Spatial Statistical Analysis Method Research Articles

Climate change, cultural adaptations, and lower coastal plain occupations of Georgia and Florida from the early to middle Holocene: Extrapolating spatial trends into the offshore

Predictive modeling for high probability zones for detection of submerged prehistoric sites remains an integral part of this subdiscipline. It typically relies on a combination of physiographic parameters detectable in offshore zones and known archaeological trends, most of which lie onshore, not offshore. These models are not always temporally and spatially scaled to account for changes in cultural practices and/or baseline ecological conditions associated with climate changes, however. To account better for these potential variations, we used a Geographic Information Systems (GIS) based spatial statistical analysis method. Our study seeks evidence of variation in site correlations to environmental patterns to detect spatial and temporal variation in site locations, and for where site patterns depart from robust quantitative correlations to ecological conditions. Our results support a hypothesis that sites do tend to correlate to certain ecological parameters, but these effects vary across the study area and through time. We also found that some site groups did not correlate well to any particular set of hypothetically favorable ecological conditions, suggesting that other undetected variables played significant roles in those site locations. These may be undetected/untested ecological variables or may represent culturally-based decision making with non-linear relationships with ecological conditions.

Spatial Patterns and Driving Forces of Conflicts among the Three Land Management Red Lines in China: A Case Study of the Wuhan Urban Development Area

The delimitation of three land management red lines (LMRLs), which refers to urban growth boundaries (UGBs), ecological protection redlines (EPRs), and basic farmland protection zones (BFPZs), has been regarded as a control method for promoting sustainable urban development in China. However, in many Chinese cities, conflicts extensively exist among the three LMRLs in terms of spatial partitioning. This study clarifies the connotation of conflicts among the three LMRLs. Moreover, a red line conflict index (RLCI) is established to characterize the intensity of conflicts among the three LMRLs. The Wuhan Urban Development Area (WUDA) is used for a case study, in which the spatial patterns of the three types of conflicts among the three LMRLs (i.e., conflicts between EPRs and BFPZs, EPRs and UGBs, and UGBs and BFPZs) are analyzed through numerous spatial statistical analysis methods (including spatial autocorrelation, urban-rural gradient, and landscape pattern analyses). In addition, the driving forces of these conflicts are identified from the perspectives of natural physics, socioeconomic development, neighborhood, policy and planning using three binary logistic regression models. Results show that the conflicts between EPRs and BFPZs, EPRs and UGBs, and UGBs and BFPZs are mainly distributed on the edge of the WUDA, inside Wuhan’s third circulation line, and at the urban–rural transition zone, respectively. The patch of conflict between BFPZs and UGBs has the lowest aggregation degree, the highest fragmentation degree, and the most complex shape. Logistic regression results show that the combination and relative importance of driving factors vary in the three types of conflicts among the three LMRLs. In the conflict between EPRs and BFPZs, the distance to city centers is the most important influencing factor, followed by the proportion of ecological land and elevation. In the conflict between UGBs and EPRs, the proportion of construction land, the distance to city centers, and whether the land unit is within the scope of a restricted development zone are the three most important factors. The proportion of construction land, the distances to the Yangtze and Han Rivers, and the proportion of cultivated land significantly influence the conflict between UGBs and BFPZs. This study aids in our understanding of the causes and mechanisms of conflicts among the three LMRLs, and provides important information for the “integration of multi-planning” and land management in Wuhan and similar cities.

Research on social vulnerability evaluation of urban fringe based on street scale—Taking Chang’an district of Xi’an as an example

Vulnerability theory is an important tool for analyzing the degree, mechanism and process of human-land interaction, and provides a new perspective for sustainability assessment research.The interference factor of this study is rapid urbanization, and the entry point is the street space scale.Taking the northwestern part of Chang’an District of Xi’an as an example, the social vulnerability assessment index suitable for the study area is selected, and the social vulnerability theoretical framework and the index evaluation method are combined. The RS/GIS spatial statistical analysis method analyzes the social vulnerability assessment and its influencing factors of the street units in the study area. The research results show that: (1) The spatial distribution of social vulnerability is unbalanced and the contradiction between human and land is prominent.The spatial unit is highly correlated with the system in which it is located.(2) Changes in land use patterns and landscape fragmentation are the direct causes of the vulnerability of social systems in urban fringe areas, while the social system transition and urbanization in urban fringe areas are dislocated to aggravate the negative impact of urbanization.

ESTIMATING HOUSING VACANCY RATE IN QINGDAO CITY WITH NPP-VIIRS NIGHTTIME LIGHT AND GEOGRAPHICAL NATIONAL CONDITIONS MONITORING DATA

Abstract. Accompanying China's rapid urbanization in recent decades, especially in the new millennium, the housing problem has become one of the most important issues. The estimation and analysis of housing vacancy rate (HVR) can assist decision-making in solving this puzzle. It is particularly significant to government departments. This paper proposed a practical model for estimating the HVR in Qingdao city using NPP-VIIRS nighttime light composed data, Geographic National Conditions Monitoring data (GNCMD) and resident population distribution data. The main steps are: Firstly, pre-process the data, and finally forming a series of data sets with 500*500 grid as the basic unit; Secondly, select 400 grids of different types within the city as sample grids for SVM training, and establish a reasonable HVR model; Thirdly, using the model to estimate HVR in Qingdao and employing spatial statistical analysis methods to reveal the spatial differentiation pattern of HVR in this city; Finally test the accuracy of the model with two different methods. The results conclude that HVR in the southeastern coastal area of Qingdao city is relatively low and the low-low clusters distributed in patches. Simultaneously, in other regions it shows the tendency of the low value accumulation in the downtown area and the increasing trend towards the outer suburbs. Meanwhile the suburban and scenery regions by the side of the sea and mountains are likely to be the most vacant part of the city.

A System Analysis on Steppe Sustainability and Its Driving Forces—A Case Study in China

Steppe is an indispensable component for terrestrial ecosystems and it is of great significance to systematically analyze steppe sustainability and its driving forces. In this study, we propose a steppe dynamics ranking method based on Pauta criterion and a steppe sustainability assessment method with an effect matrix. The natural driving forces on steppe sustainability were systematically analyzed using the copula model, and the anthropogenic driving factors, including land use, were analyzed by using spatial overlay and statistical analysis methods. The results showed the following: (1) in general, steppe sustainability showed a trend of improvement from 2001 to 2010 in China. However, there were still some degraded areas scattered within the study area; (2) the consistent effect of steppe dynamics on steppe sustainability was significant on the whole, although there was a diverse effect on it; (3) among the natural factors, precipitation was the strongest positive driving force, followed by temperature average, while sunshine duration had strong negative driving force. The impact caused by land use factors was controlled during that decade, and the steppe land that evolved from urban and built-up land, cropland, and forest was vulnerable and resulted in steppe sustainability degradation.

Research on the optimization of air quality monitoring station layout based on spatial grid statistical analysis method

ABSTRACTIn recent years, with the significant increase in urban development, it has become necessary to optimize the current air monitoring stations to reflect the quality of air in the environment. Highlighting the spatial representation of some air monitoring stations using Beijing’s regional air monitoring station data from 2012 to 2014, the monthly mean particulate matter concentration (PM10) in the region was calculated and through the IDW interpolation method and spatial grid statistical method using GIS, the spatial distribution of PM10 concentration in the whole region was deduced. The spatial distribution variation of districts in Beijing using the gridding model was performed, and through the 3-year spatial analysis, PM10 concentration data including the variation and spatial overlay (1.5 km × 1.5 km cell resolution grid), the spatial distribution result obtained showed that the total PM10 concentration frequency variation exceeded the standard. It is very important to optimize the layout of the existing air monitoring stations by combining the concentration distribution of air pollutants with the spatial region using GIS.

Response of Inflow Water Quality to Land Use Pattern in Northern Watershed of Lake Erhai

The inherent relationship between land use pattern and inflow water quality is essential for nonpoint source pollution study. Response of inflow river quality to land use pattern in Northern part of Lake Erhai Watershed was analyzed in aspects of land use composition and configuration using spatial analysis and statistical analysis methods. The results indicated that as land use composition indexes, average slope and vegetation area percentage had significant relationship with TN and TP of inflow rivers. As land use configuration indexes, patch density, patch density of agriculture land and landscape shape index of water had significant relationship with TP and NH4+-N of inflow rivers. Response of inflow river quality to land use pattern was better at class level than at landscape level. Water quality response indicators were TP in rainy season and NH4+-N in dry season, of which regression adjustment coefficient R2 was 0.761 and 0.978, respectively. Response of inflow river quality to land use pattern was better in dry season than in rainy season, and the water quality response indicators were TN, TP and NH4+-N. Improving vegetation coverage and agriculture land intensive degree and avoiding human disturb to natural water area especially in dry season were suggested in nonpoint source pollution control of northern watershed of Lake Erhai Watershed. Later research on relationship between land use configuration and inflow river quality should better be at class level.

Using social media for disaster emergency management

Social media have become a universal phenomenon in our society (Wang et al., 2012). As a new data source, social media have been widely used in knowledge discovery in fields related to health (Jackson et al., 2014), human behaviour (Lee, 2014), social influence (Hong, 2013), and market analysis (Hanna et al., 2011). <br><br> In this paper, we report a case study of the 2012 Beijing Rainstorm to investigate how emergency information was timely distributed using social media during emergency events. We present a classification and location model for social media text streams during emergency events. This model classifies social media text streams based on their topical contents. Integrated with a trend analysis, we show how Sina-Weibo fluctuated during emergency events. Using a spatial statistical analysis method, we found that the distribution patterns of Sina-Weibo were related to the emergency events but varied among different topics. This study helps us to better understand emergency events so that decision-makers can act on emergencies in a timely manner. In addition, this paper presents the tools, methods, and models developed in this study that can be used to work with text streams from social media in the context of disaster management.

Using social media for disaster emergency management

Abstract. Social media have become a universal phenomenon in our society (Wang et al., 2012). As a new data source, social media have been widely used in knowledge discovery in fields related to health (Jackson et al., 2014), human behaviour (Lee, 2014), social influence (Hong, 2013), and market analysis (Hanna et al., 2011). In this paper, we report a case study of the 2012 Beijing Rainstorm to investigate how emergency information was timely distributed using social media during emergency events. We present a classification and location model for social media text streams during emergency events. This model classifies social media text streams based on their topical contents. Integrated with a trend analysis, we show how Sina-Weibo fluctuated during emergency events. Using a spatial statistical analysis method, we found that the distribution patterns of Sina-Weibo were related to the emergency events but varied among different topics. This study helps us to better understand emergency events so that decision-makers can act on emergencies in a timely manner. In addition, this paper presents the tools, methods, and models developed in this study that can be used to work with text streams from social media in the context of disaster management.

Using Social Media for Emergency Response and Urban Sustainability: A Case Study of the 2012 Beijing Rainstorm

With the proliferation of social media, information generated and disseminated from these outlets has become an important part of our everyday lives. For example, this type of information has great potential for effectively distributing political messages, hazard alerts, or messages of other social functions. In this work, we report a case study of the 2012 Beijing Rainstorm to investigate how emergency information was timely distributed using social media during emergency events. We present a classification and location model for social media text streams during emergency events. This model classifies social media text streams based on their topical contents. Integrated with a trend analysis, we show how Sina-Weibo fluctuated during emergency events. Using a spatial statistical analysis method, we found that the distribution patterns of Sina-Weibo were related to the emergency events but varied among different topics. This study helps us to better understand emergency events so that decision-makers can act on emergencies in a timely manner. In addition, this paper presents the tools, methods, and models developed in this study that can be used to work with text streams from social media in the context of disaster management and urban sustainability.

Fine-scale genetic structure in Tibouchina papyrus (Pohl) Toledo (Melastomataceae), an endemic and habitat-restricted species from Central Brazil

Spatial genetic structure (SGS) is the non-random distribution of genotypes in space, which is usually correlated with life history traits and is driven by ecological and demographic processes. This study aimed to use spatial statistical analysis methods to assess genetic diversity and spatial genetic structure in three known disjunct localities where Tibouchina papyrus occurs, varying in aggregation and density of individuals and in landscape characteristics. This small tree species is endemic to the “Cerrado” (savannas) region of Central Brazil and is also restricted to elevation rock fields (“campo rupestre”). Therefore, it can be considered a model species to help guide studies on Cerrado endemic plants that are isolated with geographic distributions restricted to this highland habitat. The analyses were based on the polymorphisms at ten microsatellite loci. Our working hypothesis was that wind-dispersed species, such as T. papyrus, present no or low SGS because of the long distance seed gene flow. The spatial genetic structure was indeed weak for two of the three populations. The intensity and shape of the SGS are related to density and aggregation (defined by Ripley’s K statistic of spatial aggregation) of individuals in the three localities. Low SGS occurs in populations with aggregation patterns, corroborating the overall hypothesis, although in this species, this pattern depends on the landscape characteristics of each local population.

Assessing the impact of dairy waste lagoons on groundwater quality using a spatial analysis of vadose zone and groundwater information in a coastal phreatic aquifer

Dairy waste lagoons are considered to be point sources of groundwater contamination by chloride (Cl−), different nitrogen-species and pathogens/microorganisms. The objective of this work is to introduce a methodology to assess the past and future impacts of such lagoons on regional groundwater quality. The method is based on a spatial statistical analysis of Cl− and total nitrogen (TN) concentration distributions in the saturated and the vadose (unsaturated) zones. The method provides quantitative data on the relation between the locations of dairy lagoons and the spatial variability in Cl− and TN concentrations in groundwater. The method was applied to the Beer-Tuvia region, Israel, where intensive dairy farming has been practiced for over 50 years above the local phreatic aquifer. Mass balance calculations accounted for the various groundwater recharge and abstraction sources and sinks in the entire region. The mass balances showed that despite the small surface area covered by the dairy lagoons in this region (0.8%), leachates from lagoons have contributed 6.0% and 12.6% of the total mass of Cl− and TN (mainly as NO3−-N) added to the aquifer. The chemical composition of the aquifer and vadose zone water suggested that irrigated agricultural activity in the region is the main contributor of Cl− and TN to the groundwater. A low spatial correlation between the Cl− and NO3−-N concentrations in the groundwater and the on-land location of the dairy farms strengthened this assumption, despite the dairy waste lagoon being a point source for groundwater contamination by Cl− and NO3−-N. Mass balance calculations, for the vadose zone of the entire region, indicated that drying of the lagoons would decrease the regional groundwater salinization process (11% of the total Cl− load is stored under lagoons). A more considerable reduction in the groundwater contamination by NO3−-N is expected (25% of the NO3−-N load is stored under lagoons). Results demonstrate that analyzing vadose zone and groundwater data by spatial statistical analysis methods can significantly contribute to the understanding of the relations between groundwater contaminating sources, and to assessing appropriate remediation steps.

Spatial investigation of the temporal urban form to assess impact on transit services and public transportation access

The rapid urban growth in developing city increases the requirement of the efficient and sustainable public transportation system. The urban growth affects the urban form, which indicates the change in human and urban development activity. Urban form affects directly and indirectly access to the public transportation system as an assessment of potential riders and proximity to stops increase transit services users. Therefore, access is one of the important aspects for the assessment of transit service efficiency. Public transportation access can be represented by a coverage area and useful to estimate potential riders of public transportation. In this study, a Geographical Information System (GIS)-based spatial statistical analysis method is used to examine the spatial relationship of different urban form indicators with population or riders of transit service in a coverage area and to ascertain how urban form influences public transportation trips in this coverage area. The coverage area is delineated using a GIS-based road/street network distance approach. The spatial analysis results suggested that urban forms have certain impact on trips in coverage area at both ward level and zone level. The statistical analysis implies that significant and positive values of spatial lag coefficient indicate a positive spatial interaction between wards and variable like total coverage area; worker density have shown positive and significant effects on trips of public transportation.

Application of integration of spatial statistical analysis with GIS to regional economic analysis

This paper summarizes a few spatial statistical analysis methods for to measuring spatial autocorrelation and spatial association, discusses the criteria for the identification of spatial association by the use of global Moran Coefficient, Local Moran and Local Geary. Furthermore, a user-friendly statistical module, combining spatial statistical analysis methods with GIS visual techniques, is developed in Arcview using Avenue. An example is also given to show the usefulness of this module in identifying, and quantifying the underlying spatial association patterns between economic units.

Twenty Years Before and Hence; Ecological Risk Assessment at Multiple Scales with Multiple Stressors and Multiple Endpoints

In the 20 years since risk assessment was codified it has been applied to the management of ecological systems, first tentatively with one chemical and one receptor, to its current application at large spatial and temporal scales. The original risk assessment paradigm in the National Research Council's report Risk Assessment in the Federal Government: Managing the Process, known as the “Red Book,” was modified by the risk assessment group at Oak Ridge National Laboratory so that it could be applied to ecological systems. Even in the early 1990s, it was apparent that to be ultimately successful as a management tool, risk assessment had to be applied to populations, communities, and eventually to the ecological landscape at large scales. The risk analysis of multiple stressors, not just multiple chemicals but multiple types of agents, was also seen as a major challenge. During the late part of the 1990s and early 2000s, attempts were made to conduct risk assessments at the watershed and other comparable landscape levels. Studies on the fjord of Port Valdez, Alaska; the Clinch River in Tennessee, the Big Darby in Ohio, and Codorus Creek in Pennsylvania have attempted such risk assessments. Currently it appears possible to conduct landscape scale risk assessments, although the development of appropriate spatial statistical and uncertainty analysis methods is necessary. The future ecological risk assessment is broadening to include not only chemicals but also a wide variety of environmental stressors. These stressors include urbanization, changes in land use, fishing, and climate change. The structure of ecological risk assessment also provides a common framework allowing the multiple stakeholders, regulatory groups, and scientists to come to terms with the inherent difficulties of managing complex systems. Risk assessment has the potential of becoming the generalized quantitative tool of environmental management and decision-making at multiple scales.

A new approach for associating earthquakes with geological structures: Application to epicenters in southern Illinois and southeastern Missouri

A spatial statistical analysis method has been applied successfully on diffuse seismicity of southern Illinois and southeastern Missouri. The study area is a region of diffuse deformation and seismicity close to the New Madrid Seismic Zone. The New Madrid Earthquake Catalog is examined through the Blade Method applied on collapsed epicenters. This is a new approach since the Blade Method is applied on improved locations through the Best Estimate Method. The Blade Method performs tests on binomial distributions for the detection of significant seismic alignments within a sparse epicenter distribution. From the epicenters of the New Madrid Earthquake Catalog, using the Blade Method on collapsed epicenters, it is statistically valid to state that seismicity is associated with the New Madrid Seismic Zone and the Black, Ellington, Salem and Ste Genevieve faults.

Texture analysis of CT images

The present study has shown some promise in the use of texture for the extraction of diagnostic information from CT images. A number of features are obtained from abdominal CT scans of the liver using the spatial domain statistical texture analysis methods: SGLDM, GLRLM, and GLDM. This study investigated whether (a) the texture could be used to discriminate among the various tissue types that are inaccessible to human perception and, (b) if so, then what are the most useful feature parameters for such an application? The efficacies of the different methods were evaluated from the consistency of the computed values within a class and from their differences with other classes. The study has demonstrated the use of texture for tissue characterization of CT images. In particular, we have been successful in identifying the onset of disease in liver tissue, which can not be recognized even by trained human observers. Three useful features, namely entropy (H), local homogeneity (L) and grey level distribution (GLD), have been found effective for pattern recognition. The performance of these features has been compared on the basis of statistical significance. The results show that, except for L, (Direction 0/spl deg/) all feature parameters perform equally well and detect early malignancy with a confidence level of above 99%-a finding that will not only help in automation, but more importantly, in early detection of malignancy in the liver. >