جستجوی مقالات مرتبط با کلیدواژه « spatial analysis » در نشریات گروه « آب و خاک »

Introduction Landslide occurrence is caused by severe ground movement and fault fractures that lead to structural damage, road blockage, human death, and significant damage to other features. Landslide is one of the most destructive natural phenomena that can cause great damage to property and human loss. One of the basic measures to reduce potential damage is to identify landslide-prone areas. Due to the location of most cities in the mountainous and foothill areas and the topographic, geological, and geomorphological features, the natural conditions are vulnerable to a wide range of landslides. Tehran, as the largest city in Iran, has almost 12% of the total population of the country and is partly located in the foothills and mountainous areas. Tehran, has many important infrastructures, including crowded roads, and a large population, therefore, determining areas prone to future landslides is an important management issue. Also, debris flow is one of the main factors that cause serious damage to properties. Thus quantitative assessment and management are required to reduce the possible damages. In addition, technologies are needed to assess disaster prevention facilities and structures in disaster-prone areas. Therefore, using combined methods for landslide susceptibility areas can be very effective in managing the risk of reducing casualties.Materials and MethodsIn this study, the effective factors on landslide occurrence such as rainfall, earthquake, vegetation, land use, geology, river, fault, slope and aspect, and roads are employed using an integrated approach. Then, spatial analysis was performed in ArcGIS using Euclidean distance and Curvature functions. The Haraz and Lavasanat roads were selected as a case study, and each of the criteria was examined and classified using the Euclidean distance method and inverse distance weighted (IDW) technique.Results and Discussion The results showed that the areas facing northeast and southwest parts were ranked 1st and the rest of the area was ranked 0. The areas with slope values higher than 50%, had a higher risk of landslide. The curvature of the selected main and secondary roads was located in convex hillslopes indicating the areas at a high-risk level. These Haraz and Lavasan roads are at risk of slipping during rain, earthquakes, and other hazards. According to the area obtained from the regional statistical properties.Conclusion The mountainous roads of Tehran are vulnerable to landslide and debris flows due to the geographical location, and the existence of faults. The excessive interference in the nature and increase of additional load on the slopes and excessive influence on agricultural and road use are important reasons for instability in the slope and increasing the debris flow in these land uses. The controlling of landslide and debris flow phenomena depends on a comprehensive management plan. Factors such as population growth, land-use change, and climate change are intensifying the landslide and debris flow occurrence. Since rainfall is one of the accelerating the occurrence of natural disasters, the existence of a management system such as an early warning to the endangered population is necessary.

Understanding the ecological and geomorphological processes of the spatial distribution of loess deposits helps us to find their interactions in the arid and semi-arid regions. The Iranian loess plateau with a unique landscape and complex topography also located in steppe vegetation with semi-arid climate. The aims of present study are point pattern analysis of hillside, stream, and their interactions using different summary statistics in the particular part of Iranian loess plateau. As there is a small distance between hillslope and complex topography in the study area, unmanned aerial vehicle (UAV) imagery used to prepare precise colored aerial photos for statistical analyses. Further, regarding to the mentioned purposes, this research has enough novelty compare with previous studies, and thus, it is a new step in studying the spatial pattern of loess facies; In other words, this study attempts to find the effective relationship between the hillside and streams in terms of the expansion of channel erosion in the study region.

The study area has dry Xeric soil moisture and Thermic soil temperature regimes. The UAV technique used to prepare the precise colorful images with highly spatial/temporal resolution to model the spatial patterns of hillside and streams density. The topographic attributes (primary and secondary) obtained from digital elevation model (DEM) applied with a spatial resolution of 20×20 cm. The univariate and bivariate point analyses (modelling) used for variable analyses in Spatstat package in R and Progammita software. Finally, Mark correlation function (MCF) used to investigate the question of reducing the size of density dependent.

The results of univariate g(r) and O-ring (r) showed that different hillside facing i.e. flat, north, south, east, and west have the aggregated pattern in all distances in the study area. These implied that the same directions are distributed more closely next to each other and their arrangements follow the special pattern. In addition, the interaction between streams and north-face using the bivariate g12(r) and O12(r) confirmed the positive interaction between streams and north-face in all distances in the study area. The MCF analysis also showed that the slope as the effective factor has positive interaction with streams, and steep slopes are more aggregated compare with the low slopes. This indicates which the steeper slopes are more likely to form streams than flat lands.

Generally, the streams probability form in the steep slopes more than flat areas due to their shear energy, which leads to more soil losses. Further, the soil loss on the steep slopes is more than flat terrain. Finally, UAV technologies are recommended in the study of spatial pattern of deposits for detailed observations, highly accurate data, and deciding natural resource managers to reduce soil erosion.

Accurate planning for adaptation to climate change is very important in each region. In this study, using the meteorological data of the six synoptic stations in the Ghezel Ozan basin in the period 1989-2016, and by employing the four GCM models, under the two scenarios RCP4.5 and RCP8.5, data were generated for the horizons 2050. Then, some parameters such as the air temperature, precipitation, potential evapotranspiration (ET0), precipitation deficit (PD) during the growing season, dryness intensity were calculated. ET0 was calculated by Pristeley-Taylor (PT) and Penman-Monteith (PM) methods. Then, ET0 obtained from the PT method was calibrated using four Artificial Intelligence methods (namely Eureqa Formulize, ANN, ANFIS and SVM) with PM method for each station. For spatial analysis, three geostatistical methods namely IDW, Kriging, and Cokriging were utilized. The results indicated an increase of 0.9 - 2 ºC in mean air temperature and an increase in precipitation between 27 and 49 mm will be experienced in the future period. Furthermore, ET0 and dryness intensity will be increased at all the stations. The increase in average PD (in the whole basin) will be about 6% to 9%. In average, the rate of increase in agroclimatic indices in the RCP8.5 scenario will be about four percent more than the RCP4.5 scenario. Among the methods of interpolation, the modified Cokriging based on DEM (Digital Elevation Model) showed the more suitable one among others. The length of the growing season will be elongated from 15 to 35 days. No significant changes will be occurred for dryness period. The spatial variation of future climate variables is expected to be not changed comparing the base period.