A new approach to minimize the loss of life after natural hazards by using Android operating system

Nowadays, the usage rates of smartphones are increasing rapidly. With the versatility of its features, smartphones have succeeded in attracting users. Performing this study has also affected the usage rate of smartphones every day. It is possible to determine the position with GPS (Global Positioning System) technology which is located in smartphones. In this study, smartphone location notification was used to detect the locations of the people who were under debris after the earthquake by means of the phones on them. People who cannot be reached for any reason will be immediately identified, and emergency interventions will be possible. Thus, the survival rate of the injured will be high with early intervention. In this study, it was aimed to minimize the loss of life after the earthquake and all the negativities that would be experienced in society due to this loss. The developed application has been tested in the external world, and the obtained data are given in results section.

     

Effects of reverse geocoding on OpenStreetMap tag quality assessment

OpenStreetMap (OSM), a widely-used open-source geographic information system platform, provides a vast geographic dataset in which users contribute both geometric information (nodes, ways, and relations) and semantic information (tags). This method of voluntary contributions is governed by the collective effort of the users. It is widely acknowledged that the quantity of tag information is substantial, but its quality is often poor. Researchers are therefore trying to assess the quality of the tags and enhance the data through various integration experiments. This article investigates the validity of the tags for geographical objects in metropolitan areas using municipal data and a reverse geocoding technique. The proposed method evaluates the data quality and the matching process carried out by reverse geocoding, using municipal points of interest as a reference. The accuracy of the tag and address information and road network centrality metrics were assessed for the OSM objects that were matched to the locations of interest. The tags were found to match the points of interest with an accuracy of 88%. Furthermore, the tag values were categorized and analyzed based on their similarity. It is concluded that in metropolitan settings where centers of interest are closely located, the accuracy of tags and addresses tends to decrease.     

A physically constrained wavelet-aided statistical model for multi-decadal groundwater dynamics predictions

A physically constrained wavelet-aided statistical model (PCWASM) is presented to analyse and predict monthly groundwater dynamics on multi-decadal or longer time scales. The approach retains the simplicity of regression modelling but is constrained by temporal scales of processes responsible for groundwater level variation, including aquifer recharge and pumping. The methodology integrates statistical correlations enhanced with wavelet analysis into established principles of groundwater hydraulics including convolution, superposition and the Cooper–Jacob solution. The systematic approach includes (1) identification of hydrologic trends and correlations using cross-correlation and multi-time scale wavelet analyses; (2) integrating temperature-based evapotranspiration and groundwater pumping stresses and (3) assessing model prediction performances using fixed-block k-fold cross-validation and split calibration-validation methods. The approach is applied at three hydrogeologicaly distinct sites in North Florida in the United States using over 40 years of monthly groundwater levels. The systematic approach identifies two patterns of cross-correlations between groundwater levels and historical rainfall, indicating low-frequency variabilities are critical for long-term predictions. The models performed well for predicting monthly groundwater levels from 7 to 22 years with less than 2.1 ft (0.7 m) errors. Further evaluation by the moving-block bootstrap regression indicates the PCWASM can be a reliable tool for long-term groundwater level predictions. This study provides a parsimonious approach to predict multi-decadal groundwater dynamics with the ability to discern impacts of pumping and climate change on aquifer levels. The PCWASM is computationally efficient and can be implemented using publicly available datasets. Thus, it should provide a versatile tool for managers and researchers for predicting multi-decadal monthly groundwater levels under changing climatic and pumping impacts over a long time period.     

Climate change in Turkey for the last half century

Climate change and its urban-induced bias in selected Turkish cities is studied with a quality controlled temperature and precipitation data of Turkish stations in the period of 1950–2004. These stations are classified into two groups according to their populations; S1, including rural and suburban stations and S2, including large urban stations. Moving average signals, 365-day, and their digital low pass filtered versions are produced to eliminate the short term fluctuations and examine the possible trends or anomalies in climate data. Furthermore, ‘relative difference’ signals are introduced and applied to temperature and precipitation series to observe the actual local changes in the climate data independent from large-scale effects. Mann–Kendall test statistics are calculated for maximum, minimum, mean temperature and precipitation series and plotted on maps to determine any spatial trend patterns. Signal analysis show a cool period extending from early 1960s till 1993, generally with the lowest temperature values on 1992–1993 owing to the eruption of Mount Pinatubo. A last decade significant warming trend is observed in both of the series, S1 and S2, leading to 2000–2002 temperatures to be recorded as maximums in record history. The variability of urban precipitation series is generally larger than the rural ones, suggesting that urban stations can experience more frequent and severe droughts and floods. Though not significant, an increase in the urban precipitation compared to the rural one is also found. Spatial analysis resulted in significant warming in southern and southeastern parts of the country. Particularly, minimum temperature series show significant warming in almost all of the regions indicating the effect of urbanization. Significant decreases of precipitation amounts in the western parts of Turkey, such as Aegean and Trachea regions, are found. On the other hand, some Turkish northern stations show increases in precipitation of which some are significant.