Interpretation Of High-resolution Satellite Images Research Articles

Co-Seismic Landslides Triggered by the 2014 Mw 6.2 Ludian Earthquake, Yunnan, China: Spatial Distribution, Directional Effect, and Controlling Factors

The 2014 Mw 6.2 Ludian earthquake exhibited a structurally complex source rupture process and an unusual spatial distribution pattern of co-seismic landslides. In this study, we constructed a spatial database consisting of 1470 co-seismic landslides, each exceeding 500 m2. These landslides covered a total area of 8.43 km2 and were identified through a comprehensive interpretation of high-resolution satellite images taken before and after the earthquake. It is noteworthy that the co-seismic landslides do not exhibit a linear concentration along the seismogenic fault; instead, they predominantly extend along major river systems with an NE–SW trend. Moreover, the southwest-facing slopes have the highest landslide area ratio of 1.41. To evaluate the susceptibility of the Ludian earthquake-triggered landslides, we performed a random forest model that considered topographic factors (elevation, slope, aspect, distance to rivers), geological factors (lithology), and seismic factors (ground motion parameters, epicentral distance, distance to the seismogenic fault). Our analysis revealed that the distance to rivers and elevation were the primary factors influencing the spatial distribution of the Ludian earthquake-triggered landslides. When we considered the directional variation in ground motion parameters, the AUC of the model slightly decreased. However, incorporating this variation led to a significant reduction in the proportion of areas classified as “high” and “very high” landslide susceptibility. Moreover, SEDd emerged as the most effective ground motion parameter for interpreting the distribution of the co-seismic landslides when compared to PGAd, PGVd, and Iad.

Geoecological effects of the outflow of 11-T Gunyushki geothermal well in the territory of the Chechen Republic

The purpose of the study is a geoecological assessment of the effect of groundwater flowing from geothermal wells through an energetically saturated coolant with its mineral component on natural and natural-economic components as well as on the structure of the entire enclosing landscape for the case of 11-T Gunyushki well of the Chechen Republic (Russia). The impact of the mineralized waters outflowing from geothermal wells on natural and natural-economic components and on the whole structure of the entire enclosing landscape is a challenging environmental problem for all oil and gas regions of Russia. Long-term outflow of thermal water from the well under consideration resulted in landscape trans-formation and suppression of the vegetation cover. Moreover, a stable source of pollution was formed in the place where untreated water from hand-crafted balneological facilities (baths, showers) was discharged that caused a radical restructuring of plant communities. The conducted research is based on the field data obtained by a team of authors on landscape mapping. Interpretation of high-resolution satellite images has shown the dynamics of landscape changes under the influence of thermal waters. The authors took water and soil samples and questioned local residents, which made it possible to adjust the scale and possibilities of using these waters. The research performed allowed to develop a physical-geographical profile, create a landscape map of the area affected by a geothermal well and an index map of the geoecological zoning of the area under investigation as well as identify the main types of the most transformed landscapes resulting from the combined impact of several anthropogenic factors (humidification and impact on the soil and vegetation cover). Conducted study has shown that more than 120 hectares of fertile lands were withdrawn from agriculture due to the anthropo-genic impact. The analysis of the index map of geoecological zoning demonstrates that 79 % of the territory is located in the zone of a weak indirect environmental impact, 7.14 % – in the zone of a strong indirect environmental impact, 13.5 % – in the zone of a strong direct environmental impact. The latter, requires reclamation in order to restore landscapes, since it undergoes desertification. Having performed a number of chemical analyses of water, the authors gave recommendations for the further use of thermal waters in the economy of the Groznensky region.

Морфометрический анализ агроландшафтов переходной зоны южных черноземов и темно-каштановых почв Волгоградской области

This article presents the results of geoinformation cameral mapping and morphometric analysis of one of the types of agrolandscape - arable land in the Mikhailovsky district of the Volgograd region. The relevance of the study is due to the lack of statistical data regarding the areas and configuration of individual fields, as well as the rapid development of areas of application of geographic information systems and remote sensing data in agriculture. For mapping, the method of visual expert interpretation of multispectral Earth remote sensing data of high (Sentinel satellite images for 2021) and medium (Landsat satellite images for 1986) spatial resolution was used. For morphometric analysis, a digital elevation model “SRTM” with a height resolution of 10 m was used. All operations with raster and vector materials were carried out in the geoinformation environment “QGIS”, statistical processing of the obtained data was carried out in “MS Excel”. 2,248 fields were mapped, which are arable land and fallows, with a total area of 229.8 thousand hectares. It was revealed that the predominant spatial orientation of the fields is the southwestern and northeastern direction, the smallest area is occupied by fields with a southeastern orientation. The largest field area is located in areas with surface slopes up to 1.5°. The maximum slope is 4°. Based on the results of the work, maps-schemes of the exposition and the steepness of the slopes of the fields in the Mikhailovsky district were compiled. The used mapping method based on the interpretation of high-resolution satellite images showed high accuracy. The data obtained can be used as a basis for more detailed studies of arable land in the Mikhailovsky district, as well as for planning land reclamation measures.

Assessment of Shoreline Transformation Rates and Landslide Monitoring on the Bank of Kuibyshev Reservoir (Russia) Using Multi-Source Data

This study focuses on the Kuibyshev reservoir (Volga River basin, Russia)—the largest in Eurasia and the third in the world by area (6150 km2). The objective of this paper is to quantitatively assess the dynamics of reservoir bank landslides and shoreline abrasion at active zones based on the integrated use of modern instrumental methods (i.e., terrestrial laser scanning—TLS, unmanned aerial vehicle—UAV, and a global navigation satellite system—GNSS) and GIS analysis of historical imagery. A methodology for the application of different methods of instrumental assessment of abrasion and landslide processes is developed. Different approaches are used to assess the intensity of landslide and abrasion processes: the specific volume and material loss index, the planar displacement of the bank scarp, and the planar-altitude analysis of displaced soil material based on the analysis of slope profiles. Historical shoreline position (1958, 1985, and 1987) was obtained from archival aerial photo data, whereas data for 1975, 1993, 2010, 2011, and 2012 were obtained from high-resolution satellite image interpretation. Field surveys of the geomorphic processes from 2002, 2003, 2005, 2006, 2014 were carried out using Trimble M3 and Trimble VX total stations; in 2012–2014 and 2019 TLS and UAV surveys were made, respectively. The monitoring of landslide processes showed that the rate of volumetric changes at Site 1 remained rather stable during the measurement period with net material losses of 0.03–0.04 m−3 m−2 yr−1. The most significant contribution to the average annual value of the material loss was snowmelt runoff. The landslide scarp retreat rate at Site 2 showed a steady decreasing trend, due to partial overgrowth of the landslide accumulation zone resulting in its relative stabilization. The average long-term landslide scarp retreat rate is—2.3 m yr−1. In 2019 earthworks for landscaping at this site have reduced the landslide intensity by more than 2.5 times to—0.84 m yr−1.

Paleocryogenesis and erosional landform development in the Baikal region, Siberia, during the second half of the Late Pleistocene and the Holocene

In the Cis- and Trans-Baikal regions of the southern part of Eastern Siberia, the detailed study and dating of geoarchaeological deposits and the erosion channel network (gullies, floodplains, and river terraces), along with the interpretation of high-resolution satellite images, have revealed areas of modern cryogenic processes as well as horizons with cryoturbations from the second half of the Late Pleistocene and the Holocene (MIS 3–1). Modern cryogenic landforms are found in swampy areas on gentle slopes, floodplains, and river terraces and are mainly represented by cryogenic cracks, hummocks, and thaw sinks; in river beds they are represented by icings. This paper establishes the formation ages of cryogenic horizons and distinguishes the permafrost phenomena of MIS 3–1.The stages of cryogenesis are associated with cold events, permafrost aggradation, the activation of cryogenic processes, and ice wedge polygon relief formation. During interglacials and interstadials, climate warming lead to permafrost degradation, ice thawing, active layer growth, erosion, cryokarst (thermokarst) development, suffusion, the acceleration of slope processes, the infilling of cryogenic relief forms, erosion network changes, the activation of erosion-accumulative processes, and sedimentation in river valleys.The second half of the Late Pleistocene contains five stages of active cryogenesis (49–42 k, 38–32.5 k, 29–23 k, 21–14.5 k, 12.9–11.7 k cal. BP),11Most dates are calibrated BP. Uncalibrated dates are presented as BP. each of which can be further divided into shorter phases. For example, in the Nadeino section (Western Trans-Baikal), three layers are distinguished with cryoturbations dated ~14.5–14.4 k, ~12.7–12.5 k, and 11.9–11.7 k cal. BP. In the Nizhniaia Bulanka section, one cryogenic horizon (formed at ~12.8–11.8 k cal. BP) was identified. Cryogenic horizons are categorized as syngenetic or epigenetic depending on the formation process.Polygonal-block reliefs (hummocks) are clearly visible in high-resolution space images of river basins on floodplains, terraces, watersheds, and gentle slopes within arable lands. These hummocks range from 4 to 50 m wide and 0.5–3 m high, and are divided by swales and hollows. The paleocryogenic relief on the watersheds and slopes formed in Early MIS 2 (29–23 k cal. BP) and, subsequently, experienced several stages of aggradation and degradation, resulting in a hummocky-hollow relief with sporadic permafrost distribution. Degradation of the permafrost during Late Glacial (15–11 k BP) and Early Holocene warming caused the formation of thermokarst (cryokarst), sheet and gully erosion, suffusion, sedimentation in river valleys, and changes in the microrelief of the upper links of the erosion network. Existing dells, rills, and gullies are the modern manifestations of paleocryogenic depressions and troughs.

Landslide probability mapping by considering fuzzy numerical risk factor (FNRF) and landscape change for road corridor of Uttarakhand, India

Landslide poses severe threats to the natural landscape of the Lesser Himalayas and the lives and economy of the communities residing in that mountainous topography. This study aims to investigate whether the landscape change has any impact on landslide occurrences in the Kalsi-Chakrata road corridor by detailed investigation through correlation of the landslide susceptibility zones and the landscape change, and finally to demarcate the hotspot villages where influence of landscape on landslide occurrence may be more in future. The rational of this work is to delineate the areas with higher landslide susceptibility using the ensemble model of GIS-based multi-criteria decision making through fuzzy landslide numerical risk factor model along the Kalsi-Chakrata road corridor of Uttarakhand where no previous detailed investigation was carried out applying any contemporary statistical techniques. The approach includes the correlation of the landslide conditioning factors in the study area with the changes in land use and land cover (LULC) over the past decade to understand whether frequent landslides have any link with the physical and hydro-meteorological or, infrastructure, and socioeconomic activities. It was performed through LULC change detection and landslide susceptibility mapping (LSM), and spatial overlay analysis to establish statistical correlation between the said parameters. The LULC change detection was performed using the object-oriented classification of satellite images acquired in 2010 and 2019. The inventory of the past landslides was formed by visual interpretation of high-resolution satellite images supported by an intensive field survey of each landslide area. To assess the landslide susceptibility zones for 2010 and 2019 scenarios, the geo-environmental or conditioning factors such as slope, rainfall, lithology, normalized differential vegetation index (NDVI), proximity to road and land use and land cover (LULC) were considered, and the fuzzy LNRF technique was applied. The results indicated that the LULC in the study area was primarily transformed from forest cover and sparse vegetation to open areas and arable land, which is increased by 6.7% in a decade. The increase in built-up areas and agricultural land by 2.3% indicates increasing human interference that is continuously transforming the natural landscape. The landslide susceptibility map of 2019 shows that about 25% of the total area falls under high and very high susceptibility classes. The result shows that 80% of the high landslide susceptible class is contained by LULC classes of open areas, scrubland, and sparse vegetation, which point out the profound impact of landscape change that aggravate landslide occurrence in that area. The result acclaims that specific LULC classes, such as open areas, barren-rocky lands, are more prone to landslides in this Lesser Himalayan road corridor, and the LULC-LSM correlation can be instrumental for landslide probability assessment concerning the changing landscape. The fuzzy LNRF model applied has 89.6% prediction accuracy at 95% confidence level which is highly satisfactory. The present study of the connection of LULC change with the landslide probability and identification of the most fragile landscape at the village level has been instrumental in delineation of landslide susceptible areas, and such studies may help the decision-makers adopt appropriate mitigation measures in those villages where the landscape changes have mainly resulted in increased landslide occurrences and formulate strategic plans to promote ecologically sustainable development of the mountainous communities in India's Lesser Himalayas.

From surface morphologies to inner structures: insights into hypermobility of the Nixu rock avalanche, southern Tibet, China

Large rock avalanches often result in many deaths and catastrophic damage to infrastructure far from source. No consensus has yet been reached on mechanisms causing their extraordinarily long runout since the first study at the Elm Slide, Switzerland. Much current understanding of rock avalanche kinematics and dynamics has been gained from observations of their surface morphologies and inner structures. Based on field surveys, high-resolution satellite image interpretation, and laboratory sieving, we analyzed the ancient, earthquake-induced Nixu rock avalanche in southern Tibet, China, which has unique exposures of both morphological features and inner structures of the deposits. The study revealed that (1) the Nixu rock avalanche probably could be disintegrated into three emplacement stages, transforming from an initial deep-seated rockslide into a large secondary debris avalanche, plus a relatively small third debris avalanche. The spreading of the secondary debris avalanche contributed to the subsequent long-runout propagation. (2) The morphological features observed in successive proximal to distal exposures (such as scarps, flowbands, transverse ridges, grid grooves, hummocks, and splash zones) reflect the change in stress-strain state of debris in motion from tension, to compression, to shear and tension. (3) The complicated inner structures exposed along river banks (such as jigsaw structures, fragmented clasts, inner shear zones, conjunction faults, convoluted lamination, decollements, sand injections, and intrusions) indicate the existence of a thin basal shear zone and a pressurized entrained substrate between the substrate and rock avalanche debris. (4) This suggests turbulent flow with bulldozing in the front, but a laminar flow under a simple shear model for the main body. (5) The analysis suggests that the rock avalanche’s extraordinary mobility involves a combination of momentum transfer, substrate entrainment, liquefied basal shearing, internal shearing, and rock fragmentation.

Environmental factors and human activity as drivers of tree cover and density on the Island of Socotra, Yemen

Socotra Island, in the western Indian Ocean, harbors high biodiversity and endemism and makes up the largest part of the Socotra archipelago UNESCO World Heritage site. Its climatic, pedological, and geomorphological characteristics, together with the long geological isolation and inaccessibility, led to the flourishing of unique tree diversity, with great cultural and ecological value. Lately, trees on Socotra are facing new threats linked to the abandonment of traditional management practices, climate change impacts, and growing human pressure. This study assesses the relative influence of environmental factors and human activity as drivers of tree cover and density, which can be used to support land management policies for the conservation of this key local resource. Tree cover and density were assessed on a total of 3600 plots of 0.5 ha each, laid on a regular grid covering the entire area of the island through Collect Earth, a free open source software tool that allows an augmented visual interpretation of high-resolution satellite images. A total of 770,000 trees, with an average of 2.14 trees/ha, were estimated on the island. The collected data was validated by ground surveys in 26 plots. The relative influence of selected predictors (seven environmental, two anthropic) on tree cover and density was analyzed through logistic and survival regression. Tree cover and density were found to be impacted positively by steeper slopes, higher rainfall, and marked precipitation seasonality and negatively by relatively warmer temperatures and a higher sand content in the soil. Distance of each plot from the nearest road and settlement was calculated and neither of these anthropic predictors emerged as significant, indicating that the limited number of trees present are not currently as affected by anthropic pressure, but, instead, their presence is mostly limited by the harsh climatic and pedological factors. However, as human population and development increase, periods of drought rise, and extreme and random climatic events intensify, these additional stresses on the environment could negatively impact the availability of natural resources in the terrestrial environment. Lastly, potential recommendations to the existing conservation policies and Socotra Conservation Zoning Plan are discussed based on the results.

Timing and seismic origin of Nixu rock avalanche in southern Tibet and its implications on Nimu active fault

In tectonically active mountain areas, the identification, dating and determination of origin of large landslides are of special importance in recognizing the seismicity and earthquake magnitude of regional faults, reconstructing the prehistoric landscape evolution and estimating the seismic hazards. Based on field survey, high-resolution satellite image interpretation and 14C dating of substrate, this paper studied the large, long-runout Nixu rock avalanche (the NXRA) in the Angang graben of the southern Tibetan Plateau. The study revealed that: (1) the deep-seated Nixu rock avalanche straddles the Nimu active normal fault and spreads onto the Angang basin with a deposit volume of 47 Mm3 and a travelling distance of 4960 m. (2) Humus samples immediately under the deposit of rock avalanche along the natural river-erosion section suggest a 14C age of 820 ± 30 BP (1220 ± 30 CalAD) for the NXRA event. The age well matches the 1264 CE Chubushi earthquake recorded in Tibetan documents. (3) 23 adjacent landslides have been recognized with co-seismic distribution features, such as clustering and distance effect, ridge-end amplification effect and slope aspect effect. Sand liquefaction and peat deformation were discovered in the substrate beneath and at a distance of ~300 m away from the avalanche deposit. (4) This information indicate that the NXRA was triggered most likely by the 1264 Chubushi earthquake with a magnitude of Mw 7.0–7.2 estimated by empirical equations of Keefer (1994) and Wells & Coppersmith (1994). It is suggested that the Nimu fault of the Yadong-Gulu rift may be more hazardous than the northern and southern part due to its high susceptibility of large co-seismic landslides.

СОВРЕМЕННЫЕ ДЕСТРУКТИВНЫЕ РУСЛОВЫЕ ПРОЦЕССЫ р. ОНОН ЗАБАЙКАЛЬСКОГО КРАЯ

The specificity of the territory of the upper Amur basin is shown, which consists in a significant variety and complexity of natural complexes. The object of the study was the Onon river, the subject-riverbed processes that occur in the territory under the influence of natural factors. The purpose of the study is to identify, analyze and evaluate the scale of development of riverbed processes in the upper Amur basin. The tasks were to identify active areas of water erosion. Onon, spatial analysis of the received information, identification of the dynamics and intensity of riverbed processes in active areas during the destructive leash of 2018 and beyond. The relevance of the work has been determined by the need to quickly identify and prevent the development of riverbed processes for erosion control and rational use of land resources for further industrial use. The research methods used are analysis and interpretation of high-resolution satellite images and other multi-time cartographic materials, processing and digitization of images. The main natural channel-forming factors of the Onon river that determine the current dynamics of channel deformations are identified and analyzed. The theoretical and practical significance of the study is to determine the degree of influence on riverbed processes of various riverbed-forming natural factors. The necessity of carrying out measures on the territory of the upper Amur basin to solve water management problems is justified

Опыт определения площади городской застройки по космическим снимкам для задач метеорологического моделирования (на примере Москвы)

Detailed weather and climate modeling for urban areas is in demand in various scientific and applied tasks, starting from a numerical weather forecast and ending with an assessment of the bioclimatic conditions of the city and long-term urban planning. The application of modern meteorological models for urban areas requires the determination of a set of parameters characterizing the urban environment and urban canopy features. One of these parameters is the area fraction, occupied by buildings. In this paper, we propose a universal method for determining building area fraction based on the interpretation of high-resolution satellite images from the Sentinel-2 satellites. The methodology was tested on the example of the territory of the city of Moscow, characterized by a variety of forms of urban development. The calculation of the building area fraction was performed for the cells of the computational grid of the COSMO mesoscale numerical meteorological model with 1 km spacing. To verify the developed method, we used an alternative estimate of the building area fraction based on the crowdsourcing cartographic data OpenStreetMap. The data on the building area fraction derived from the satellite images and from OpenStreetMap data have shown a good mutual agreement, which confirms the promise of using the proposed methodology. On the example of territories where the two methods show significant differences, their typical causes are identified, namely the lack of information about buildings in the OpenStreetMap database, or the masking of buildings by trees, which does not allow them to be revealed from satellite images.

Thematic interpretation of high-resolution satellite images of vegetation based on field research data

Thematic interpretation of high-resolution satellite images of vegetation based on field research data

10Be dating and seismic origin of Luanshibao rock avalanche in SE Tibetan Plateau and implications on Litang active fault

Moderate-large earthquakes usually trigger a large number of landslides. The prehistoric large landslides can be analyzed to determine the probability of its seismic origin, and further recognized as an indicator of fault activity and earthquake intensity. Based on field investigation, high-resolution satellite image interpretation and cosmogenic exposure dating of landslide deposit, the paper presents a large, long-runout Luanshibao rock avalanche (the LSB rock avalanche), southeast Tibet. The study reveals that (1) the LSB rock avalanche straddles the Litang active strike-slip fault and deposits on the open-flat Quaternary Maoya basin, with a deposit volume of 67 Mm3 and an apparent coefficient of friction of 0.22. (2) Totally, 8 granite blocks from the proximal to the medial part of deposit dated by the Terrestrial Cosmogenic Nuclide method suggests an average 10Be exposure age of 3510 ± 346 a B.P. for the LSB rock avalanche; (3) the spatial-temporal intercutting relationships among the LSB rock avalanche, Quaternary sediments, and the Litang active fault suggest five strong paleoseismic events in the Maoya basin, which is temporally in accordance to the result defined by paleoearthquake-trench research; (4) the corresponding maximum magnitude could reach MW 7.1 ± 0.1 by the empirical equations between landslide volume and earthquake magnitude. It suggests that the Maoya section of Litang fault is probably more dangerous than other sections due to the high density of large co-seismic landslides, which could present useful reference for the alignment selection of future Sichuan-Tibet railway.

Contemporary gully erosion trend in the northern part of the forest-steppe zone of the Russian Plain: a case study from the Republic of Tatarstan, European Russia

Abstract. This article presents results for gully head cut retreat rates (GHRR) in the Pre-Kama region (Republic of Tatarstan, Russia) based on monitoring (1984–1994 and 2015–2018) and the interpretation of high-resolution satellite images (2004–2014). The results suggested that the mean linear GHRR have reduced by about five times, from 1.6 m per year (1983–1994) to 0.4 m per year (2015–2018). The main reason for the significant decrease in gully erosion was the increase in winter-spring air temperatures, which resulted in a reduction in the depth of soil freezing and surface runoff. The impact of land use, as well as erosion control measures, which were implemented in the study area during the late 1980s and early 1990s, was found to be less important.

Earthquake geology of the last millennium along the Boconó Fault, Venezuela

The Holocene tectonic activity of Latin American countries is poorly constrained because of the short time span of the instrumental record and the lack of any seismic calendar during pre-colonization times. Therefore, some areas with low and diffused seismicity have been catalogued as a “seismic gap”. It has been suggested that the northernmost segment of the Boconó Fault in Venezuela is one of these areas, although a recent MW 7.4 event that occurred in 1812 has been well documented by a historical investigation. In this study, we mapped the historical events triggered by the Boconó Fault using a paleoseismological investigation, a geological interpretation of high-resolution satellite images, field mapping as well as ground-penetrating radar (GPR) profiles at selected trench sites. Our results suggest that at least three seismic events had produced surface ruptures in the trench site based on the exposed trench stratigraphy as well as the results of radiocarbon dating and age models: i) a latest event (E3) that occurred between 1545 and 1825 CE, ii) a previous event (E2) that occurred between 1483 and 1743 CE and iii) an older event (E1 before 1456–1636 CE). The E3 event might correspond to the 1812 major earthquake. These results further support the fact that the 1812 event was triggered by the Boconó Fault and that the rupture reached the surface. The potential slip deficit along the studied segment ranges from 1.7 to 2.3 m and corresponds to Mw ~7, assuming that the 1812 CE earthquake released all of the strain stored earlier. As the time span between events E2 and E3 is short (<360 years), it is worth to pay a great attention to the seismic risk assessment for a densely inhabited Boc-e fault segment.

Chronology of Magmatic Activity and Petrologic–Mineralogical Characteristics of Lavas of Kazbek Quaternary Volcano, Greater Caucasus

The paper presents detailed isotope-geochronological, geological, and petrologic–mineralogical data on lavas of one of the greatest Quaternary magmatic area in the Greater Caucasus, the Kazbek neovolcanic center, including polygenetic Kazbek stratovolcano and a number of subordinate volcanic cones in its vicinities. The research was conducted based on a representative collection of more than 150 geological samples that characterize most of the volcanic cones and lava flows of different age, some of which were known previously, and other were discovered by the authors. The high-precision K–Ar data obtained on these materials make it possible to reproduce the evolutionary history of youngest magmatism at the Kazbek center and evaluate the total duration of this evolution at ~450 ka. The magmatic activity was subdivided into four phases (at 460–380, 310–200, 130–90, and <50 ka) with long-lasting interludes in between. Because the latest eruptions occurred in the Kazbek vicinity in the Holocene, this volcano is regarded as potentially active. The volcanic rocks of the Kazbek center make up a continuous compositional succession of basaltic (trachy)andesite–(trachy)andesite–dacite and mostly belong to the calc–alkaline series. The principal petrographic characteristics of the rocks and the composition of their phenocryst minerals are determined, mineral assemblages of these minerals are distinguished in the lavas of different type, and the temperature of the magmatic melts is evaluated. A principally important role in the petrogenesis of the Kazbek youngest magmas is proved to have been played by fractional crystallization and replenishment of mafic melts in the magmatic chambers beneath the volcano, which resulted in their mixing and mingling with the residual dacite melt and the origin of high-temperature hybrid andesite lavas. The comprehensive geological studies, involving interpretation of high-resolution satellite images, allowed the authors to compile the first detailed (1: 25 000) volcanologic map of the Kazbek center and a geochronologic chart supplemented with a stratigraphic column, which illustrate the origin sequence of the volcanic vents and their lava flows, geological relations between them, as seen in reference geological sections, and variations in the composition of the magmatic products with time.

Multi-Task Joint Sparse and Low-Rank Representation for the Scene Classification of High-Resolution Remote Sensing Image

Scene classification plays an important role in the intelligent processing of High-Resolution Satellite (HRS) remotely sensed images. In HRS image classification, multiple features, e.g., shape, color, and texture features, are employed to represent scenes from different perspectives. Accordingly, effective integration of multiple features always results in better performance compared to methods based on a single feature in the interpretation of HRS images. In this paper, we introduce a multi-task joint sparse and low-rank representation model to combine the strength of multiple features for HRS image interpretation. Specifically, a multi-task learning formulation is applied to simultaneously consider sparse and low-rank structures across multiple tasks. The proposed model is optimized as a non-smooth convex optimization problem using an accelerated proximal gradient method. Experiments on two public scene classification datasets demonstrate that the proposed method achieves remarkable performance and improves upon the state-of-art methods in respective applications.

Landslide susceptibility maps using different probabilistic and bivariate statistical models and comparison of their performance at Wadi Itwad Basin, Asir Region, Saudi Arabia

The purpose of the current study is to produce landslide susceptibility maps using different probabilistic and bivariate statistical approaches; namely, frequency ratio (FR), weights-of-evidence (WofE), index-of-entropy (IofE), and Dempster–Shafer (DS) models, at Wadi Itwad, Asir region, in the southwestern part of Saudi Arabia. Landslide locations were identified and mapped from interpretation of high-resolution satellite images, historical records, and extensive field surveys. In total, 326 landslide locations were mapped using ArcGIS and divided into two groups; 75 % and 25 % of landslide locations were used for training and validation of models, respectively. Twelve layers of landslide-related factors were prepared, including altitude, slope degree, slope length, topography wetness index, curvature, slope aspect, distance from lineaments, distance from roads, distance from streams, lithology, rainfall, and normalized difference vegetation index. The relationships between the landslide-related factors and the landslide inventory map were calculated using different statistical models (FR, WofE, IofE, and DS). The model results were verified with landslide locations, which were not used during the model training. In addition, receiver operating characteristic curves were applied, and area under the curve (AUC) was calculated for the different susceptibility maps using the success (training data) and prediction (validation data) rate curves. The results showed that the AUC for success rates are 0.813, 0.815, 0.800, and 0.777, while the prediction rates are 0.95, 0.952, 0.946, and 0.934 for FR, WofE, IofE, and DS models, respectively. Subsequently, landslide susceptibility maps were divided into five susceptibility classes, including very low, low, moderate, high, and very high. Additionally, the percentage of training and validating landslides locations in high and very high landslide susceptibility classes in each map were calculated. The results revealed that the FR, WofE, IofE, and DS models produced reasonable accuracy. The outcomes will be useful for future general planned development activities and environmental protection.

Landslide susceptibility delineation in the Ar-Rayth area, Jizan, Kingdom of Saudi Arabia, using analytical hierarchy process, frequency ratio, and logistic regression models

Mountain areas in the southern western corner of the Kingdom of Saudi Arabia (KSA) frequently suffer from various types of landsides induced by rainstorms and anthropogenic activities. To mitigate these problems, landslide susceptibility mapping and classification is important to develop quick and safe mitigation or remediation measures and to help the decision making in future planning by identifying the most vulnerable areas. This paper summarizes the findings of a landslide susceptibility analysis in the Ar-Rayth area, Jizan, KSA, using an analytical hierarchy process (AHP), frequency ratio (FR), and logistic regression (LR) models with the aid of GIS tools and remote sensing data. The landslide inventory map was prepared according to historical data, interpretation of high-resolution satellite images (Geo-Eye 0.5 m resolution and QuickBird 0.6 m resolution), topographic maps (1:10,000), and verified by field investigations. An inventory map with 253 landslides locations was extracted from many sources. The landslide inventory was randomly divided into two datasets: 75 % for training the models and 25 % for validation. An enhanced thematic mapper plus 15 m satellite image acquired in 2006 was used for determining the Normalized Difference Vegetation Index. A contour map (1:10,000 with a 10 m contour interval) was converted to digital elevation model 10 m resolution and subsequently converted to slope, slope aspect, curvature, elevation, and drainage networks. Geological data obtained with the help of satellite images were used to prepare lithological units and lineaments. Roads were digitized from the high-resolution image and a rainfall map was prepared from the rainfall gauges distributed throughout the study area. All these data were used to construct a spatial database using GIS and image processing. Three landslide susceptibility maps were constructed; one on the basis of a heuristic method using an AHP, the other two on the basis of landslide inventories and causative factors, using FR and LR. Furthermore, each causative factor’s weight was determined according to these three models and landslide susceptibility indices were calculated. For verification, receiver operating characteristic curves were calculated and the areas under the curve (AUC) for success rate are 0.755, 0.828, and 0.749 and for prediction rate are 0.708, 0.781, and 0.727 for the AHP, FR, and LR, respectively. In addition, the percentage of existing training landslides data in high and very high zones of the susceptibility maps is of 73.2, 85.31, and 88.59 % and for the validation landslides data is 73.2, 85.31, and 88.59 % for the AHP, FR, and LR, respectively. The findings indicated that the values of AUC are above 0.7 for both success and prediction rate which indicate these three models are suitable for susceptibility analysis. Also, percent of training and validation landslides data of high and very high zones indicate that LR model is more accurate followed by FR model and AHP model.

Landslide susceptibility mapping at Al-Hasher area, Jizan (Saudi Arabia) using GIS-based frequency ratio and index of entropy models

Mountain areas in the southern western corner of the Kingdom of Saudi Arabia frequently suffer from various types of landslides due to rain storms and anthropogenic activities. To resolve the problem related to landslides, landslide susceptibility map is important as a quick and safe mitigation measure and to help making strategic planning by identifying the most vulnerable areas. This paper summarizes findings of landslide susceptibility analysis at Al-Hasher area, Jizan, KSA, using two statistical models: frequency ratio and index of entropy models with the aid of GIS tools and remote sensing data. The landslide locations (inventory map) were identified in the study area using historical records, interpretation of high-resolution satellite images that include Geo-Eye in 2.5 m and Quickbird in 0.6m resolution, topographic maps of 1:10,000 scale, and multiple field investigations. A total of 207 landslides (80% out of 257 detected landslides) were randomly selected for model training, and the remaining 50 landslides (19%) were used for the model validation. Ten landslide conditioning factors including slope angle, slope-aspect, altitude, curvature, lithology, distance to lineaments, normalized difference vegetation index (NDVI), distance to roads, precipitation, and distance to streams, were extracted from spatial database. Using these conditioning factors and landslide locations, landslide susceptibility and weights of each factor were analyzed by using frequency ratio and index of entropy models. Our findings showed that the existing landslides of high and very high susceptibility classes cover nearly 80.4% and 79.1% of the susceptibility maps produced by frequency ratio and index of entropy models respectively. For verification, receiver operating characteristic (ROC) curves were drawn and the areas under the curve (AUC) were calculated for success and prediction rates. For success rate the results revealed that for the index of entropy model (AUC = 77.9%) is slightly lower than frequency ratio model (AUC = 78.8%). For the prediction rate, it was found that the index of entropy model (AUC = 74.9%) is slightly lower than the frequency ratio model (AUC = 76.7%). The landslide susceptibility maps produced from this study could help decision makers, planners, engineers, and urban areas developers to make suitable decisions.