Landform Features Research Articles

Optically dating of a Paleolithic site in coastal regions of South China and its correlation with the late Pleistocene environment evolution

The coastal regions of South China are crucial for the emergence and migration of early Austronesian hominids to Taiwan Island and the Pacific islands, but most Paleolithic sites in this area remain unexplored wilderness areas without clear archaeological stratigraphy or formal excavation. The research on archaeological chronology faces challenges due to the absence of direct evidence for determining site ages; instead, it relies on indirect methods such as comparing lithology, knapping techniques, and other usage characteristics with regional stratigraphic ages based on recovered stone tools. This presents a challenge when studying prehistoric human-land relationships in the region. However, the Kuahaicun site located on coastal islands along the southeastern coast offers valuable materials for investigating activities of Paleolithic populations along both South China’s coast and its islands since the late Pleistocene period. This study employs a comprehensive investigation and sampling approach, utilizing optically stimulated luminescence dating to determine burial age. Furthermore, by integrating regional aeolian landform characteristics and trends in sea level changes, we examine the influence of geomorphic environmental evolution during the transition from Paleolithic to Neolithic periods on ancient human migration and diffusion patterns. 1) The findings suggest that the stratigraphy primarily consists of sedimentary layers dating back to 25–10 ka, representing the transition from Late Paleolithic to Early Neolithic. The luminescence sensitivity of quartz grains indicates diverse sediment sources in this area, including aeolian deposits with efficient long-distance transportation due to thorough and repeated bleaching, as well as alluvium and colluvium deposits with limited bleaching. 2) By comparing the developmental process of coastal aeolian sand with regional sea level changes, it becomes evident that the main period of Austronesian ancestor activity in South China, as evidenced by this site, significantly aligns with a crucial phase of aeolian deposition. Moreover, this correlation coincides with three low sea level phases during the late Pleistocene Fujian marine transgression. 3) Commencing from the Middle Paleolithic period onwards, Austronesian ancestors gradually migrated downstream along the Minjiang River and Jiulong River towards their respective estuaries. The presence of a transient land bridge during the Late Pleistocene Fujian marine transgression (18–15 ka) potentially facilitated the migratory movements and territorial expansions of ancient populations along China’s southern coastline, enabling their transition from mainland coastal regions to nearby islands.

Characteristics of the micropseudokarst landforms in Pâclele Mari mud volcanic area (Romania)

In this paper, we present the results of the geomorphological study of the micro pseudokarst landfoms developed on Pâclele Mari mud volcanic site that belongs to the famous mud volcanic area Berca-Arbănași, Buzău Subcarpathians, Romania. Different types of pseudokarstic cavity formation can be observed in the area, especially in the sloping periphery of the mud volcanic area, where badlands developed (badland pseudokarst), and rheogene pseudokarst in the mud flows. The liquid mud material gets denser and wimple on the surface of the mud that flows in the trough, it compiles and then covers the liquid mud channel. These micro-size covered tunnels are similarly formed as lava tubes at the lava flows of real volcanic areas. In order to complement the field measurements, we carried out surveys with a DJI Phantom 3 and 4, and Mavic Pro quadcopter to determine the landforms for the photogrammetry. Granular composition tests were carried out on sediment samples collected in the mud volcanic area by a laser diffraction particle analyser.

Review article: Retrogressive thaw slump characteristics and terminology

Abstract. Retrogressive thaw slumps (RTSs) are spectacular landforms that occur due to the thawing of ice-rich permafrost or melting of massive ground ice, often in hillslope terrain. RTSs occur in the Arctic, the subarctic, and high mountain (Qinghai–Tibet Plateau) permafrost regions and are observed to expand in size and number due to climate warming. As the observation of RTSs is receiving more and more attention due to their important role in permafrost thaw; impacts on topography; mobilization of sediment, carbon, nutrients, and contaminants; and their effects on downstream hydrology and water quality, the thematic breadth of studies increases and scientists from different scientific backgrounds and perspectives contribute to new RTS research. At this point, a wide range of terminologies originating from different scientific schools is used, and we identified the need to provide an overview of variable characteristics of RTSs to clarify terminologies and ease the understanding of the literature related to RTS processes, dynamics, and feedbacks. We review the theoretical geomorphological background of RTS formation and landform characteristics to provide an up-to-date understanding of the current views on terminology and underlying processes. The presented overview can be used not only by the international permafrost community but also by scientists working on ecological, hydrological, and biogeochemical consequences of RTS occurrence and by remote-sensing specialists developing automated methods for mapping RTS dynamics. The review will foster a better understanding of the nature and diversity of RTS phenomena and provide a useful base for experts in the field but also ease the introduction to the topic of RTSs for scientists who are new to it.

Outburst flood events since the Last Glacial Maximum in the Hutiao Gorge of Jinsha River: Geomorphological evidence from eddy gravel bars

Breaching of natural dams in the Hutiao Gorge of the Jinsha River across the Yulong-Haba Mountains is one of the major geomorphological events in the largest river of Asia. Catastrophic flood events have an important influence on the geomorphological evolution of the First Bend of the Yangtze River since the Last Glacial Maximum (LGM). However, detailed geomorphological evidence, ages, and depositional phases of outburst flooding remain unclear. In this paper, large-scale gravel bars overlying the river terraces and dammed lakes are analyzed within the Daju Basin. The macroscopic geomorphological characteristics of megaflood landforms with large thickness and uniform gravel bars are similar to those of Missoula and Altai megafloods. Morphological analysis shows that eddy gravel bars (EGBs) with rhythmic structure are characterized by a dome-shaped protrusion in the cross section and a gravel mound in the longitudinal section. Each bar with oblique, parallel and massive bedding was analyzed from the horizontal and vertical directions. Three dome-shaped bars clearly show at least three palaeoflood phases. Quartz grain surface macrotextures are mainly V-shaped pits and conchoidal fractures, which exhibits a high-energy environment during the flood. The stratigraphic sequence model of EGBs is dominated by coarse sand and fine gravel rhythmic bedding in high-energy eddy environments and suspended sand deposits in low-energy backwater environments. Such phenomenon reveals megaflood fluctuates, which is also confirmed by geochemical difference. The episode of natural dam break floods triggered by tectonic activity and glacier fluctuation was dated to 20–17 ka during the LGM. Sedimentary pattern of EGBs offers fresh insights into understanding the megaflood geomorphological characteristics of the upper Yangtze River and better identification similar high-energy palaeoflood landforms in the southeast Tibetan Plateau.

Integrating terrain structure characteristics into generative adversarial nets for hillshade generation

A hillshade is a visualization technique that represents three-dimensional terrain in a two-dimensional plane by illumination mapping. The digital relief shading promotes the visualization of the terrain efficiently using DEM data. However, compared with manual shading, the digital algorithm-based method still has a gap in the visual effect of illumination strategy and terrain generalization. The typical landform characteristics and micro-geomorphic properties usually are destroyed. The reason is that the complexity of illumination rules is hard to summarize for different terrain phenomena. In this study, namely the data-driven artificial intelligent method, an alternative strategy based on generative adversarial networks (GANs) is proposed rather than the rule-based method. The DEM and the terrain skeleton lines are input to the model and part of the manual relief shading of Swisstopo is used for the training samples. Through the GAN training and learning, the manual skill imbedded in the hillshade is discovered in the generation model. The results show that the proposed model performs better than the digital relief shading on various landforms in aesthetic visualization and geo-scientific representation. Compared to other models, including other convolution neural network (CNN) based methods, terrain structure is maintained more significantly through the proposed model.

Potential for Events Similar to the Deadly West Salt Creek Landslide, Grand Mesa Area, Colorado

ABSTRACT The deadly West Salt Creek Landslide of 2014, one of the largest landslides to occur in the United States in historical time, was surprising in its suddenness and length of runout. Its source area, the edge of Grand Mesa in western Colorado, was potentially the source of other similar landslides in the past, based on previous mapping in the region. The purpose of this research was to evaluate the potential for similar events by detailed mapping of several canyons flanking West Salt Creek, using aerial imagery and age-dating techniques not available to previous mappers. We conclude that, while the West Salt Creek Landslide has the potential to reactivate in a similar manner to the 2014 movement, the potential for a similar event in the flanking canyons is low. Mapping and semi-quantitative geomorphic methods suggest that the deposits present in several canyons on either side of West Salt Creek are glacial or stream deposits, with one canyon containing debris-flow deposits. Our interpretations are based on the morphology of deposits in the canyons, the presence of specific landform features, measurements of mobility index and longitudinal profiles, and comparison with regional analogs. Furthermore, other mass movements in the region that are of similar magnitude had either slower movement or much shorter runout. The large block at the head of West Salt Creek and the earlier block that shattered and mobilized in 2014 are also unique features locally, distinguishing this setting from others, but also indicating the potential for a future similar event.

Research on Zoning and Carbon Sink Enhancement Strategies for Ecological Spaces in Counties with Different Landform Types

Ecological carbon sinks, pivotal in mitigating carbon emissions, are indispensable for climate change mitigation. Counties, as the fundamental units of ecological space management, directly impact the achievement of regional dual carbon targets through their levels of carbon sink. However, existing research has overlooked the intricate relationship between terrain features and ecological spaces, leading to a lack of specific guidance on enhancing the carbon sink for counties with diverse landform characteristics. This study focused on Jingbian County (Loess Plateau), Fuping County (Guanzhong Plain), and Chenggu County (Qinba Mountains), each characterized by distinct landform characteristics. This study proposes a comprehensive identification model for ecological space within the context of dual carbon targets. Utilizing this model as a basis, the land use structure, carbon sink potential, and ecological spatial patterns of different counties were systematically analyzed. The results indicated substantial disparities in land use structure, carbon sink capabilities, and ecological space distributions among counties with different landform types. Specifically, Jingbian County was predominantly covered by grassland, exhibiting a moderate overall carbon sink capacity, with baseline ecological spaces playing a significant role. Conversely, Fuping County, dominated by cultivated land and construction land, exhibited the lowest carbon sink capacity, with non-ecological spaces accounting for a staggering 85.93%. Chenggu County, on the other hand, was characterized by the dominance of forestland, with nearly all its carbon sink originating from forestland, and core ecological spaces occupying a leading position. Tailored optimization strategies are recommended based on varying terrain features: Jingbian County should prioritize ecosystem restoration and conservation, while Fuping County should concentrate on optimizing land use structure and promoting urban greening. Reinforcing the carbon sink capacity of existing ecosystems is crucial for Chenggu County. This study broadens the perspective on ecological space optimization and provides scientific guidance and pragmatic insights tailored to regional disparities, which are instrumental in assisting various regions to achieve their dual carbon targets.

Spatial disaggregation of a legacy soil map to support digital soil and land evaluation assessments in Scotland

In recent years, the importance of soils and soil functions has been recognised for supporting the delivery of ecosystem services and for the realisation of international initiatives, such as the UN Sustainable Development Goals. At the same time, Digital Soil Mapping (DSM) has emerged as a modelling technique that can satisfy increased end-user needs for new soil datasets by producing fine resolution soils and soil property maps to support complex digital soil and land evaluation assessments. Spatial disaggregation is a popular DSM technique that is used to transform legacy soil maps to more spatially-explicit soils datasets, which can also be used in conjunction with soil databases to generate digital soil property maps. In this study, we performed spatial disaggregation of the National Soil Map of Scotland (originally published at 1:250,000 scale) at the taxonomic level of Soil Series, with the specific objective to facilitate the production of harmonised digital soil property maps to support soil and land evaluation assessments in Scotland through linking to the Scottish Soil Database. We divided Scotland into Landscape Units of similar soil and landform characteristics and trained probability random forest models within each Landscape Unit using area-proportion random sampling of both single- and multiple- (complex) Soil Series map units and selected environmental covariates to produce Soil Series probability layers at 50 m grid resolution. The performance of the disaggregated Soil Series maps was evaluated using prediction uncertainties of individual soil types and independent soil profile classifications. Evaluation results indicated that the random forest algorithm was successful in promoting effective spatial disaggregation of both single soil and complex soil polygons and provided good prediction accuracies for most soil types with the exception of some of the least extensive soil types typically found within complex map units. This was attributed mainly to algorithm's tendency to favour dominant, more extensive classes, along with its difficulty to distinguish between similar soils within spatially diverse areas. However, training Soil Series models at a Landscape Unit level instead of nationally helped to limit both the underestimation of these minority soil types and the overestimation of the dominant ones. In addition, map evaluation results showed the usefulness of using the generated conditional Soil Series probabilities for exploring soil spatial variability, especially within complex areas such as river floodplains covered by multiple alluvial and non-alluvial soils. Overall, this study demonstrates the potential of using spatial disaggregation to extract pedological knowledge embedded in legacy soil maps and use it to generate new dynamic and harmonised soil and soil property maps by effectively using readily-available and easily-updated soils information from existing databases.

Understanding Dynamics of Land Cover Changes Using GIS Technique in a River Catchment with High Altitude Differences – an Analysis from Kosovo

This article analyses Land Cover Changes in the Lumbardhi of Prizreni (LP) River catchment in southern Kosovo. As a landlocked country, Kosovo has highly diverse landform features. LP River catchment is located in Sharri's transboundary high mountain range and the southern part of Dukagjini Plain. In the last two decades, the landscape has experienced a transformation in land cover changes, especially in the increasing of artificial surfaces in the plains. Using GIS techniques, data were calculated for the selected years, and their dynamics were visualised for the last two decades. The analysis shows a decrease in agricultural land and complex cultivation patterns (-806 ha), an increase in artificial surface, especially discontinuous urban fabric (+354 ha), and small changes in forest and seminatural areas, which are primarily included in "Sharri" National Park.

Landsystem analysis of temperate non‐surging glaciers on the Mýrdalsjökull Ice Cap, southern Iceland

Glacial deposits are important sources of palaeoclimatic information but not all deposits are formed by processes that reflect the overall climatic conditions of a region; surge‐type glaciers undergo periodic episodes of rapid ice movement, often unrelated to ambient climatic conditions. This study examines the glacier forefields of Öldufellsjökull and western Sléttjökull, two outlet glaciers of the Mýrdalsjökull Ice Cap in southern Iceland, to identify landform characteristics indicative of past episodes of fast flow. Previous studies suggest episodes of fast flow at these glaciers in the past century. Remotely sensed data and field investigations were combined to complete a landsystem analysis of the forefields of these glaciers and an uncrewed aerial vehicle was used to collect high‐resolution imagery of areas of particular interest. Two assemblages of landsystems are identified on each forefield, which pass from streamlined landforms containing abundant flutes close to the glacier to spatially restricted bands of arcuate moraines with associated glaciofluvial and glaciolacustrine deposits more distally. This distribution of landsystem tracts has limited similarity to the current surge‐type glacier landsystem model, suggesting that other processes are controlling the development of landform–sediment assemblages. Using a high‐resolution digital elevation model of an area within the 1984 ice margin, two distinct landform types were identified that were not apparent on the coarse resolution imagery: hummocky moraine and a circular feature hypothesized to have formed as a result of water escape caused by changing hydrological regimes. The forefields of Öldufellsjökull and western Sléttjökull lack many of the characteristics typical of surge‐type landsystems and instead are more similar to the active temperate landsystem common in Iceland.

Landscape Pattern Vulnerability and Its Driving Forces in Different Geomorphological Divisions in the Middle Yellow River

The ecological environment of the middle Yellow River is highly vulnerable. Conducting a scientific assessment of landscape pattern vulnerability holds great significance, as it serves as the basis for the rational construction of the ecological environment in this area. Based on five periods of land use data from the middle Yellow River from 1990 to 2018, the landscape pattern vulnerability index was employed to analyze the spatio-temporal evolution of the landscape pattern vulnerability. Furthermore, the influencing factors for landscape pattern vulnerability in different natural geomorphological divisions were explored using an optimal parameters-based geographical detector model. The results showed that:① From 1990 to 2018, cultivated land (which accounted for 36.96 % to 39.97 % of the area) remained the predominant landscape in the middle Yellow River. Among all landscape types, cultivated land and construction land exhibited the most significant changes. The area of cultivated land decreased by 10 185.00 km2, whereas the area of construction land increased by 7 678.46 km2. ② From 1990 to 2018, the landscape pattern was dominated by low and medium vulnerability and accounted for 70 %-80 % of the total area. The high and higher vulnerability areas were concentrated in the loess hilly and gully region, whereas the lower vulnerability area was concentrated in the valley plain and the earth-rock mountain regions. During this period, landscape pattern vulnerability underwent an incipient decrease, followed by a subsequent increase. From 1990 to 2000 and from 2000 to 2005, the changes in the level of landscape pattern vulnerability were dominated by a "reduction in the degree of vulnerability". However, from 2005 to 2010 and from 2010 to 2018, it was mainly an "increase in the degree of vulnerability". ③ Annual precipitation and NDVI were the main factors influencing the vulnerability of landscape patterns, whereas the influencing factors varied across different natural geomorphological divisions:the loess hilly and gully region and the earth-rock mountain region were dominated by natural factors, with annual precipitation and DEM being the dominant factors, respectively; the loess plateau tableland-gully region, valley plain region, and sandy land and desert region were dominated by human factors, with population density, degree of land use, and distance from roads being the dominant factors, respectively. The interaction results of any two influencing factors were manifested as two-factor enhancement or nonlinear enhancement. Risk detection revealed that high vulnerability areas of landscape patterns in different natural geomorphological divisions were distributed over distinct ranges of their corresponding dominant factors. Therefore, in the practices of ecological management in the middle Yellow River, appropriate management strategies should be implemented based on the vulnerability characteristics of different natural landforms, to further improve the ecological management level of the watershed.

Using a Public Preference Questionnaire and Eye Movement Heat Maps to Identify the Visual Quality of Rural Landscapes in Southwestern Guizhou, China

Rural landscapes serve as important platforms to determine the landscape characteristics (LCs) of rural areas, demonstrating the landscape characteristics specific to certain regions to the public. However, the development trend of urban and rural areas is continuous and impacts the characteristics of rural landscapes, which directly affects the public’s visual experience and landscape perception. In order to improve the characteristics of rural landscapes, this study evaluates and analyzes their visual quality based on public preferences and eye movement heat maps. The results show that most subjects have a high preference for horizontal, open-view rural landscapes with fields and landform features as the dominant landscape elements. This study also found that the combination of strip-like or planar settlement buildings with regional characteristics and landform features has an active impact on the visual quality of rural landscapes. These results show that rural landscapes characterized by scattered settlement buildings without significant regional characteristics, horizontally curved roads, bridges, and other human-made landscape elements, and mixed and disorderly vegetation have low landscape preference, which degrades their visual quality. These research results provide crucial suggestions for landscape managers to protect and renew rural landscape features.

Geomorphological Structure of Landform Characteristics As A Reference for Development Recommendations in Active Volcanic and Faulting Areas, A Case Study in Kerinci Region, Jambi Province, Indonesia

Kerinci Regency is located on the western to the southwestern part of the capital city of Jambi Province, Indonesia. It has interesting geomorphological sites consisting of the physiography of the Barisan Mountain Zone associated with the Sumatran Fault System known as a volcanic-tectonic complex. Geomorphology has an important role in providing information of the landscape in an area. This paper aims to determine the geomorphological characteristics of the area which can provide information regarding disaster mitigation, the direction of land-use innovation, and infrastructure development strategies. This research uses analyses of morphographic, morphometric, morphogenetic, morphoconservation, and morphochronological aspects. Analysis of satellite images and topographic contours is a method used to determine the characteristics of drainage patterns and geological mapping. A significant result of this research is a geomorphological map of Kerinci that divides the area into several geomorphological units, namely volcanic-denudational, karst, structural, volcanic-structural, structural-denudational, and fluvial morphologies. Based on the geomorphological map, the area has a very high potential hazard consisting of volcanic structural landforms, which are Tanco Isolated Hill (TIH), Kerinci Fault Escarpment Undulation (KFEU), Kerinci Fault Escarpment Volcanic Undulation (KFEVU), structural landforms (Alang Structural Valley (ASV), Kumun Fault Hills (KFH), and Pengasih Fault Undulation (PGFU)). This map can be used to design the Standard Operating Procedures (SOP) for regional development in Kerinci.

Study on the Application of Water Resource Management Based on GF-7 Stereo Mapping Satellite

Abstract. GF-7 satellite was successfully launched on 3 Nov 2019. The two-line stereo camera can effectively obtain 20 km-width panchromatic stereo images with resolution better than 0.8m and 3.2m-resolution multispectral images. Through the composite mapping mode of stereo camera and laser altimeter, the satellite realizes 1:10,000-scale stereo mapping. This article selected the Qiafuqihai Reservoir and its upstream of the Yili River Basin as the study area. Hydrological landforms and vegetation coverage were monitored and three-dimensional dynamic simulation software was developed to verify the potential application of GF-7 stereo mapping satellite data in supporting drainage basin water resource allocation and management in future scenarios. 3 meters DSM derived from GF-7 surveying and mapping satellite finely portrayed the characteristics of hydroponic landforms of small watersheds. The upstream of Qiafuqihai was divided into eleven small watersheds. The water density was 8.5 times more than which was produced from STRM 90m. The elevation of the water-level fluctuation zone of the Qiafuqihai Reservoir ranged from 970 to 998 meters with the water area changed from 28.3 to 57.6 square kilometres. The terrain in the northwest and northeast was flat, with the main vegetation types being natural grasslands (64.9%) and arid lands (5.03%). The three-dimensional dynamic visualization software was developed and demonstrated hydrology information, vegetation coverage information and dynamic changes in the landform of the basin in three-dimensional environment. GF-7, the stereo surveying and mapping satellite, could be perfectly able to support the application of water resources deployment and management in the future.

Judgment criteria for significant wind speed-up regions in natural complex terrain

Flashover incidents due to wind-induced motion of overhead power line components are a not uncommon phenomenon during very strong winds, e.g. typhoons, and an important contributing factor is the speed-up effect caused by small-scale topographic features. In this study, wind speed-up ratios and significant speed-up regions in natural complex terrain are comprehensively analyzed from three perspectives: analysis of landform characteristics of flashover locations, Computational Fluid Dynamics (CFD) simulation, and wind tunnel experiments. Through the analysis of flashover locations, judgment criteria based on the elevation coefficient of variation are proposed to attempt to identify significant speed-up regions in natural complex terrain. Wind tunnel experiments and CFD simulations are conducted to analyze the wind speed-up ratios in 12 wind directions for both a small isolated mountainous area and a large continuous mountainous area. The significant speed-up regions are determined by consolidating the speed-up ratios from all 12 wind directions. The reliability of the judgment criteria is then validated. The results confirm that significant speed-up ratios are predominantly concentrated at the edges of mountainous areas, particularly at peaks and high ridges around areas with larger elevation coefficient of variation. These regions largely coincide with the locations where flashover incidents mainly occurred and the results from wind tunnel experiments and CFD simulations. In summary, the clearly identified significant speed-up regions include (1) small isolated mountainous areas; (2) peaks and high ridges around areas with larger elevation coefficient of variation within large continuous mountainous areas, and the higher crests within these regions. Based on these findings, the study suggests that wind speed-up ratios in design standards should be amplified in the vicinity of these regions to enhance safety measures.

A statistical evaluation of the morphological variability of shortening landforms on Mercury

Observations of Mercury from both the Mariner 10 and MESSENGER missions showed that Mercury has a global population of shortening landforms, with several thousands of individual structures identified to date. The accommodation of widespread tectonic shortening is widely regarded to be the result of global contraction—the long, sustained cooling of the interior that has caused the planet to shrink. Shortening landforms on Mercury have been traditionally categorized into three distinct categories: lobate scarps, wrinkle ridges, and high-relief ridges. Although the clearest examples of shortening landforms at the time were used to describe and define these categories qualitatively, later studies showed that shortening landforms on Mercury display morphological characteristics that do not make for a ready classification into one of these “traditional” groups. More recently, other studies have classified shortening landforms based on the terrain that those landforms reside in to avoid generalizing morphology. In this study, we quantitatively assess the shape of shortening landforms by measuring and compiling a suite of 12 morphological parameters for 100 such structures across the planet. These parameters were evaluated for their importance in defining categories using two multivariate statistical analyses, a Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA). These methods allow us to assess any correlation that the traditional categories, terrain types, or alternative classification schemes have with the variation observed across our set of measurements. Our results show that the morphologic characteristics of shortening landforms on Mercury are not accurately captured by traditionally recognized groups. Instead, shortening landforms fall along a morphological spectrum, where only a few ideal examples of lobate scarps or wrinkle ridges provide clear endmembers. Therefore, despite the frequent use of the terms “lobate scarps” and “wrinkle ridges” in works regarding planetary tectonics, we find that such terminology does not appropriately define the morphology of shortening landforms found on Mercury and may lead to the generalization, or misinterpretation of landforms described as accommodating shortening on Mercury's surface. Future studies should test if a distinction between the landforms is found in the underlying thrust fault systems.

Airborne single-photon LiDAR towards a small-sized and low-power payload

Single-photon light detection and ranging (LiDAR) has played an important role in areas ranging from target identification and 3D imaging to remote sensing. Its high sensitivity provides the feasibility of lightweight LiDAR systems for the resource-limited airborne and spaceborne platforms. Here, we design and demonstrate an airborne single-photon LiDAR towards the compact, small-sized, and low-power payload. To reduce the system size, we utilize small telescopes with an optical aperture of 47 mm and develop the sub-pixel scanning approach to enhance the imaging resolution. With the fine scanning mirrors, we validate the super-resolution ability in the ground experiment by surpassing the system’s resolution by 2.5 times and achieve high-resolution 3D imaging in the airborne experiment. To realize low-power LiDAR, we employ photon-efficient computational algorithms and high-quality single-photon avalanche diode (SPAD) arrays. This enables us to reconstruct images from noisy data even under challenging conditions of two signal photons per pixel. Using the airborne single-photon LiDAR system, we demonstrate 3D imaging during daytime over a large area for remote sensing applications and show the capability to reveal the detailed features of various landforms and objects.

Spatial distribution of near-fault landslides along Litang fault zones, eastern Tibetan Plateau

Active fault zones are areas impacted by intense tectonic activity, where geohazards such as landslides occur and their distribution characteristics vary across segments. Using the Litang fault zone in the eastern Tibetan Plateau as an example, this study cataloged landslides within a 10 km range on both sides of the fault zone. The Litang fault zone was divided into four sections based on landform characteristics and the spatial distribution of active faults. A comprehensive analysis was conducted on the relationship between landslide distribution and topography, lithology, and active faults in different sections. Additionally, the study employed a random forest model to compare landslide susceptibility between the whole-region and its sub-regions. The results show that lithology and topography significantly influence the distribution of landslide types. The Upper Triassic sandstone, Slate exhibit more debris flows in areas with slopes ranging from 5° to 35°, while slopes >35° in the Upper Triassic sandstone, Slate are prone to unstable slopes. Rock avalanche occur in Upper Triassic sandstone, Slate, and Quaternary sand and gravel. Active faults play a key role in control ling landslides distribution through distance, hanging wall, locked segment, and direction effects. The number of landslides is positively correlated with the activity of faults. Additionally, the dip angle and motion characteristics of faults have significant influence on the distribution of landslides. The results of landslide susceptibility evaluation show that sub-region models have higher accuracy than the whole-region model. This study provides a new method for exploring the spatial distribution of landslides and can provide scientific reference for reducing landslide disasters in active fault zones.

An Overview of Geomorphological Mapping: A Case Study of Rimbi Chhu River Basin, Sikkim, India

Geomorphology is the primary science which demonstrates the basic understanding and mapping of terrain features. A geomorphological map consists of scientific data and dynamic source of information on characteristics of landforms, their origin and evolution, which can be recorded in a map form. Basin hydrology also gets impacted by the terrain features of a basin as overland flow, stream flow and through flow is largely determined by the underneath surface. The configuration of the basin topography reflects the nature of the interaction between process and form. Profound understanding and in depth analysis of geomorphological features of a river basin can provide beneficial information for predicting, preventing and mitigating natural hazards; managing natural resources sustainably for future generation. Implementation of remote sensing and GIS techniques have fostered incredible improvements in landform recognition and accelerated the growth of geomorphological research. The river Rimbi Chhu has been selected as the study area in order to determine terrain configuration in relation with geomorphological features of the basin area. Visual representation of terrain (such as aspect, slope, channel networks, different river profiles, shaded relief and flow direction) and geomorphological (saddle, ridge line, convex-concave slope, rounded hills, fault for instance) derivatives is therefore illustrated, as well as a description of the challenges and crisis that can occur in this context.

Segment Anything Model Can Not Segment Anything: Assessing AI Foundation Model’s Generalizability in Permafrost Mapping

This paper assesses trending AI foundation models, especially emerging computer vision foundation models and their performance in natural landscape feature segmentation. While the term foundation model has quickly garnered interest from the geospatial domain, its definition remains vague. Hence, this paper will first introduce AI foundation models and their defining characteristics. Built upon the tremendous success achieved by Large Language Models (LLMs) as the foundation models for language tasks, this paper discusses the challenges of building foundation models for geospatial artificial intelligence (GeoAI) vision tasks. To evaluate the performance of large AI vision models, especially Meta’s Segment Anything Model (SAM), we implemented different instance segmentation pipelines that minimize the changes to SAM to leverage its power as a foundation model. A series of prompt strategies were developed to test SAM’s performance regarding its theoretical upper bound of predictive accuracy, zero-shot performance, and domain adaptability through fine-tuning. The analysis used two permafrost feature datasets, ice-wedge polygons and retrogressive thaw slumps because (1) these landform features are more challenging to segment than man-made features due to their complicated formation mechanisms, diverse forms, and vague boundaries; (2) their presence and changes are important indicators for Arctic warming and climate change. The results show that although promising, SAM still has room for improvement to support AI-augmented terrain mapping. The spatial and domain generalizability of this finding is further validated using a more general dataset EuroCrops for agricultural field mapping. Finally, we discuss future research directions that strengthen SAM’s applicability in challenging geospatial domains.