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Managing and living with geohazards is especially challenging in mountain landscapes and requires an understanding of catchment‐scale sediment dynamics and internal system functioning. While sediment budgeting is a valuable framework, challenges remain including partitioning sediment yield by source and grain size and addressing scale issues. This study advances our understanding of bed material dynamics in glacierized mountain catchments by applying a range of complementary techniques to measure sediment transfers in the Fitzsimmons Creek watershed. First, we measured the historical bed material yield using field surveys and historical air photo analysis, revealing an average specific sediment yield of 210 Mg km−2 yr−1, that varied by a factor of 17 over the 76‐year record. Hydro‐meteorological and historical analyses suggest that gravel extraction had the largest impact over the past three decades, while an extreme landslide and flood event produced the highest recorded sediment yield. Second, we constructed a detailed sediment budget along the river system using high‐resolution, multi‐temporal lidar and geomorphic mapping data. Sediment source partitioning indicates that landslide, active channel, and floodplain sources each contributed about one‐third of the total sediment supply. Net degradation occurred along the valley bottom upstream of the fan‐delta, resulting in steadily increasing downstream sediment yield. This trend is punctuated by chronic landsliding near the outlet, driven by postglacial incision through glaciogenic sediments at a hanging valley step. Contemporary glacial and proglacial sources were not measured directly but surprisingly contributed minimally. These findings provide insight into the sediment dynamics of glacierized mountain catchments and their potential controls. Plain Language Summary: Managing and living with geohazards in mountain landscapes can be quite challenging. To manage these risks effectively, it's crucial to understand how sediment moves through these landscapes and how they change over time. Sediment budgeting, which describes how much sediment is added to, stored in, or removed from the landscape, can be used as a practical management tool. In this study, we aimed to refine our understanding of sediment movement in mountain landscapes with glaciers using the Fitzsimmons Creek watershed as an example. To do this, we first looked at how much sediment had accumulated in the river delta over the past 76 years and found that the amount varied by up to 17 times. Gravel removal and a very large landslide and flood event had the most control on the amount of sediment reaching the delta. Next, we used detailed elevation data and field surveys to look at the spatial patterns of erosion, deposition, and transport. Interestingly, we found that landslides, the riverbed, and floodplains each contributed about one‐third of the sediment, while very little sediment came from glaciers. This research provides valuable insights into sediment dynamics in glacierized mountain areas and helps inform better management strategies. Key Points: The 76‐year bed material yield record varied by up to a factor of 17, primarily in response to an extreme event and gravel extractionSediment source partitioning suggests that landslide, active channel, and floodplain sources each contribute one third of the total yieldGlacial landscape configuration was important, while contemporary glacial and proglacial sources supplied little sediment [ABSTRACT FROM AUTHOR]

Mount Meager is a deeply eroded quaternary volcanic complex located in southwestern British Columbia (BC) and is known for its frequent large landslides. In 2010, the south face of Mount Meager collapsed, generating a long-runout debris avalanche that was one of the largest landslides (50 × 106 m3) in Canadian history. Over the past 14 years, the landslide deposit has been reworked by stream action, delivering large amounts of sediment to Lillooet River, just downstream. In this study, we investigate 10 years of geomorphic evolution of the landslide deposit using orthophotos and digital elevation models (DEMs) generated using Structure from Motion (SfM) photogrammetry on aerial photographs acquired during unmanned aerial vehicle (UAV) and Global Navigation Satellite System (GNSS) surveys. The SfM products were used to produce a series of precise maps that highlight the geomorphological changes along the lower Meager Creek within the runout area of the landslide. Comparison of DEMs produced from 2010, 2012, 2015, and 2019 imagery allowed us to calculate deposit volume changes related to erosion, transport, and redeposition of landslide material. We estimate that about 1.1 × 106 m3 of sediment was eroded from the landslide deposit over the period 2015–2019. About 5.2 × 105 m3 of that sediment was redeposited inside the study area. About 5.8 × 105 m3 of sediment, mainly sand, silt, and clay, were exported from the study area and are being carried by Lillooet River towards Pemberton, 40 km from Mount Meager, and farther downstream. These remobilized sediments likely reduce the Lillooet River channel capacity and thus increase flood hazards to the communities of Pemberton and Mount Currie. Our study indicates a landslide persistence in the landscape, with an estimated 47-year half-life decay, suggesting that higher flood hazard conditions related to increased sediment supply may last longer than previously estimated. This study shows the value of using SfM in tandem with historic aerial photographs, UAV photos, and high-resolution satellite imagery for determining sediment budgets in fluvial systems. [ABSTRACT FROM AUTHOR]

This study is focused on the use of digital close-range remote surveying techniques for the identification and mapping of landslide phenomena along rock slopes in protected areas. This activity is part of a research project aimed at the digital analysis of slope models. The techniques compared herein are based on photographic and photogrammetric applications, carried out from both ground and aerial surveys, and on the use of infrared thermography in two test sites located within the Cinque Terre National Park (Liguria, Italy) and the “Timpa di Acireale” nature reserve (Sicily, Italy). The analysis of oblique aerial photographs allowed detecting key geomorphological indicators of past landslide movements and to carry out preliminary observations on unstable outcrops. The use of digital close-range sensors for the aerial photogrammetric survey allowed building a digital slope model to be analysed for the recognition and mapping of previous landslides. Moreover, key structural features, likely controlling the slope stability, were highlighted. Infrared thermography allowed detecting signs of landslides, providing the possibility of validating the photogrammetric data. In both protected areas, an almost zero level of environmental disturbance was guaranteed. Finally, both the potential and limitations of the techniques, used for the noninvasive morphological survey, are highlighted. [ABSTRACT FROM AUTHOR]

The morphoevolution of coastal areas is due to the interactions of multiple continental and marine processes that define a highly dynamic environment. These processes can occur as rapid catastrophic events (e.g., landslides, storms, and coastal land use) or as slower continuous processes (i.e., wave, tidal, and current actions), creating a multi-hazard scenario. Maronti Bay (Ischia Island, Southern Italy) can be classified as a pocket beach that represents an important tourist and environmental area for the island, although it has been historically affected by slope instability, sea cliff recession, and coastal erosion. In this study, the historical morphoevolution of the shoreline was analysed by means of a dataset of aerial photographs and cartographic information available in the literature over a 25-year period. Furthermore, the role of cliff recession and its impact on the beach was also explored, as in recent years, the stability condition of the area was worsened by the occurrence of a remarkable landslide in 2019. The latter was reactivated following a cloudburst on the 26th of November 2022 that affected the whole Island and was analysed with the Dem of Difference technique. It provided an estimate of the mobilised volumes and showed how the erosion and deposition areas were distributed and modified by wave action. The insights from this research can be valuable in developing mitigation strategies and protective measures to safeguard the surrounding environment and ensure the safety of residents and tourists in this multi-hazard environment. [ABSTRACT FROM AUTHOR]

Intense rainfall-induced shallow landslides can have severe consequences, including soil erosion and vegetation loss, making in-depth research essential for disaster risk management. However, vegetation recovery processes after shallow landslides and their influencing multivariate factors are not well known. This study aims to address this gap by investigating the vegetation recovery processes after shallow landslides and the impact of topography on this recovery. We focus on two regions in Japan: the Shobara district in Hiroshima Prefecture and the Obara district in Aichi Prefecture. The Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) derived from long-term Landsat images, as well as aerial photographs and environmental datasets, are used to measure vegetation recovery. Then, statistical analysis and the Seasonal Autoregressive Integrated Moving Averages (SARIMA) model were employed to investigate the dynamic response of vegetation under different combinations of environmental conditions using NDVI and EVI time series. Historical aerial photographs and vegetation index trend analysis suggest that vegetation in the study areas will take more than ten years to return to a stable state. The results also demonstrate the influence of atmospheric and land cover conditions when monitoring vegetation response using NDVI and EVI. In Obara, concave and convergent terrain positively influenced NDVI, while non-steep, low-elevation, and north-facing terrain positively influenced EVI. In Shobara, gentle and northwest-facing slopes were positively correlated with NDVI, and gentle and west-facing slopes were positively correlated with EVI. SARIMA modeling found that NDVI is more suitable for modeling the middle and late stages of vegetation recovery within 10–25 years after the landslide. In comparison, EVI is better for modeling the early stage of vegetation recovery within 10 years after the landslide. [ABSTRACT FROM AUTHOR]

Timber harvesting and related management practices associated with industrial timberlands have changed dramatically in the last two decades. Industrial timberlands are now more carefully assessed and mitigated. Recent studies of mass wasting in northern California included a review of historical aerial photographs from the early 1940s through 2016 and field measurements of nearly 3,000 shallow landslides on industrially managed timberlands. Significant improvements have been seen in management practices over time that include but are not limited to reduced harvest unit sizes, increased streamside tree retention, reduced road density, and improved road-building practices. These improvements are a result of a variety of sources such as evolving state regulations, voluntary conservation plans, and increased professional oversight. Subsequently, significant decreases in management-related erosion are being observed across the area included in this study. Observations show that improvements in management practices have positively affected regional mass wasting. In this investigation, significant changes have been noted in both causal mechanisms and landslide erosion rates. The study data shows that before the year 2000, nearly 85 percent of landslide-related erosion was determined to be the result of historical logging, either by harvesting or from roads (generally poor design and/or location). Shallow landslide erosion rates have varied over the duration of time reviewed for this study, peaking in the 1970s. Since 2000, erosion rates across the study area have decreased to 20 m3/km2/yr, which is a 92 percent reduction compared with the historical rate. [ABSTRACT FROM AUTHOR]

At 12:52 pm on September 5, 2022, an Ms 6.8 earthquake occurred in Luding County, Sichuan Province, China. Based on high-resolution aerial photographs and satellite imageries obtained after the earthquake, as well as field investigation, a total of 8685 earthquake-triggered landslides (EQTLs) were interpreted. The landslides covered an area of 30.7 km2, with a source area of 9.4 km2. These EQTLs were mainly distributed in areas with a seismic intensity of VIII and IX. Most of the landslides were small and medium in size, and their types included landslide, rockfall, and rock slump. Characteristic landslide distributions were found, EQTLs were distributed along the Xianshuihe fault, landslide area decreased gradually with an increased distance to the fault; EQTLs were distributed along the Daduhe River and roads; besides, landslide distribution was associated with ground deformation caused by the earthquake. EQTLs' characteristics indicated that, a large number of EQTLs were located near the foot of the slope; the full area of EQTLs and their source area followed a power function. This study concluded that Luding EQTLs were greater in number and area but relatively smaller in terms of affected area. Investigations on geo-hazards post-earthquake and risk assessment were proposed in the earthquake-stricken area to support the rehabilitation and reconstruction. [ABSTRACT FROM AUTHOR]

Detailed and accurate geomorphological historical landslide inventory maps are an invaluable source of information for many research topics and applications. Their systematic preparation worldwide has been advised by many researchers as it may foster our knowledge on landslides, their spatial and temporal distribution, their potential interaction with the built environment, their contribution to landscape dynamics, and their response to climate change in the past. Due to the extreme variability of the morphological and radiometric elements that can reveal historical landslides, geomorphological historical landslide inventory maps are produced by expert interpretation, which makes it a time-consuming and expensive process, which often discourages wide-area mapping activities. In this paper we present a new geomorphological historical landslide inventory map for a 1460 km 2 area in the Daunia Apennines, the north-western sector of the Apulia (Puglia) region, in southern Italy. The inventory contains 17 437 landslides classified according to relative age, type of movement, and estimated depth. Landslides were mapped according to rigorous and reproducible criteria applied by two teams of expert photo interpreters to two sets of stereoscopic aerial photographs taken in 1954/55 and 2003. The dataset consists of a digital archive publicly available at 10.1594/PANGAEA.942427 (Cardinali et al., 2022). [ABSTRACT FROM AUTHOR]

The Svalbard Archipelago represents the northernmost place on Earth where cryospheric hazards, such as thaw slumps (TSs) and thermo-erosion gullies (TEGs) could take place and rapidly develop under the influence of climatic variations. Svalbard permafrost is specifically sensitive to rapidly occurring warming, and therefore, a deeper understanding of TSs and TEGs is necessary to understand and foresee the dynamics behind local cryospheric hazards' occurrences and their global implications. We present the latest update of two polygonal inventories where the extent of TSs and TEGs is recorded across Nordenskiöld Land (Svalbard Archipelago), over a surface of approximately 4000 km 2. This area was chosen because it represents the most concentrated ice-free area of the Svalbard Archipelago and, at the same time, where most of the current human settlements are concentrated. The inventories were created through the visual interpretation of high-resolution aerial photographs as part of our ongoing effort toward creating a pan-Arctic repository of TSs and TEGs. Overall, we mapped 562 TSs and 908 TEGs, from which we separately generated two susceptibility maps using a generalised additive model (GAM) approach, under the assumption that TSs and TEGs manifest across Nordenskiöld Land, according to a Bernoulli probability distribution. Once the modelling results were validated, the two susceptibility patterns were combined into the first multi-hazard cryospheric susceptibility map of the area. The two inventories are available at 10.1594/PANGAEA.945348 (Nicu et al., 2022a) and 10.1594/PANGAEA.945395 (Nicu et al., 2022b). [ABSTRACT FROM AUTHOR]

In recent decades, multiple researchers have produced landslide susceptibility maps using different techniques and models, including the information value method, which is a statistical model that is widely applied to various coastal environments. This study aimed to evaluate susceptibility to landslides in the Essaouira coastal area using bivariate statistical methods. In this study, 588 distinct landslides were identified, inventoried, and mapped. Landslides are performed by means of observation and interpretation of different data sources, namely high-resolution satellite images, aerial photographs, topographic maps, and extensive field surveys. The rocky coastal system of Essaouira is located in the middle of the Atlantic coast of Morocco. The study area was split into 1534 cliff terrain units that were 50 m in width. For training and validation purposes, the landslide inventory was divided into two independent groups: 70 % for training and 30 % for validation. Twenty-two layers of landslide conditioning factors were prepared – namely, elevation, slope angle, slope aspect, plan curvature, profile curvature, cliff height, topographic wetness index, topographic position index, slope over area ratio, solar radiation, presence of faulting, lithological units, toe lithology, presence and type of cliff toe protection, layer tilt, rainfall, streams, land-use patterns, normalised difference vegetation index, lithological material grain size, and presence of springs. The statistical relationship between the conditioning factors and the different landslide types was calculated using the bivariate information value method in a pixel-based model and in the elementary terrain units-based model. Coastal landside susceptibility maps were validated using landslide training group partitions. The receiver operating characteristic curve and area under the curve were used to assess the accuracy and prediction capacity of the different coastal landslide susceptibility models. Two methodologies, considering a pixel-based approach and using coastal terrain units, were adopted to evaluate coastal landslide susceptibility. The results allowed for the classification of 38 % of the rocky coast subsystem as having high susceptibility to landslides, which were mostly located in the southern part of the Essaouira coastal area. These susceptibility maps will be useful for future planned development activities as well as for environmental protection. [ABSTRACT FROM AUTHOR]

A rainfall-induced deep large landslide occurred on March 12, 2012, in the city of Azazga (Northern Algeria), causing heavy damages to residential buildings and public infrastructures. In this work, we investigate the inventory mapping, the deformation characteristics, the controlling factors, and the failure mechanisms of this landslide based on the field investigation, aerial photographs and satellite images interpretation, deep boreholes equipped with piezometers and inclinometers, as well as subsurface geophysical imaging by electric resistivity tomography (ERT). The obtained landslide inventory map shows that the landslide of March 2012 affected an area of 0.40 km2. This landslide is considered as a partial reactivation of a large pre-existing one (0.606 km2), which represents 6.65% of the total urban area. Moreover, the analyses identified two types of causative factors: (1) the triggering factor related to the high intensity and antecedent rainfall as well as human activity through slope excavations and embankments; and (2) the susceptibility factors related to the lithological nature and the internal structure of the flysch deposits, their weak mechanical resistance characteristics, the presence of shallow aquifers, and basal undercutting erosion of the Iazoughen and Aboud river torrents. The inclinometer measurements and ERT imaging reveal a complex, deep-seated and rapidly moving landslide whose failure surfaces are located at a depth of 11–29 m with an average velocity of 1–29 cm year−1. The entire slip surface is located along the geotechnical interface between the flysch bedrock and the overlying scree. This comprehensive study provides useful information on rainfall-induced landslides and may constitute guidance for landslide hazard mitigation and prevention. [ABSTRACT FROM AUTHOR]

Detailed and accurate geomorphological historical landslide inventory maps are an invaluable source of information for many research topics and applications. Their systematic preparation worldwide has been advised by many researchers as it may foster our knowledge on landslides, their spatial and temporal distribution, their potential interaction with the built environment, their contribution to landscape dynamics, their response to climate change in the past. Due to the extreme variability of the morphological and radiometric elements that can reveal historical landslides, geomorphological historical landslide inventory maps are produced by expert interpretation, which makes it a time consuming and expensive process, which often discourages wide area mapping activities. In this paper we present a new geomorphological historical landslide inventory map for a 1,460 km² area in the Daunia Apennines, the northern-western sector of the Apulia (Puglia) region, in Southern Italy. The inventory contains 17,437 landslides classified according to relative age, type of movement and estimated depth. Landslides were mapped according to rigorous and reproducible criteria applied by two teams of expert photo interpreters to two sets of stereoscopic aerial photographs taken in 1954/55 and 2003. The dataset consists of a digital archive publicly available at https://doi.pangaea.de/10.1594/PANGAEA.942427 (Cardinali et al., 2022). [ABSTRACT FROM AUTHOR]

The Svalbard Archipelago represents the northernmost place on Earth where cryospheric hazards, such as thaw 15 slumps (TS) and thermo-erosion gullies (TEG) could take place and rapidly develop under the influence of climatic variations. Svalbard permafrost is specifically sensitive to rapidly occurring warming and therefore, a deeper understanding of TS and TEG is necessary to understand and foresee the dynamics behind local cryospheric hazards' occurrences and their global implications. We present the latest update of two polygonal inventories where the extent of TS and TEG is recorded across Nordenskiöld Land (Svalbard Archipelago), over a surface of approximately 4000 km2. This area was chosen because 20 it represents the most concentrated ice-free area of the Svalbard Archipelago and, at the same time, where most of the current human settlements are concentrated. The inventories were created through visual interpretation of high-resolution aerial photographs, as part of our ongoing effort toward creating a pan-Arctic repository of TS and TEG. Overall, we mapped 562 TS and 908 TEG, from which we separately generated two susceptibility maps using a Generalized Additive Modelling (GAM) approach, under the assumption that TS and TEG manifest across Nordenskiöld Land, according to a Bernoulli 25 probability distribution. Once validating the modelling results, the two susceptibility patterns were combined into the first multi-hazard cryospheric susceptibility map of the area. The two inventories are available at https://doi.org/10.1594/PANGAEA.945348 (Nicu et al., 2022a) and https://doi.pangaea.de/10.1594/PANGAEA.945395 (Nicu et al., 2022b). [ABSTRACT FROM AUTHOR]

Landslides are a widespread natural hazard that cause damages to people and to the built up environment. Accurate knowledge of landslide distribution is crucial to develop planning strategies, prevention and resilient communities worldwide. One of the most diffuse way of reporting landslides distribution in a territory is by preparing landslide inventory maps. Such a task is mostly accomplished by expert photo-interpretation of historical aerial photographs, which are an invaluable source of information because they portray the landscape when the anthropic pressure was lower than the present day, providing an observation of the landscape closer to the natural conditions. Despite such a common use of aerial photographs, they are poorly exploited to obtain quantitative measures to support landslide mapping activities. In this paper we present a comparison of two photogrammetric approaches to measure elevation changes in a 50-years period for an area densely affected by landslides in Southern Italy. The obtained results allowed to revisit the original expert mapping proving that such a method is a useful tool to support geomorphological mapping and to improve the overall accuracy of landslide inventories. [ABSTRACT FROM AUTHOR]

Generating precise and up-to-date landslide susceptibility maps (LSMs) in landslide-prone areas is important to identify hazard potential in the future. The data quality and the method selection affect the accuracy of the LSMs. In this context, the accuracy and precision of the digital elevation models (DEMs) used as input are among the most important performance elements. Therefore, the influence of DEM accuracy and spatial resolution in producing LSMs was investigated here. A high accuracy DEM with 5 m grid spacing produced from aerial photographs and the EU-DEM v1.1 freely accessible from Copernicus Land Monitoring Service with 25 m spatial resolution were used for producing two different LSMs using the Random Forest (RF) method in this study. The RF method has proven success for this purpose. A total of eight conditioning factors, which include topographical and geological features, was used as model input. The landslide inventory was derived with the help of aerial stereo images with 20 cm and 30 cm ground sampling distances. The performances of the LSMs were assessed with receiver operating characteristics (ROC) area under curve (AUC) values. In addition, the results were compared with visual inspection. The results show that although the AUC values obtained from the aerial DEM (0.95) and EU-DEM v1.1 (0.93) were comparable; based on the visual assessments, the LSM obtained from the higher resolution DEM was found more successful in detecting the landslides and thus exhibited better prediction performance. [ABSTRACT FROM AUTHOR]

During the last few decades, many researchers have produced landslide susceptibility maps using different techniques and models including the information value method, which qualified as a wide applied statistical model in several coastal environments. The aim of this study was to evaluate the susceptibility for the occurrence of landslides in Essaouira coastal area using this bivariate statistical method. In this coastal area were identified, inventoried and mapped 588 landslides, of different types, mostly from the observation and interpretation of different data sources, namely high-resolution satellite images, aerial photographs, topographic maps, and extensive field surveys. The rocky coastal system of Essaouira is located in the middle part of Morocco Atlantic coastal area. The study area was split into 1534 cliff terrain units of 50m width. For training and validation purposes the landslide inventory was divided into two independent groups: training (70%) and for validating (30%). Twenty-two layers of landslide-conditioning factors were prepared, including: elevation, slope angle, slope aspect, plan curvature, profile curvature, cliff height, topographic wetness index, topographic position index, slope over area ratio, solar radiation, presence of faulting, lithological units, toe lithology, presence and type of cliff toe protection, layer tilt, rainfall, streams, land-use patterns, NDVI, lithological material grain size, and presence of springs. The statistical relationship between the conditioning factors and the different types of landslides were calculated using the bivariate information value method, in a pixel and in elementary terrain units base model. Validation of the coastal landside susceptibility maps was done using the landslide training group partitions. The ROC curves and Area Under the Curve were used to assess the accuracy and prediction capacity of the different coastal landslide susceptibility models. Two methodologies were adopted to evaluate coastal landslide susceptibility, one considering a pixel base approach and another one using coastal terrain units. The resulted coastal landslide susceptibility maps allowed classifying 38 % of the rocky coast subsystem with high susceptibility to landslides, being the majority of these high susceptible areas located in the southern part of the Essaouira coastal area. Those susceptibility maps would be useful for general planned development activities in the future as well as for environmental protection. [ABSTRACT FROM AUTHOR]

In January 1980, during exceptional cyclonic rainfall, an atypical landslide, called déboulé, rapidly generated the permanent 700 m-long gully of the Ravine de l'Eglise on an inhabited plateau in Reunion Island (Indian Ocean). Retrieving the initial conditions that led to this historical process is both challenging and necessary for understanding the mechanism of gully incision and providing pointers for improving risk mitigation in relation to this phenomenon. In this study, we reconstruct the pre- and post-failure topographies using SFM (structure from motion) applied on archive aerial photographs. Based on the comparison of these digital elevation models, we estimate the volume of material eroded to be ca. 0.63 Mm3. Groundwater level increase, part of the triggering mechanism, is hindcast in the catchment of the gully using a lumped hydrological model. This model shows that in only a fortnight the groundwater level probably rose by 36 m, which could have caused a progressive increase in pore pressure and triggered formation of the gully by retrogressive landslides. We test this hypothesis by considering the pre-failure topography and the hindcast groundwater level in a deterministic model based on limit equilibrium equations to explore ground stability. The evolution of ground stability with a rise in the water table shows that the gully may have extended in a headward direction by retrogressive landslides. This is the first quantitative reconstruction of an exceptional historical event affecting the territory of Reunion Island. The methods used to investigate the Ravine de L'Eglise incision thus offer new complementary insights and challenges for understanding the mechanism and the temporality of gully formation. [ABSTRACT FROM AUTHOR]

Aims: We aim (a) to investigate and describe the species composition of vegetation that has recolonized landslides and describe its relationship to environmental variables; and (b) to propose a set of plant species and restoration strategies applicable for speeding up the restoration process. Location: Elevation between 240 and 1,350 m a.s.l. in central Taiwan, East Asia. Methods: We delimited the boundaries of landslides using aerial photographs taken between 1975 and 2015. We sampled 52 plots from 48 selected landslides and measured 21 environmental variables to identify the significant factors related to species composition. Cluster analysis and transformation‐based redundancy analysis were used to determine the vegetation groups and corresponding environmental variables; the environmental differences between different vegetation types were evaluated by ANOVA. Results: We classified the vegetation into four types and related each of them to a successional age, landslide position and soil pH, as well as Mn and Mg contents. Two early‐successional types (aged 5–10 years) mainly occurred in habitats in steep slip zones, which are dominated by pioneer woody species and have a high coverage of grasses, forbs, or ferns thickets. In contrast, the mid‐successional vegetation type (aged 16–40 years), growing on flat habitats, consists of pioneer woody species in the canopy layer and seedlings or saplings of shade‐tolerant species in the understorey. Conclusions: We confirmed that the composition and recruitment of species can be well explained by environmental differences between landslide zones and successional age. Some framework species and some shade‐tolerant woody species can be applied to landslide scars with plant dispersal limitation problems and habitats suffering from poor local species pools, respectively. To overcome the problem of vegetation succession blocked by Miscanthus and ferns thickets, we suggest that pioneer woody species and herb species can be seeded on landslide scars at once for erosion control. [ABSTRACT FROM AUTHOR]

The aim of this study is to assess and compare two clustering algorithms, namely, the Wave-cluster and Density Based Spatial Clustering of Application with Noise (DBSCAN) algorithms, for landslide susceptibility assessment in Baota District, China. Based on historical reports, interpretation of aerial photographs and field survey reports, 293 were identified in the study area. Seven factors associated with landslide occurrence were prepared and used as inputs into the models for landslide susceptibility modelling. The models divided the study area grids into 478 and 465 subclasses, respectively, which were further grouped into five susceptibility levels using K-means algorithm, based on the landslide density values of the obtained subclasses. The resulting two models were validated and compared using area under the receiver operating characteristics (AUC-ROC) curve and statistical measures including sensitivity, specificity and accuracy. The analysis demonstrated that the Wave-cluster model outperformed the DBSCAN model with sensitivity, specificity and accuracy values of 88.05%, 89.2%, and 88.54%, respectively, while DBSCAN had sensitivity, specificity and accuracy values of 86.69%, 86.38%, and 86.56% respectively. In addition, the Wave-cluster model had higher value AUC of 0.823 than the DBSCAN model (0.808). This indicates that, the landslide susceptibility maps (LSMs) generated in this study had good performance for assessing landslide susceptibility in the study area and can be useful tools in assessing landslides, as the foundation for preventing and reducing landslide consequences for suitable social and economic development. [ABSTRACT FROM AUTHOR]

Relatively cool tropical climate with high annual rainfall experienced in mountainous tropical region creates favorable agricultural areas where intensive agricultural practices often correlate with increasing landslide events. While it has long been associated with landslides, agricultural practice in such areas especially in Cameron Highlands, Malaysia continues to flourish with minimal regard to environmental sustainability and safety. Therefore, this study aims to confirm the relationship between human activities and landslide occurrences and identify human practices that directly or indirectly cause landslides. Aerial photograph was used to identify landslides and anthropogenic features while other remotely sensed data including Interferometric Synthetic Aperture Radar (IFSAR) were used to establish the geomorphology of study area. A total of 207 landslides were identified in a 25 km2 area from remote sensing study and field mapping. They were superimposed over several potential contributing factors including geology, slope gradient and human activities. This study found that landslides are more likely to occur in areas greater than 15° of slope angle. The main factor, however, is the human factor where 164 landslides (79.22% of total identified landslides) were located in agricultural lands. Poorly planned and engineered agricultural farms were identified as the main causal factors for landslide occurrences at the study area, either directly or indirectly. These issues were observed through remote sensing study using aerial photograph which were then verified through site observations. New district development plan called for a stricter regulations in new tourism and agricultural developments. Improvements should also be implemented on existing agricultural activities where most of these landslides were located at this area. Therefore, in addition to controlling new developments, improving of existing agricultural practices in Cameron Highlands shall be a major focus in ensuring slope safety and their sustainability. [ABSTRACT FROM AUTHOR]

Landslide susceptibility mapping is a necessary tool in order to manage the landslides hazard and improve the risk mitigation. In this research, we validate and compare the landslide susceptibility maps (LSMs) produced by applying four geographic information system (GIS)-based statistical approaches including frequency ratio (FR), statistical index (SI), weights of evidence (WoE), and logistic regression (LR) for the urban area of Azazga. For this purpose, firstly, a landslide inventory map was prepared from aerial photographs and high-resolution satellite imagery interpretation, and detailed fieldwork. Seventy percent of the mapped landslides were selected for landslide susceptibility modeling, and the remaining (30%) were used for model validation. Secondly, ten landslide factors including the slope, aspect, altitude, land use, lithology, precipitation, distance to drainage, distance to faults, distance to lineaments, and distance to roads have been derived from high-resolution Alsat 2A satellite images, aerial photographs, geological map, DEM, and rainfall database. Thirdly, we established LSMs by evaluating the relationships between the detected landslide locations and the ten landslides factors using FR, SI, LR, and WoE models in GIS. Finally, the obtained LSMs of the four models have been validated using the receiver operating characteristics curves (ROCs). The validation process indicated that the FR method provided more accurate prediction (78.4%) in generating LSMs than the SI (78.1%),WoE (73.5%), and LR (72.1%) models. The results revealed also that all the used statistical models provided good accuracy in landslide susceptibility mapping. [ABSTRACT FROM AUTHOR]

The paper describes the multitemporal landslide inventory map prepared for the urban areas of Motta Montecorvino and Volturino, two municipalities located in the Southern Apennines (Apulia Region, Italy). These territories show a high propensity to landslides of different types and magnitude, which periodically interfere with the anthropic structures and infrastructures. For the study area, the spatial and temporal distribution of landslides is detected for the period between 1954 and 2003, through the visual interpretation of multiple sets of black and white digital stereoscopic aerial photographs at different scales. The analysis reveals locally high frequency of landslide occurrence and built-up areas on existing landslides, either on the body or on the crown areas. In particular, we show that over the years new residential areas were developed despite the presence of large old mass movements. [ABSTRACT FROM AUTHOR]

In a southern suburb of Pittsburgh, Pennsylvania (PA), a portion of a housing development was constructed in the 1950s on an unrecognized, marginally stable prehistoric landslide mass. Grading practices of that era included placement of poorly compacted fill over a sanitary sewer behind houses on the downslope side of a street across the upslope part of the prehistoric landslide mass. A shallow landslide developed in fill and near-surface colluvium (old landslide debris). This shallow landslide was fully active by 1973 and continued to move, at least intermittently, thereafter. Landslide movements observed by a homeowner behind his house circa 2003–2004 led him to sue the Municipality, alleging that sewer leakage had caused the landslide. A detailed forensic investigation with heavy emphasis on observational engineering geology, including but not limited to historical aerial photographs and high-quality sewer inspection videotapes, clearly showed that the sewer was not leaking in the landslide area. Rather, the sewer was acting as a drain to reduce groundwater levels, thereby improving stability of the landslide. [ABSTRACT FROM AUTHOR]

The increasing availability of EO data from the Copernicus program through its Sentinel satellites of the medium spatial and spectral resolution has generated new applications for risk management and disaster management. The recent growth in the intensity and number of hurricanes and earthquakes has demanded an increase in the monitoring of landslides. It is necessary to monitor large areas at a detailed level, which has previously been unsatisfactory due to its reliance on the interpretation of aerial photographs and the cost of high-resolution images.Using the differential Bare Soil Index for optical imagery interpretation in combination with cloud-computing in Google Earth Engine is a novel approach. Applying this method on a recent landslide event in Oaxaca in Mexico around 62% of the landslides were detected automatically, however, there is a big potential for improvement. Including NDVI values and considering images with a higher spatial resolution could contribute to the enhancement of landslide detection, as the majority of missed events have a size smaller than half a pixel. Landslide detection in Google Earth Engine has become a promising approach for big data processing and landslide inventory creation. [ABSTRACT FROM AUTHOR]

Active‐layer detachments (ALD) and retrogressive thaw slumps (RTS) are landslides that occur as a result of thaw in permafrost regions. I mapped the extent of bare soil exposed in these thaw‐related slope failures in four study areas with continuous permafrost in Alaska's Arctic National Parks, on mosaics of aerial photographs from 1977–1985 (sampling episode 1), satellite images from 2006–2009 (sampling episode 2), and satellite images from 2018–2019 (sampling episode 3). In all four study areas the count of ALD and RTS, and the area of bare soil they exposed, was greater during the first or second sampling episode than the third sampling episode, in spite of record high mean annual temperatures in 2014–2019. One study area had frozen debris lobes (FDL) in addition to ALD and RTS. In that study area the bare ground exposed by destabilization and rapid movement of FDL was greatest in the third sampling episode, probably as a result of deep thaw and talik formation. The destabilization of FDL in episode 3 was probably a long‐term consequence of warming and permafrost loss, while the observed pulses of ALD and RTS in episodes 1 and 2 were closely tied to short‐term deep thaw events in areas where the underlying permafrost remained stable. [ABSTRACT FROM AUTHOR]

Landslides, the most significant geohazards in Iran, adversely affect the region's socioeconomic conditions and the environment. Landslide susceptibility mapping is crucial for proactive risk management, sustainable development, and protecting human lives, infrastructure, and the environment. It enables decision-makers to make informed choices, implement appropriate mitigation measures, and plan for potential landslide events, leading to safer and more resilient communities. Using a recommended subdivision methodology, this research has developed a landslide susceptibility map for a significant Gilan, Iran region. The production of the map involved utilizing an artificial neural network (ANN) model. This model incorporated sixteen causal components from several characteristics, including topographic and geomorphologic features, geological factors, land use patterns, hydrological aspects, and hydrogeological properties. Three hundred seventy instances were identified using multiple verified sources and analyzing aerial photographs to create the landslide inventory map. Examining and verifying the weights assigned to the causal elements were conducted per accepted mathematical standards, incorporating sensitivity analysis, earlier research, and empirical data on landslides. The area under the receiver operating characteristic curve (AUROC) was used to compare the various models. The study's findings indicated that the best swarm size value for COA-MLP 1 1 Cuckoo Optimization Algorithm (COA). is equal to 450, and the accuracy indices for this algorithm were 0.998 and 0.995 in training and testing datasets, respectively. Similarly, the AUC 2 2 Area under the curve (AUC). for the HS-MLP, 3 3 Harmony Search Algorithm (HS). SFS-MLP, 4 4 Stochastic Fractal Search (SFS). and TLBO-MLP 5 5 Teaching- Learning-Based Optiization (TLBO). were 0.997, 0.999, and 0.999 in training and 0.995, 0.996, and 0.995 in the testing dataset, respectively. Therefore, the use of optimization algorithms leads to an increase in the performance and accuracy of the neural network, and the high accuracy of the SFS-MLP model demonstrates the existence of a dependable criterion for delineating the susceptibility zones about forthcoming landslide occurrences. The model is a cost-effective and potentially indispensable tool for urban planners in growing cities and municipalities. Its effectiveness is demonstrated by comparisons with previous susceptibility analyses conducted in the region. [ABSTRACT FROM AUTHOR]

Landslides are hillslope processes controlled by natural changing topographic conditions. Landslides are also influenced by human activities. Yet, understanding the space-time occurrence of landslides and their interactions with these typically long-term natural and short-term human-induced controls remains a key challenge in many regions, especially in tropical environments where data scarcity is commonplace. Here we decipher these dynamic processes in the Ruzizi Gorge located in the Kivu Rift (Central Africa), that is an exceptional geomorphological landmark whose origin is associated with the rerouting of >7000 km2 of drainage area from Lake Kivu during the Holocene. This bedrock river has also seen its landscape disturbed over the past decades by the development of the city of Bukavu (DR Congo). In this study, we combine detailed field observations, historical aerial photographs, archive analysis and satellite imagery to compile a multi-temporal inventory of 385 landslides and constrain their dynamics. We show that extremely high incision rates during the early stage of the formation of the gorge explain the space-time clustering of thousand-year-old large (up to ∼2 km2) landslides, independently from the lithological context. These landslides are currently non-active and poorly eroded. Their deposit areas partly cover the riverbed with boulders, armouring the channel and inhibiting further incision. The landslides that occurred over the last 60 years are shallower slope failures of smaller size and higher mobility. They tend to disappear rather quickly from the landscape, sometimes within a few years. Their distribution is primarily controlled by threshold slopes, lithology, and the past large landslides, the influence of the land use being less pronounced. Overall, the sediment mobilization rates associated with these high frequency landslides significantly outpace the extreme landslide erosion pulse associated with the gorge formation. Our results provide insight on interactions between channel-hillslope coupling and feedbacks among landslide processes and river gorge formation in a unique environment. • Extremely high bedrock incision rates at the early stage of the gorge formation. • Incision dominates over lithology as the main control on a pulse of large landslides. • Large landslides are old, non-active, and inhibit further incision. • Recent, smaller landslides are controlled by threshold slopes and lithology, less by land use. • Sediment mobilization rates of recent landslides outpace that of the large landslide pulse. [ABSTRACT FROM AUTHOR]

As demonstrated at Anak Krakatau on December 22nd, 2018, tsunamis generated by volcanic flank collapse are incompletely understood and can be devastating. Here, we present the first high-resolution characterisation of both subaerial and submarine components of the collapse. Combined Synthetic Aperture Radar data and aerial photographs reveal an extensive subaerial failure that bounds pre-event deformation and volcanic products. To the southwest of the volcano, bathymetric and seismic reflection data reveal a blocky landslide deposit (0.214 ± 0.036 km3) emplaced over 1.5 km into the adjacent basin. Our findings are consistent with en-masse lateral collapse with a volume ≥0.175 km3, resolving several ambiguities in previous reconstructions. Post-collapse eruptions produced an additional ~0.3 km3 of tephra, burying the scar and landslide deposit. The event provides a model for lateral collapse scenarios at other arc-volcanic islands showing that rapid island growth can lead to large-scale failure and that even faster rebuilding can obscure pre-existing collapse. The authors here present a detailed reconstruction of the landslide mass following the 2018 eruption of Anak Krakatau. Bathymetry data reports the volume of the collapsed submarine flank to be much larger than previously reported. [ABSTRACT FROM AUTHOR]

Landslide inventories provide the knowledge basis for many geomorphological applications and also planning and emergency management. Detailed landslide inventories should also be prepared where pre-existing inventories are available, as knowledge updates. In this paper, we present a new geomorphological landslide inventory for an area of the High Agri Valley, Southern Italian Apennines. The map was prepared through systematic interpretation of historical aerial photographs testing extensive use of anaglyph glasses in StereoPhoto Maker freeware. A total of 2124 landslides were classified based on the type of movement, estimated depth, estimated relative age and three levels of uncertainty, providing landslide attributes and map constraints useful for land planning and hazard studies. The map also documents the relationships between landslides and fluvial landforms of different generations, recording important information to investigate the geomorphological evolution of the area further. We expect that landslide mapping in similar environments will benefit from the workflow here presented. [ABSTRACT FROM AUTHOR]

The city of Azazga is facing extensive and damaging landslide hazard. The aim of this study was to investigate the inventory mapping, the deformation characteristics, the controlling factors and the failure mechanisms of the landslides in the urban area of Azazga based on field surveys, aerial photographs/satellite images interpretation and the exploitation of available data including rainfall database, boreholes, piezometers, inclinometers and laboratory tests. The prepared landslide inventory map indicates that the unstable urban perimeter covers an area of 281.6 ha which represents about 31% of the urban area. Analysis of the inventory data highlighted the action of two types of conditioning factors: (i) susceptibility factors represented by the presence of clay, marl deposits with low mechanical resistance characteristics, the presence of shallow aquifers, the morphology and steep slope, the tectonic features network and a dense hydrographic network; (ii) the triggering factors corresponds to the high intensity rainfall and the uncontrolled human activity. Statistical analysis of the relationship between the landslide occurrence and the landslide-conditioning factors shows that the highest density of landslides occur in quaternary scree and cretaceous clay flysch located on slopes ranging between 5° to 20°. The statistical results indicate that the highest concentration of landslides occurred in the highest rainfall classes ranging between 950 to 1050 mm. Additionally, the results showed the important role of the fluvial incision with more of the landslides occur at a distance of 50 m from the nearest rivers. These data also indicated that the high density of the landslides is concentrated in the farming and urban zones. The inclinometer measurement results reveal a deep rupture surfaces between 4 and 28 m located at the scree–flysch bedrock interface. According to the mechanism modes, landslides are controlled by the following: (i) the dip of the flysch formation layers, the schistosity planes and fractures downward slope direction; and (iii) the interface contact between the quaternary scree and flysch substratum. This work presents an exhaustive understanding of the causes, deformation characteristics and failure mechanisms of the large-scale landslides as a useful information for landslide hazard and risk mitigation. [ABSTRACT FROM AUTHOR]

In recent years, the incidence of localized heavy rainfall has increased as abnormal weather events occur more frequently. In densely populated urban areas, this type of heavy rain can cause extreme landslide damage, so that it is necessary to estimate and analyze the susceptibility of future landslides. In this regard, deep learning (DL) methodologies have been used to identify areas prone to landslides recently. Therefore, in this study, DL methodologies, including a deep neural network (DNN), kernel-based DNN, and convolutional neural network (CNN) were used to identify areas where landslides could occur. As a detailed step for this purpose, landslide occurrence was first determined as landslide inventory through aerial photographs with comparative analysis using field survey data; a training set was built for model training through oversampling based on the landslide inventory. A total of 17 landslide influencing variables that influence the frequency of landslides by topography and geomorphology, as well as soil and forest variables, were selected to establish a landslide inventory. Then models were built using DNN, kernel-based DNN, and CNN models, and the susceptibility of landslides in the study area was determined. Model performance was evaluated through the average precision (AP) score and root mean square error (RMSE) for each of the three models. Finally, DNN, kernel-based DNN, and CNN models showed performances of 99.45%, 99.44%, and 99.41%, and RMSE values of 0.1694, 0.1806, and 0.1747, respectively. As a result, all three models showed similar performance, indicating excellent predictive ability of the models developed in this study. The information of landslides occurring in urban areas, which cause a great damage even with a small number of occurrences, can provide a basis for reference to the government and local authorities for urban landslide management. [ABSTRACT FROM AUTHOR]

Aerial photography has been extensively used for civil engineering applications for more than a century. The availability of digital photogrammetry tools has allowed for aircraft, UAV, and ground-based digital photogrammetry to become a reliable and standard tool for landslide management. Digital photographs and digitized historic aerial photos can be used to develop digital surface elevation models. This technical note presents a recent example of the use of historical aerial photographs in combination with modern remote sensing techniques and digital photogrammetry tools. The note provides valuable insights into landslide kinematics and evolution of the Chin Coulee landslide in southern Alberta, Canada. Conventional aerial photo interpretation allowed for a qualitative understanding of landslide feature evolution as a response to external factors (road construction and reservoir infilling at the toe of the landslide). More importantly, topographic changes were quantified through change detection techniques between topographic surfaces derived from historical photographs and a ground-based laser scanner. The results from change detection allowed to confirm the kinematics of the Chin Coulee landslide as a compound slide, an assumption which was previously based on limited deformation measurements. Furthermore, the results helped define the boundary between the active wedge of the landslide moving downslope as it pushes the passive wedge into the reservoir. Although challenges remain regarding the aggregation of datasets with different resolutions, this note demonstrates the valid practical application of this approach for landslide assessment and management. [ABSTRACT FROM AUTHOR]

A landslide inventory is indispensable for determination of landslide susceptibility, hazard, risk assessment and disaster mitigation strategies. These inventories were traditionally developed using manual digitization of remote sensing images and aerial photographs, and pixel-based image classification. Recently, Object-Based Image Analysis (OBIA) supersedes visual interpretation and pixel-based methods. OBIA utilizes spectral, textural, contextual, morphological and topographical information in remote sensing images. However, OBIA-based landslide detection methods are often designed for specific areas and remote sensing dataset. The aim of this study is to evaluate the transferability of three published OBIA landslide detection methods for semi-automated landslide detection in the Himalaya mountainous region of northern Pakistan. A SPOT-6 multi-spectral image with Advanced Land Observing Satellite (ALOS) Phased Array type L-band Synthetic Aperture Radar (PALSAR) Digital Elevation Model (DEM) derivatives, i.e. slope, aspect, hill-shade, relief, elevation and stream network are used for landslide detection using eCognition developer software. The three published methods scale parameters for image segmentation and parameter thresholds are evaluated first. It is observed that the aforementioned methods are not directly applicable to our study area and remote sensing datasets. Therefore, an alternate (proposed) method is developed for semi-automated landslide detection. Accuracy assessment of the selected methods and proposed method is assessed by Precision, Recall and F1 measures. Using the proposed method, a total of 357 landslides are detected with 91.46% Precision, 93.31% Recall and 92.38% F1 measure accuracy. [ABSTRACT FROM AUTHOR]

We examined the characteristics of landslides triggered by the 2016 Kumamoto earthquake (Mw = 7.0: focal depth=10.0 km) in forests and grasslands within two affected watersheds (Tokosegawa: 6.9 km2 and Nigorigawa: 6.1 km2) in southwestern Japan. We identified 190 landslides using aerial photographs and analyzed their sizes by geographic information system (GIS). Field investigations were conducted to obtain landslide depth, volume and residual sediment for 38 selected landslides (21 in forests and 17 in grasslands). The minimum area of detected landslides in grasslands (400 m2) was smaller than in forests (1000 m2), probably because of reduced detectability of landslides under tree cover. The ratio of total area occupied by landslides for a given range of slope gradient in the watersheds increased from 3.2% on gentle grassland slopes (10–15°) to 15.5% on steep (>45°) slopes, whereas the maximum landslide‐area ratio in forest sites (7.4%) occurred on relatively gentle slopes (25–30°). Estimated landslide volume ranged from 27 to 9622 m3, based on mean depth of each landslide measured around individual landslide scars. Moreover, the volumetric ratio of landslide deposit volume to total landslide volume exceeded 100% for 48% of the landslides within forests and 35% of the landslides within grasslands. Our findings show that land cover had extensive and recognizable effects on the characteristics of landslides and resulting in‐channel sediment accumulations. Resetting sediment dynamics after earthquakes associated with different land cover distributions needs to be considered within watersheds. © 2019 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

This work was to generate landslide susceptibility maps for the Three Gorges Reservoir (TGR) area, China by using different machine learning models. Three advanced machine learning methods, namely, gradient boosting decision tree (GBDT), random forest (RF) and information value (InV) models, were used, and the performances were assessed and compared. In total, 202 landslides were mapped by using a series of field surveys, aerial photographs, and reviews of historical and bibliographical data. Nine causative factors were then considered in landslide susceptibility map generation by using the GBDT, RF and InV models. All of the maps of the causative factors were resampled to a resolution of 28.5 m. Of the 486289 pixels in the area, 28526 pixels were landslide pixels, and 457763 pixels were non-landslide pixels. Finally, landslide susceptibility maps were generated by using the three machine learning models, and their performances were assessed through receiver operating characteristic (ROC) curves, the sensitivity, specificity, overall accuracy (OA), and kappa coefficient (KAPPA). The results showed that the GBDT, RF and InV models in overall produced reasonable accurate landslide susceptibility maps. Among these three methods, the GBDT method outperforms the other two machine learning methods, which can provide strong technical support for producing landslide susceptibility maps in TGR. [ABSTRACT FROM AUTHOR]

A rainfall-induced complex landslide occurred on April 4, 2013, in Wanzhou County, Three Gorges Reservoir, China. Approximately 1.5 × 106 m3 of earth and rock mass slid over a distance of ~ 30 m, destroying residential buildings and rural roads. We perform a comprehensive assessment of the cause of this landslide using field surveys, borehole drillings, and interpretations of aerial photographs. This landslide exhibited a complex failure mode in which the upper part of the earth slope first deformed and slid along geotechnical interfaces. This then triggered the slide of the lower part of the flysch bedding rock. In this study, the landslide mass was divided into nine separate blocks considering their internal geological features and movements. The study also shows that antecedent rainfall, in association with the geological and morphological features of the steep slope, the presence of weak interlayers, and human interventions such as slope excavations, jointly caused this disaster. This well-observed event study facilitates comprehensive recognition of the deformation characteristics and failure mechanisms of rainfall-induced complex landslides and also provides an insight into landslide hazard mitigation. [ABSTRACT FROM AUTHOR]

The exploitation of a suitable cartography of a well-identified geographical territory inevitably passes by reliefs drawn by the movements of ground. The most frequent of these movements are landslides such as the case of the Taounate city in the mountainous area of northern Morocco. The aim of the work is to develop a landslide susceptibility map of Taounate city based on the evidence belief function (EBF) and the frequency ratio (FR) Models. The landslide inventory map was prepared using interpretation of aerial photographs, satellite images and field visits. Twelve predisposition and release factors (slope, lithology, aspect, annual precipitation, elevation, curvature, normalized difference vegetation index (NDVI), land cover, distance from rivers, and distance from roads, topographic wetness index (TWI), and surface roughness) are taken into account in this study to develop susceptibility maps. The validation of the resulting susceptibility maps was obtained by analyzing the area under the curve. The results of the validation showed that the combination of the predictive factors: terrain slope, terrain aspect, lithology, TWI and NDVI proved to be the best combination for both FR and EBF models and give values for the area under the curve equal to 98% (0.9779) and 87% (0.8712) respectively. These coefficients reflect the good degree of reliability of the models used. [ABSTRACT FROM AUTHOR]

A large-scale landslide occurred in 2015 in Senninvalley, Mt. Hakusan, Central Japan, releasing large amounts of sediment. To mitigate continuous erosion in the landslide area and its downstream adverse effects, reforestation activities were implemented from 2016 to 2021. This study assessed the status of vegetation recovery and erosion condition after 7 years using aerial photographs, light detection and ranging data, satellite imagery, and published documents. The results show that the greenery (herbaceous and woody plants) is mainly recovering on the upper slope of the landslide area where reforestation works were implemented, while the lower slope, where no reforestation activities have been applied, still lacks greenery. The lower slope suffered nearly 1–4 m of continued erosion from 2016 to 2022, while upper slope has no significant erosion. Within this 7-year period, the vegetation coverage on the upper slope of the landslide, where artificial restoration was applied, increased significantly from 10 to 43%. [Display omitted] • Large-scale landslides can result in denuded slopes that may experience prolonged erosion over an extended period. • Restoration of vegetation on landslide slopes can be achieved by carefully selecting native plant species. • Air photos and remote sensing data can assist in assessing erosion status and vegetation recovery in remote landslides. [ABSTRACT FROM AUTHOR]

[Display omitted] • We estimated SOC and TN transport rates due to landslides during 64 years. • Mean SOC and TN transport rates were 5.8–9.3 MgC km−2 yr−1 and 0.5–0.9 MgN km−2 yr−1. • SOC and TN transports in young forests (<20 yr) accounted for 87% of the total. • Forest harvesting increased landslide frequency, and SOC and TN transport rates. • Our results are useful for optimizing forestry practice to sequestrate more carbon. Landslides considerably affect soil organic carbon (SOC) and total nitrogen (TN) transports. However, the quantitative assessment of these effects remain limited. Furthermore, it is unresolved how forestry practices, especially clearcutting and subsequent planting, affect the SOC and TN transports by facilitating landslides. Therefore, we quantified the SOC and TN transports attributable to landslides from 1948 to 2012 in a steep mountainous area in Japan and examined the impacts of forest clearcutting on SOC and TN transports through landslides. We used 12 aerial photographs and two LiDAR DEMs to identify the landslide areas and to estimate their scar depths. In addition, we sampled soil at 17 points to examine the relationship between SOC and TN and soil depth. Subsequently, we estimated the temporal changes in SOC and TN transports due to landslides and examined the relationships between forest age and rates of SOC or TN transport due to landslides. During the 64 years, the average annual rate of landslide was 3.7 × 10−2 ha km−2 yr−1. Large temporal variability existed in rates of landslide, and the maximum rate of landslide was around 11.0 × 10−2 ha km−2 yr−1, while almost no landslide occurred in some periods. The average annual SOC and TN transport rates were 5.8–9.3 MgC km−2 yr−1 and 0.5–0.9 MgN km−2 yr−1, respectively. Many landslides occurred at places where trees were 15 years old or less in plated forests. The amount of SOC and TN transports in landslide areas with < 20 forest age accounted for 87% of the total amounts moved owing to landslides. That is, our results clearly showed that forest harvesting increased landslide frequency and SOC and TN transport rates. We expect our results to be useful for predicting carbon stock in forest ecosystems and optimizing forestry practices in steep mountainous regions. [ABSTRACT FROM AUTHOR]

Record-breaking heavy rainfall in July 2018 caused an extremely large number of slope movements over a broad area of western Japan. We mapped the distribution of slope movements in the southern part of Hiroshima Prefecture through an interpretation of aerial photographs that were acquired after the rainfall by the Geospatial Information Authority of Japan, and counted a total of 8,497 slope-movement starting points. The widespread distribution of slope movements - from Etajima City of Hiroshima Prefecture to Kasaoka City of Okayama Prefecture - suggests that the heavy rain affected a very large area. The starting points of debris flow during this disaster were commonly close to the crest of mountain ranges. We compared the distribution of slope movements to the 24-hr rainfall accumulation during the heaviest rainfall event to clarify the factors that caused regional difference in slope-movement distribution. We found the area of highest density of the slope movements was consistent with the area receiving a cumulative rainfall of >250 mm. This observation indicated that the position of slope-movement starting points was not related to differences in geology. [ABSTRACT FROM AUTHOR]

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The edges of the Ethiopian Plateau are affected by frequent landslides predisposed by pronounced seasonality in precipitation, thick weathering mantle of volcanic material, and rough relief. We analyzed the three‐dimensional dynamics of three large landslides in Dessie using digital elevation models and ortho‐images derived from a time‐series of aerial photographs reaching back to 1936. Furthermore, we utilized repeated photography based on terrestrial photographs from the 1930s and 1940s to analyze landscape changes. It was revealed that the large sliding zone (25.4 ha) in lacustrine sediments at Kerra locality existed approximately in the present extent already before 1936. The volume of depleted material of the 1986–1994 rock slide at Doro Mezleya locality was assessed as 1.82 106 m3 with mean vertical thickness of 48 m. Additionally, we described the nowadays inactive Hot Spring landslide (12.9 ha). We documented a large scale reforestation of the area carried out as a remediation measure and rapid changes in land cover and settlement structure. We conclude that two out of three studied large landslides existed before 1936 and thus are not induced by the increased human pressure on the landscape of the last decades. Additionally, we provide an overview about collections of historical aerial photographs of Ethiopia, and we discuss their potential and drawbacks for mass wasting studies. [ABSTRACT FROM AUTHOR]

This study discusses the compilation of landslide inventories and their possible application in landslide research and risk assessment. A case study was conducted in the Abava River valley (western Latvia) between the towns of Sabile and Kandava to determine the most effective methods of landslide mapping and to demonstrate the possible applications of landslide inventories there. Landslide inventories are necessary for landslide risk zoning and landslide hazard prevention. An efficient landslide mapping is one of the first steps for creating a landslide inventory. The effectiveness of different landslide mapping approaches was compared in the real-world study area of the Abava River valley. Hillshade maps and stereoscopic aerial photographs were used to map landslides. To evaluate the accuracy of the applied landslide mapping methods, field surveys were conducted in the study area. During the field surveys, the slopes of the Abava River valley were inspected for the occurrence of landslides. During the field surveys, landslides were also classified according to their morphological expression. By comparing the results of landslide mapping through stereoscopic aerial photographs and hillshade maps with the field surveys, the most appropriate methodology for landslide identification was determined. The information containing the spatial location of landslides and their morphological characteristics reveals factors controlling landslide formation in the study area and delivers information for landslide research and risk assessment. [ABSTRACT FROM AUTHOR]

Ground displacement mapping has become a crucial issue for landslide hazards assessment. Unmanned Aerial Vehicle (UAV) offers many advantages in mapping applications. The objective of this study is to analyze ground displacement by UAV. This study utilizes UAV DJI 4 Pro for the landslide area in conservational forest Semarang, Indonesia. The study area for mapping is 12 ha, divided into 8 points. Three Control Points 2 × 2 meters were applied. Aerial photographs were taken during the rainy season, August 21st, 2021 and March 30th, 2022. Agisoft software was used to obtain the point cloud and Cloud Compare was used to estimate the landslide surface area. The final results show there are 2 point areas occur ground displacements. In the first location, the landslide surface area is 3420 m2, with the depth of landslide 19 m. The ground displacement occurs in 79.4 m western. The second location landslide surface area is 3576 m2, with the depth of landslide 4 m. The ground displacement occurs in 60.3 m to the west. This study concludes that UAV is applicable in photogrammetry to analyze ground displacement. The procedures in this study can be used for monitoring a landslide area with rapid results and a low-cost budget. • Ground displacement estimation informs how landslide develops. • UAV photogrammetry enable surface, depth, and direction of landslide information. • Agisoft and Cloud Compare are used in post-processing method. • Results show a rapid and low-cost method of landslide assessment is suggested. [ABSTRACT FROM AUTHOR]

This paper assesses the performance of the landslide susceptibility analysis using frequency ratio (FR) with an iterative random sampling. A pair of before-and-after digital aerial photographs with 50 cm spatial resolution was used to detect landslide occurrences in Yongin area, Korea. Iterative random sampling was run ten times in total and each time it was applied to the training and validation datasets. Thirteen landslide causative factors were derived from the topographic, soil, forest, and geological maps. The FR scores were calculated from the causative factors and training occurrences repeatedly ten times. The ten landslide susceptibility maps were obtained from the integration of causative factors that assigned FR scores. The landslide susceptibility maps were validated by using each validation dataset. The FR method achieved susceptibility accuracies from 89.48% to 93.21%. And the landslide susceptibility accuracy of the FR method is higher than 89%. Moreover, the ten times iterative FR modeling may contribute to a better understanding of a regularized relationship between the causative factors and landslide susceptibility. This makes it possible to incorporate knowledge-driven considerations of the causative factors into the landslide susceptibility analysis and also be extensively used to other areas. [ABSTRACT FROM AUTHOR]