (0.137) and farmland (0.477), building land had the largest expansion, verifying its principal land sources. (4) The center of gravity of building land overall migrated towards the north, and green space and bare land towards the south due to building encroachment. The findings could inform future sustainable urban development.

Spatial-temporal evolution characteristics and drivers of carbon emission intensity of resource-based cities in china

As the key object of carbon emission reduction, resource-based cities’ carbon emission problems are related to the achievement of China’s goals to peak carbon emission and achieve carbon neutrality. In this paper, 115 resource-based cities with abundant natural resources in China were studied, and spatial analysis techniques such as LISA (Local Indicators of Spatial Association) time path and spatial-temporal transition were used to explore their spatial divergence pattern and spatio-temporal evolution characteristics of carbon emission intensity from 2000 to 2019, while geodetector model was used further to reveal their drivers and impacts on the environment. It is found that 1) the carbon emission intensity of resource-based cities shows a significant decreasing trend, with significant differences in carbon emission intensity and its decreasing rate in different development stages and resource-type cities. The overall trend of growing cities, declining cities, mature cities and regenerating cities decreases in order. The carbon emission intensity of cities in the energy, forest industry, general, metal and non-metal categories gradually decrease. The spatial pattern of carbon emission intensity has strong stability, with an overall spatial distribution of high in the north and low in the south. 2) The spatial structure of carbon emission intensity in resource-based cities has strong stability, dependence and integration, with the stability gradually increasing from north to south and the path dependence and locking characteristics of the carbon emission intensity pattern slightly weakened. 3) The spatial divergence of carbon emission intensity in resource-based cities is the result of the action of multiple factors, among which the level of financial investment, urban economic density, urban population density, urban investment intensity and energy use efficiency are the dominant factors. 4) The leading drivers of carbon emission intensity are different in cities at different development stages and with various resources, and grasping the characteristics of carbon emission intensity changes and drivers of various resource-based cities can better provide targeted countermeasures for resource-based cities to achieve carbon emission reduction targets and sustainable development.

Tingkat Pelayanan Ruang Terbuka Hijau Publik Berdasarkan Kebutuhan Masyarakat di Perumnas Pucang Gading Demak

Green open space in residential areas is one of the facilities that must be provided as a space for community activities and has an ecological function for the environment. Perumnas Pucang Gading is a settlement that has existed since the 1990s and there is green open space in each hamlet as a space for residents' activities. However, in its utilization, green open space is not widely used and instead is used for personal interests, one of which is for parking lots. This study aims to evaluate the level of green open space services at Perumnas Pucang Gading based on the needs of the community. The research approach was carried out in a quantitative descriptive manner using spatial analysis techniques, scoring, and frequency distribution. The results of the study show that in terms of quantity, the availability of green space services has been 75% fulfilled, namely based on the distribution, range, and area needed. Then in terms of quality, green open space obtained a sufficient/average score from the functional, technical, and behavioral aspects with a score of 3.1 out of 5.0. However, it turns out that the availability of green open space is not in accordance with the criteria needed by the community, namely a sports field with social space and is fulfilled by vegetation elements which are not in accordance with the current existing conditions.

How applicable is geospatial analysis in maternal and neonatal health in sub-Saharan Africa? A systematic review

BackgroundSub-Saharan Africa (SSA) has the world's highest maternal and neonatal morbidity and mortality and has shown the slowest progress in reducing them. In addition, there is substantial inequality in terms of maternal and neonatal morbidity and mortality in the region. Geospatial studies can help prioritize scarce resources by pinpointing priority areas for implementation. This systematic review was conducted to explore the application of geospatial analysis to maternal and neonatal morbidity and mortality in SSA.MethodsA systematic search of PubMed, SCOPUS, EMBASE, and Web of Science databases was performed. All observational and qualitative studies that reported on maternal or neonatal health outcomes were included if they used a spatial analysis technique and were conducted in a SSA country. After removing duplicates, two reviewers independently reviewed each study's abstract and full text for inclusion. Furthermore, the quality of the studies was assessed using the Joanna Briggs Institute (JBI) critical appraisal checklists. Finally, due to the heterogeneity of studies, narrative synthesis was used to summarize the main findings, and Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline was strictly followed to report the review results. A total of 56 studies were included in the review.ResultsWe found that geospatial analysis was used to identify inequalities in maternal and neonatal morbidity, mortality, and health care utilization and to identify gaps in the availability and geographic accessibility of maternal health facilities. In addition, we identified a few studies that used geospatial analysis for modelling intervention areas. We also detected challenges and shortcomings, such as unrealistic assumptions used by geospatial models and a shortage of reliable, up-to-date, small-scale georeferenced data.ConclusionsThe use of geospatial analysis for maternal and neonatal health in SSA is still limited, and more detailed spatial data are required to exploit the potential of geospatial technologies fully.

Land-Use Transformation and Landscape Ecological Risk Assessment in the Three Gorges Reservoir Region Based on the “Production–Living–Ecological Space” Perspective

Rapid urbanization and land-use change cause risk in regional ecological security. It is very significance to explore the evolutionary trend of land-use change and landscape ecological risk (LER) in an ecologically fragile area, especially in terms of maintaining sustainable development in a regional ecological environment. We selected the Three Gorges Reservoir Region (TGRR) as the study area based on land-use and land-cover data for 2000, 2010, and 2020. The land-use classification system used here was constructed using the perspective of the production–living–ecological space (PLES). The GIS spatial-analysis technique and FRAGSTATS 4 software were used. We used the method of the land-use transfer matrix, the landscape ecological risk assessment model, the ecological contribution rate of land-use transfer, and spatial autocorrelation analysis. We performed quantitative analysis of the spatio-temporal pattern of PLES and its LER in the TGRR over the past 20 years. The results show that: (1) The area of human living space (HLS) has expanded significantly—by 1469.37 km2 (+326.66%), while the area of agricultural production space (APS) has been compressed by both the urban/rural living space (URLS) and the forestland ecological space (FES), particularly during the last 10 years; (2) The overall LER results were medium, but LER is increasing; (3) The LER in the northern area of the Yangtze River is higher than in the south. The Wanzhou district and the downstream areas had a lower LER; and (4) The transformation from agricultural production space to forestland ecological space and urban/rural living space has had a higher contribution rate to the LER compared to other events. These results can be used as a reference for land planning, sustainable development, and ecological civilization construction in ecologically fragile areas.

Evolutionary characteristics of ecosystem services and ecological risks at highly developed economic region: A case study on Yangtze River Delta, China.

Ecosystem services (ES) can mitigate ecological risks (ER), yet these services can also be affected by ER. Based on land use data, socioeconomic data, landscape index, and spatial analysis techniques such as spatial autocorrelation, we study the spatial and temporal characteristics of ES and ER in the Yangtze River Delta from 2000 to 2019. The conclusions are as follows: (1) During the study period, construction land has been growing rapidly, and the depth, complexity, and intensity of land use have been increasing. The reserve land resources in the Yangtze River Delta are scarce. (2) From 2000 to 2019, the ecosystem service value (ESV) has been declining, with a total loss of 107.562 billion RMB. The area of low ESV continues to grow rapidly, while the area of high ESV continues to shrink. High ecological risk potential exists in rivers, lakes, and coastal areas. (3) Although the ecological environment in economically developed areas is more fragile, the ecological risk potential can be reduced in two ways: strengthening urban clusters, thus improving cooperation and communication among them; and protecting ecosystems with high ES such as water area and forestland. When formulating regional development plans, in addition to socioeconomic benefits, managers and policy makers need to focus on natural benefits as well.