Developing Landslide Hazard Scenario of Kashmir Himalaya from the Historical Events

Kashmir Himalaya being a rugged and tectonically active zone has complex, unstable geology along with steep slopes, creating a favorable environment for landslide hazards, especially along the National Highway (NH-44) that connects the Vale of Kashmir with the rest of India. The historical landslide database for the whole country has not yet been developed and the data provided by various government organizations are often very limited because most of the time local and small-scale landslide events do not get recorded, thus, leading to misinterpretations. The present study focuses on retrieving the information on landslide events and their impacts to develop a comprehensive database for the period from 1990 to 2020 in Jammu and Kashmir, emphasizing Jammu-Srinagar National Highway (NH-44). A hotspot analysis tool (Getis-ord-Gi* algorithm) was used to understand the spatial distribution and concentration of the events throughout the region. The annual and seasonal analysis of the 739 landslide events reported in the valley for the selected period suggests an increasing trend causing 1000 fatalities and 267 injuries. The findings show that out of 20 districts, 16 are relatively more exposed to landslides and the socio-impact induced by landslides was found more along the NH-44 with 303 landslide occurrences reported in 260 days in the past three decades having a high intensity of damage and loss. The results of this study are expected to be of potential use for developing a Landslide Early Warning System (LEWS) and for mitigating the impacts of landslides in the Kashmir Himalaya.

Protection Effect and Vacancy of the Ecological Protection Redline: A Case Study in Guangdong–Hong Kong–Macao Greater Bay Area, China

The Ecological Protection Redline (EPR) is an innovative measure implemented in China to maintain the structural stability and functional security of the ecosystem. By prohibiting large-scale urban and industrial construction activities, EPR is regarded as the “lifeline” to ensure national ecological security. It is of great practical significance to scientifically evaluate the protection effect of EPR and identify the protection vacancies. However, current research has focused only on the protection effects of the EPR on ecosystem services (ESs), and the protection effect of the EPR on ecological connectivity remains poorly understood. Based on an evaluation of ES importance, the circuit model, and hotspot analysis, this paper identified the ecological security pattern in Guangdong–Hong Kong–Macao Greater Bay Area (GBA), analyzed the role of EPR in maintaining ES and ecological connectivity, and identified protection gaps. The results were as follows: (1) The ecological sources were mainly distributed in mountainous areas of the GBA. The ecological sources and ecological corridors constitute a circular ecological shelter surrounding the urban agglomeration of the GBA. (2) The EPR effectively protected water conservation, soil conservation, and biodiversity maintenance services, but the protection efficiency of carbon sequestration service and ecological connectivity were low. In particularly, EPR failed to continuously protect regional large-scale ecological corridors and some important stepping stones. (3) The protection gaps of carbon sequestration service and ecological connectivity in the study area reached 1099.80 km2 and 2175.77 km2, respectively, mainly distributed in Qingyuan, Yunfu, and Huizhou. In future EPR adjustments, important areas for carbon sequestration service and ecological connectivity maintenance should be included. This study provides a comprehensive understanding of the protection effects of EPR on ecological structure and function, and it has produced significant insights into improvements of the EPR policy. In addition, this paper proposes that the scope of resistance surface should be extended, which would improve the rationality of the ecological corridor simulation.

Integrating Quantity and Quality to Assess Urban Green Space Improvement in the Compact City

Urban green space (UGS) has gained much attention in terms of urban ecosystems and human health. Measures to improve green space in compact cities are important for urban sustainability. However, there is a knowledge gap between UGS improvement and planning management. Based on the integration of quantity and quality, this research aims to identify UGS changes during urban development and suggest ways to improve green space. We analyse land use changes, conduct a hotspot analysis of land surface temperature (LST) between 2005 and 2015 at the city scale, and examine the changes in small, medium and large patches at the neighbourhood scale to guide decision-makers in UGS management. The results show that (i) the redevelopment of urban brownfields is an effective method for increasing quantity, with differences depending on regional functions; (ii) small, medium and large patches of green space have significance in terms of improving the quality of temperature mitigation, with apparent coldspot clustering from 2005 to 2015; and (iii) the integration of UGS quality and quantity in planning management is beneficial to green space sustainability. Green space improvement needs to emphasize the integration of UGS quantity and quality to accommodate targeted planning for local conditions.

Surveillance of COVID-19 Using Geospatial Data: An Emergency Department Perspective

<b><i>Background:</i></b> The outbreak of coronavirus 2019 (COVID-19) which emerged in December 2019 spread rapidly and created a public health emergency. Geospatial records of case data are needed in real time to monitor and anticipate the spread of infection. <b><i>Methods:</i></b> This study aimed to identify the emerging hotspots of COVID-19 using a geographic information system (GIS)-based approach. Data of laboratory-confirmed COVID-19 patients from March 15 to June 12, 2020, who visited the emergency department of a tertiary specialized academic hospital in Dubai were evaluated using ArcGIS Pro 2.5. Spatiotemporal analysis, including optimized hotspot analysis, was performed at the community level. <b><i>Results:</i></b> The cases were spatially concentrated mostly over the inner city of Dubai. Moreover, the optimized hotspot analysis showed statistically significant hotspots (<i>p</i> &#x3c; 0.01) in the north of Dubai. Waxing and waning hotspots were also observed in the southern and central regions of Dubai. Finally, there were nonsustaining hotspots in communities with a very low population density. <b><i>Conclusion:</i></b> This study identified hotspots of COVID-19 using geospatial analysis. It is simple and can be easily reproduced to identify disease outbreaks. In the future, more attention is needed in creating a wider geodatabase and identifying hotspots with more intense transmission intensity.

Spatial Characteristics and Regional Transmission Analysis of PM2.5 Pollution in Northeast China, 2016–2020

Northeast China is an essential industrial development base in China and the regional air quality is severely affected by PM2.5 pollution. In this paper, spatial autocorrelation, trajectory clustering, hotspot analysis, PSCF and CWT analysis are used to explore the spatial pollution characteristics of PM2.5 and determine the atmospheric regional transmission pattern for 40 cities in Northeast China from 2016 to 2020. Analysis of PM2.5 concentration characteristics in the northeast indicates that the annual average value and total exceedance days of PM2.5 concentration in Northeast China showed a U-shaped change, with the lowest annual average PM2.5 concentration (31 μg/m3) in 2018, decreasing by 12.1% year-on-year, and the hourly PM2.5 concentration exploding during the epidemic lockdown period in 2020. A stable PM2.5 pollution band emerges spatially from the southwest to Northeast China. Spatially, the PM2.5 in Northeast China has a high degree of autocorrelation and a south-hot–north-cool characteristic, with all hotspots concentrated in the most polluted Liaoning province, which exhibits the H–H cluster pattern and hotspot per year. Analysis of the air mass trajectories, potential source contributions and concentration weight trajectories in Northeast China indicates that more than 74% of the air mass trajectories were transmitted to each other between the three heavily polluted cities, with the highest mean value of PM2.5 pollution trajectories reaching 222.4 μg/m3, and the contribution of daily average PM2.5 concentrations exceeding 60 μg/m3 within Northeast China. Pollution of PM2.5 throughout the Northeast is mainly influenced by short-range intra-regional transport, with long-range transport between regions also being an essential factor; organized integration is the only fundamental solution to air pollution.