Slope stability assessment in the seismically and landslide-prone road segment of Gerese to Belta, Rift Valley, Ethiopia.

Slope instability on several sections of the Gerese-Belta route in Southern Ethiopia poses a major risk to infrastructure and safety. This research was aimed at evaluating certain areas of the road susceptible to slope instability. Through intensive fieldwork including geological analysis, surveys, and testing, three crucial slope portions were determined. Both limit equilibrium and finite element calculations demonstrated that these sections are problematic under different circumstances. The slope modification analysis shows that the safety factor increases as bench widths and the number of benches increase. In the slope section D1S3, this factor reached 1.222 when two benches measuring 5 meters in width were used on slide 2D. This initially showed an unstable safety factor of 0.26. Three benches of the same width were used under slide 2D. This resulted in a safety factor of 1.219. At the slope section (D1S2), flattening of the slope angle from initial 45° to 35°, 28°, 25° and 18° increases the factor of safety of the slope from initial 0.284 to 0.77, 0.89, 1.022, and 1.151 respectively under slide 2D analysis. At the slope section (D2S1), flattening the slope angle from initial 46° to 35°, 25°, 23°, and 20° increases the safety factor from initial 0.412 to 0.684, 0.920, 1.02, and 1.315 respectively. Based on the analysis of the study results, it can be concluded that the identified slope sections are susceptible to failure under actual field scenarios, depending on the conditions under which they are predicted to occur. According to this study, the Benching method is an economical method for mitigating soil slopes, as a result of which it was recommended to be used.

Influence of buffer distance on environmental geological hazard susceptibility assessment.

Previous researches seldom studied the selection of buffer distance between geological hazards (positive samples) and non-geological hazards (negative samples), and its reasonable selection plays a very important role in improving the accuracy of susceptibility zoning, protecting the environment and reducing the cost of hazard management. Based on GIS technology and random forest (RF) and frequency-ratio random forest (FR-RF) models, this study innovatively explored the influence of randomly selected non-geological hazard samples outside different buffer distances on the susceptibility evaluation results, with buffer distances of 100 m, 500 m, 1000 m and 2000 m in sequence. The results show that through the confusion matrix and ROC curve test, the accuracy of the model increases first and then decreases with the increase of buffer distance. Both RF and FR-RF models have the highest accuracy when the buffer distance is 1000 m, and the accuracy of the RF model is generally higher than that of the FR-RF model under the same buffer distance. Similar attribute values of positive samples and randomly selected negative samples or "extreme" attribute values of negative samples are the main reasons for the differences in evaluation results of different buffer distances. According to the weight analysis of causative factors, the distance from road, the distance from river and the normalized vegetation index (NDVI) are the main factors affecting the occurrence of hazards. The high and very high susceptibility areas in the study area are mainly distributed on both sides of roads and water systems, which are the key areas for hazard prevention and reduction. The HMC of RF-1000m decreased by 3.55% on average compared with other models. The results of this study improve the accuracy of geological hazard susceptibility assessment, maintain the safety of ecological environment, and provide a scientific basis for the selection of buffer distance index in local and surrounding areas in the future.

Susceptibility assessment of environmental geological disasters in Liulin County based on RF: from the perspective of positive and negative sample proportion.

The rational selection of the proportion between geological disasters (positive samples) and non-geological disasters (negative samples) holds significant importance in enhancing the precision of geological disaster susceptibility assessment and maintaining the sustainable development of the ecological environment. This paper, using Liulin County as an example, employs correlation analysis to select appropriate evaluation factors. A Random Forest (RF) model, based on GIS technology, is used for susceptibility mapping. Sample ratios of 1:1, 1:1.5, 1:3, 1:5, and 1:10 are applied. The results indicate that, through a confusion matrix test, the model's predictive performance reaches a "tipping point" at a sample ratio of 1:5. The receiver operating characteristic (ROC) curve test shows that the 1:5 model performs best. Combining the proportion of susceptibility zones and disaster points, 1:5 is identified as the most suitable ratio for assessing geological disaster susceptibility in the study area. High and very high susceptibility zones are primarily concentrated in the central and northern regions alongside roads and rivers, making these areas key focuses for disaster prevention and reduction in Liulin County. The accuracy of the model's predictions increases with a greater number of samples, but it does not continue to rise indefinitely; accuracy declines after a critical threshold is crossed. These research findings complement prior studies, promote advances in geological disaster prevention technology, and maintain geological environmental stability, all of which are crucial for the local economy's stability and sustainable development.

Colima volcano's archive of observations: The invention of a geological history from Johann Mortiz Rugendas to Paul Waitz.

In 1936 the Austrian geologist Paul Waitz published a seminal bibliographical, historical essay on Colima volcano, Mexico. His article exemplifies well the paths by which geology became what Lorraine Daston has termed sciences of the archive, that is, the manner in which scientific disciplines became concerned with archival work. Waitz's historical description of studies of Colima volcano built a genealogy of observations, ultimately constructing a history of the volcano itself. By bringing attention not only to Waitz's discourse but also to his treatment of visual objects, such as pictorial and photographic landscapes, my article points out how long-term aesthetics, such as the picturesque and the sublime, functioned as tropes which enabled a standardized perception, essential to visualize a clear history of scientific observations, from the landscape paintings of the nineteenth-century artist Johann Moritz Rugendas to Waitz's own photographs.

Stability and probabilistic assessment of a large asymmetric bedding slope with a weak interlayer.

The mining of open-pit mines has a significant influence on the surrounding ecological environment and safety. Once the slope of an open pit is unstable, it will bring extremely severe disasters to the surrounding environment. The south slope of the Fushun West open-pit mine is a large bedding slope with weak interlayer and asymmetrical features between the eastern and western regions. The different deformation mechanisms are worth further discussion, and the deformation mechanism of the eastern region needs to be systematically investigated. In this study, a comprehensive method combining a numerical model, the limit equilibrium method, and a probabilistic approach is used. The different deformation mechanisms of the slope are explored. Thereafter, the sensitivity of the geometric and mechanical parameters of the slope is determined. Finally, the probability of failure (PF) and slope stability are evaluated. The results illustrate that the difference in geological characteristics and constraint conditions is the fundamental reason for the difference in deformation features of the slope. The sensitivity analysis results show that the friction angle of the weak layer exhibits the most sensitivity and that the unit weight is irrelevant to the slope stability. Taking the friction angle of the weak layer as a variable, when the thickness of the basalt layer is less than 140 m and the height of the slope is more than 360 m, the PF of the slope reaches a high value. When the inclination of the weak layer exceeds 30°, the PF of the slope increases to a high value. When the Ru coefficient exceeds 0.2, the slope presents a high PF. The results illustrate that decision-makers should pay attention to the strength degradation, transitional mining of the basalt layer, and establish a good drainage system. The comprehensive method can also provide an effective way to assess the stability and PF of similar large-scale bedding slopes under complex geological conditions.

Land subsidence susceptibility mapping: comparative assessment of the efficacy of the five models.

Land subsidence (LS) as a major geological and hydrological hazard poses a major threat to safety and security. The various triggers of LS include intense extraction of aquifer bodies. In this study, we present an LS inventory map of the Daumeghan plain of Iran using 123 LS and 123 non-LS locations which were identified through field survey. Fourteen LS causative factors related to topography, geology, hydrology, and anthropogenic characteristics were selected based on multi-collinearity test. Based on the results, five susceptibility maps were generated employing models and input data. The LS susceptibility models were evaluated and validated using the receiver operating characteristic (ROC) curve and statistical indices. The results indicate that the LS susceptibility maps produced have good accuracy in predicting the spatial distribution of LS in the study area. The result showed that the optimization models BA and GWO were better than the other machine learning algorithm (MLA). In addition, The BA model has 96.6% area under of ROC (AUROC) followed by GWO (95.8%), BART (94.5%), BRT (93.1%), and SVR (92.7%). The LS susceptibility maps formulated in our study can serve as a useful tool for formulating mitigation strategies and for better land-use planning.

Linking health to geology-a new assessment and zoning model based on the frame of medical geology.

With the growing concerns about the Earth's environment and human health, there has been a surge in research focused on the intersection of health and geology. This study quantitatively assesses the relationship between human health and geological factors using a new framework. The framework considers four key geological environment indicators related to health: soil, water, geological landform, and atmosphere. Results indicate that the atmospheric and water resource indicators in the study area were generally favorable, while the scores of geological landforms varied based on topography. The study also found that the selenium content in the soil greatly exceeded the local background value. Our research underscores the importance of geological factors on human health, establishes a new health-geological assessment model, and provides a scientific foundation for local spatial planning, water resource development, and land resource management. However, due to varying geological conditions worldwide, the framework and indicators for health geology may need to be adjusted accordingly.

Assessment of environmental geological disaster susceptibility under a multimodel comparison to aid in the sustainable development of the regional economy.

Environmental geological disasters pose a significant threat to human life, property and environmental safety. It is necessary to conduct targeted governance in key prevention and control areas based on reasonable susceptibility assessment. Using the debris flow disaster in Xiuyan County as an example, this study compares and analyzes prone prediction models such as the frequency ratio (FR), decision tree (DT) and random forest (FR) models and evaluates the cost of prevention and control and the protection of life and property. The research results show that the FR, DT and RF models have good performance. The ROC test, disaster point density statistics and cross-validation results show that the RF model has the best performance. The study area was mainly less and mildly prone areas. The highly prone areas are mainly distributed in the northeast and southwest of the study area. It is the key area of disaster prevention and control. Elevation, rainfall intensity and population density have the largest influence on the susceptibility to debris flows. Based on the RF model, the disaster points in the highly prone areas account for 54% of the disaster points of the whole area, and the project treatment cost of the disaster points is 0.78 million yuan per single gully, which protects 56% of the lives and property in the study area, which is better than the DT and FR models. The RF model not only has good prediction performance in terms of susceptibility. It can realize the targeted management of disasters, achieve the targeted investment of governance costs and the effective protection of life and property and serve the sustainable development of the regional environment and economy with greater value.

Quality and hydrochemical assessment of groundwater in geological transition zones: a case study from N.E. Nigeria.

Sustainable management of groundwater resources in geological transition zones (GTZ) is essential due to their complex geology, increasing population, industrialization, and climate change. Groundwater quality monitoring and assessment represent a viable panacea to this problem. Therefore, there is a great need to investigate groundwater resources in terms of their chemistry and pollution to ascertain their quality and implement robust pollution abatement strategies. This study focused on the characterization of groundwater in a typical geological transition zone in northeastern Nigeria. Eighty-seven (87) groundwater samples were collected from dug wells and boreholes during the 2017 dry season. pH, conductivity, and total dissolved solids (TDS) were measured in situ using a multiparameter probe, while major cations and anions were measured using atomic absorption spectrometry and ion chromatography, respectively. Data were analyzed using descriptive statistics, principal component analysis (PCA), water quality index, and standard hydrochemical plots. TDS ranged between 95 and 1154 mg L-1 in basement terrains and between 49 and 1105 in sedimentary areas. pH ranged between 6.8 and 7.7 mg L-1 in basement terrains and between 5.0 and 6.5 in sedimentary areas, suggesting a moderately acidic to alkaline low mineralized groundwater. Calcium (2.6-128.0 mg L-1) was the dominant cation in the basement areas, suggesting silicate weathering/dissolution, while sodium (1.9-106.0 mg L-1) dominated the sedimentary zones due to base exchange reactions. The PCA analysis suggests that mineral dissolution (mostly silicate weathering) controls the hydrochemistry of the basement aquifers, while ion exchange and albite weathering, with some influence of anthropogenic factor, control the sedimentary aquifers. The water quality index revealed that the basement setting was predominated by poor to unsuitable groundwater, while the sedimentary terrain was characterized by potable groundwater. The dominant hydrochemical facie in the basement areas was Ca2+-(Mg2+)-HCO3- characteristic of recharge meteoric water. The Na+- (K+)-HCO3- facie characterized the sedimentary zones, indicative of cation exchange reactions, while the mixed water facie typifies the geological contact zones. The shallow nature of the basement groundwaters makes them more susceptible to geogenic and anthropogenic pollution compared to the sandstone aquifers. However, the basement aquifers have better irrigation indices (Kelly ratio and soluble sodium percent) as compared to the sandstone aquifers, which exhibit poor Kelly ratios (< 1) and soluble sodium percent (> 50) ratings. Results from the study clearly highlight the poor-unsuitable groundwater quality in parts of the studied GTZ and can be very instrumental to the policymakers in implementing sustainable water treatment strategies and cleaner production technologies in GTZ to forestall the incidence of water-related diseases.

A Cost-Effective Distributed Acoustic Sensor for Engineering Geology.

A simple and cost-effective architecture of a distributed acoustic sensor (DAS) or a phase-OTDR for engineering geology is proposed. The architecture is based on the dual-pulse acquisition principle, where the dual probing pulse is formed via an unbalanced Michelson interferometer (MI). The necessary phase shifts between the sub-pulses of the dual-pulse are introduced using a 3 × 3 coupler built into the MI. Laser pulses are generated by direct modulation of the injection current, which obtains optical pulses with a duration of 7 ns. The use of an unbalanced MI for the formation of a dual-pulse reduces the requirements for the coherence of the laser source, as the introduced delay between sub-pulses is compensated in the fiber under test (FUT). Therefore, a laser with a relatively broad spectral linewidth of about 1 GHz can be used. To overcome the fading problem, as well as to ensure the linearity of the DAS response, the averaging of over 16 optical frequencies is used. The performance of the DAS was tested by recording a strong vibration impact on a horizontally buried cable and by the recording of seismic waves in a borehole in the seabed.

Spatio-temporal landslide inventory and susceptibility assessment using Sentinel-2 in the Himalayan mountainous region of Pakistan.

The 2005 Kashmir earthquake has triggered widespread landslides in the Himalayan mountains in northern Pakistan and surrounding areas, some of which are active and are still posing a significant risk. Landslides triggered by the 2005 Kashmir earthquake are extensively studied; nevertheless, spatio-temporal landslide susceptibility assessment is lacking. This can be partially attributed to the limited availability of high temporal resolution remote sensing data. We present a semi-automated technique to use the Sentinel-2 MSI data for co-seismic landslide detection, landslide activities monitoring, spatio-temporal change detection, and spatio-temporal susceptibility mapping. Time series Sentinel-2 MSI images for the period of 2016-2021 and ALOS PALSAR DEM are used for semi-automated landslide inventory map development and temporal change analysis. Spectral information combined with topographical, contextual, textural, and morphological characteristics of the landslide in Sentinel-2 images is applied for landslide detection. Subsequently, spatio-temporal landslide susceptibility maps are developed utilizing the weight of evidence statistical modeling with seven causative factors, i.e., elevation, slope, geology, aspect, distance to fault, distance to roads, and distance to streams. The results reveal that landslide occurrence increased from 2016 to 2021 and that the coverage of areas of relatively high susceptibility has increased in the study area.

Design of a Comprehensive Assessment Model for the Stability and Engineering Geology of Slope Based on Improved Convolutional Neural Network.

The geological mechanics, geotechnical characteristics, and hydrogeological conditions of slopes are complex and changeable, so their stability assessment is a complicated system; their traditional engineering geological assessment does not consider the opposition of the system, the uncertainty of performance indicators, and the ambiguity of index classification, being easy to distort results due to the ambiguity. Improved convolutional neural network (CNN) has outstanding advantages in analyzing problems with randomness and fuzziness. It can perform unified numerical processing on slope assessment indicators with precise values, interval values, and qualitative judgment values, making the traditional qualitative description is transformed into quantitative calculation. Therefore, on the basis of summarizing and analyzing previous research works, this paper expounded the research status and significance of the comprehensive assessment model for slope stability and engineering geology; elaborated the development background, current status, and future challenges of the improved CNN; introduced the methods and principles of the model structure, convolutional layer design, and data flow optimization of the improved CNN; performed the assessment index system establishment and index weight determination; established the mathematical assessment model for slope stability; conducted the assessment module design for slope stability based on the improved CNN; analysed the importance of individual factors to the comprehensive engineering geological characteristics; discussed the determination of assessment value of comprehensive unit engineering geological characteristics; explored the assessment module design for slope engineering geology based on the improved CNN; and finally carried out an engineering application and its result analysis. The study results show that the improved CNN can select some universal and objective factors according to the actual conditions of slopes, including topography, stratum lithology, geological structure, atmospheric rainfall, groundwater, engineering activities, setting up factor sets and judgment sets, and making fuzzy inferences. The comprehensive assessment model can use appropriate mathematical methods to judge the pros and cons of slope's stability and engineering geology according to certain principles and standards, and grade the results and identify the most important geological problems. The results of this paper provide a reference for further researches on the design of a comprehensive assessment model for slope stability and engineering geology based on the improved CNN.

Coupling coordination relationship between geology-geomorphology and ecology in Northeast China.

Northeast China is an important ecological barrier and commodity grain base in China. The coupling coordination relationship between geology-geomorphology and ecology has become a critical background condition for ecosystem protection and sustainable development. Taking Northeast China as a case (accounting for about 13% of China's land area), 9 divisions are divided according to the characteristics of regional ecology and geology-geomorphology, and 17 indicators are selected to build an evaluation index system. Methods of analytic hierarchy process, entropy weight and game theory are used to determine the index weights. Based on the coupling coordination degree (CCD) model, the spatial coupling coordination characteristics of geology-geomorphology and ecology are studied. The variation characteristics of the Normalized Difference Vegetation Index (NDVI) are evaluated by Sen+Mann-Kendall (Sen+MK) method. Our results are as follows. (1) The coupling between geology-geomorphology and ecology is strong, but the spatial differentiation of CCD is obvious. Nine divisions are evaluated as two high-level, three medium-level and three low-level coordination types and one mild imbalance type. (2) The plain divisions Ⅰ and Ⅳ where the typical black soil belt is located are high coordination types. Restricted by geology-geomorphological conditions or ecological conditions, mountain divisions Ⅲ and Ⅶ and plain division Ⅴ are moderate coordination types, mountain divisions Ⅱ and Ⅷ and plateau division Ⅸ are low coordination types, and mountain division Ⅵ is mild imbalance type. (3) The variation trend of NDVI shows a significant increase in divisions Ⅲ, Ⅴ, Ⅰ, Ⅱ and Ⅶ. it shows a significant decrease in part of divisions Ⅳ, Ⅵ, Ⅷ and Ⅸ, and ecological management and construction should be strengthened in these divisions. The research shows that the CCD model method is feasible for evaluating the relationship between geology-geomorphology and ecology and can provide eco-geological background information for Northeast China.

Analysis on the spatial differentiation characteristics of poverty risk caused by disaster under the stress of geological disasters: a case study of Sichuan Province.

Research on the poverty risk caused by geological disasters in disaster-prone areas is a useful exploration to coordinate social economic development with disaster prevention and reduction, and is of great significance to the regional sustainable development. Based on statistical data and spatial data, this paper takes Sichuan Province as the typical research area. Remote sensing and geographic information technology are used to study the poverty risk caused by disasters based on the quantitative evaluation of geological disasters risk and regional development level. The spatial differentiation characteristics of poverty risk caused by disasters are explored on the 1 km × 1 km grid scale. The results indicate that (1) the overall risk of geological disasters in Sichuan Province is relatively high, with high and relatively high risk areas accounting for more than 40% and low and relatively low risk areas accounting for less than 30%. The risks in Mountain and Ravine Areas are significantly higher than other areas. (2) The regional development level in Sichuan Province is relatively high, but with significant spatial differences. The development level of high-altitude areas and remote mountainous areas is quite different from that of the Chengdu Plain in the middle Sichuan Province. The uneven development in the east, middle, and west is a prominent problem. (3) The poverty risk caused by disasters is high, and the spatial pattern presents a characteristic of "high in the west and low in the east" with high positive spatial correlation. High-High Cluster Areas are mainly distributed in western and southwestern Sichuan. Low-Low Outlier Areas are mainly distributed in Chengdu Plain and Hilly Areas of Sichuan Basin. High-Low Outlier and Low-High Outlier Areas occupy a relatively small percentage with scattered distribution. This paper provides some theoretical support for policy formulation and management of coordinated development of regional socioeconomic and ecological environment.

Empirical study of the coupling relationship between biodiversity and environmental geology under different ecological status: Evidence from five typical areas in Guizhou, China.

Analyzing the coupling relationship between biodiversity and environmental geology and exploring the factors affecting the coupling degree are of vital significance for the protection and restoration of the ecological environment. In this study, we selected five typical areas (i.e., Caohai, Chishui, Fanjingshan, Maolan, and Guanshanhu) to represent the whole Guizhou Province, China. Based on the coupling coordination degree model, we analyzed their coupling coordination trend. The results showed that the coordinated development stages of the Chishui and Fanjingshan areas both could be categorized as the synchronous development type of primary coordination because of their excellent nature conditions; the Maolan area was categorized as having restrained environmental geology because of its weak environmental geology condition; and the Guanshanhu and Weining areas were strongly affected by human activities, and both could be categorized as having restrained biodiversity. In combination with practical situation, Guizhou province can be categorized into the following three zones: an original ecological zone, a zone with fragile ecological environment, and a zone affected by human activities. Biodiversity conservation measures should be proposed according to the specific ecological situation of these different zones. In this way, the harmonious coexistence of economic development and the ecological environment can be realized.

Slide type landslide susceptibility assessment of the Büyük Menderes watershed using artificial neural network method.

The Büyük Menderes watershed is the largest drainage watershed in Western Anatolia with an area of approximately 26,000 km2. In the study area, almost 863 landslides occurred, extending over 222 km2 with a mean landslide area of 0.21 km2. In this study, landslide susceptibility assessments were carried out using artificial neural network method, which is one of the data-driven methods. In this study, that will contribute to the mitigation or control of the landslides caused by the reasons controlling the spatial and temporal distribution of landslides created in the GIS and MATLAB environment by using scientific and technological approaches within the framework. Since derivative activation function is also used in back-propagation artificial neural networks, its derivative is easily calculated in order not to slow down the calculation. Levenberg-Marquardt back-propagation (LM), resilient back propagation back-propagation (trainrp), scaled conjugate gradient back-propagation (trainscg), conjugate gradient with Powell/Beale restarts back-propagation (traincgb), and Fletcher-Powell conjugate gradient back-propagation (traincgf) algorithms are used, which constantly interrogate the link between the input parameter and the result output, and at least one cell's output is given as an input to any other cell. Geology, digital elevation model, slope, topographic wetness index, roughness index, plan, profile curvatures, and proximity to active faults and rivers were used as landslide conditioning factors. In susceptibility assessments, landslides were separated by 70% analysis, 15% test, and 15% validation datasets by random selection method. The performances of the landslide susceptibility maps were assessed by the area under the ROC curve (AUC), accuracy (ACC), precision, recall, F1 score, Kappa test error histogram, and confusion matrix, respectively. The area under the receiver operating characteristic curves, analysis, testing, validation, landslides, and study areas were found between 0.873 and 0.911. The susceptibility map had a high prediction rate in which high and very high susceptible zones corresponded to 26% of the study area including 82% of the recorded landslides.

Distribution of rare earth elements in soils of contrasting geological and pedological settings to support human health assessment and environmental policies.

Establishing quality reference values (QRVs) for rare earth elements (REEs) in soils is essential for the screening of these emergent contaminants. Currently, Brazil has the second-largest reserve of REEs, but data regarding background concentrations and distributions in soils remain scarce. The aim of this study was to establish the QRVs and assess the spatial distribution of REEs in soils, including REE fractionations and anomalies in (Piauí) state (251,529.186 km2), northeastern Brazil. This study reports the most detailed data on REE geochemistry in Brazilian soils. A total of 243 composite soil samples was collected at 0-20 cm depth. The mean background concentrations in soils followed the abundance of the earth's upper crust: Ce > La > Nd > Pr > Sm > Dy > Gd > Er > Yb > Eu > Tb > Lu. The ∑REEs (mg kg-1) showed the following order based on the individual mesoregions of Piauí state: Southeast (262.75) > North and Central-North (89.68) > Southwest (40.33). The highest QRVs were observed in the Southeast mesoregion. The establishment of QRVs based on the mesoregion scale improves data representativeness and the monitoring of natural REE values by identifying hot spots. Geostatistical modeling indicated significant local variability, especially in the Southeast mesoregion. The levels of these elements in this spatial zone are naturally higher than the other values across Piauí state and the mesoregion itself and indicate a high potential to exceed the QRVs. Our approach provides much needed data to help strengthen policies for both human health and environmental protection.

Landslide Susceptibility Assessment Using an AutoML Framework.

The risks associated with landslides are increasing the personal losses and material damages in more and more areas of the world. These natural disasters are related to geological and extreme meteorological phenomena (e.g., earthquakes, hurricanes) occurring in regions that have already suffered similar previous natural catastrophes. Therefore, to effectively mitigate the landslide risks, new methodologies must better identify and understand all these landslide hazards through proper management. Within these methodologies, those based on assessing the landslide susceptibility increase the predictability of the areas where one of these disasters is most likely to occur. In the last years, much research has used machine learning algorithms to assess susceptibility using different sources of information, such as remote sensing data, spatial databases, or geological catalogues. This study presents the first attempt to develop a methodology based on an automatic machine learning (AutoML) framework. These frameworks are intended to facilitate the development of machine learning models, with the aim to enable researchers focus on data analysis. The area to test/validate this study is the center and southern region of Guerrero (Mexico), where we compare the performance of 16 machine learning algorithms. The best result achieved is the extra trees with an area under the curve (AUC) of 0.983. This methodology yields better results than other similar methods because using an AutoML framework allows to focus on the treatment of the data, to better understand input variables and to acquire greater knowledge about the processes involved in the landslides.

Appraisal of Low-Cost Pushbroom Hyper-Spectral Sensor Systems for Material Classification in Reflectance.

Near infrared (NIR) remote sensing has applications in vegetation analysis as well as geological investigations. For extra-terrestrial applications, this is particularly relevant to Moon, Mars and asteroid exploration, where minerals exhibiting spectral phenomenology between 600 and 800 nm have been identified. Recent progress in the availability of processors and sensors has created the possibility of development of low-cost instruments able to return useful scientific results. In this work, two Raspberry Pi camera types and a panchromatic astronomy camera were trialed within a pushbroom sensor to determine their utility in measuring and processing the spectrum in reflectance. Algorithmic classification of all 15 test materials exhibiting spectral phenomenology between 600 and 800 nm was easily performed. Calibration against a spectrometer considers the effects of the sensor, inherent image processing pipeline and compression. It was found that even the color Raspberry Pi cameras that are popular with STEM applications were able to record and distinguish between most minerals and, contrary to expectations, exploited the infra-red secondary transmissions in the Bayer filter to gain a wider spectral range. Such a camera without a Bayer filter can markedly improve spectral sensitivity but may not be necessary.

Assessment of radiation hazards from phosphate rocks, Sibaiya area, central eastern desert, Egypt.

The present work used the integrated Carbone γ-ray spectrometric data and HPGe γ-ray spectrometer data to the prospect of radioactive zones at the Sibaiya area, Central Eastern Desert, Egypt. Carbone γ-ray spectrometric survey revealed ten uranium anomalies distributed along the car traverse from west to east direction have values of 240, 104, 44, 34, 150, 124, 232, 132, 60, and 90 ppm, respectively. These significant anomalies are associated mainly with phosphates mines characterized by a substantial increase of eU/eTh and eU/K ratios. Ten phosphate samples were collected from the determining anomalies. They were analyzed using the HPGe detector gamma-ray spectrometer. It was found that the results of radioelement concentrations by carborne survey agree well with that obtained by HPGe. The average activity concentration for the Sibaiya phosphate samples under study is 152.5, 947, and 33.2 Bq/kg against the worldwide accepted limit of 412, 33, and 45 Bq/kg for 40K, 238U, and 232Th, respectively. The radium equivalent ranges from 499 to 3484.9 Bq/kg, which is higher than the recommended value 370 Bq/kg. The external hazard's (Hex) calculated values range from 1.35 to 9.42 mGy/yr, and the internal hazard (Hin) ranges from 2.58 to 18.69. These indexes must be lower than unity to keep the radiation hazard insignificant. The value of the radioactivity level index (Iγ) is found to be more than unity, which varies between 1.68 and 11.63. The dose rate (DR) ranges from 149.5 to 970 nGy/h, higher than the international mean value of 55 nGy/h. The annual effective dose ranges from 0.18 to 1.19 mSv, which less than unity in almost all values. Meanwhile, the values of activity of 226Ra ranged from 454 to 3429 Bq/kg and the mean of mass radon exhalation rate (Jm) is 6615 mBq kg-1 h-1 which is lower than the worldwide average.