Spatial Analysis Software Research Articles

Knowing the lay of the land: changes to land use and cover and landscape pattern in village tank cascade systems of Sri Lanka

Social-ecological systems (SESs) possess a great diversity of land use and land cover (LULC) types with unique assemblages of biodiversity and ecosystem services. However, LULC changes due to landscape fragmentation are emerging as major threats to the system productivity of SESs around the world. This study examined changes to LULC extent and landscape patterns in the Village Tank Cascade Systems (VTCSs) of Sri Lanka using satellite imagery and GIS techniques between 1994 and 2021. Multispectral Landsat images (5 TM and 8 OLI/TIRS) obtained from Google Earth Engine were classified using machine learning algorithms. Overall accuracies obtained were 85.9% (1994) and 88.6% (2021). The LULC change matrix and spatial pattern metrics were used to examine LULC and landscape pattern change dynamics over the VTCS landscapes. LULC change matrix results revealed that forest, which is the dominant LULC class covering 73.7% of the total land area was reduced by 206,725 ha due to transformation into agricultural (70.43%) and scrub (24.33%) lands between 1994 and 2021. Over this time landscape pattern of the VTCS has gradually changed from forest to agricultural land-dominated landscape, with forest and agricultural land types showing a significant negative correlation (p < 0.001; R2 > 0.868), particularly in the southeastern region. Landscape patterns were analysed based on eight spatial metrics calculated at both the landscape and class levels using FRAGSTATS spatial pattern analysis software. At the landscape level, the structure became more dispersed and complex in shape. Heterogeneity was noted to have gradually increased with weakening connectivity, whereas the fragmentation process had gradually accelerated. At the class level, the dominance of forest patches decreased, fragmentation and isolation increased, and connectivity and shape complexity reduced leading to the loss of fragmented forest habitats. The number of patches within the agricultural class increased and became more aggregated and complex in shape. Landscape performance indicators show that VTCSs have experienced a gradual loss of environmental sustainability. Assessment of LULC along with fragmentation can help to monitor the spatial pattern impacts that determine ecological integrity. Thus, the study provides scientific guidance for ecological restoration in degraded VTCSs to effectively improve ecological productivity.

Epidemiologic Look at Teen Birth [ID 2683394

INTRODUCTION: To take an epidemiologic look at the most up-to-date geographical variation in the average teenage birth rates by county in the United States. METHODS: Data from the National Center for Health Statistics were used in this retrospective cohort to count the total number of live births to females aged 15–19 years by county between 2003 and 2020. Software for disease surveillance and spatial cluster analysis was used to identify clusters of high or low birth rates in counties or areas of greater than 100,000 teenage females. The data were then further analyzed by unemployment rate, no high school diploma rate, Hispanic rate, African American rate, and poverty rate per county as influence on the prediction of teenage birth rate. RESULTS: Spatial analysis identified 94 significant spatial clusters of teenage births. When adjusted for time and space, there were three significant clusters within Texas, all within 2013–2020, showing a steep increase in teenage birth rates. The top cluster with a 60% higher chance of teenage birth than the remainder of the country. Individual covariates examined showed the best predicter of teenage birth is unemployment followed by low education. CONCLUSION: Nationally, teenage births have declined over the last 30 years; however, clusters of elevated teenage birth rates remain predominantly in the southeastern United States and Texas. When adjusting for covariates of social determinants of health, some of these clusters remained, indicating other factors with influence on teenage birth rate.

Abstract LB252: iCellSight: An interactive tool for analyzing and visualizing in-situ high-plex cellular protein data

Abstract Introduction The increased use of tissue-based multiplex immunohistochemistry (mIHC) in cancer research has significantly enhanced the generation of spatial hyper-plex images, crucial for understanding complex tumor-immune microenvironments. This advancement has led to a growing demand for spatial data analysis tools that enable quick and insightful evaluation. While existing spatial analysis software like Steinbock and SPIAT offer foundational support, effectively managing the high-dimensional and voluminous cellular data to derive meaningful biological insights remains challenging. This is especially true for researchers lacking bioinformatics expertise who seek to conduct quick preliminary evaluations. To address this gap, we introduce iCellSight: a user-friendly, code-free interactive analysis and visualization tool tailored to empower researchers with rapid and intuitive interpretation of in-situ cellular data. Material and methods A formalin-fixed, paraffin-embedded colorectal carcinoma (CRC) patient tissue section was subjected to staining using COMET (Lunaphore, Switzerland), which automates sequential immunofluorescence staining and imaging of up to 40 protein markers. The stacked image file produced was analyzed with HALO (Indica Labs, USA), which generated cell-level data like cell coordinates, stain intensity values and user-defined cell types. We developed a Shiny App tool, using the Shiny R package, with key features for cell data interpretation: (1) user-input cell number subsampling; (2) dimensional reduction plots with PhenoGraph for unsupervised clustering, allowing a choice of UMAP or t-SNE, and neighbor number selection of 30, 50 or 150; (3) 2D tissue space mapping of PhenoGraph clusters; and (4) heatmap visualizations displaying cluster-wise biomarker expression (with customizable color schemes and scaling), biomarker co-expression, and cluster pair-wise distance. Results Using iCellSight, 297,000 cells were detected from the CRC sample, where 27 clusters were identified. We observed 3 distinct clusters from the t-SNE plot that consist of macrophages, granulocytes, and NK cells and monocytes respectively. From the cluster projection in 2D tissue space, the cluster of NK cells and monocytes was found to be densely populated in a particular area of the tumor nest. Conclusion We presented iCellSight, a code-free visualization and analysis tool which streamlines the semi-automated analysis of spatial hyper-plex protein data. Designed with an intuitive user interface, this app enables researchers to efficiently navigate its features without requiring any prior coding expertise. We anticipate that the visualizations and analysis provided by this tool will significantly assist researchers in their data analyses and facilitate the validation of experimental hypotheses. Citation Format: Yancun Zhu, Felicia Wee, Menaka Priyadharsani Rajapakse, Esther Gek Teo, Nicholas Ang, Solomonraj Wilson, Zheng Yi Ho, Willa Wen-You Yim, Li Yen Chong, Craig Ryan Joseph, Jeffrey Chun Lim, Zhen Wei Neo, Chwee Ming Lim, Bernett Lee, Olaf Rotzschke, Joe Yeong, Mai Chan Lau. iCellSight: An interactive tool for analyzing and visualizing in-situ high-plex cellular protein data [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr LB252.

Abstract 2912: SFRP2 and CD38 colocalize in triple negative breast cancer microenvironment

Abstract Introduction: A promising target for breast cancer is secreted frizzled-related protein 2 (SFRP2), and a humanized monoclonal antibody to SFRP2 (hSFRP2 mAb) inhibits primary triple negative breast cancer (TNBC) in vivo. CD38 is a known cause of PD-1 inhibitor resistance in some tumors, and in metastatic osteosarcoma hSFRP2 mAb overcomes PD-1 mAb resistance by reducing CD38 in tumor infiltrating lymphocytes (TILs). Could this phenomenon be replicated in TNBC? This is unknown as the expression of CD38 in TNBC has not been studied. This study will establish the presence of SFRP2 and CD38 in the TNBC microenvironment. Methods: Immunohistochemistry (IHC) was performed on an 88 core human TNBC tissue microarray (TMA) with antibodies to SFRP2 and CD38. Spatial analysis software was used to determine percent positivity. Each core was categorized using the scoring system for the estrogen receptor in breast cancer (<1% negative, 1-10% low positive, and >10% positive). Multiplex IHC was performed on 4 human triple TNBCs sections. Tissues were stained with antibodies to CD38, CD68 (macrophage), CD3 (T-cell), CD19 (B-cell), CytoKeratin (tumor), and SFRP2. Percent positivity of each marker was analyzed with a software package. For flow cytometry of tumor associated macrophages (TAMs), 1 million EO771 cells were injected into the mammary fat pad of female C57/BL6 mice. After 4 weeks tumors were extracted and a cell suspension was incubated in a mastermix with antibodies to SFRP2, CD38, PD1, CD11B and F480. Cells were fixed and conjugated to a fluorochrome secondary antibody. TAM gated cells were analyzed for the presence of SFRP2 and CD38. Results: For the TNBC TMA, 83 cores were positive and 4 cores were low positive for SFRP2, 1 not evaluable; 87 cores were positive and 1 low positive for CD38. For multiplex IHC there was a total of 1,753,544 individual cells in all 4 human TNBC tumors that were stained. 94% of cells stained positive for SFRP2, and 65% stained positive for CD38. Of the cells that were positive for SFRP2, 70% were also positive for CD38, 15% were positive for CD68, 1% were positive for CD19, 77% were positive for CytoKeratin, and 10% were positive for CD3. Of the cells that were CD38 positive, 99% were also positive for SFRP2, 15% were positive for CD68, 1% were positive for CD19, 81% were positive for CytoKeratin, and 9% were positive for CD3. Flow cytometry analysis of TAMs confirmed the presence of SFRP2, CD38 on TAMs. TAMs that were negative for PD1 and CD38 (pro-inflammatory) had a 56% reduction in SFRP2 compared to TAMs that were double positive for PD1 and CD38 (anti-inflammatory). Conclusion: SFRP2 and CD38 are prevalent in human TNBC and colocalize in the TNBC microenvironment in tumor cells, TAMs and TILs, but not B-cells. The presence and co-localization of SFRP2 and CD38 in TAMs was confirmed with flow cytometry. This confirms that SFRP2 is a therapeutic target in TNBC and provides a mechanistic rational for combination therapy with PD-1 inhibitor. Citation Format: Lillian Hsu, Patrick Nasarre, Rupak Mukherjee, Eleanor Hilliard, Martin Romeo, Elizabeth O'Quinn, Whitney Christians, Nancy Klauber DeMore. SFRP2 and CD38 colocalize in triple negative breast cancer microenvironment [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2912.

Spatial Clustering of Malnutrition and Anemia Among Reproductive Women and Its Associated Risk Factors in India: Evidence From National Family Health Survey-5.

Malnutrition and anemia are 2 severe public health concerns, predominantly in low-and middle-income nations. Malnutrition is defined as poor nutritional condition that encompass both under nutrition and over nutrition. The prevalence of overweight or obesity and anemia has increased in India from 2016 to 2021. The study aims to investigate the spatial clustering and factors responsible for underweight, overweight/obesity, and anemia among reproductive women (15-49 years) in India using the data from National Family and Health Survey-5 (2019-2021). We conducted hot-spot analysis using Moran's Index (MI) with the help spatial analysis software (i.e., GeoDa 1.18 and ArcGIS 10.8). It also demonstrates the autocorrelation. Multivariable logistic regression analysis has been performed to examine different determinants and risk associated with underweight, overweight/obesity, and anemia with various dependent variable by using Stata-14 software. Moran's Index for underweight (MI = 0.68), overweight/obesity (MI = 0.72), and anemia (MI = 0.62) indicates a high level of spatial-autocorrelation (P < .001) exists across the districts in India. As a result, a total of 156, 143, and 126 hot-spot districts are detected for underweight, overweight/obesity, and anemia, respectively. The burden of undernutrition and anemia is higher in rural areas. Risk of under nutrition and anemia are both reduced by media exposure and eating habits. Moreover, low income and low education level raises the risk of anemia and undernutrition, while obesity shows an inverse trend with income and education level. The study recommends targeting hot-spot districts for malnutrition and anemia, and policy level initiatives by addressing the responsible risk factors.

A Study on the Problem of Starting and Depositing of Ming Dynasty Fields Based on the Perspective of HGIS

The origination, transportation, and retention of field levies are the core contents of the Ming Dynasty financial research, and in the past, the academic community's attention to the origination, transportation, and retention problems only stayed in the discussion of the amount of field levies and the institutional level. With the use of digital humanities and historical geographic information systems in historical research, the spatial information implied in the Ming dynasty field levies can also be presented in the study. The book "Wanli Accounting Record" compiled by the Ministry of Revenue during the Wanli period contains the collection and storage of field levies at all levels of provinces and counties in the Ming Dynasty, and the historical documents are converted into data and then the GIS software is utilized to present them in a hierarchical manner on a nationwide scale. The results of the hierarchical presentation are further analyzed by using spatial analysis software to analyze the spatial relationship between the field levies in each state and county in the Ming Dynasty.

Spatial correlation and interaction effect intensity between territorial spatial ecological quality and new urbanization level in Nanchang metropolitan area, China

While promoting the rapid development of social economy, new urbanization has brought great pressure to the ecological environment. It is of great significance to explore the interaction mechanism between ecological environment and new urbanization for the sustainable development of metropolitan area. The metropolitan area of Nanchang in China was taken as the research area, and based on remote sensing, meteorological and social statistics data, and considering the functions, structures and effects of urban, agricultural and ecological spaces as well as the realistic demands of new urbanization construction, this research constructed “natural foundation-structure-coerce-benefit” (NSCB) and “land use-economic-population-infrastructure-public service” (LEPIP) comprehensive assessment models to quantitatively analyze the spatial and temporal heterogeneity, spatial correlation and interaction strength of ecological quality and new urbanization level in the study area from mesoscopic and microscopic perspectives by using spatial analysis software such as ENVI, ArcGIS, Fragstats, Geoda and Geodetector. The results showed that the ecological environment quality and urbanization level of the land space in the study area were improved from 2005 to 2018, and the overall gap within the region was gradually reduced. The spatial relationship between land use efficiency and ecological quality was “synergistic-trade-off-synergistic”. The economic development level and ecological quality showed a gradually enhanced synergistic relationship, and the population urbanization, infrastructure construction and ecological quality showed an “N” type synergistic relationship. The results of interaction intensity showed that the combined effects of population urbanization, public service guarantee, land use efficiency and economic development had a great impact on the spatial heterogeneity of territorial ecological quality in the study area. Finally, we suggest that the urbanization construction in the study area should strengthen the industrial agglomeration effect, improve the efficiency of land output, build a good urban ecological network, and promote the coordinated and healthy development of natural resources and urban construction. The results of this study can provide scientific basis for the precise formulation of spatial planning, ecological restoration and spatial collaborative development strategies in the study area, and provide reference experience for the coordinated development of natural environment and social economy in other metropolitan areas and urban agglomerations.

Community conservation and remote sensing of the desert-adapted lions in northwest Namibia

Community-based conservation of the desert-adapted lions takes place within the semi-arid and arid environments of northwest Namibia. This area is primarily designated as communal conservancies, a form of community-based natural resource management (CBNRM). The article describes the activities of the Lion Rangers program, a CBNRM organization, emphasizing how the use of remote sensing techniques, including the Spatial Analysis and Report Tools (SMART) software and mobile-app, GPS/satellite collars, and trail cameras, contribute to lion monitoring and limiting human–lion conflict (HLC). Remote sensing data are being integrated with historical and sociological research, with applicable lessons for lion conservation and conservation of other problem-causing species.

Quantitative 3D assessment of the lung cancer microenvironment using multi-resolution open-top light-sheet microscopy.

2616 Background: Non-small cell lung cancer (NSCLC) tissue is a valuable resource for diagnosis, treatment planning, and drug development. Current 2D histopathological techniques introduce under-sampling error (i.e., a single 5 µm section represents 0.5% of a 1 mm thick biopsy), interobserver variability, and failure to capture the biology contained within the entire tissue sample. We have developed a suite of technologies to stain, chemically clarify, image, visualize, and analyze entire, intact lung tissue samples. Herein, we present analysis methods for comprehensive 3D assessment of intact NSCLC tissue. Methods: Human NSCLC tissue, stored frozen in optimal cutting temperature (OCT) compound, was fixed in 4% paraformaldehyde, stained with nuclear (TOPRO-3) and general protein (Eosin) fluorescent dyes, and optically cleared using a modified iDISCO protocol with ethyl cinnamate as the refractive index matching solution. Twenty tissue samples measuring 1-5 mm3 in volume were imaged at 2 µm/pixel resolution with a hybrid open-top light-sheet microscope. Smaller regions of interest (ROIs) with interesting pathologic features were re-imaged at higher resolution, 0.17 µm/pixel. Visualization and analysis was performed using Aivia software, custom spatial analysis software and python scripts. Results: All NSCLC tissue samples were successfully imaged in 3D at both low and high resolution. Computational approaches, such as machine learning, were used to segment and classify tumor cells and lymphocytes within the high resolution ROIs. In one example we quantified a 0.0045 mm3 ROI containing 1x109 voxels. We segmented 1,474 unique objects, and classified 683 (46%) of the objects as lymphocytes and 309 (20%) of the cells as tumor cells. We found that on average the lymphocytes were within 12 µm of the nearest tumor cell. Additionally the tissue was broken into separate lymphocyte dense (58% of volume) and tumor dense regions (42% of volume). Further analysis is in progress to quantify more features, such as tertiary lymphoid structures, stromal cells, and fibrosis over the full 20 sample dataset. Conclusions: We successfully implemented 3D machine learning analysis pipelines using images from intact NSCLC tissue samples measuring up to 5 mm3. The imaging was performed using our custom hybrid open-top light-sheet microscope. This novel method enables us to identify and quantify key histological features such as tumor cells and lymphocytes within the tumor microenvironment. In addition, machine learning driven algorithms clustered cells into distinct tissue regions in 3D which enables a more precise assessment of disease state and heterogeneity. Further investigation is ongoing to link these results to patient outcomes.

Identifying spatial clustering of diarrhoea among children under 5 years across 707 districts in India: a cross sectional study

BackgroundDiarrhoea is one of the leading reasons for under-five child mortality and morbidity across the globe and especially in low- and middle-income countries like India. The present study aims to investigate and identify the spatial clustering and the factors associated with diarrhoea across 707 districts of different states in India.MethodsThis study used National Family Health Survey-4 & 5 (2015–16 & 2019–21) data in India. Spatial analysis software i.e., ArcGIS and GeoDa including Moran’s statistics have been applied to detect the spatial prevalence and auto-correlation of diarrhoea among neighbourhood districts. Bivariate analysis with a chi-square test and logistic regression has been performed to identify the factors associated with the morbidity condition.ResultsThe result shows out of 2,23,785 children, 7.3 percent children suffer from diarrhoea in India. The prevalence is highest in Bihar (13.7%) and lowest in Lakshadweep (2.3%). Around 33 percent of districts have reported more than the national average level of diarrhoea prevalence. The study also found a medium to high level of autocorrelation with 0.41 Moran’s Index value and detected 69 hot-spots districts mostly from Maharashtra, Bihar, Odisha, and Gujarat. The study has also found, with an increase in children’s age as well as mother's age the prevalence of the disease decreases. The prevalence is more among male children than females. Underweight [OR = 1.08, 95% CI (1.03–1.13)] children have a greater risk of suffering from diarrhoeal diseases. The odds of children living in a pucca house [OR = 0.89, 95% CI (0.68–1.16)] are less likely to suffer from diarrhoea. On the other hand, rich economic status [OR = 0.91, 95% CI (0.86–0.97)], reduce the risk of such morbid conditions.ConclusionThe study recommends targeting the hot-spot districts with high prevalence areas, and district-level interventions by improving housing type and child nutrition status, which can help to prevent diarrhoeal diseases among children in India. Thus, the identification of hotspot districts and suggested policy interventions by the current study can help to prevent childhood mortality and morbidity, as well as to achieve the target given by Sustainable development Goals 3.2.

Spatial analysis of malaria hotspots in Dilla sub-watershed: Western Ethiopia.

This study aimed to examine the spatial variations in malaria hotspots along Dilla sub-watershed in western Ethiopia based on environmental factors for the prevalence; and compare the risk level along with districts and their respective kebele. The purpose was to identify the extent of the community's exposure to the risk of malaria due to their geographical and biophysical situations, and the results contribute to proactive interventions to halt the impacts. The descriptive survey design was used in this study. Ethiopia Central Statistical Agency based meteorological data, digital elevation model, and soil and hydrological data were integrated with other primary data such as the observations of the study area for ground truthing. The spatial analysis tools and software were used for watershed delineation, generating malaria risk map for all variables, reclassification of factors, weighted overlay analysis, and generation of risk maps. The findings of the study reveal that the significant spatial variations in magnitudes of malaria risk have persisted in the watershed due to discrepancy in their geographical and biophysical situations. Accordingly, significant areas in most of the districts in the watershed are characterized by high and moderate in malaria risks. In general, out of the total area of the watershed which accounts 2773 km2, about 54.8% (1522km2) identified as high and moderate malaria risk area. These areas are explicitly identified and mapped along with the districts and kebele in the watershed to make the result suitable for planning proactive interventions and other decision making. The research output may help the government and humanitarian organizations to prioritize the interventions based on identified spatial situations in severity of malaria risks. The study was aimed only for hotspot analysis which may not provide inclusive account for community's vulnerability to malaria. Thus, the findings in this study needs to be integrated with the socio-economic and other relevant data for better malaria management in the area. Therefore, future research should comprehend the analysis of vulnerability to the impacts of malaria through integrating the level of exposure to the risk, for instance identified in this study, with factors of sensitivity and adaptation capacity of the local community.

Vulnerability of Mangroves to Changing Coastal Regulation Zone: A Case Study of Mandovi and Zuari Rivers of Goa

Goa is a coastal State located on the west coast of India, known for its pristine sandy beaches and environment. Ministry of Environment and Forest implemented Coastal Regulation Zone Notification in 1991 for monitoring the coastal zones for unplanned developmental activities but has been just for name-sake purposes (Mascarenhas 1999, Agarwal 2019). The regulation has been changed in recent years thereby making the coastal and the riverine ecosystem more vulnerable to human interference. In the name of development, various hap-hazardous, unplanned activities have taken place which is degrading the coastal and riverine environment, especially mangroves. This paper studies the vulnerability of mangroves to the changing regulations with respect to 1991 and the 2018 CRZ notifications considering the land use land cover changes in the regulated zones of Mandovi and Zuari rivers. Spatial analysis techniques and software such as Arc GIS 10.3, and ERDAS IMAGINE 2014 have been used for analysis and results. The findings from the study can be effectively implemented in monitoring the regulated zones and protecting mangroves efficiently.

Synoptic analysis of the January 2004 snowstorm: Example of Çanakkale

Many natural disasters have occurred on the Earth we live in. Humans have always been in a struggle with these natural phenomena. Today, people are still struggling with atmospheric extreme events. One of the most important disasters like this is snowstorms that occur suddenly in winter. Especially countries in the middle belt (30-60 latitudes in the Northern Hemisphere) are constantly affected by snowstorms. Turkey, located in the Middle Belt, is also exposed to these storms during the winter season. From this perspective, the analysis of synoptic conditions and weather forecast is an important factor for risk analysis and take precautions for winter storms. Thus, the predictions made with the tracking of air masses and synoptic analysis make it easier to understand how the storm occurred. For this purpose, synoptic analyses were conducted to understand the development of the snowstorm that occurred in the high atmosphere in Çanakkale on January 20-30, 2004. This study examined how weather conditions change. Radiosonde data, surface maps, and daily bulletins provided from the Turkish State Meteorological Service were used in the study. Archival data were used to track air mass orbits using the Hysplit trajectory method. Stability and instability assessments of air masses were evaluated using the data from radiosonde stations using the K Index. Spatial analysis software was used to analyze the data and show the thematic distribution of topography. According to the findings, during the passage of a cold front of air masses coming from the north to Çanakkale on January 22, gusty winds began, suddenly dropped the temperatures, and began heavy snow events. Later, it turned into a blizzard and formed a type of snow.

Geographic modeling of weighted regression of self-reported malaria cases associated with environmental risk factors in Benin during the rainy season

Background: Geographically Weighted Regression (GWR) is a technique applied to capture variation by calibrating a multiple regression model, which allows different relationships to exist at different points in space. With malaria elimination at the top of the health agenda, integrated action on all elements of the malaria system that contributes to improved knowledge and local capacity building for positive effects on the health of the local population is needed. Methods: Several variables were collected for 192 sampling points in 12 communes in Benin, one per department. A questionnaire was sent to the head of the household to analyze the impact of environmental factors on reported malaria cases. Numerous GIS classification software for spatial analysis, remote sensing, data analysis/modeling and GPS management, R and MGWR software were used for geographic modeling. Results: An abundance of malaria cases reported in crop areas than in non-crop areas and in rural areas than in urban areas. The Hot Spot Analysis shows the localities of South Benin and Malanville as priority issue areas with a remarkable increase in crop diversity favorable to malaria vector proliferation. The spatial autocorrelation z-score of 4.83653470763 shows that there is less than a 1% probability that this clustered pattern is the result of chance. Conclusion: The observed non-stationarity means that the relationship between the variables studied varies from location to location depending on the physical factors of the environment that are spatially auto-correlated. Environmental factors therefore influence the intensity of transmission, seasonality, and geographic distribution of malaria. With minimal funding, we plan to correlate these data with parasitological and entomological da.

Evaluation on the urban green space layout in the central city of Yuxi based on big data

As an important part of urban public infrastructure, urban green space plays an indispensable role in urban development and public physical, mental, and emotional health. By collecting open data such as POI, OSM, and ASTER GDEM and using spatial analysis software such as ARCGIS, QGIS, and Global Mapper, this study conducted thermal analysis of crowd activities, service pressure analysis, and demand evaluation for the layout of park green space in the central urban area of Yuxi City. The results show that there are great differences in the area and spatial layout of the thermal classes of crowd activity. Class II occupies the largest area, accounting for 60.73%, while class V occupies the least area, accounting for 2.04%. The thermal classes of crowd activity decrease from the center of the city to the periphery, and their area increases with the decrease of the thermal classes. With the increase in the level of green space service pressure, the proportion of the area decreased, among which the proportion of grade I was as high as 53.20%, while that of grade V was only 1.89%, which was mainly affected by the spatial location. The demand level and the area of park green space are obviously different, mainly concentrated in the first level, accounting for 69.68% of the total demand, and the large area is scattered in the periphery of the central urban area, followed by the fourth level, accounting for 10.46%. The area of other levels, especially the high level of demand, is less. Comprehensive analysis shows that the service level, type of green space, service pressure, and demand of green space have a strong correlation with the geographical location. In future planning, Yuxi City should combine the population distribution density and land development intensity and carry out reasonable layout and planning of park green space by reducing the low-demand area, increasing the green space area of high-demand area, improving public transportation, and improving accessibility.

Open Source Software for Spatial Data Science

Much progress has been made in the development of software tools for spatial analysis since the special issue of Geographical Analysis appeared in 2006, devoted to “Recent advances in software for spatial analysis in the social sciences” (Rey and Anselin 2006). The 15 some years since the publication of the issue have been marked by major changes in the spatial analytical software landscape. Arguably, three important and somewhat related phenomena can be distinguished that drove these changes: the embedding of spatial analysis into spatial data science; the growing recognition of open science/open source principles in empirical work; and the increasing adoption of a literate programming perspective.

Evolution and Driving Mechanism of Tourism Flow Networks in the Yangtze River Delta Urban Agglomeration Based on Social Network Analysis and Geographic Information System: A Double-Network Perspective

This study’s purpose was to analyze the network structural characteristics, nodal roles, spatial structure, and evolution laws from the dual network perspective, and apply the Quadratic Assignment Procedure (QAP) to conduct correlation analysis and regression analysis on the influencing factors of tourism flow networks in the Yangtze River Delta urban agglomerations. Using a mixed-method of social network and spatial analysis, Ucinet and ArcGIS software were used to comprehensively analyze the nodes in the travel routes covered in travel notes. The results show that the density of tourism flow network increases on the whole, while the spatial difference decreases, and the overall network density value is much lower than the average of the network density of provinces. Degree centrality, closeness centrality, betweenness centrality and the core–periphery structure analysis were used to examine the tourism function, distribution function, connection function and the position of nodes in the network, and nodes were divided into various types of roles according to their function. Meanwhile, the role changes of each node in different periods were also investigated. This study also builds an evaluation model of the influencing factors of the evolution of tourism flow network structure and uses QAP to find that the tourism network is affected by factors such as tourism resource endowment, transportation convenience, economic development level, tourism reception and service capacity. The research results are helpful for the Chinese government and tourism enterprises to understand the spatial behavior of tourists and its evolution rules, and to clarify the role and status of node cities in the tourism flow network and their influencing factors. It is of great significance for the formulation of joint marketing measures and promotion of the sustainable development of tourism in the Yangtze River Delta urban agglomeration.

Multilevel Assessment of Seismic Damage and Vulnerability of Masonry Buildings (MUSE-DV) in Historical Centers: Development of a Mobile Android Application

Empirical data on the seismic behavior of masonry buildings are collected by technicians through rapid visual assessment procedures, i.e., by filling in forms that organize information in short answers or ticks. The resulting empirical database serves as a basis for prevention strategies, but the archiving and the post-processing of data are always a potential cause of losses and misinterpretations. New technologies are nowadays entering seismic risk analyses as a support to the usual visual approach. This paper proposes a new application for Android mobile devices that digitalizes an assessment form (MUSE-DV) able to collect damage and vulnerability data of masonry buildings in seismic areas, including information on strengthening interventions applied to buildings in the past. The client–server architecture of the app considers local devices communicating over the web with a central unit; data processing is split between them to reduce network and resource needs. This approach is convenient with thin devices, such as smartphones, and in post-disaster situations, when the mobile network may not be available. Data collected onsite can be stored in remote archives and therefore shared among technicians without affecting the integrity and consistency of the database. The whole dataset can be extracted and processed by a dedicated software for statistical and spatial analysis. The MUSE-DV procedure was validated in the area struck by the 2016 Central Italy earthquake and the app presented here was preliminarily tested onsite on the buildings of Castelsantangelo sul Nera (Macerata district); the results contributed to damage and vulnerability analyses by the means of thematic maps.

Spatial prevalence and its contextual determinants of early initiation of breastfeeding in cases of C-section deliveries in India: a study based on National Family Health Survey-4, 2015-2016

Background: Delayed early initiation of breastfeeding (EIBF) between 2 to 23 hours has increased 1.3 times risk of neonatal and it goes up double when it crosses more than 24 hours. Babies who were born through caesarean section (C-section) were less likely to initiate early breastfeeding as compared to normal vaginal delivery.Methods: The present study has utilized 14774 weighted samples of C-section delivered women from National Family Health Survey-4 (NFHS-4) (2015-2016). Spatial analysis software i.e. ArcGIS 10.8 and STATA 14 including logistics regression has been utilized to show the spatial prevalence and contextual determinants of EIBF on C-section birth babies in India.Results: In India, around 31.8% of C-section mothers breastfeed their children within one hour of delivery. The prevalence of EIBF is highest in Goa and lowest in Rajasthan. The central part of India mostly from the empowered action group (EAG) states practices a very low level of EIBF practices whereas, the north-east region represents the highest prevalence for the same. The odds of logistic regression shows that mother’s higher education (OR: 1.38), everyday mass media exposure (OR: 1.66), and initiation of postnatal care (PNC) within one hour (OR: 1.79) help to increase the practices of EIBF. On the other hand, delivery in the private hospital (OR: 0.61).Conclusions: The study shows remarkable geographical variations in EIBF and its correlates in the country. It recommends that the public health programmes need to target the states with less practice of EIBF (i.e. EAG state or central part of India) F among C-section delivery mothers. By increasing the level of mothers’ education status, mass media exposure and early PNC care can improve the EIBF practices among C-section mothers in India.

山水资源型城市景观生态风险评价及生态安全格局构建——以张家界市为例

PDF HTML阅读 XML下载 导出引用 引用提醒 山水资源型城市景观生态风险评价及生态安全格局构建——以张家界市为例 DOI: 10.5846/stxb202012313341 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 基于多准则决策的城乡国土空间冲突识别及调控机制研究（20YJC630207）；华中师范大学中央高校基本科研业务费（CCNU18TS002） Landscape ecological risk assessment and ecological security pattern construction in landscape resource-based city: A case study of Zhangjiajie City Author: Affiliation: Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:区域生态安全是现代城市健康发展的重要内容，科学认识与评价区域生态风险与构建生态安全格局，有利于综合提升区域生态安全水平。以张家界市2019年高分二号遥感解译数据为基础，使用GIS空间分析与Fragstats软件构建景观生态风险指数，对景观生态风险空间分布特征进行分析；利用最小累积阻力模型（MCR），以9个自然保护地为生态源地，以景观生态风险指数、植被覆盖度、高程、坡度、与道路距离、与水域距离构建阻力面，识别生态廊道与生态节点，构建生态安全格局并提出生态安全保护策略。结果表明：（1）研究区景观生态风险空间差异明显，生态风险呈现"中部、四周低，高值区总体沿澧水水系呈条带状延伸"的空间分布规律；（2）低、较低、中、较高、高生态风险分别占比21.59%、41.79%、22.57%、12.08%、1.98%，其中较低生态风险占比最高，高生态风险占比最低，各区县高生态风险压力排序为：永定区 > 慈利县 > 桑植县 > 武陵源区；（3）研究共识别出生态廊道24条，生态节点47个，生态廊道累积长达872.35km，生态廊道与生态节点分别呈现"三横四纵"、"中多西少，南多北少"的空间分布特征；（4）研究区形成了由9处生态源地、47处生态节点、24条生态廊道以及3个生态安全区构成的生态安全格局，在此基础上提出了生态安全保护策略，为张家界市生态环境建设提供科学指导。 Abstract:Regional ecological security is an important part of the healthy development of modern cities. Scientific understanding and evaluation of regional ecological risks and construction of ecological security pattern are conducive to comprehensively improving the level of regional ecological security. Based on the remote sensing interpretation data onto Gaofen-2 of Zhangjiajie City in 2019, this paper used GIS spatial analysis and Fragstats software to construct landscape ecological risk index, and analyzed the spatial distribution characteristics of landscape ecological risk. And the minimum cumulative resistance model is used to construct resistance surface. At the same time, in order to intuitively reflect the magnitude of resistance encountered during species migration, this paper uses 9 natural protected areas as ecological sources, and selects six resistance factors including landscape ecological index, vegetation coverage, elevation, slope, distance from roads, and distance from waters calculate the resistance value. Combining the ecological source area and the minimum cumulative resistance value, Then we identified ecological corridors and ecological nodes, and finally built an ecological security pattern and proposed ecological security protection strategies. This paper takes Zhangjiajie city as an example to verify the function and effectiveness of the method. The results show that:(1) there are obviously spatial differences in landscape ecological risk in the study area, and the ecological risk presents a spatial distribution pattern of "the middle and surrounding areas are low, and the high value area generally extends along the Lishui River in a strip"; (2) Low, relatively low, medium, relatively high, and high ecological risks area account for 21.59%, 41.79%, 22.57%, 12.08%, and 1.98%, respectively, among which the relatively low ecological risk area account for the highest proportion and the high ecological risk area account for the lowest proportion. The order of high ecological risk area pressure is:Yongding District > Cili County > Sangzhi County > Wulingyuan District; (3) The research identifies 24 ecological corridors and 47 ecological nodes. The cumulative length of ecological corridors is 872.35 km. And the spatial distribution characteristics of ecological corridors and ecological nodes are "three horizontal and four vertical" and "they are mainly distributed in the central and southern regions, and relatively few in the western and northern regions"; (4) The study area has formed an ecological security pattern consisting of 9 ecological sources, 47 ecological nodes, 24 ecological corridors and 3 ecological safety areas. On this basis, the protection strategy of ecological security is proposed to provide scientific guidance for the ecological environment construction of Zhangjiajie city. 参考文献 相似文献 引证文献