In this paper a three-dimensional agro-hydrological model for shallow landslides' prediction is presented. The model is an extension of the CRITERIA-3D free-source model for crop development and soil hydrology, developed by the Hydrometeorological service of the Regional Agency for Environmental prevention and Energy of EmiliaRomagna region (Arpae-simc). The soil-water balance is computed through the coupling of surface and subsurface flows in multi-layered soils over areas topographically characterized by Digital Elevation Model (DEM). The rainfall infiltration process is simulated through a three-dimensional version of Richards' equation. Surface runoff, lateral drainage, capillarity rise, soil evaporation and plant transpiration contribute to the computation of the soil hydrology on an hourly basis. The model accepts meteorological hourly records as input data and outputs can be obtained for any time step at any selected depth of the soil profile. Among the outputs, volumetric water content, soil-water potential and the factor of safety of the slope can be selected. The validation of the proposed model has been carried out considering a test slope in Montue` (northern Italy), where a shallow landslide occurred in 2014 a few meters away from a meteorological and soil moisture measurement station. The paper shows the accuracy of the model in predicting the landslide occurrence in response to rainfall both in time and space. Although there are some model limitations, at the slope scale the model results are highly accurate with respect to field data even when the spatial resolution of the Digital Elevation Model is reduced.

Landslides can cause severe damage to property and human life. Identifying their locations and characteristics is crucial for emergency rescue and disaster risk assessment. However, existing methods need help in accurately detecting landslides because of their diverse characteristics and scales, as well as the differences in spectral features and spatial heterogeneity of remote sensing images. To overcome these challenges, a multiscale feature fusion landslide-detection network (MFLD-Net) is proposed. This network utilizes reflectance difference images from pre- and post-landslide Sentinel-2A images, along with digital elevation model (DEM) data. Moreover, a multichannel differential landslide dataset was constructed through spectral analysis of Sentinel-2A images, which facilitates network training and enables differentiation between landslides and other objects with similar spectral features, such as bare soil and buildings. The proposed MFLD-Net was tested in Shuzheng Valley and Detuo town in Sichuan, China, where earthquakes have occurred. The experimental results revealed that compared with advanced deep learning models, MFLD-Net has promising landslide detection performance. This study provides suggestions for selecting optimal deep learning methods and spectral band combinations for landslide detection and offers a publicly available landslide dataset for further research.

Erosive processes occur naturally and are essential for soil formation. However, they have been accelerated by anthropogenic actions, contributing to social, environmental, and economic damages. The aim of this study was to develop a methodology for the identification and quantification of soil loss using digital elevation models obtained through imagery from unmanned aerial vehicles (UAVs). In the three selected study areas in Te & oacute;filo Otoni - MG, the generated models were compared before and after precipitation events. The annual erosivity factor can be classified as very low, indicating regional characteristics of low erosive potential. This work proposed different equations for the use of Digital Elevation Models as a data source for the identification and quantification of soil loss through water erosion. The results obtained indicate that flights conducted up to 70 meters contribute to mapping quality and highlight the need for further studies to calibrate the methodology for quantifying soil loss and making it replicable in different situations.

Three-dimensional slope stability study is preferable to 2D stability assessments since all slopes are three-dimensional. Based on 3D extensions of the ordinary slice method and simplified Bishop's method, this study presents 3D slope stability analysis results for homogenous and heterogeneous soil slopes. The geometry of the slope is built with the help of the Digital Elevation Modelling (DEM) technique. Both the ordinary column method (OCM) and simplified Bishop's method (SBM) in 3D satisfy the moment equilibrium of the failure mass. The obtained FS values for all three problems match the published results closely. The effects of pore water pressure applications and seismic loadings are further investigated by considering different combinations. The pore pressure ratio (ru) and horizontal seismic coefficient (keq), with values ranging from 0.25 to 0.50 and 0.05 to 0.10, respectively, have been considered in the present analysis. The detailed variations of normal and shear forces acting on the base of the 3D columns, as well as the variations of other important parameters such as true dip angle and apparent dip angles along the longitudinal and lateral direction of the failure surface, are shown to highlight the mechanisms of generation of internal forces inside the failure mass, both along longitudinal and lateral directions of the slope. The plots of normal and shear forces along the longitudinal direction of the slope follow a symmetric distribution. In contrast, these plots along the lateral direction of the slope follow an asymmetric profile. It is further seen that when pore pressure and earthquake forces are considered, the normal forces increase, and the mobilised shear forces decrease along both longitudinal and lateral directions of the 3D slope.

Urban cover-collapse sinkholes pose a significant global challenge due to their destructive impacts. Previous studies have identified groundwater fluctuations, subsurface soil conditions, pipeline leakage, precipitation, and subterranean construction activities as key contributors to these phenomena. However, unique geological settings across different urban environments lead to variations in the primary factors influencing sinkhole formation. This study focuses on Shanghai, a city notable for its extensive urbanization and rich historical context, to explore the dynamics of sinkholes within urbanized areas worldwide. We employ spatial analysis and statistical methods to examine data on sinkholes recorded in the past two decades in Shanghai, correlating these events with the city's shallow sand layer, ground elevation, and proximity to surface water. Our goal is to identify the dominant factors governing sinkhole occurrence in Shanghai and to lay the groundwork for their effective scientific management and prevention. Key findings indicate that most sinkholes in the area are associated with a thin shallow sand layer, low to moderate ground elevations, and the absence of nearby rivers. Additionally, many sinkholes correlate with subterranean voids within the confined aquifer beneath the cohesive soil layer. The lack of historical river channels, obscured by urban development, also indirectly contributes to sinkhole formation. We recommend enhancing urban river management and drainage systems to mitigate potential damage from water accumulation.

Tree windbreaks have multifunctional benefits including wind damage reduction, soil erosion control, and biodiversity conservation. The removal and low adoption of tree windbreaks due to agricultural expansion are issues in many regions despite their critical role in improving agricultural sustainability. Farmers' and landowners' recognition of the benefits of windbreaks in their cultivation environments is necessary to preserve windbreaks. To visualize the benefits of windbreaks using remote sensing techniques, we focused on the top-tobottom height of soil ridges, which are created homogeneously throughout the field using a machine. In this paper, we propose the use of soil ridge height as a remote sensing indicator to evaluate the spatial distribution of wind erosion. We tested two different remote sensing approaches at a potato field: one was an unmanned aerial vehicle (UAV) and the other was an Apple iPad Pro with a built-in light detection and ranging (LiDAR) sensor. Based on geographic information systems (GIS), the digital elevation model (DEM) was divided into grids with one ridge-furrow pair, with the ridge height given by the difference between the maximum and the minimum elevations in each grid element. The grid-based analysis of the differences in ridge heights between two periods was less affected by the positioning error than the DEM of difference. In a year with large erosion of up to 0.07 m, the spatial pattern of the wind erosion was identified from a single post-erosion survey. Structure-from-motion (SfM) and multiview stereo (MVS) photogrammetry from real-time kinematic-UAV identified smaller wind erosion in an area sheltered by the windbreak and just leeward of a grass-covered road. The iPad LiDAR exhibited higher accuracy in reproducing the ridge height than UAV-SfM-MVS and successfully visualized the windbreak effects by scanning plots at different distances from the windbreak. The iPad LiDAR system is considerably less expensive than UAV-SfM-MVS. In addition, compared to UAV techniques, it is easier to create DEMs with the iPad LiDAR system. Thus, this technique would be beneficial for the spatial evaluation of wind erosion in various fields with different site conditions. This approach is also expected to contribute to the effective visualization of windbreak benefits through three-dimensional printing of DEMs. It provides rapid and innovative method to send a clear message to stakeholders about the importance of windbreaks. To extend smart device applications to remote sensing, our findings emphasize the importance of devising measurement targets to improve detectability and simplify survey designs.

The Ms6.4 Yangbi earthquake occurred in Yunnan Province, the southwestern part of China. Under the influence of severe seismic motion, slopes were damaged and lots of tensile cracks appeared on the slope surface. Considering the potential further failure of damaged slope in the post-earthquake rainy season after Yangbi earthquake, the stability analysis of damaged slope is necessary to be carried out to evaluate its safety in the following rainy season. Through field investigation including UAV shooting and ERT measurement, the surface topography and subsurface geological condition of the damaged slope are obtained based on DEM and resistivity profile. The numerical mesh model of the damaged slope is built using mesh model reconstruction method with tetrahedron element. By using the result of DEM and ERT to define the geometry of upper gravel soil elements, a mesh model considering the damage characteristic of damaged slope is reconstructed. The stability of the damaged slope was calculated by the strength reduction method. The results show that the deformation is concentrated on the rear edge of the damaged slope, and the upper part above the excavation area of damaged slope may lose stability during the following rainy season. The results of numerical calculation are verified by the phenomenon observed in the investigation after post-earthquake rainy season, indicating the validity of reconstructed mesh model using DEM and ERT.

全球气候变暖严重影响冰川的稳定性，南极多条冰川表面发生塌陷。由于缺少高空间和高时间分辨率的南极地表高程模型DEM （Digital Elevation Model），目前单支冰川表面时空变化的研究不充分。利用2011年—2016年11期南极参考高程模型REMA （The Reference Elevation Model of Antarctica）数据，开展东南极达尔克冰川表面塌陷区域的高程变化监测，并利用Landsat 7/8和Worldview-2光学影像等数据分析塌陷过程和原因。结果表明，达尔克冰川在2013年发生了一起严重的塌陷事件，塌陷深度最大约45.29 m，造成了约26.29×10～6 m3的水体损失；塌陷发生后，该区表面高程不断增加，于2016年恢复至塌陷前的高程。塌陷区具有明显的整体性沉降特征，并存在融水聚集，推测塌陷和达尔克冰川冰下湖的排水过程存在密切的联系。本研究证明达尔克冰川存在较大的不稳定性，同时验证了REMA数据监测冰川表面塌陷的可行性，为未来精细化监测南极冰盖/冰架响应气候变化提供技术参考。

Assessing biodiversity in arctic-alpine ecosystems is a costly task. We test in the current study whether we can map the spatial patterns of spider alpha and beta diversity using remotely-sensed surface reflectance and topography in a heterogeneous alpine environment in Central Norway. This proof-of-concept study may provide a tool for an assessment of arthropod communities in remote study areas. Data on arthropod species distribution and richness were collected through pitfall trapping and subjected to a detrended correspondence analysis (DCA) to extract the main species composition gradients. The DCA axis scores as indicators of species composition as well as trap species richness were regressed against a combined data set of surface reflectance as measured by the Sentinel-2 satellite and topographical parameters extracted from a digital elevation model. The models were subsequently applied to the spatial data set to achieve a pixel-wise prediction of both species richness and position in the DCA space. The spatial variation in the modelled DCA scores was used to draw conclusions regarding spider beta-diversity. The species composition was described with two DCA axes that were characterized by post hoc-defined indicator species, which showed a typical annidation in the arctic-alpine environment under study. The fits of the regression models for the DCA axes and species richness ranged from R-2 = 0.25 up to R-2 = 0.62. The resulting maps show strong gradients in alpha and beta diversity across the study area. Our results indicate that the diversity patterns of spiders can at least partially be explained by means of remotely sensed data. Our approach would likely benefit from the additional use of high resolution aerial photography and LiDAR data and may help to improve conservation strategies in arctic-alpine ecosystems.

A process-based, spatially distributed hydrological model was developed to quantitatively simulate the energy and mass transfer processes and their interactions within arctic regions (arctic hydrological and thermal model, ARHYTHM). The model first determines the flow direction in each element, the channel drainage network and the drainage area based upon the digital elevation data. Then it simulates various physical processes: including snow ablation, subsurface flow, overland flow and channel flow routing, soil thawing and evapotranspiration. The kinematic wave method is used for conducting overland flow and channel flow routing. The subsurface flow is simulated using the Darcian approach. The energy balance scheme was the primary approach used in energy-related process simulations (snowmelt and evapotranspiration), although there are options to model snowmelt by the degree-day method and evapotranspiration by the Priestley-Taylor equation. This hydrological model simulates the dynamic interactions of each of these processes and can predict spatially distributed snowmelt, soil moisture and evapotranspiration over a watershed at each time step as well as discharge in any specified channel(s). The model was applied to Imnavait watershed (about 2.2 km(2)) and the Upper Kuparuk River basin (about 146 km(2)) in northern Alaska. Simulated results of spatially distributed soil moisture content, discharge at gauging stations, snowpack ablations curves and other results yield reasonable agreement, both spatially and temporally, with available data sets such as SAR imagery-generated soil moisture data and field measurements of snowpack ablation, and discharge data at selected points. The initial timing of simulated discharge does not compare well with the measured data during snowmelt periods mainly because the effect of snow damming on runoff was not considered in the model. Results from the application of this model demonstrate that spatially distributed models have the potential for improving our understanding of hydrology for certain settings. Finally, a critical component that led to the performance of this modelling is the coupling of the mass and energy processes. Copyright (C) 2000 John Wiley & Sons, Ltd.