ArcGIS Pro Research Articles

Global, regional and national trends in tuberculosis incidence and main risk factors: a study using data from 2000 to 2021

BackgroundDespite the significant progress over the years, Tuberculosis remains a major public health concern and a danger to global health. This study aimed to analyze the spatial and temporal characteristics of the incidence of tuberculosis and its risk factors and to predict future trends in the incidence of Tuberculosis.MethodsThis study used secondary data on tuberculosis incidence and tuberculosis risk factor data from 209 countries and regions worldwide between 2000 and 2021 for analysis. Specifically, this study analyses the spatial autocorrelation of Tuberculosis incidence from 2000 to 2021 by calculating Moran’s I and identified risk factors for Tuberculosis incidence by multiple stepwise linear regression analysis. We also used the Autoregressive Integrated Moving Average model to predict the trend of Tuberculosis incidence to 2030. This study used ArcGIS Pro, Geoda and R studio 4.2.2 for analysis.ResultsThe study found the global incidence of Tuberculosis and its spatial autocorrelation trends from 2000 to 2021 showed a general downward trend, but its spatial autocorrelation trends remained significant (Moran’s I = 0.465, P < 0.001). The risk factors for Tuberculosis incidence are also geographically specific. Low literacy rate was identified as the most pervasive and profound risk factor for Tuberculosis.ConclusionsThis study shows the global spatial and temporal status of Tuberculosis incidence and risk factors. Although the incidence of Tuberculosis and Moran’s Index of Tuberculosis are both declining, there are still differences in Tuberculosis risk factors across countries and regions. Even though literacy rate is the leading risk factor affecting the largest number of countries and regions, there are still many countries and regions where gender (male) is the leading risk factor. In addition, at the current rate of decline in Tuberculosis incidence, the World Health Organization’s goal of ending the Tuberculosis pandemic by 2030 will be difficult to achieve. Targeted preventive interventions, such as health education and regular screening of Tuberculosis-prone populations are needed if we are to achieve the goal. The results of this study will help policymakers to identify high-risk groups based on differences in TB risk factors in different areas, rationalize the allocation of healthcare resources, and provide timely health education, so as to formulate more effective Tuberculosis prevention and control policies.

A New Approach to Enhance Smart City Applications Through Integrating GIS BIM Technology

The research deals with the study and analysis of smart cities, the requirements for their establishment, and the role of Building Information Modeling (BIM) in building sustainable, energy-efficient smart cities. The primary objective is to put a smart city transformation methodology and apply it on Lattakia city as a case study, using Building Information Modeling (BIM). We proposed new tools in an integrated methodology to transform from ordinary to smart city, and implemented basics of its objects, including GISBIM technologies integration, insuring both sustainable and energy saving vision at general planning designs. Implementing the chosen methodology steps at an organized area in Syria – Lattakia City, starting with building an accurate geodatabase, then, obtaining Sun Shadow Frequency analysis, which shows that December contains the highest shade values, with cumulative coverage rate 79.84%, while June instead contain the lowest shade value, reaching only 33.84%. But in general, most of the area has shade coverage that does not exceed 15% most of the day, therefore no need to make an adjustment to the distribution of building blocks. After that, in order to secure the energy needed for the study Area, analyzing the Land Surface Temperature (LST) done using the ArcGIS Pro® software, and locating a renewable energy station site (solar plant). On the other hand, analyzing a residential building energy through annual PV analysis has been done, by using Revit® software through Insight™ extension, with two cases: first one, building without changing building material, while second one done after changing building material to save solar energy inside and rising roof slope up to 10%, and we achieve valuable energy savings by applying this modification to building material. And finally, introducing the infrastructure underground network, that serving transformation to smart city.

СУЧАСНА ОЦІНКА ЗЕМЕЛЬНОГО ФОНДУ РЕКРЕАЦІЙНО ЗНАЧЕННЯ МІСТА ЖИТОМИРА

Purpose. The purpose of the article is a modern assessment of the land fund of recreational value in the city of Zhytomyr, the process of formation and use of recreation areas and their characteristics. Methods. When writing the article, such methods as analysis, synthesis and generalization, system and graphic methods were used. The information base for research is the works of domestic scientists, geoinformation technologies (GIS) based on the ArcGIS PRO and R programs, city master plan data, and official documents. Results. The article examines the main features of the modern formation, development and use of recreation areas in the city of Zhytomyr. The relevance of the use of land for recreational purposes in the city has been studied, and their necessity and importance have been shown. The delineation of the city territory into functional zones helps to solve the city's problems and identify them. The current state of the city's recreational areas and investment sites under construction is analyzed. Scientific novelty. Tourist and recreational resources and recreational facilities were analyzed. An analysis of the functional zones of the city was carried out to determine the assessment of the peculiarities of the development of recreational zones. A number of problems of recreational importance have been identified. The practical significance of the article is determined by the possibility of using the research results by employees of recreation and tourism establishments in the city of Zhytomyr, as well as during educational and educational activities of the population.

Health for all: Primary care facility localization in Lesotho using qualitative research and GIS

BackgroundLesotho has made significant strides towards universal health coverage and yet a significant proportion of the population has difficulty accessing health care services due to mountainous terrain and long travel times to nearest health facility. There have been previous studies that utilized Geographical Information Systems (GIS) to assess access to healthcare and to identify optimal locations for placement of new health facilities, though never in Lesotho. MethodsThe authors employed a mixed-methods design. Qualitative research consisting of semi-structured interviews and focus group discussions was used to gain a deep understanding of the problem with access to healthcare and to allow for the perspectives of the people of Lesotho to guide decision-making about placement of new healthcare facilities. GIS analysis was done using ArcGIS Pro v. 2.3 software and modern satellite imagery to map current access to healthcare facilities and create site recommendations for new healthcare facilities. ResultsQualitative research revealed that walking was the primary mode of transport to healthcare facilities and that distance was the crucial barrier in limiting access to care. Decentralization in decision-making was identified as an important element in health policy decisions and study participants recommended placing health facilities centrally in large villages. GIS analysis identified that 77.7 % of the population was currently within 3-h walking distance to nearest health facility and that the addition of fifty new healthcare facilities would increase that proportion to 90.0 %. ConclusionThis study mapped current access to care in Lesotho in rural and urban areas. It also provided an objective strategy for identifying the location of new healthcare facilities while incorporating the voices of the people of Lesotho in the process. The findings can be used to assist policymakers, and the methodology can be employed in the allocation of other public-service facilities in different countries or regions.

Archaeological Research on the Former KL Auschwitz I and KL Auschwitz II-Birkenau Site

For many years Auschwitz-Birkenau State Museum has been conducting excavation works on the site of the former German concentration and extermination camp Auschwitz II-Birkenau, related to the implementation of projects to preserve the authenticity and other ad hoc maintenance works, as well as those related to the extension of the necessary infrastructure network in the area of the former camp. These works, carried out in various parts of the former Birkenau, are subject to obligatory archaeological research. Over the years, a large number of reports on archaeological works have been collected. Researchers faced the challenge of accumulating dispersed archaeological information, mainly about the location of archaeological research sites and about the findings that were noted during the works. The chosen solution was the use of GIS software. Initially, this was QGIS, which is to be replaced by ArcGIS Pro over time. This makes it possible to place excavation sites in a generalised form on a map (contemporary or historical) or on a properly prepared aerial photo (for any year from the years available: 1944-2022). The outline of the excavation in the above-mentioned programs is interactive with the user. The description of the findings from a given place is added to it. The set of data thus prepared can then be filtered and selected, like in a popular spreadsheet. The amount of information on one map can be enhanced with underground infrastructure networks (as information about possible collisions) and road and construction infrastructure of the camp area which enables better orientation in the surroundings. Introduction of the possibilities of deeper analytics of large data sets is the main basis for outlining the possibilities of Geographic Information Systems.

Novel GIS-based fuzzy TOPSIS and filtration algorithms for extra-large scale optimal solar energy sites identification

Solar energy stands as an increasingly attractive and environmentally responsible energy source, possessing the potential to meet the burgeoning power needs of the Sarawak region. This paper proposes a novel methodology that combines Geographic Information System-based fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and filtration algorithms to identify the top 100 optimal Solar Energy Sites (SES). The research encompasses the extra-large scale potential SES comprising 19,237 coordinated data points. It evaluates SES based on 12 diverse criteria spanning climatic conditions, technical feasibility, accessibility, environmental considerations, and social factors. This research employs a meticulous double-layer filtration process to systematically eliminate unsuitable locations, resulting in a refined list of 1,862 potential SES. Subsequently, the fuzzy TOPSIS algorithm has further narrowed down the selection to the top 100 SES, constituting the core results of this research. The results reveal an interesting distribution of the identified SES, which mainly clustered in 3 huge categories (Kuching-Samarahan, Sibu-Kapit-Mukah and Bintulu-Miri). The identified 100 SES possess high closeness coefficients, which range from 0.7 to 0.85, where 1 indicates the best solution of the fuzzy TOPSIS algorithm. Additionally, the paper presents a spatial distribution analysis of the top-ranking sites across various divisions and districts. To validate the results obtained from the proposed model, a solar suitability map has been developed in ArcGIS Pro. When comparing the results from the proposed model to those obtained from the solar suitability map, most SES have consistent relative percentages, with only one SES falling below 50 %. To provide an overview of the similarity between the two models, the average relative percentage is computed at 69.01 %, signifying the proximity of SES to the optimal value of the solar suitability map. Furthermore, the developed source code in this research exhibits flexibility, featuring filtration algorithms that can accommodate any raster maps. It serves as an asset for researchers interested in conducting comprehensive large-scale SES identification in future case studies.

Geologic Map of the Bedford 30- x 60-minute Quadrangle, Indiana

The Geologic Map of the Bedford 30- x 60-minute Quadrangle shows the Mississippian and lower Pennsylvanian bedrock units and the overlying Pleistocene and Holocene deposits distributed over eight counties. The mapped area includes five physiographic divisions of the Southern Hills and Lowlands Region in south-central Indiana. Bedrock units and unconsolidated deposits were characterized by outcrop field observations, and new and archived borehole data. Bedrock data was consolidated into a single mapping database, which was then processed using gridding and contouring tools in ArcGIS Pro, resulting in rock formation contact lines, mappable at 1:100,000 scale. Additional information used to delineate contacts for unconsolidated deposits was based upon Indiana Department of Natural Resources water well database and soils data from the Soil Survey Geographic (SSURGO) database. Light detection and ranging (LiDAR) digital elevation models were also used to identify landforms and refine contacts between surficial units. The mapped bedrock units, from east to west, range in age from the Borden Group (lower Mississippian) to the Raccoon Creek Group (Lower Pennsylvanian) with the strike oriented generally from northwest to southeast. Quaternary deposits are found in river and stream valleys and filling the Wabash and Scottsburg lowlands with glacial deposits. Quaternary sediments were mostly deposited during the last two major advances of the Laurentide Ice Sheet into south-central Indiana. Brief summaries of all mapped bedrock units and unconsolidated deposits are listed on the map sheet, with more detailed descriptions in the accompanying pamphlet. Bedrock survey drill hole data points are also displayed on the map with corresponding links to expanded drill hole information for each of the survey drill holes listed in the pamphlet. In addition to the map and pamphlet, a composite spatial data set that conforms to the standardized database schema known as GeMS (Geologic Map Schema) is also available for download from this site. Both ESRI-licensed geodatabase and open shapefile versions of the spatial data set are available for download. Metadata records associated with each element within the spatial data set contain detailed descriptions of their purpose, constituent entities, and attributes. This geologic map was funded in part through the STATEMAP program supported by the U.S. Geological Survey under Cooperative Agreement No. G21AC10646.

Benchmark for Automatic Clear-Cut Morphology Detection Methods Derived from Airborne Lidar Data

Forest harvest detection techniques have recently gained increased attention due to the varied results they provide. Correctly determining the acreage of clear-cut areas is crucial for carbon sequestration. Detecting clear-cut areas using airborne laser scanning (ALS) could be an accurate method for determining the extent of clear-cut areas and their subsequent map display in forest management plans. The shapes of ALS-detected clear-cut areas have uneven edges with protrusions that might not be readable when displayed correctly. Therefore, it is necessary to simplify these shapes for better comprehension. To simplify the shapes of ALS-scanned clear-cut areas, we tested four simplification algorithms using ArcGIS Pro 3.0.0 software: the retain critical points (Douglas–Peucker), retain critical bends (Wang–Müller), retain weighted effective areas (Zhou–Jones), and retain effective areas (Visvalingam–Whyatt) algorithms. Ground-truth data were obtained from clear-cut areas plotted in the forest management plan. Results showed that the Wang–Müller algorithm was the best of the four ALS algorithms at simplifying the shapes of detected clear-cut areas. Using the simplification algorithm reduced the time required to edit polygons to less than 1% of the time required for manual delineation.

Capacity assessment and spatial analysis of cervical cancer services in The Gambia

BackgroundCervical cancer is the most common cancer and the leading cause of cancer-related death in Gambian women. The Gambian Ministry of Health is striving to improve access to screening, diagnostic, and treatment services for cervical cancer, but comprehensive data on currently available services is limited making it challenging to appropriately prioritize the ideal next steps for expanding care. This study aims to describe the current services available for the prevention, screening, and treatment of cervical cancer in The Gambia and provide suggestions for expanding geographic access to care.MethodsA survey aimed at assessing the availability of key cervical cancer-related services was developed and then administered in person by research assistants to all secondary and tertiary health facilities (HFs) in The Gambia. ArcGIS Pro Software and 2020 LandScan population density raster were used to visualize and quantify geographic access to care. Survey results were compared with published targets outlined by the Gambian Ministry of Health in the “Strategic Plan for the Prevention and Control of Cervical Cancer in The Gambia: 2016–2020.”ResultsOne hundred and two HFs were surveyed including 12 hospitals, 3 major health centers, 56 minor health centers, and 31 medical centers/clinics. Seventy-eight of these HFs provided some form of cervical cancer-related service. HPV vaccination was available in all health regions. Two-thirds of the population lived within 10 km of a HF that offered screening for cervical cancer and half lived within 10 km of a HF that offered treatment for precancerous lesions. Ten HFs offered hysterectomy, but nine were located in the same region. Two HFs offered limited chemotherapy. Radiotherapy was not available. If all major health centers and hospitals started offering visual inspection with acetic acid and cryotherapy, 86.1% of the population would live within 25 km of a HF with both services.ConclusionsGeographic access to cervical cancer screening, and precancer treatment is relatively widespread across The Gambia, but targeted expansion in line with the country’s “Strategic Plan” would improve access for central and eastern Gambia. The availability of treatment services for invasive cancer is limited, and establishing radiotherapy in the country should continue to be prioritized.

Geospatial mapping of 2-hour access to timely essential surgery in the Philippines

ObjectivesTimely access to safe and affordable surgery is essential for universal health coverage. To date, there are no studies evaluating 2-hour access to Bellwether procedures (caesarean section, laparotomy, open fracture...

Abstract A101: Assessing contemporary cancer prevention infrastructure in neighborhoods of historical residential segregation to better understand patterns of breast cancer disparities

Abstract Background: Breast cancer disparities among minoritized women in the United States (U.S.) not only persist but continue to widen. Neighborhood attributes are established drivers of cancer disparities in the U.S. An emerging area of research centers on the associative relationship of historical processes of segregation, particularly redlining practices, on breast cancer disparities. However, these studies have not considered the differences in contemporary neighborhood attributes in historically segregated and non-segregated neighborhoods. This study focuses on 2019 neighborhood attributes that work together to better understand differences in physical environment access to breast cancer prevention lifestyle habits such as access to fresh produce, green spaces, and clinical sites for prevention screenings. Methods: Using ArcGIS Pro we created GIS maps of Tucson, Arizona capturing food environments, green spaces, public transportation, and Medicaid cancer screenings site. The current neighborhood attributes were then layered over historic neighborhoods identified from historical documents to determine differences in access to these resources for breast cancer prevention. We used U.S. Census data to map sociodemographic data to the Census tract neighborhood level. Findings: The GIS maps demonstrate the neighborhoods established by historical segregation have more food deserts, fewer green spaces, limited public transportation, and no Medicaid Well WomanCheck mammography screening sites were located in close proximity to the historically segregated neighborhoods. The historically non-segregated communities did not have similar levels of disinvestment and had a higher presence of resources for non-genetic cancer prevention lifestyle habits. Discussion: To our knowledge, this is the first study to compare contemporary neighborhood attributes based on the historical status of segregated and non-segregated to understand how this impacts access to cancer prevention resources that may contribute to breast cancer disparities experienced among historically marginalized communities. The historical legacy of segregation shapes contemporary geographies, structural social determinants of health, and the gaps in non-genetic cancer prevention resources influencing breast cancer disparities. To build health equity, local policymakers must implement policies to address remnants of historical segregation in these communities that still navigate the reverberations of these historical processes. Zoning laws should be considered as a key target for structural interventions to build equitable access to breast cancer prevention infrastructure in neighborhoods established by historical segregation. Citation Format: Celina I. Valencia, Francisco Mendoza. Assessing contemporary cancer prevention infrastructure in neighborhoods of historical residential segregation to better understand patterns of breast cancer disparities [abstract]. In: Proceedings of the 16th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2023 Sep 29-Oct 2;Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2023;32(12 Suppl):Abstract nr A101.

Detection of Prostate Cancer Screening Disparities Using Geospatial Analysis of Laboratory Results

Abstract Black men experience higher prevalence and mortality from prostate cancer (PCa) but are less likely to undergo PCa screening with prostate-specific antigen (PSA). The reasons for this disparity are multifactorial and include lack of access, PCa education, and mistrust in the healthcare system. Identifying geographic regions with low PSA screening and high positivity rates could potentially help inform targeted interventions. This study aimed to examine racial, socioeconomic, and geospatial disparities in PSA screening and positivity rates in the Siteman Cancer Center (St. Louis, MO) catchment region. The results of all PSA screening tests ordered in the Barnes-Jewish Healthcare Corporation (St. Louis, MO) and performed from 9/2019-12/2022 were retrieved from the laboratory information system with patient demographics. Patient addresses were geocoded using ArcGIS Pro (ESRI, Redlands, CA) and assigned to a census tract of residence. The PSA screening-eligible population was defined as the number of persons ≥50 years of age based on U.S. Census data. Social Vulnerability Index (SVI) values were retrieved from the Centers for Disease Control. The PSA screening rate was calculated by census tract as the total number of PSA tests performed/PSA screening-eligible population. The PSA positivity rate was calculated by census tract as the number of PSA positive tests/total PSA tests. All census tracts with fewer than 10 PSA tests performed were omitted from PSA positivity analysis. Hotspot analysis was performed by calculating Local Moran’s I statistic per census tract and comparing with 999 randomly-generated maps. A total of 90,994 screening tests for 60,005 patients (48,024 White [80%], 10,425 Black [17%], and 1,556 Other [3%]) were performed for patients in the catchment region. Black patients were 78% more likely to receive a positive PSA screen than White patients (p&amp;lt;0.001). Of those screening positive, Black patients had a significantly higher median[IQR] (7.94[6.2-13.7 ng/mL]) PSA result compared to White patients (7.4[6.2-10.1 ng/mL]) (p&amp;lt;0.001) and a median[IQR] age of 67[61-74 years] vs. 69[63-76 years] (p&amp;lt;0.001). In a multivariate logistic regression using age, race, and census tract of residence SVI to predict PSA positivity, only census tract SVI was not statistically significant. A model using only age and race demonstrated that every 10 years of age and Black race were associated with 11% and 7% increased odds of receiving a PSA positive test, respectively (p&amp;lt;0.001). 75 and 191 of 789 census tracts in the catchment region were identified as PSA positivity hotspots and PSA screening cold spots, respectively. In conclusion, this study confirms previous reports of higher PSA values among Black patients and suggests that geospatial analysis of PSA testing can identify geographic regions with low testing and high positivity rates.

Ecological correlates and predictors of Lassa fever incidence in Ondo State, Nigeria 2017–2021: an emerging urban trend

Lassa fever (LF) is prevalent in many West African countries, including Nigeria. Efforts to combat LF have primarily focused on rural areas where interactions between rodents and humans are common. However, recent studies indicate a shift in its occurrence from rural to urban areas. We analysed secondary data of reported LF outbreaks from 2017 to 2021 in Ondo State, Nigeria to identify the distribution pattern, ecological variations, and other determinants of disease spread from the ward level using nearest neighbour statistics and regression analysis. Data utilised include LF incidence, ecological variables involving population, nighttime light intensity, vegetation, temperature, market presence, road length, and building area coverage. ArcGIS Pro 3.0 software was employed for spatial analysis. Results revealed spatio-temporal clustering of LF incidents between 2017 and 2021, with an increasing trend followed by a decline in 2021. All wards in Owo Local Government Area were identified as LF hotspots. The ecological variables exhibited significant correlations with the number of LF cases in the wards, except for maximum temperature. Notably, these variables varied significantly between wards with confirmed LF and those without. Therefore, it is important to prioritise strategies for mitigating LF outbreaks in urban areas of Nigeria and other LF-endemic countries.

Distribution characteristics of the free-roaming dog population of the western area of Tongatapu, Kingdom of Tonga: Developing a GIS for biosecurity and animal welfare projects

The free-roaming dog population of Tongatapu, Kingdom of Tonga, is a ubiquitous, well-known and persistent feature of the island. Information on the quantity, condition and spatial distribution characteristics of these dogs is needed for projects aimed at improving biosecurity conditions in different impacted sectors of society, while addressing the management of an animal associated with humans. Health and safety of the human population, agriculture and biodiversity are directly affected by the presence of free-roaming dogs in Tongan communities. A survey conducted over western Tongatapu recorded locations of free-roaming dogs sighted when driving along the roads of 12 towns and villages. Locations were recorded using an iPad and the mobile application Collector for ArcGIS. A total of 1152 dogs was recorded, mostly within villages and residential roads. Patterns of spatial distribution of dog locations were described using kernel density, hotspot analysis, and cluster and outlier analysis tools available in ArcGIS Pro. Using the species distribution modelling algorithms Maxent and random forest (RF), the suitability of the entire island for free-roaming dogs was determined using as input the dog locations and environmental variables consisting of population, land use and road types. Results of both algorithms show that roads and residential areas consistently show the highest probability of free-roaming dog presence. The RF algorithm also produced maps that show predictions of the values of other variables collected during the survey, including body-condition scores, age group and sex types over the entire island. Overall, the maps produced and the database created contribute a baseline biosecurity knowledge-base supporting rational decision-making and governance for the island.

Simulation of the Impacts of Sea-Level Rise on Coastal Ecosystems in Benin Using a Combined Approach of Machine Learning and the Sea Level Affecting Marshes Model

Sea-level rise in Benin coastal zones leads to risks of erosion and flooding, which have significant consequences on the socio-economic life of the local population. In this paper, erosion, flood risk, and greenhouse gas sequestration resulting from sea-level rise in the coastal zone of the Benin coast were assessed with the Sea Level Affecting Marshes Model (SLAMM) using ArcGIS Pro 3.1 tools. The input features used were the Digital Elevation Map (DEM), the National Wetland Inventory (NWI) categories, and the slope of each cell. National Wetland Inventory (NWI) categories were then created using Support Vector Machines (SVMs), a supervised machine learning technique. The research simulated the effects of a 1.468 m sea-level rise in the study area from 2021 to 2090, considering wetland types, marsh accretion, wave erosion, and surface elevation changes. The largest land cover increases were observed in Estuarine Open Water and Open Ocean, expanding by approximately 106.2 hectares across different sea-level rise scenarios (RCP 8.5_Upper Limit). These gains were counterbalanced by losses of approximately 106.2 hectares in Inland Open Water, Ocean Beaches, Mangroves, Regularly Flooded Marsh, Swamp, Undeveloped, and Developed Dryland. Notably, Estuarine Open Water (97.7 hectares) and Open Ocean (8.5 hectares) experienced the most significant expansion, indicating submergence and saltwater intrusion by 2090 due to sea-level rise. The largest reductions occurred in less tidally influenced categories like Inland Open Water (−81.4 hectares), Ocean Beach (−7.9 hectares), Swamp (−5.1 hectares), Regularly Flooded Marsh (−4.6 hectares), and Undeveloped Dryland (−2.9 hectares). As the sea-level rises by 1.468 m, these categories are expected to be notably diminished, with Estuarine Open Water and Open Ocean becoming dominant. Erosion and flooding in the coastal zone are projected to have severe adverse impacts, including a gradual decline in greenhouse gas sequestration capacity. The outputs of this research will aid coastal management organizations in evaluating the consequences of sea-level rise and identifying areas with high mitigation requirements.

Impact of land use changes on the land surface thermal environment in Nanchang, Jiangxi province, China

Throughout human history, human activities have resulted in land use and land cover changes (LUCC) and can have a direct impact on the land surface thermal environment (LSTE). In the existing studies, the holistic nature of changes in land use and land cover (LULC) has been neglected in favor of focusing on the interactions between different LULC types and the land surface thermal environment. This study used ArcGIS Pro 3.0, ENVI 5.3, and SPSS software to construct a contribution index model and stepwise regression equation to investigate the relationship between LULC type, structure, and pattern changes and LSTE changes in Nanchang City, Jiangxi Province, China, from 1990 to 2020. The findings revealed that 1) rapid urbanization has led to a surge in the area of built-up land and a decrease in the area of arable land in Nanchang; between 1990 and 2020, the area of built-up land in Nanchang increased by 433.29 km2, while the area of arable land decreased by 291.99 km2; 2) The land surface temperature (LST) was divided into five classes according to the equal spacing method, and the areas with the highest and lowest temperature classes were the high temperature zone and the low temperature zone, respectively. Over the past 30 years, the LSTE in Nanchang has gradually deteriorated, with the area of the low temperature zone shrinking by 554.2 km2 and the area of other classes appearing to increase significantly; 3) the contribution index and stepwise regression equation demonstrate that the primary reasons for the worsening of the LSTE are an increase in the scale of cultivated land and construction land. It was found that rationalization of urban LULC type, structure, and pattern can effectively reduce land surface temperature.

Histogram cube: towards lightweight interactive spatiotemporal aggregation of big earth observation data

ABSTRACTIn the era of Earth Observation (EO) big data, interactive spatiotemporal aggregation analysis is a critical tool for exploring geographic patterns. However, existing methods are inefficient and complex. Their interactive performance greatly depends on large-scale computing resources, especially data cube infrastructure. In this study, from a green computing perspective, we propose a lightweight data cube model based on the preaggregation concept, in which the frequency histogram of EO data is employed as a specific measure. The cube space was divided into lattice pyramids by the Google S2 grid system, and histogram statistics of the EO data were injected into in-memory cuboids. Therefore, exploratory aggregation analysis of EO datasets could be rapidly converted into multidimensional-view query processes. We implemented the prototype system on a local PC and conducted a case study of global vegetation index aggregation. The experiments showed that the proposed model is smaller, faster and consumes less energy than ArcGIS Pro and XCube, and facilitates green computing strategies involving a cube infrastructure. Due to the standalone mode, larger dataset will result in longer cube building time with indexing latency. The efficiency of the approach comes at the expense of accuracy, and the inherent uncertainties were examined in this paper.

Designing an IoT-Based System for Monitoring Noise Levels in the Computer Science Faculty and Library of the Technological University of Panama.

Noise pollution is a growing problem in urban areas, and it is important to study and evaluate its impact on human health and well-being. This work presents the design of a low-cost IoT model and implementation of two prototypes to collect noise level data in a specific area of the regional center of Chiriquí, at the Technological University of Panama that can be replicated to create a noise monitoring network. The prototypes were designed using Autodesk Fusion 360, and the data were stored in a MySQL database. Microsoft Excel and ArcGIS Pro were used to analyze the data, generate graphs, and display the information on maps. The results of the analysis can be used to develop strategies to reduce noise pollution and improve the quality of life in urban areas.

Future land use land cover changes in El-Fayoum governorate: a simulation study using satellite data and CA-Markov model

This study aims to monitor the changes in land use land cover (LULC) in El-Fayoum governorate over time (past, present, and future) to provide current information for stakeholders involved in land use planning. The study utilized Landsat satellite images and applied the Support Vector Machine algorithm using ArcGIS Pro 2.8.3 to classify the images into four major LULC classes: water, desert, built-up, and agricultural. To evaluate the accuracy of the LULC maps, the study used kappa statistical parameters, which ranged from 0.91 to 0.94, indicating acceptable results for further analysis. To predict spatio-temporal LULC changes, the study considered biophysical and socioeconomic factors such as distance to canals, distance to roads, distance to urban areas, a digital elevation model, and slope. A combination of Multi-Criteria Evaluation, a Fuzzy Membership Function, and the Analytic Hierarchy Process were employed to develop a land cover suitability map. The Hybrid CA-Markov model of the IDRISI-TerrSet software was used to simulate LULC changes, and the accuracy of the simulation was validated using 2020 imagery data. The values gained from the kappa indices for agreement (standard) = 0.9006, kappa for lack of information (no) = 0.916, and kappa for location at grid cell level (location) = 0.9572 demonstrate that the results of the simulation of the LULC changes were deemed satisfactory. The future scenarios modeled in LULC indicate a significant change in the LULC classes over time, specifically for 2030. The change rates of agriculture, desert, built-up, and water areas in El-Fayoum in 2030 compared to 2020 are estimated to be 9.68%, − 17.58%, 133.62%, and 6.06%, respectively. These findings establish both past and future LULC trends and provide crucial data useful for planning and sustainable land use management.

Fifteen-, Ten-, or Five Minute City? Walkability to Services Assessment: Case of Dubai, UAE

The rapid urbanization growth in Dubai has resulted in connectivity issues and is therefore considered tremendous development pressure. That has led the local authorities to set a vision for Dubai as a 15–20 min city by 2040. In a 15 min city, all services can be reached within 15 min of travel time using sustainable mobility means, including walking, cycling, or electric biking. This study aims to assess the current walkability situation within 15 min in the most significant parts of Dubai. The study considered 13 communities, including Bur-Dubai and Business Bay, which were selected to represent ungated communities and eleven major gated communities. Those neighborhoods were selected based on the developments’ socio-economic status and population density. The assessment considered 14 essential services, grouped into five categories: educational, health, social, entertainment, and religious. The data for this study was collected through desktop research, site visits, and residents’ interviews. The data layers were prepared in ArcGIS Pro 3.0, which was used to perform the network analysis. The results indicate that 28.25% of residents in the ungated neighborhoods have access to essential services within 15 min, similar to gated communities where residents rely on cars to access many services. Furthermore, results suggest that service distribution patterns and walkability infrastructure outside these communities should be developed to obtain higher walkability indicators.