Explore the vast range of titles available.

The topographic slope method is an innovative, fast and very low-cost technique for estimating the average S-wave velocity in the upper 30 m (Vs30) based on the relationship between this quantity and the slope of the ground, obtained using a Digital Elevation Model (DEM). The method is based on the good linear correlations log(Vs30)–log(slope) found experimentally, which, ideally, should be determined for each region. If measured Vs30 data are not available to carry out this fitting for the study area, correlations from other areas could be used, although the reliability of the estimated Vs30 results would be lower. In this article, Vs30 observations are made for the city of Almeria, using Spatial Autocorrelation Surveys (SPAC) and Multichannel Analysis of Surface Waves (MASW), obtaining two types of fitting: (a) linear relationship log(Vs30)–log(slope); and (b) considering additional dependence on geological units. The reliability, evaluated by Multiple R-Squared (MRS), varies between 79.2% in the first case and 87.0% in the second, lowering the mean absolute values of the residuals at the observation points in the first case from 40.0 m/s to 29.0 m/s. Using a more generic correlation obtained for other areas of the world, the mean absolute residuals increase to 74.7 m/s.

1. Climate warming is predicted to alter ecological boundaries in high-latitude ecosystems including the elevational or latitudinal extent of tall shrubs in Arctic and alpine tundra. Over 60 studies from 128 locations around the tundra biome have investigated shrub expansion in tundra ecosystems; however, only six studies test whether shrublines are actually advancing up hill-slopes or northward into tundra where tall shrubs are currently absent. 2. We test the hypothesis that willow shrublines have expanded to higher elevations in relation to climate across a 50 × 50 km area in the Kluane Region of the southwest Yukon Territory, Canada by surveying of 379 shrubs at 14 sites and sampling of 297 of the surveyed shrubs at 10 sites. We compared growth and recruitment to climate variables to test the climate sensitivity of shrub increase using annual radial growth analysis, age distributions and repeat field surveys to estimate the current rate of shrubline advance. 3. We found consistent and increasing rates of recruitment of alpine willows, with estimates of faster advancing shrublines on shallower hill-slopes. Mortality was extremely low across the elevation gradient. Aspect, elevation and species identity did not explain variation in recruitment patterns, suggesting a regional factor, such as climate, as the driver of the observed shrubline advance. 4. Annual radial growth of willows was best explained by variation in summer temperatures, and recruitment pulses by winter temperatures. Measured recruitment rates are ~20 ± 5 individuals per hectare per decade (M ± SE) and measured rates of increased shrub cover of ~5 ± 1% per decade (M ± SE) measured at the Pika Camp site between field surveys in 2009 and 2013. Our results suggest that shrubline will continue to advance over the next 50 years, if growing conditions remain suitable. However, if future conditions differ between summer and winter seasons, this could lead to contrasting trajectories for recruitment vs. growth, and influence the vegetation change observed on the landscape. 5. Synthesis. Our findings in the context of a review of the existing literature indicate that elevational and latitudinal shrublines, like treelines, are advancing in response to climate warming; however, the trajectories of change will depend on the climate drivers controlling recruitment vs. growth.

Heavy air pollution is strongly influenced by weather conditions and is thus sensitive to climate change. Especially, for the areas with complex topography such as the Sichuan Basin (SB), one of the most polluted areas of China, the synergistic effects of synoptic weather patterns and topography on air quality are unclear and warrant investigation. This study examined the typical synoptic patterns of SB in winter days of 2013–2017 and revealed their synergistic effects with topography on air quality. Three categories of synoptic patterns including dry low-trough, high-pressure, and wet low-vortex patterns accompanying heavy, medium, and slight air pollution, respectively, were identified. In particular, the dry low-trough patterns occur most frequently, accounting for around 62% of the total days. In the case of this pattern, westerly wind prevails over the SB and the aloft atmosphere is warmer than the Tibetan Plateau (TP) at the same height, which induces the cold air over TP moving eastward to the SB. Under the synergistic effects of the cold air eastward movement and TP, a strong descending motion (known as foehn) is observed on the leeward slope of the towering TP. This foehn warming causes a stable layer above the planetary boundary layer (PBL), which suppresses secondary circulation and PBL. These features restrict atmospheric pollutant dispersion, resulting in poor air quality. In contrast, for the high-pressure and wet low-vortex patterns, cold air masses from the north invade southward and cover the northwest SB. This invasion remarkably decreases the atmospheric stability of the lower troposphere, deepens the PBL, and enhances the height of secondary circulation, thereby facilitating air pollutant dispersion. Moreover, the wet low-vortex pattern is accompanied by frequent precipitation events (with 80% rainy days), further bringing down air pollution levels. These findings provide an insight for improving air pollution forecast in the complex terrain areas under global warming.

In this paper, we attempted to review the soil erosion studies conducted throughout the globe using Revised Universal Soil Loss Equation (RUSLE). We searched the SCI, Scopus, Web of Science, Google Scholar database and various theses for this study. Though RUSLE is the most widely used model for estimation of soil erosion, the factors, namely rainfall erosivity, soil erodibility, slope length and steepness, cover management and conservation practice; vary greatly over different climatic zones, soil properties, slope, land cover and crop phase, respectively. Depending upon those variations, researchers have developed various sets of equation for different factors of RUSLE. These equations can be useful to map soil loss for many places on this planet.

Digital elevation models (DEMs) are widely used in geoscience. The quality of a DEM is a primary requirement for many applications and is affected during the different processing steps, from the collection of elevations to the interpolation implemented for resampling, and it is locally influenced by the landcover and the terrain slope. The quality must meet the user’s requirements, which only make sense if the nominal terrain and the relevant resolution have been explicitly specified. The aim of this article is to review the main quality assessment methods, which may be separated into two approaches, namely, with or without reference data, called external and internal quality assessment, respectively. The errors and artifacts are described. The methods to detect and quantify them are reviewed and discussed. Different product levels are considered, i.e., from point cloud to grid surface model and to derived topographic features, as well as the case of global DEMs. Finally, the issue of DEM quality is considered from the producer and user perspectives.

Lidar remote sensing has proven to be a powerful tool for estimating ground elevation, canopy height, and additional vegetation parameters, which in turn are valuable information for the investigation of ecosystems. Spaceborne lidar systems, like the Global Ecosystem Dynamics Investigation (GEDI), can deliver these height estimates on a near global scale. This paper analyzes the accuracy of the first version of GEDI ground elevation and canopy height estimates in two study areas with temperate forests in the Free State of Thuringia, central Germany. Digital terrain and canopy height models derived from airborne laser scanning data are used as reference heights. The influence of various environmental and acquisition parameters (e.g., canopy cover, terrain slope, beam type) on GEDI height metrics is assessed. The results show a consistently high accuracy of GEDI ground elevation estimates under most conditions, except for areas with steep slopes. GEDI canopy height estimates are less accurate and show a bigger influence of some of the included parameters, specifically slope, vegetation height, and beam sensitivity. A number of relatively high outliers (around 9–13% of the measurements) is present in both ground elevation and canopy height estimates, reducing the estimation precision. Still, it can be concluded that GEDI height metrics show promising results and have potential to be used as a basis for further investigations.

The biological and functional diversity of ectomycorrhizal (ECM) associations remain largely unknown in South America. In Patagonia, the ECM tree Nothofagus pumilio forms monospecific forests along mountain slopes without confounding effects of vegetation on plant–fungi interactions. To determine how fungal diversity and function are linked to elevation, we characterized fungal communities, edaphic variables, and eight extracellular enzyme activities along six elevation transects in Tierra del Fuego (Argentina and Chile). We also tested whether pairing ITS1 rDNA Illumina sequences generated taxonomic biases related to sequence length. Fungal community shifts across elevations were mediated primarily by soil pH with the most species-rich fungal families occurring mostly within a narrow pH range. By contrast, enzyme activities were minimally influenced by elevation but correlated with soil factors, especially total soil carbon. The activity of leucine aminopeptidase was positively correlated with ECM fungal richness and abundance, and acid phosphatase was correlated with nonECM fungal abundance. Several fungal lineages were undetected when using exclusively paired or unpaired forward ITS1 sequences, and these taxonomic biases need reconsideration for future studies. Our results suggest that soil fungi in N. pumilio forests are functionally similar across elevations and that these diverse communities help to maintain nutrient mobilization across the elevation gradient.

A significant drying tendency over the southern slope of the Tibetan Plateau (SSTP) in summer (especially in July–September) during 1980–2018 is identified in this study. Moisture budget analysis reveals that the drying tendency is dominated by a decreased vertical moisture advection due to weakened upward motion, which is mainly resulted from an anticyclonic trend appeared over the northeastern TP. This anomalous anticyclone can weaken the upper-tropospheric divergence pumping over the SSTP. In addition, moist static energy diagnosis indicates that the southern branch of the anomalous anticyclone advects low moist enthalpy air into the SSTP, which also suppresses local upward motion and convection. Moreover, the anticyclonic trend over the northeastern TP is found not a local phenomenon, but is rather associated with the large-scale atmospheric change in the middle latitudes that shows a circumglobal teleconnection (CGT)-like pattern. Our results highlight that the long-term CGT-like trend of atmospheric circulation plays a crucial role in triggering the drying tendency over the SSTP in recent decades.

Land use/land cover (LULC) change has serious implications for environment as LULC is directly related to land degradation over a period of time and results in many changes in the environment. Monitoring the locations and distributions of LULC changes is important for establishing links between regulatory actions, policy decisions, and subsequent LULC activities. The normalized difference vegetation index (NDVI) has the potential ability to identify the vegetation features of various eco-regions and provides valuable information as a remote sensing tool in studying vegetation phenology cycles. Similarly, the normalized difference built-up index (NDBI) may be used for quoting built-up land. This study aims to detect the pattern of LULC, NDBI, and NDVI change in Lodhran district, Pakistan, from the Landsat images taken over 40 years, considering four major LULC types as follows: water bodies, built-up area, bare soil, and vegetation. Supervised classification was applied to detect LULC changes observed over Lodhran district as it explains the maximum likelihood algorithm in software ERDAS imagine 15. Most farmers (46.6%) perceived that there have been extreme changes of onset of temperature, planting season, and less precipitation amount in Lodhran district in the last few years. In 2017, building areas increased (4.3%) as compared to 1977. NDVI values for Lodhran district were highest in 1977 (up to + 0.86) and lowest in 1997 (up to − 0.33). Overall accuracy for classification was 86% for 1977, 85% for 1987, 86% for 1997, 88% for 2007, and 95% for 2017. LULC change with soil types, temperature, and NDVI, NDBI, and slope classes was common in the study area, and the conversions of bare soil into vegetation area and built-up area were major changes in the past 40 years in Lodhran district. Lodhran district faces rising temperatures, less irrigation water, and low rainfall. Farmers are aware of these climatic changes and are adapting strategies to cope with the effects but require support from government.

The 2013 heavy rainfall event (from June to July) in the Tianshui area triggered the most serious rainfall-induced group-occurring landslides since 1984, causing extensive casualties and economic losses. To better understand the characteristics and triggers of these loess landslides, we conducted a detailed analysis of the landslides and relevant influencing factors. Based on the detailed rainfall-induced landslide database obtained using visual interpretation of remote sensing images before and after rainfall, the correlation between the landslide occurrence and different influencing factors such as terrain, geomorphology, geology, and rainfall condition was analyzed. This rainfall event triggered approximately 54,000 landslides with a total area of 67.9 km2, mainly consisting of shallow loess landslides with elongated type, shallow rockslides, collapses, and mudflows. The landslides exhibited a clustered distribution, with the majority concentrated in two specific areas (i.e., Niangniangba and Shetang). The abundance index of landslides was closely associated with the hillslope gradient, total rainfall, and drainage (river) density. The landslide area density (LAD) was positively correlated with these influential factors, characterized by either an exponential or a linear relationship. The Middle Devonian Shujiaba formation (D2S) was identified to be highly susceptible to landslides, and the landslide events therein accounted for 35% of the total landslide occurrences within 22% of the study area. In addition, the E-SE aspect was more prone to landslides, while the W-NW aspect exhibited a low abundance of landslides.