Slope Degree Research Articles

Influence analysis of the different ash plane in the waveguide on the measurement of the carbon content of the fly ash by the microwave method

Microwave attenuation method has been one of the possible methods to measure the carbon content in fly ash online with high accuracy in recent years. However, the uncertainty of the shape of fly ash accumulation in waveguide brings many errors to the measurement of carbon content. To correct the errors, based on the study of ash level measurement, the influences of different inclined planes on the measurement of medium height and transmission attenuation are compared. Then, a model was established to quantify the influence of slope degree on carbon content of fly ash. Finally, the interference of different inclined planes on the measurement of carbon content in fly ash is analyzed. The result shows that with the increase of the inclination angle of the dielectric top slope in the waveguide, the transmission attenuation effect gradually increases. This will lead to the large measured value of carbon content in fly ash.

Impacts of Topographic Complexity on Modeling Moisture Transport and Precipitation over the Tibetan Plateau in Summer

The non-hydrostatic global variable resolution model (MPAS-atmosphere) is used to conduct the simulations for the South Asian Summer monsoon season (June, July, and August) in 2015 with a refinement over the Tibetan Plateau (TP) at the convection-permitting scale (4 km). Two experiments with different topographical datasets, complex (4-km) and smooth (60-km) topography, are designed to investigate the impacts of topographical complexity on moisture transport and precipitation. Compared with the observations and reanalysis data, the simulation can successfully capture the general features of key meteorological fields over the TP despite slightly underestimating the inflow through the southern TP. The results indicate that the complex topography can decrease the inward and outward moisture transport, ultimately increasing the total net moisture transport into the TP by ∼11%. The impacts of complex topography on precipitation are negligible over the TP, but the spatial distributions of precipitation over the Himalayas are significantly modulated. With the inclusion of complex topography, the sharper southern slopes of the Himalayas shift the lifted airflow and hence precipitation northward compared to the smooth topography. In addition, more small-scale valleys are resolved by the inclusion of complex topography, which serve as channels for moisture transport across the Himalayas, further favoring a northward shift of precipitation. Overall, the difference between the two experiments with different topography datasets is mainly attributed to their differing representation of the degree of the southern slopes of the Himalayas and the extent to which the valleys are resolved.

Searching for refuge: A framework for identifying site factors conferring resistance to climate‐driven vegetation change

AbstractAimClimate change is occurring at accelerated rates in high latitude regions such as Alaska, causing alterations in woody plant growth and associated ecosystem patterns and processes. Our aim is to assess the magnitude and speed that climate‐induced changes in woody plant distribution and volume may be reduced and/or slowed by relatively static landscape features like physical characteristics (e.g. depth to gravel, mineral cover percent and slope degree) and/or edaphic properties (e.g. soil organic matter, soil pH and site wetness rating) that resist climate‐vegetation responses.LocationWe leveraged a large field data set collected across a network of Alaskan national parks, which allows for comprehensive spatial data analysis over a uniquely large spatial extent.MethodsTo learn about the conditions that may either impede or accelerate vegetation changes in northern Alaska, we used a Bayesian hierarchical model to identify which landscape features may decelerate change or offer refuge for plant species. Our model quantifies the contribution of fast (‘dynamic’) versus slow (‘static’) changing variables to predict plant volume and categorize landscape types into either robust or nonrobust to climate changes.ResultsWe found that two landscape features, low soil wetness and low soil organic matter comprising 63.1% of sites in the data set, were the most likely landscape features to inhibit vegetation expansion. We also found that fewer numbers of sites have the potential to offer refuge to existing plant species (5.43% on average) because few sites had high soil wetness as a landscape feature.Main conclusionsOur analyses highlight the importance of incorporating static covariates representing landscape resistance to vegetation change for improving realism in forecasts of vegetation change in Alaska.

Utilising high-fidelity 3D building model for analysing the rooftop solar photovoltaic potential in urban areas

There are multiple approaches of estimating solar power generation by rooftop solar photovoltaic (PV) systems. Methods processed using GIS as well as 3D models provide the most reliable and accurate results. However, with the restriction of a limited detail 3D model area, estimations on a regional scale are hard to achieve. The regional power potential can be predicted by identifying the correlation of rooftop areas and the shadowing effect changing between the Level of Detail (LOD)1 and LOD2 models in the case study areas. This research considers the aspects and angles of the rooftops, to try and not only figure out the optimal PV installation conditions but also to make a general estimation for optimal angle, 2-axis solar tracking as well as total solar radiation received scenarios. The results of the research indicate that the optimal annual angle is 177° and 13° in aspect and slope degree, respectively, and the improvements of power generation under those three scenarios increase from about 2 to 16% in the test area, respectively. This research also showed that the power potential in partial small areas had the same tendency as the whole region even though each part of the small area had uneven city pattern. Additionally, different from most of the study, north-facing rooftops had been proved to have the strong potential to be developed as a solar power PV panel site and should not be neglected from the whole PV system.

Interaction of elevation and climate change on fire weather risk

Most wildfire studies are regional to global in scale; however, many of the values of interest and the weather are local phenomena that may give rise to large spatial variability in risk. We assessed the interaction of elevation and climate on fire weather for the Penticton Creek watershed in southwestern Canada for historic weather, and five climate change scenarios. Daily temperature and precipitation records spanning 100 years were generated using the LARS-WG5 weather generator and were used to calculate the fire weather indices of the Canadian Forest Fire Danger Rating System. Fire season length, restricted activity season, and fire season severity are all projected to increase by the 2050s and in some scenarios to increase further by the 2080s. Low and mid-elevations had substantially worsening risks, whereas at the highest elevations, risks were mitigated by the continuation of the snowpack. Increasing temperatures lengthened the fire season while decreasing (increasing) precipitation exacerbated (ameliorated) the intensity of the fire risk. These results indicate more variable climate change effects than in the literature. Over 24 million km2globally of forestland have a similar or higher degree of slope, highlighting the need for detailed topographic integration in fire studies to meet the needs of local planners.

Multi-hazard spatial modeling via ensembles of machine learning and meta-heuristic techniques

Considering the large number of natural disasters on the planet, many areas in the world are at risk of these hazards; therefore, providing an integrated map as a guide map for multiple natural hazards can be applied to save human lives and reduce financial losses. This study designed a multi-hazard map for three important hazards (earthquakes, floods, and landslides) to identify endangered areas in Kermanshah province located in western Iran using ensemble SWARA-ANFIS-PSO and SWARA-ANFIS-GWO models. In the first step, flood and landslide inventory maps were generated to identify at-risk areas. Then, the occurrence places for each hazard were divided into two groups for training susceptibility models (70%) and testing the models applied (30%). Factors affecting these hazards, including altitude, slope aspect, slope degree, plan curvature, distance to rivers, distance to roads, distance to the faults, rainfall, lithology, and land use, were used to generate susceptibility maps. The SWARA method was used to weigh the subclasses of the influencing factors in floods and landslides. In addition, a peak ground acceleration (PGA) map was generated to investigate earthquakes in the study area. In the next step, the ANFIS machine learning algorithm was used in combination with PSO and GWO meta-heuristic algorithms to train the data, and SWARA-ANFIS-PSO and SWARA-ANFIS-GWO susceptibility maps were separately generated for flood and landslide hazards. The predictive ability of the implemented models was validated using the receiver operating characteristics (ROC), root mean square error (RMSE), and mean square error (MSE) methods. The results showed that the SWARA-ANFIS-PSO ensemble model had the best performance in generating flood susceptibility maps with ROC = 0.936, RMS = 0.346, and MSE = 0.120. Furthermore, this model showed excellent results (ROC = 0.894, RMS = 0.410, and MSE = 0.168) for generating a landslide map. Finally, the best maps and PGA map were combined, and a multi-hazard map (MHM) was obtained for Kermanshah Province. This map can be used by managers and planners as a practical guide for sustainable development.

Risk Assessment of Riverine Terraces: The Case of the Chenyulan River Watershed in Nantou County, Taiwan

The purpose of this study is to establish a method of hazard assessment for the river terraces along the Chenyulan River and use 40 of them as protected objects. Using a geographic information system, the researchers extracted nine parameters for such terraces. These are length to attack shore, distance away from fault, distance from river channel, number of creeks and streams with possibility of debris flows, height above stream level, average slope degree, geology, number of erosion ditches, and distance from landslide area behind. Next, the weightings identified by analytic hierarchy process analysis were used as the basis for grading the various factors affecting river terraces. Hazard assessment for the river terraces then proceeded via totaling of the potential trends of the various factors and the protected objects, as well as comparison of historical disaster conditions and satellite images. The results showed that there were 8 high-risk river terraces, 14 medium–high-risk river terraces, 14 medium–low-risk river terraces and 4 low-risk river terraces. The evaluation of the current conditions of the settlement environment through parameter weighting has a certain accuracy and reference value in reducing the disaster impact of the riverine terrace settlement.

Evaluation of Shannon Entropy and Weights of Evidence Models in Landslide Susceptibility Mapping for the Pithoragarh District of Uttarakhand State, India

Landslide susceptibility mapping is considered a useful tool for planning, disaster management, and natural hazard mitigation of a region. Although there are different methods for predicting landslide susceptibility, the bivariate statistical analysis method is considered to be simple and popular. In this study, the main aim is to evaluate the performance of Shannon entropy (SE) and weights of evidence (WOE) statistical models in landslide susceptibility mapping of Pithoragarh district of Uttarakhand state, India. For this purpose, ten landslide affecting factors, namely, slope degree, aspect, curvature, elevation, land cover, slope forming materials, geomorphology (landforms), distance to rivers, distance to roads, and overburden depth were used for the development of landslide susceptibility maps using the SE and WOE methods. Data extracted from the Google Earth images, Aster Digital Elevation Model, and Geological Survey of India report were used for the construction and evaluation of landslide susceptibility models and maps. The landslide data of 91 locations were randomly divided into two parts in the ratio of 70 : 30 using GIS software that is 70% data was used for training the models and 30% data was used for testing and validating the models. Performance of the applied models was evaluated using area under the AUC (area under the curve) ROC (receiver operating characteristics) curve. Results indicated that the WOE model is having better accuracy (AUCWOE = 68.75%) than the SE model (AUCSE = 52.17%) in the development of landslide susceptibility maps. Hence, WOE model can be used for the development of accurate landslide susceptibility maps which can provide useful information to decision maker and policy planner in better development of landslide prone areas.

Stability Analysis of Loess High Slope under Dynamic Compaction Based on Matrix Discrete Element Method

In order to investigate the safety and stability of loess high slope under dynamic ramming, the MatDem software was used to simulate the process of heavy rammer compacting the spot which was 11 m away from the toe of loess high slope. The rammer was applied with different energies of 10000 kN·m, 8000 kN·m, and 6000 kN·m. In this way, the safety and stability of slope under the action of different dynamic tamping energies can be determined. The results show that the loess high slope presented circular landslide damage by dynamic compaction. Under the same ramming times, with the decrease of ramming energy, the damage degree of loess high slope gradually reduced. According to the displacement value of different monitoring points, the large horizontal and vertical displacement points in landslide were obtained. When the ramming energy was 10000 kN·m and 8000 kN·m, the maximum horizontal displacements were 15.45 m and 10.72 m, and the maximum vertical displacements were 17.43 m and 11.91 m. When the ramming energy was 6000 kN·m, the soil at the bottom of slope would produce slight vibration. Considering the actual project, when the ramming energy was 10000 kN·m and 8000 kN·m, the minimum safe distance was recommended to be 25 m and 20 m. When the ramming energy was 6000 KN·m, the slope remained stable as a whole, and the minimum safe distance suggested should not be less than 11 m. A safety distance of collapse of loess high slope under dynamic compaction was determined, which provided a strong safety guidance for loess high slope construction under dynamic compaction.

Landslide susceptibility zonation using analytical hierarchy process and GIS for the Nandakini River Valley, Central Himalaya

Nandakini River is a tributary of Ganga located in the central Himalayas of the Indian state of Uttarakhand. The area lies in the upper Ganga basin of the Himalayan rugged train. Landslide susceptibility mapping is of the foremost importance in an area like this one. It is required to alert the people. For the present study, eleven responsible causatives were considered namely drainage density, drainage, elevation, geology, geomorphology, groundwater depth, LULC, NDVI, rainfall, slope, and temperature. Analytical Hierarchy Process has been used to prioritize the factors. The degree of slope varies from 0 to 84. 54 where the high slope is in the northeastern and the low is in the northwestern part. Elevation varies from 827 meters to 6586 meters. Drainage density (0 to 4.67/sq.km), Rainfall (1224 to 1230 mm), Groundwater depth (41.79 to 42.29) etc. All the hydrological factors also accelerate landslide susceptibility. Rugged geomorphology with vulnerable geology helps the region to be landslide prone. The final landslide susceptible map indicates the area is highly vulnerable to landslides.

高寒地区煤矿排土场植被恢复研究--以内蒙古扎哈淖尔煤矿为例

PDF HTML阅读 XML下载 导出引用 引用提醒 高寒地区煤矿排土场植被恢复研究——以内蒙古扎哈淖尔煤矿为例 DOI: 10.5846/stxb202202090317 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: Plant rehabilitation at dump sites of open-pit mine in alpine region: A case study of Inner Mongolia Zhahanaoer Mine 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:高寒煤矿排土场植被恢复是制约我国矿区绿色可持续发展亟待解决问题，内蒙古扎哈淖尔煤矿通过不同的生态措施对排土场进行人工植被恢复的实践。在2020年和2021年对该高寒煤矿排土场75个样地进行野外连续监测，对不同生态恢复措施影响高寒地区内蒙古扎哈淖尔露天煤矿排土场植物恢复过程中的群落组成、盖度、物种多样性进行分析，阐明不同恢复措施在高寒地区煤矿排土场植被恢复中的作用。研究结果表明：从2020年到2021年排土场的植物群落物种数、植被盖度和群落多样性存在显著的季节变化规律；周边原生草原的非人工种植植物随恢复时间增加而不断进入排土场，导致群落物种数显著增加；植物群落多样性在平面、坡面与田字格地形存在显著差异，田字格上Shannon-Wiener多样性指数最低；坡度显著影响群落多样性，同时受到季节变化影响；喷播加灌木种植方式与其他4种播种方式相比显著增加群落香浓维纳多样性指数；但不同坡向、土壤施肥方式和水分灌溉方式对植物群落多样性没有显著影响。研究结果可为完善草原露天煤矿植被恢复技术提供科学依据。 Abstract:Plant rehabilitation at dump sites in alpine region is the critical issue for the sustainable development of open pit mine in China. Several artificial restoration measures were applied for plant rehabilitation in Inner Mongolia Zhahanaoer Mine. Field investigations and monitoring were continually carried out at 75 sample plots at dump site of open-pit mine of Zhahanaoer from 2021 to 2022. We analyzed plant community composition, plant cover and biodiversity. Results showed that there are significant seasonal and annual variation pattern for plant growth. The increasing plant species number with increasing restoration period may due to the coming non-planting plant species from around grassland. There are significant higher biodiversity in flat and slope topography than that of in "Tianzige". There was significant effect of slope degree on diversity, which varied with seasonal change. Plant biodiversity by spray seedling plus shrub method was significantly higher than those of other three methods. However, there were no significant differences of plant biodiversity in slope aspect, soil fertilization and irrigation treatments, respectively. Our results could contribute to the scientific evidences for plant rehabilitation of the dump sites of open pit mine in alpine region. 参考文献 相似文献 引证文献

Study on Deformation Evolution Characteristics of Reverse-Dip Rock Slope under the Influence of Rainfall

In Southwestern China, there exists deep river valleys and abundant rainfall, which leads to a large number of reverse-dip rock slopes. In order to investigate the evolution characteristics of toppling deformation of reverse-dip slope under the influence of rainfall, and a typical reverse-dip slope was taken as an engineering case. Firstly, the temporal and spatial evolution nephogram of toppling displacement under different rainfall was obtained based on the discrete surface displacement monitoring data of bank slope. Then, taking bank slope, gully buffer zone, and development degree of bank slope as development characteristics based on geological field survey, afterward, the evolution characteristics in different strong deformation zones were analyzed by superimposing the development characteristic partition and the spatial and temporal displacement nephogram. The results showed that the horizontal displacement mainly occurred on the right front and middle rear of the bank slope while large vertical displacement occurred on the middle of the bank slope under the influence of rainfall. As the rainfall increased to the maximum, the toppling deformation reached the peak, and vertical displacement was more sensitive to the rainfall than horizontal displacement. After the superposition, the largest strong deformation zone was located in the middle and rear part of the bank slope, which is characterized by medium and high slope and mature stage and 50 m gully buffer zone. This paper explores the deformation and failure process of reverse-dip rock slope considering the change of rainfall through real displacement monitoring data and focuses on the real deformation evolution law of each characteristic zone combined with different development characteristics partition.

Practical Applications of Sustainability Science in Landscape Planning Preliminary Stage of Bunaken-Tangkoko-Minahasa Biosphere Reserve

Sustainability Science (SS) is important in resource management, however not always well translated into actions. This research aims to find and implement practical applications of SS in the preliminary stage of landscape planning in Bunaken-Tangkoko-Minahasa Biosphere Reserve (BTMBR). The researchers put both perception and role of all local parties from the problem definition stage in landscape planning into account. The primary data was collected by using questionnaires. The secondary data includes literature review of SS in landscape planning, BTMBR’s characteristics, regulations and organizations. The researchers analyse landscape firstly by its 3-in-1-components namely space, environment, and human an later as unity. All parties consider watershed management as the entry point to sustainable and resilient landscape planning in this research case. The upstream part is perceived playing an important role, and because it is located in BTMBR core zone, this can be useful in future landscape management programs. The slope degree, which relates to watershed parts, is an important factor therefore landscape planning should consider different demand according to it. The Tondano Lake, as an important water element in BTMBR, do not have any conservation status. The researchers propose efforts to improve regulation and program including all local parties integration and involvement.

Predictive habitat suitability models to aid the conservation of elasmobranchs in Isla del Coco National Park (Costa Rica)

Worldwide there is increasing concern for elasmobranch species given that their biological and ecological characteristics make them highly vulnerable to fishing pressure. The disappearance of these species could affect the structure and function of marine ecosystems, which would induce changes in trophic interactions at the community level. For effective conservation and management of elasmobranchs detailed knowledge of their habitat preferences is essential. Yet, there is a poor understanding of their spatial ecology. Isla del Coco National Park is an oceanic island in Pacific Costa Rica and renowned for being a sanctuary for migratory pelagic species, such as elasmobranchs and other non-migratory species. However, the abundance of many of these species has been rapidly declining over the last decades as a result of overexploitation (legal and illegal fishing). Within this context, Generalized Additive Models were performed to investigate the environmental preferences of eight elasmobranch species in Isla del Coco National Park using six predictors (i.e., sea surface temperature, salinity, chlorophyll-a concentration, bathymetry, distance from the coast and slope). Results demonstrate similar habitat preferences based on distance from the coast, slope and chlorophyll, which indicates that elasmobranchs prefer shallow waters near the island with varying degrees of slope. This study helps to identify both some of the hotspots for elasmobranchs biodiversity in Isla del Coco National Park. This approach provides an essential and relatively easy tool, such as predictive distribution maps, to increase our knowledge of marine habitats in Isla del Coco to better manage them and other offshore marine protected areas.

Effect of Tibial Slope on Coronal Alignment in Total Knee Arthroplasty.

Malalignment of total knee arthroplasty (TKA) components affects function and survivorship. Common practice is to set coronal alignment prior to adjusting slope. With improper jig placement, adjustment of the slope may alter coronal alignment. The purpose of this study was to quantify the change in coronal alignment with increasing posterior tibial slope while comparing two methods of jig fixation. A prospective consecutive series of 100 patients underwent TKA using computer navigation. Fifty patients had the extramedullary cutting jig secured proximally with one pin and 50 patients had the jig secured proximally with two pins. Coronal alignment (CA) was recorded with each increasing degree of posterior slope (PS) from 0 to 7 degrees. Mean CA and change in CA were compared between cohorts. Utilizing one pin, osteotomies drifted into varus with an average change in CA of 0.34 degrees per degree PS. At 4 degrees PS, patients started to have >3 degrees of varus with 12.0% having >3 degrees of varus at 7 degrees PS. Utilizing two pins, osteotomies drifted into valgus with an average change of 0.04 degrees in CA per degree PS. No patients in the two-pin cohort fell outside 3 degrees varus/valgus CA. CA was significantly different at all degrees of PS between the cohorts. Changes in PS influenced CA making verification of tibial cut intraoperative critical. Use of >1 pin and computer navigation were beneficial to prevent coronal plane malalignment. This relationship may explain why computer navigation has been shown to improve alignment as well as survivorship and outcomes in some patients, especially those <65 years.

Assessment of landslide risk in the mountainous area. Case study: Bumiaji Sub-District

Throughout 2016-2021, there were 31 landslides that have caused physical, economic, and social damages. Bumiaji Sub-District has several tourist destinations that are potentially exposed to landslides. This study aims to create a landslide risk map in Bumiaji Sub-District. This research was conducted during the COVID-19 pandemic situation. Therefore, the data collected was secondary data obtained from Google satellite images, Google Street View, the digital elevation model from the National Geospatial Institution, and other literature reviews. The data was then analysed using a landslide risk assessment based on Perka BNPB Number 2/2012. The results of this risk analysis show that Bumiaji Sub-District is dominated by low-level risk (48%), followed by high-level risk (30%), and medium-level risk (15%). High-risk level is affected by high hazards and vulnerabilities, especially in Giripurno Village. High hazard level is affected by high intensity of rainfall, slope degree, the sensitivity of soil to erosion, and the type of land cover. High vulnerabilities are affected by physical, social, and economic aspects susceptible to losses.

A modified model for predicting nutrient loss in runoff using a time-varying mixing layer

Nutrient loss caused by runoff reduces the fertility of cultivated land and pollutes the environment. Accurate prediction of such nutrient loss can inform prevention and control measures to reduce agricultural nonpoint source pollution and promote sustainable agriculture, particularly in vulnerable habitats such as the Loess Plateau, China, and for high-quality development projects such as those in the Yellow River Basin, China. In this study, a time-varying mixing layer was established to improve the nutrient transfer models already in use. 36 sets of empirical data on nutrient loss (K+, PO43−-P, NO3−-N) were compiled for the parameters α, β, and km. Another 45 sets of empirical data were used to evaluate the accuracy of the modified model. The modified and previous models were compared, and the modified model (coefficient of determination > 0.81, root mean square error < 1.27, Nash–Sutcliffe efficiency coefficient > 0.77) was the most accurate. The Markov chain Monte Carlo method was used to estimate the parameters (α, β, km) under conditions of varying rainfall intensity (p), soil initial moisture content (θ0), and slope degree (s), and as a result the mean value of parameter β (0.105) is recommended for the model. The modified model successfully simulated the processes of nutrient loss, with the greatest sensitivity for α, followed by km and β. This model can be used to improve the theoretical basis for developing runoff and erosion control methods.

AN ANALYSIS ON THE EFFICIENCY OF GREEN ROOF IN MANAGING URBAN STORMWATER RUNOFF

Modernization has created new impervious urban landscape contributed to major catastrophe. Urban drainage system incapable to convey the excess rainwater resulting in flash flood due to heavy rainfall. The combination of green roof on building have tremendously proved to control stormwater efficiently. This study is conducted to review the efficiency of intensive and extensive green roof in reducing urban storm water runoff. This study identifies characteristic of green roof that contributes to lessening urban storm water runoff. Data was collected based on rigorous literature reviews and analyzed using meta-analysis. Overall, findings revealed intensive green roof performed better in reducing storm water runoff compared to extensive green roof. Green roof performance increases as the depth of substrate increased. Origanum and Sedum plants are both highly effective for intensive and extensive green roofs. The performance of green roof reduces as degree of roof slope increased.

Computer model for tsunami vulnerability using sentinel 2A and SRTM images optimized by machine learning

This study aims to develop a software framework for modeling of tsunami vulnerability using DEM and Sentinel 2 images. The stages of study, are: 1) extraction Sentinel 2 images using algorithms NDVI, NDBI, NDWI, MSAVI, and MNDWI; 2) prediction vegetation indices using machine learning algorithms. 3) accuracy testing using the MSE, ME, RMSE, MAE, MPE, and MAPE; 4) spatial prediction using Kriging function and 5) modeling tsunami vulnerability indicators. The results show that in 2021 the area was dominated by vegetation density between (-0.1-0.3) with moderate to high vulnerability and risk of land use tsunami as a result of the decreasing of vegetation. The prediction results for 2021 show a low canopy density of vegetation and a high degree of land surface slope. Based on the prediction results in 2021, the study area mostly shows the existence of built-up lands with a high tsunami vulnerability risk (more than 0.1). Vegetation population had decreased to 67% from the original areas in 2017 with an area of 135 km2. Forest vegetation had decreased by 45% from 116 km2 in 2017. Land use for fisheries had increased to the area of 86 km2 from 2017 with an area of 24 km2.

No Difference in Neck Pain or Health-Related Quality Measures Between Patients With or Without Degenerative Cervical Spondylolisthesis.

This study is a retrospective case control. This study aims to determine whether cervical degenerative spondylolisthesis (DS) is associated with increased baseline neck/arm pain and inferior health quality states compared to a similar population without DS. Patient demographics, pre-operative radiographs, and baseline PROMs were reviewed for 315 patients undergoing anterior cervical decompression and fusion (ACDF) with at least 1 year of follow-up. Patients were categorized based on the presence (S) or absence of a spondylolisthesis (NS). Statistically significant variables were further explored using multiple linear regression analysis. 49/242 (20%) patients were diagnosed with DS, most commonly at the C4-5 level (27/49). The S group was significantly older than the NS group (58.0 ± 10.7 vs 51.9 ± 9.81, P = .001), but otherwise, no demographic differences were identified. Although a higher degree of C2 slope was found among the S cohort (22.5 ± 8.63 vs 19.8 ± 7.78, P = .044), no differences were identified in terms of preoperative visual analogue scale (VAS) neck pain or NDI. In the univariate analysis, the NS group had significantly increased VAS arm pain relative to the S group (4.93 ± 3.16 vs 3.86 ± 3.30, P = .045), which was no longer significant in the multivariate analysis. Although previous reports have suggested an association between cervical DS and neck pain, we could not associate the presence of DS with increased baseline neck or arm pain. Instead, DS appears to be a relatively frequent (20% in this series) age-related condition reflecting radiographic, rather than necessarily clinical, disease.