Suchergebnisse

Dramatic changes of forests have strong influence on regional and global carbon cycles, biodiversity, and ecosystem services. Understanding dynamics of forests from local to global scale is crucial for policymaking and sustainable development. In this study, we developed an updating and object-based image analysis method to map forests in Northeast China using Landsat images from 1990 to 2015. The spatio&ndash ; temporal patterns of forests were quantified based on resultant maps and geospatial analysis. Results showed that the percentage of forested area occupying the entire northeast China was more than 40%, about 94% of initial forest cover remained unchanged (49.37 × ; 104 km2) over the course of 25 years. A small net forest loss (1051 km2) was observed during 1990&ndash ; 2015. High forest gain (10,315 km2) and forest loss (9923 km2) both occurred from 2010 to 2015. At the provincial level, Heilongjiang demonstrated the highest rate of deforestation, with a net loss of 1802 km2 (0.89%). Forest changes along elevation, slope, and distance from settlements and roads were also investigated. Over 90% of forest changes occurred in plains and low mountain areas within the elevation of 200&ndash ; 1000 m and slope under 15° ; . The most dramatic forest changes can be found within the distance of 2000 m from settlements and roads. The reclamation of sloping land, construction of settlements and roads, and possible smallholder clearing contributed more to forest loss, while ecological projects and related government policies play an important role on afforestation and reforestation. These results can provide useful spatial information for further research on the driving forces and consequences of forest changes, which have critical implications for scientific conservation and management of forests.

Abstract
In April 2017, the Centers for Disease Control and Prevention (CDC) participated in the Gotham Shield Exercise, led by the Federal Emergency Management Agency (FEMA) and in collaboration with other federal agencies to test the federal, state and local government's ability to respond to an improvised nuclear device (IND). With active engagement from CDC leadership, 266 scientific and support staff from across the agency participated in the Gotham Shield exercise. The scenario involved a 10-kiloton detonation near the Lincoln Tunnel in New Jersey. This nuclear detonation scenario provided CDC with the opportunity to test some of the all-hazards tools the agency uses during response to other national or international emergencies, such as Geographic Information Systems (GIS) and mapping tools, and apply these tools to a nuclear emergency. Geospatial analysis associated with real time data can provide near real time information for individuals and entities associated with response and recovery activities. This type of analysis can provide timely data in regard to maps and information used to properly place staging areas for Community Reception Centers (CRC), mass care locations, and other medical care and countermeasure related services. Maps showing locations of power loss, such as locations of lost or inoperable main electrical grid and substations, combined with real time data on where power is available provides valuable information for first responders and emergency managers as well as responders engaged in communicating critical public messages to affected populations in these areas. By using real-time information, response officials can direct the response, allocate scarce resources, aid in coordination efforts, and provide a more efficient means of providing critical public health and medical services. The results of the exercise highlight the importance of using geospatial analysis for response planning and effect mitigation before, during, and after a public health event of this magnitude, and the value they represent in informed decision making.

Physician acceptance is an important dimension of access to care, especially for Medicaid patients. We constructed two new measures to quantify primary care physician (PCP) acceptance of Medicaid patients using geocoded Virginia physician addresses and population data and geospatial methods. For each Census block group, we measured the shares of "accessible PCPs" accepting any Medicaid patients or new Medicaid patients. Accessible PCPs were defined as those located within 30-minute travel from patient locations and patient locations were proxied by Census block group geographic centroids. We found that the shares of accessible PCPs accepting Medicaid varied within Virginia, and were significantly lower in urban communities where larger fractions of the population were Hispanic, even controlling for unobserved market-level traits associated with Medicaid acceptance. Policy makers and Medicaid program officials should continue to improve nonfinancial access to primary care, especially by addressing access barriers in communities with high shares of minority residents.

Research area: Taipei urban landscapes, Taiwan. Located on the north of the Taiwan Island, Taipei is the country's core urban political and economic center with population reaching over 2.6 M and continuing to expand within the city Research aim: spatio-temporal analysis of urban dynamics in study area during 15 years (1990-2005) Data capture: The data include Landsat TM images taken from the U.S.G.S. website. The software used is ENVI GIS. Research objective: application of geoinformatic tools, remote sensing data and application of methodology to spatial analysis for a case study of Taipei. Research problem: In the past decades, the process of urbanization has become more notable in the East Asia. Since past decades, Taipei city undergone serious urban changes.The development of urban landscapes in Taipei has unique feature; Taiwan's exceptional economic and industrial growth since 1980s, which is often referred as "industrial wonder of Taiwan". Recently, the country quickly transformed from an agriculture-based traditional economy into a highly industrialized society. As a result, Taiwan has now a new face of high-technology oriented, economically restructured economy. This caused changes in the face of the country, modifying both its social and natural landscape patterns. Taiwan is nowadays a highly urbanized country with almost 80% of the total population of Taiwan living in urban areas. Intensive urbanization necessarily create new conditions for human-nature co-existence, since rapidly growing city and high urbanization rate affect biodiversity and ecosystems sustainability. The process of urbanization includes transformation of natural landscapes: typical natural land cover type are being transformed into human-affected artificial surfaces and the city area enlarges. Anthropogenic pressure increased rapidly due to the expansion of Taipei metropolitan area. Rapid urbanization affects complex interrelations of natural and urban ecosystems, changes their structure, size and shape, which becames a serious ...

Background: Childhood obesity remains a public health issue globally. The latest estimate from the World Health Organization showed that over 340 million children and adolescents aged 5–19 were overweight or obese in 2016. Objective: Our study aimed to assess the density of fast food outlets around educational facilities in Riyadh, Saudi Arabia. Methods: We employed geospatial and quantitative analyses using data on fast food outlets (from surveys conducted between November 2019 and May 2020) and educational facilities in Riyadh city. Data analyses conducted using ArcMap 10.6 and Stata 15 compared the density within 500 m and 500–1000 m from the facilities. Results: We found a high density of fast food outlets around educational facilities. Nearly 80% of fast food were within twelve-minute walking or five-minute driving distances from schools, and nearly 70% of all educational facilities had at least one fast food outlet within the buffer. We also found the densities were high within both the areas closer and the areas farther away from educational facilities. In addition, the density was significantly higher around private schools compared to government schools, and the density around girls-only schools and both-gender schools was higher than that around boys-only schools. Conclusion: There is a high density of fast food outlets around educational facilities in Saudi Arabia. Effective policies are needed to help reduce potential exposure to fast food among young people in Saudi Arabia and other countries with similar settings.

Geospatial data has proven effective in identifying and monitoring deforestation, land use, and water resources in regions with a predominant focus on agriculture and livestock. The purpose of this study was to assess the use of georeferencing in identifying instances of deforestation and land use, and their respective impacts on water resources in Paragominas, Pará, during the years 2000, 2005, 2010, and 2021. The methodology utilized an inductive approach, integrating quantitative and qualitative methods along with field observations. Georeferencing data showed that deforestation has taken place since the establishment of the municipality, resulting in an 83.64% decrease in forest cover. In 2000, the urban area occupied 1,333 hectares and in 2021 it increased to 2,026 hectares. The surface water area decreased by 207.91 hectares between 2000 and 2021. From 2010 to 2021, pastures decreased from 187,561 hectares to 125,229 hectares. Agriculture also evolved from occupying 1,342 hectares in 2000 to 103,162 hectares in 2021. Of the 11 settlement projects, five are completely located within the Uraim river basin, and two others are partially located there. The literature analyzed reveals that water originates from the Uraim River, which runs through rural properties and farming communities such as Colonia do Uraim, resulting in sediment deposition, soil compaction, reduced infiltration capacity, and basin recharge. Furthermore, the right bank tributary, the Paragominas stream, has 1.5 km of developed banks. Spatial analysis utilizing geospatial data is vital for identifying deforested areas and conducting complementary studies on land use, occupation, and water quality. These studies are instrumental in devising natural resource management plans for Paragominas.

The unprecedented COVID-19 pandemic is showing dramatic impact across the world. Public health authorities attempt to fight against the virus while maintaining economic activity. In the face of the uncertainty derived from the virus, all the countries have adopted non-pharmaceutical interventions for limiting the mobility and maintaining social distancing. In order to support these interventions, some health authorities and governments have opted for sharing very fine-grained data related with the impact of the virus in their territories. Geographical science is playing a major role in terms of understanding how the virus spreads across regions. Location of cases allows identifying the spatial patterns traced by the virus. Understanding these patterns makes controlling the virus spread feasible, minimizes its impact in vulnerable regions, anticipates potential outbreaks, or elaborates predictive risk maps. The application of geospatial analysis to fine-grained data must be urgently adopted for optimal decision making in real and near-real time. However, some aspects related to process and map sensitive health data in emergency cases have not yet been sufficiently explored. Among them include concerns about how these datasets with sensitive information must be shown depending on aspects related to data aggregation, scaling, privacy issues, or the need to know in advance the particularities of the study area. In this paper, we introduce our experience in mapping fine-grained data related to the incidence of the COVID-19 during the first wave in the region of Galicia (NW Spain), and after that we discuss the mentioned aspects.

BACKGROUND: In a robust health care system, at least 80% of a country's population should be able to access a district hospital that provides surgical care within 2 hours. The objective was to identify the proportion of the population living within 2 hours of a district hospital with surgical capacity in South Africa. METHODS: All government hospitals in the country were identified. Surgical district hospitals were defined as district hospitals with a surgical provider, a functional operating theatre, and the provision of at least one caesarean section annually. The proportion of the population within two-hour access was estimated using service area methods. RESULTS: Ninety-eight percent of the population had two-hour access to any government hospital in South Africa. One hundred and thirty-eight of 240 (58%) district hospitals had surgical capacity and 86% of the population had two-hour access to these facilities. CONCLUSION: Improving equitable surgical access is urgently needed in sub-Saharan Africa. This study demonstrated that in South Africa, just over half of district hospitals had surgical capacity but more than 80% of the population had two-hour access to these facilities. Strengthening district hospital surgical capacity is an international mandate and needed to improve access.

AbstractA major obstruction of Indian society to establish equality, balanced growth and development is regional and social group‐wise inequality in availing even basic human needs as well as housing conditions. The present study focuses on mapping the nationwide spatial disparity in the distribution and inequality of temporary housing among socially marginalized and privileged groups, along with three administrative hierarchies: National–State–District. Varieties of measures (Lorenz curve, Gini coefficient, correlation, and quadrant analysis) have been employed for this study. The results indicate inequality in the spatial distribution of serviceable and non‐serviceable temporary housing in India, along with a geospatial disparity in the ownership of temporary housing among different social groups. A number of districts in Orissa, Jharkhand, Bihar, West Bengal, Uttar Pradesh, Rajasthan, Jammu Kashmir, and Tamil Nadu have shown a higher proportion of temporary housing along with more ownership among socially marginalized groups. Besides this, districts from Bihar, Orissa, Arunachal Pradesh, Assam, Meghalaya, Nagaland, and Tripura have higher proportion of non‐serviceable temporary housing than the national average, along with more ownership among marginalized groups. The categorization of the states and districts based on social group‐wise inequality in the ownership and the concentration of temporary housing is significant for improving of the policies and initiatives taken by the Government to arrange safe, affordable, adequate, and sustainable housing for all.

The unprecedented COVID-19 pandemic is showing dramatic impact across the world. Public health authorities attempt to fight against the virus while maintaining economic activity. In the face of the uncertainty derived from the virus, all the countries have adopted non-pharmaceutical interventions for limiting the mobility and maintaining social distancing. In order to support these interventions, some health authorities and governments have opted for sharing very fine-grained data related with the impact of the virus in their territories. Geographical science is playing a major role in terms of understanding how the virus spreads across regions. Location of cases allows identifying the spatial patterns traced by the virus. Understanding these patterns makes controlling the virus spread feasible, minimizes its impact in vulnerable regions, anticipates potential outbreaks, or elaborates predictive risk maps. The application of geospatial analysis to fine-grained data must be urgently adopted for optimal decision making in real and near-real time. However, some aspects related to process and map sensitive health data in emergency cases have not yet been sufficiently explored. Among them include concerns about how these datasets with sensitive information must be shown depending on aspects related to data aggregation, scaling, privacy issues, or the need to know in advance the particularities of the study area. In this paper, we introduce our experience in mapping fine-grained data related to the incidence of the COVID-19 during the first wave in the region of Galicia (NW Spain), and after that we discuss the mentioned aspects.