Interpolation Parameters in Inverse Distance-Weighted Interpolation Algorithm on DEM Interpolation Error

Although DEM occupies an important basic position in spatial analysis, so far, the quality of DEM modeling has still not reached a satisfactory accuracy. This research mainly discusses the influence of interpolation parameters in the inverse distance-weighted interpolation algorithm on the DEM interpolation error. The interpolation parameters to be studied in this paper are the number of search points, the search direction, and the smoothness factor. In order to study the optimization of IDW parameters, the parameters that have uncertain effects on DEM interpolation are found through analysis, such as the number of search points and smoothing factor. This paper designs an experiment for the optimization of the interpolation parameters of the polyhedral function and finds the optimal interpolation parameters through experimental analysis. Of course, the “optimum” here is not the only one, but refers to different terrain areas, which makes the interpolation results relatively good. The selection of search points will be one of the research focuses of this article. After determining the interpolation algorithm, the kernel function is also one of the important factors that affect the accuracy of DEM. The value of the smoothing factor in the kernel function has always been the focus of DEM interpolation research. Different terrains, different interpolations, and functions will have different optimal smoothing factors. The search direction is to ensure that the sampling points are distributed in all directions when the sampling points are sparse and to improve the contribution rate of the sampling points to the interpolation points. The selection of search shape is to improve computing efficiency and has no effect on DEM accuracy; the search radius is mainly controlled by the number of search points, and there are two methods: adaptive search radius and variable length search radius. When the weight coefficient k = 1 , 2 , 3 , 4 , the number of sampling points involved in the interpolation calculation is different, and the error in the residual varies greatly, and both increase with the increase of the number of sampling points in the parameter interpolation calculation. This research will help improve the quality evaluation of DEM.

Spatiotemporal Trends and Detection of Changes in Hydrological and Climatic Variables of Modjo River Watershed, Ethiopia

Understanding hydro-climatic trends in space and time is crucial for water resource planning and management, agricultural productivity and climate change mitigation of a region. This study examined the spatiotemporal variations in precipitation, reference evapotranspiration (ETo) and streamflow in a tropical watershed located in the central highlands of Ethiopia. Temporal trend implications were analyzed using the Mann-Kendall test, and Theil-Sen approach, whereas the inverse distance weighted interpolation method was applied for spatial trend variability analysis. The result showed that a significant decreasing trends in streamflow for the major rainy (Kiremt: Jun - Sept) season and annual time scales. At the same time, the annual and monthly ETo followed significantly increasing trends, but there has been a trendless time series for most of the months and annual mean precipitation series for the period 1986 - 2015. The study indicated that the spatial variability of annual and seasonal precipitation series decreased from north to south and west to east, while this was increased for ETo both for annual and seasonal time series over the study watershed. The contribution of rainfall and mean temperature to streamflow decline was insignificant. It is pointed out that river flow regime is weakly affected by climate changes, hence human activities are stronger in explaining the river flow trends of the watershed. Therefore, urgent calls on the needs for reducing human-induced impacts, and implementing appropriate watershed management, conservation measures and an efficient use of water resources.

The Visibility of Sound: Acoustic Archaeology in the Blue Ridge Mountains

Waterfalls are documented among Indigenous peoples as settings for the intergenerational transfer of knowledge and locations sacred to life transitions. Eastern Woodlands ethnographic literature identifies waterfalls as places where life emerges in the presence of danger, requiring the acknowledgement of those who travel near them. In the Virginia Blue Ridge Mountains, ceramic-bearing Middle and Late Woodland sites near named waterfalls are associated with small sites located outside the topographic parameters of modeled site locations and containing non-local or unique objects. Sound mapping with calibrated decibel meters, survey-grade GPS, and inverse distance weighted interpolation demonstrate a correspondence between the location of the small sites and natural sound magnification. The small sites and the deposited objects may represent the offerings of travelers made aware of the sacred/dangerous place by the sound of the waterfall. Acoustic archaeology is introduced as a practice that takes into consideration sensory experience as central to place identity.

Assessment of the Impact of a Motorway on Content andSpatial Distribution of Mercury in Adjacent Agricultural Soils

The distribution of Hg in the vicinity of roads is probably not exclusively dependent on car emissions, but also on the presence of other point or diffuse sources of Hg emissions located from metres to several km away. The source of mercury in urbanised areas is pollution derived from the burning of fuels and industrial and transport waste, while in agricultural areas, it is constituent in mineral fertilisers and crop protection products. The research objective was to evaluate the content and spatial distribution of mercury in arable soils adjacent to the A1 motorway in Poland. The research material consisted of 40 soil samples taken from 20 test points on four transects at distances of 5, 10, 25 and 50 m from a noise barrier and in the direction of an arable field, and 10 m from the noise barrier in the direction of the motorway. Total mercury content was determined by atomic absorption spectrometry using an AMA 254 analyser. The spatial relationship between adjacent observations of variables was assessed using Moran’s I overall autocorrelation coefficient. Probability maps of mercury distribution in the field and pollution indicators were elaborated in ArcGIS 10.4.1. using Inverse Distance Weighted interpolation. Analysis of the spatial correlation of Moran’s I showed a lack of spatial dependence between tested points, which may evidence that the motorway does not affect mercury contents in the soil. The elevated mercury content at a single test point may indicate a random event unrelated to the motorway’s operation.

Modelling of Evenness of Runways as an Element of Sustainable Airport Maintenance

The elevation of airport runways is specified in the operations manuals and in globally accepted design guidelines. Airport runways are constantly exposed to various physical and weather factors. However, these factors can deteriorate the condition of the runway to the point where it becomes unusable. Monitoring and the continuous inspection of runway evenness is an important element of a sustainable airport maintenance system. An important element of a sustainable airport maintenance system is a runway evenness detection and modelling system. The investigation of the use of various available methods for modelling runway evenness was conducted based on measurements of the actual condition of the existing runway at Edvard Rusjan Airport in Maribor, Slovenia. During the measurements of the runway condition, our own measurement equipment was used, which ensures the geodetic accuracy of the measurements. The novelty of the article is a comparison between five different approaches to modelling runway evenness: approximation with regression plane, inverse distance weighted interpolation (IWD) with a weighting factor of 1, 2, and 10, and interpolation based on a triangulated irregular network (TIN)–linear and cubic. In the methodology section, the advantages and disadvantages of the mentioned methods were described. The selected models were evaluated by required processor time, by the file size resulting from the modelling, and by the values of the descriptive statistics of the model deviation at the average uniform slope. It was found that the modelling method using linear triangular irregular network interpolation provided the most useful results. The results of the conducted analysis can be easily used in any runway management models at airport thet allow for professionally based actions aimed at ensuring the safety and efficiency of runway operations, especially at smaller, regional airports.

Estimates of the COVID-19 Infection Fatality Rate for 48 African Countries: A Model-Based Analysis

(1) Background: Examine global data from 48 African countries to estimate the SARS-CoV-2 infection fatality rate; (2) Methods: We analyzed time series data on the 135,126 confirmed cases and 3922 deaths from COVID-19 disease outbreak in Africa through 30 May 2020. In a Bayesian prediction model based on the Monte Carlo approach, we adjusted for demographic, economic, biological, and societal variables to account for the untested people; (3) Results: We calculated a total of 1,686,879 COVID-19 infections after correcting for possible risk variables in the Bayesian model, equal to 13 infections per confirmed case. In Africa, the IFR is projected to be 0.23% (95% CI: 0.14–0.33%). The percentages varied by country, ranging from 0.004% in Botswana and the Central African Republic to 1.53% in Nigeria. The projected IFR is twelvefold greater than the WHO’s 2009 H1N1 influenza pandemic estimate (0.02%). In four countries: Morocco, Nigeria, Cameroon, and South Africa, the inverse distance weighted interpolation map shows high IFR variability; (4) Conclusions: COVID-19 infection mortality rates can vary significantly between regions, and this might be due to changes in demography, underlying health conditions in the community, healthcare system capacity, positive health seeking behavior, and other variables.