Estimation of stress and its use in evaluation of landslide prone regions using remote sensing data

Recently, use of remote sensing data for determining the orientation of stress has been demonstrated. The present study deals with the estimation of stress pattern in the part of the Himalayan region which shows the ongoing neo-tectonic activities. The study area falls into a tectonically active zone of the Central-Himalaya, with a complex geotectonic set-up confined by a number of faults. Efforts have been made to evaluate the technique as a fast algorithm for quick and time limited analysis of linear feature from which the orientation of the lineaments are estimated by using remote sensing data. Further, the estimation of stress and the lineament analysis have been used in mapping of landslide prone areas. Terrain information such as land cover, geology, lineament, faults, mega faults, geomorphology and drainage has been derived from the satellite imageries, and the existing thematic information has been updated to enable the quantification of landslide causative parameters. Spatial and temporal multi-layered information have been used for landslides hazard susceptibility analysis. The qualitative hazard analysis has been carried out using the map overlying techniques in GIS environment along the central part of Himalayan region. It has been observed that the high potential zones have been found to have very high lineament density, moderate to low drainage density and high slope areas of the terrain. On the basis of the geological and morphological analysis, it is further suggested that the combined impacts of the crushed nature of bed rock (due to the neo-tectonic activities), heavy rainfall and lack of vegetation cover cause persistent recurrence of landslides along this region. The role of earthquake on induction of landslides will be presented.     

Flood susceptibility mapping by ensemble evidential belief function and binomial logistic regression model on river basin of eastern India

Flooding is the overflow of water from stream, river, lake and sea that occurs all over the world and has disastrous effects on human society and environment. Frequent severe flood event in eastern India cause of death and damages every year so, the development of flood susceptibility method is needed for identifying the flood vulnerability areas to reduce the damages. Techniques of Remote Sensing (RS) and Geographical Information System (GIS) can help to flood susceptibility modeling by the accrued and analyzing huge amount of data in short time. The main objectives of this study are to determine the effectiveness of Evidence Belief Function (EBF), binomial Logistic Regression (LR) and ensemble of EBF and LR (EBF-LR) model with RS and GIS techniques for flood susceptibility mapping and spatial prediction of flood-susceptible areas in the Koiya river basin of West Bengal, India. Eight flood conditioning factors; Land use and land cover (LULC), soil, rainfall, normalized differences vegetation index (NDVI), distance to river, elevation, topographic wetness index (TWI) and stream power index (SPI) have been used, and total 264 historical flooding points were mapped, and randomly divided in to training (70%) and validating (30%) dataset. Flood susceptibility map has been generated by applying EBF, LR and ensemble EBF-LR method with the help of training and eight causative factors dataset. The maps have been divided in to six classes; extremely low, very low, low, moderate, high and very high. The receiver operating characteristic (ROC) curve has been used to accuracy assessment of the susceptibility map, and the area under curve (AUC) disclosures 87.9%, 85.2% and 84.1% prediction rate for the EBF-LR, EBF and LR model, respectively. This study is helpful to flood management program, dissection makers and planning in local administrative level.     

Integration of artificial intelligence with meta classifiers for the gully erosion susceptibility assessment in Hinglo river basin,Eastern India

The main aim of this study is to evaluate the gully erosion susceptibility coupling the artificial intelligence and machine learning ensemble approaches. In the present study, the multilayer perceptron neural network (MLP) was used as the base classifier and the hybrid ensemble machine learning methods i.e. Bagging and Dagging were used as the functional classifiers. The Hinglo river basin, an important tributary of the Ajay River was selected as the study area, consists with the parts of Chhotonagpur plateau and Rarh lateritic region. The study area is facing the gully erosion problems which are interrupted the growth of the agriculture. The gully erosion susceptibility maps (GESMs), prepared by MLP, MLP-Bagging and MLP-Dagging were classified into four classes such as low, moderate, high and very high susceptibility classes with the help of natural break method (NBM) in GIS environment. The very high susceptibility class covered 19.41% (MLP), 13.52% (MLP-Bagging) and 15.30% (MLP-Dagging) areas of the basin. For the evaluation and comparison of the models, receiver operating characteristics (ROC), accuracy, mean absolute error (MAE) and root mean square error (RMSE) were applied. Overall, all the gully erosion susceptibility models were performed as excellent. Integration of hybrid ensemble models with MLP has increase the accuracy of the MLP models. Among these models MLP-Dagging has achieved the highest accuracy in compare to the other models. The importance of the selected factors in the present study was assessed by the Relief-F method. The results show that the soil type factor has the highest predictive performance. Sensitivity analysis also showed soil type as most important factor. The gully erosion susceptibility maps (GESMs) are considered as the efficient tool which could be used to take the necessary steps for mitigating and controlling the soil erosion problem and sustainable environmental management and development.     

基于多因子综合评估的月球探测软着陆区域及最佳巡航路线分析

选择合适的软着陆区域及规划合理的巡航路线是月球探测的基础工作。以位于月球背面南极—艾肯（South Pole-Aitken,SPA）盆地内的冯·卡门（Von Kármán）撞击坑作为研究区域,综合使用多因子分析评估了月球探测的着陆区域和巡航路线。评价体系主要包括能表征着陆安全性的撞击坑的密度、撞击坑的影响区域、整个区域的平整情况、部分区域的平整情况等因子和体现科学探索意义的区域垂直结构、岩石属性和（FeO+TiO₂）含量等因子,其中科学探索的评估分析是在安全可行性的基础上进行的。结果表明：在多因子叠加分析的基础上可选择出A、B及C 3个着陆区,并通过科学研究因子分析出路线2及路线3为合适的巡航路线。本研究为月球探测器着陆和巡航路线的规划提供了科学依据,为后续的月球探测工作提供了技术支持。     

Spatial modeling of flood probability using geo-environmental variables and machine learning models,case study: Tajan watershed,Iran

The main objective of this study was to produce flood susceptibility maps for Tajan watershed, Sari, Iran using three machine learning (ML) models including Self-Organization Map (SOM), Radial Basis Function Neural Network (RBFNN), and Multi-layers Perceptron (MLP). To reach such a goal, different physical-geographical factors (criteria) were integrated and mapped. 212 flood inventory map was randomly divided into training and testing datasets, where 148 flood locations (70%) were used for training and the remaining 64 locations (30%) were employed for testing. Model validation was performed using several statistical indices and the area under the curve (AUC). The results of the correlation matrix showed, three factors slope (0.277), distance from river (0.263), and altitude (0.223) were the most important factors affecting flood. The accuracy evaluation of the flood susceptibility maps through the AUC method and K-index shows that in the validation phase RBFNN (AUC = 0.90) outperform the MLP (AUC = 0.839) and SOM (AUC = 0.882) models. The highest percentage flood susceptibility of the area in MLP, SOM and RBFNN models is related to moderate (28.7%), very low (40%) and low (37%), respectively. Also, the validation results of the models using the Relative Flood Density (RFD) approach showed that very high class had the highest RFD value.     

RS-GIS based morphometrical and geological multi-criteria approach to the landslide susceptibility mapping in Gish River Basin,West Bengal,India

Darjeeling Himalaya is one of the several mountainous areas of India which is often suffered from landslide hazards. In this paper, a multi criteria evaluation is applied using 16 morphometric indicators, geology and lineaments to identify the areas vulnerable in respect to drainage and relief conditions. As both drainage and relief parameters exert strong influences on landslide intensity, both the diversity maps are integrated for final landslide susceptibility mapping. The obtained results show that 20.17?sq.?km (7.61%) area within the basin is highly susceptible for landslides, where average drainage density is 3.78?km/sq.?km, relative relief is greater than 408?m and slope is greater than 12°. The validation result shows that very high landslide susceptible zone is associated with very high frequency of landslide occurrence. Beside this, ROC curve also suggests good predicted rate (86.60%) for the model. So, the proposed method can be applied for predicting landslide susceptible zone.     

Remote sensing detection of gold related alteration zones in Um Rus area, Central Eastern Desert of Egypt

Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and Phased Array L-band Synthetic Aperture Radar (PALSAR) images covering the Um Rus area in the Central Eastern Desert of Egypt were evaluated for mapping geologic structure, lithology, and gold-related alteration zones. The study area is covered by Pan-African basement rocks including gabbro and granodiorite intruded into a variable mixture of metavolcanics and metasediments. The first three principal component analyses (PCA1, PCA2, PCA3) in a Red-Green-Blue (RGB) of the visible through shortwave-infrared (VNIR + SWIR) ASTER bands enabled the discrimination between lithological units. The results show that ASTER band ratios ((2 + 4)/3, (5 + 7)/6, (7 + 9)/8) in RGB identifies the lithological units and discriminates the granodiorite very well from the adjacent rock units.The granodiorites are dissected by gold-bearing quartz veins surrounded by alteration zones. The microscopic examination of samples collected from the alteration zones shows sericitic and argillic alteration zones. The Spectral Angle Mapper (SAM) and Spectral Information Divergence (SID) supervised classification methods were applied using the reference spectra of the USGS spectral library. The results show that these classification methods are capable of mapping the alteration zones as indicated by field verification work. The PALSAR image was enhanced for fracture mapping using the second moment co-occurrence filter. Overlying extracted faults and alteration zone classification images show that the N30E and N-S fractures represent potential zones for gold exploration. It is concluded that the proposed methods can be used as a powerful tool for ore deposit exploration.     

The POKER experiment: A 10,800 cm2 MWPC's array payload for hard X-Ray Astronomy

In this paper the POKER-HXR81M hard X-Ray payload is described. The instrument, designed and built at the Istituto di Astrofisica Spaziale of Frascati, is a very large array of MultiWire Proportional Counters (MWPC) devoted to stratospheric observations of cosmic sources in the field of hard X-Ray Astronomy. The payload basically consists of four passively collimated MWPC's having a geometric sensitive area of 2,700 cm² each with an efficiency higher than 10% in the operative range 15–200 KeV (80% at 60 KeV) with a square field of view of 5° × 5° FWHM. The overall spectral resolution is 13% at 60 KeV. The four MWPC's are filled with a very pure gas mixture of Xenon-Argon-Isobuthane at high pressure (3 bars).This experiment has been successfully flown during summer 1981 from the Milo balloon facility (Sicily, Italy). The performances of the payload and the preliminary results obtained during the 17 hours flight are discussed.     

The South Pole-Aitken basin region,Moon: GIS-based geologic investigation using Kaguya elemental information

Using Geographic Information Systems (GIS), we performed comparative analysis among stratigraphic information and the Kaguya (SELENE) GRS data of the ∼2500-km-diameter South Pole-Aitken (SPA) basin and its surroundings. Results indicate that the surface rock materials (including ancient crater materials, mare basalts, and possible SPA impact melt) are average to slightly elevated in K and Th with respect to the rest of the Moon. Also, this study demonstrates that K and Th have not significantly changed since the formation of SPA. The elemental signatures of the impact basin of Fe, Ti, Si, O through time include evidence for resurfacing by ejecta materials and late-stage volcanism. The oldest surfaces of SPA are found to be oxygen-depleted during the heavy bombardment period relative to later stages of geologic development, followed by both an increase in silicon and oxygen, possibly due to ejecta sourced from outside of SPA, and subsequent modification due to mare basaltic volcanism, which increased iron and titanium within SPA. The influence of the distinct geologic history of SPA and surroundings on the mineralogic and elemental abundances is evident as shown in our investigation.     

Identifying areas of high economic-potential copper mineralization using ASTER data in the Urumieh–Dokhtar Volcanic Belt,Iran

This study investigates the application of spectral image processing methods to ASTER data for mapping hydrothermal alteration zones associated with porphyry copper mineralization and related host rock. The study area is located in the southeastern segment of the Urumieh–Dokhtar Volcanic Belt of Iran. This area has been selected because it is a potential zone for exploration of new porphyry copper deposits. Spectral transform approaches, namely principal component analysis, band ratio and minimum noise fraction were used for mapping hydrothermally altered rocks and lithological units at regional scale. Spectral mapping methods, including spectral angle mapper, linear spectral unmixing, matched filtering and mixture tuned matched filtering were applied to differentiate hydrothermal alteration zones associated with porphyry copper mineralization such as phyllic, argillic and propylitic mineral assemblages.     

基于LOLA数据的冯·卡门地区地形特征分析

冯·卡门（Von Kármán）撞击坑位于南极—艾肯（South-Pole Aitken,SPA）盆地西北部,为“嫦娥4号”的预选着陆区。本文基于LRO卫星LOLA数据,分别采用最大平均值法、均方根高程法和盒维数法,得到并分析了冯·卡门地区的坡度、粗糙度和分形维数等地形参数信息。结果表明：冯·卡门撞击坑的海拔低,其中坑底最南部海拔最低,其余地区海拔相对较高;冯·卡门撞击坑内存在很多小的撞击结构;冯·卡门撞击坑平均坡度为1.3°,小于2°的地区约占盆地底部面积的85%;粗糙度值小于20 m的区域占95.1%;整体上有较大的分形维数。上述结果说明冯·卡门撞击坑整体上地形起伏小,结构稳定。统计结果表明：冯·卡门撞击坑南部、东南部及西北部地区都有较小的坡度、粗糙度值和较大的分形维数值,可满足探测器的着陆要求。与“嫦娥3号”着陆区地形的对比表明,冯·卡门撞击坑内部的地形条件要优于“嫦娥3号”着陆区。     

太阳耀斑硬X射线能谱演变特征

太阳硬X射线是耀斑高能电子束流与太阳大气相互作用产生的韧致辐射,根据简单的太阳耀斑环物理模型,假定具有流量与能谱同步变化的高能电子束流从耀斑环顶部注入,计算了硬X射线辐射在不同的靶物质密度区的能谱演变特征。结果表明:硬X射线辐射在低大气密度靶区呈现软一硬一硬的能谱演变特征,在高密度靶区硬X射线能谱则具有软一硬一软的变化特征。高能电子束流持续时间影响谱型转变区域在耀斑环中的高度。      

基于层次分析法的自适应决策评价方法

为改善经典层次分析法(AHP)主观性强、权重系数固定不变的缺陷,根据被评价对象指标值矩阵所蕴含的客观信息,对经典的层次分析法进行修正,提出了一种基于层次分析法的可变权重决策评价方法。该方法能够根据被评价对象指标值的分布特征,对评价指标的权重进行动态修正,降低区分度不高的指标权重,提升区分度高的指标权重,从而提升层次分析法的客观性,并在一定程度上体现出稀缺性指标的导向作用。以合成孔径雷达图像降斑算法评价为例,验证了本文方法的有效性。      

A large area multitechnique experiment for hard X-ray astronomy

A balloon-borne multitechnique large area experiment consisting of 2 co-aligned detectors (3200 cm² NaI and 1800 cm² multiwire proportional counters), is described, which is capble of producing observations of the hard X-ray sky with very high sensitivity and good spectral resolution over the whole operative range (15–300 keV).     

A comparative sporadic-E layer study between two mid-latitude ionospheric stations

Hourly systematic measurements of the highest frequency reflected by the sporadic-E layer (foEs) recorded from January 1976 to June 2009 at the ionospheric stations of Rome (Italy, 41.8°N, 12.5°E) and Gibilmanna (Italy, 37.9°N, 14.0°E) were considered to carry out a comparative study between the sporadic E layer (Es) over Rome and Gibilmanna. Different statistical analysis were performed taking into account foEs observations near the periods of minimum and maximum solar activity. The results reveal that: (1) independently from the solar activity, Es develops concurrently over extended regions in space, instead of being a spatially limited layer which is transported horizontally by neutral winds over a larger area; especially during summer months, when an Es layer is present at Rome, there is a high probability that an Es layer is also present over Gibilmanna, and vice versa; (2) Es layer lifetimes of 1–5 h were found; in particular, Es layers with lifetimes of 5 h both over Gibilmanna and Rome are observed with highest percentages of occurrence in summer ranging between 80% and 90%, independently from the solar activity; (3) latitudinal effects on Es layer occurrence emerge mostly for low solar activity during winter, equinoctial, and summer months, when Es layers are detected more frequently over Gibilmanna rather than Rome; (4) when the presence of an Es layer over Rome and Gibilmanna is not simultaneous, Es layer appearance both over Rome and Gibilmanna confirms to be a locally confined event, because drifting phenomena from Rome to Gibilmanna or vice versa have not been emphasized.     

Physical assessment of coastal vulnerability under enhanced land subsidence in Semarang,Indonesia, using multi-sensor satellite data

Research has been conducted in Semarang, Indonesia, to assess coastal vulnerability under enhanced land subsidence using multi-sensor satellite data, including the Advanced Land Observing Satellite (ALOS) Phased Array type L-band SAR (PALSAR), Landsat TM, IKONOS, and TOPEX/Poseidon. A coastal vulnerability index (CVI) was constructed to estimate the level of vulnerability of a coastline approximately 48.68?km in length using seven physical variables, namely, land subsidence, relative sea level change, coastal geomorphology, coastal slope, shoreline change, mean tidal range, and significant wave height. A comparison was also performed between a CVI calculated using seven parameters and a CVI using six parameters, the latter of which excludes the land subsidence parameter, to determine the effects of land subsidence during the coastal vulnerability assessment. This study showed that the accuracy of coastal vulnerability was increased 40% by adding the land subsidence factor (i.e., CVI 6 parameters?=?53%, CVI 7 parameters?=?93%). Moreover, Kappa coefficient indicated very good agreement (0.90) for CVI 7 parameters and fair agreement (0.3) for CVI 6 parameters. The results indicate that the area of very high vulnerability increased by 7% when land subsidence was added. Hence, using the CVI calculation including land subsidence parameters, the very high vulnerability area is determined to be 20% of the total coastline or 9.7?km of the total 48.7?km of coastline. This study proved that land subsidence has significant influence on coastal vulnerability in Semarang.     

INTERFACIAL MASS TRANSPORT IN OXIDE CRYSTAL GROWTH

A space high temperature in situobservation instrument (SHITISOI) is dedicated to visualize and record the whole growth process of oxide crystal in high temperature melts and solutions. Model experiments using transparent liquids such as KNbO3,Li2B4O7+KNbO3 were chosen to investigate effects of interracial mass transport in oxide crystal growth. For the scaling of the coupled velocity, heat and concentration fields in KNbO3 crystal growth, a rotating crystal growth process was performed and the widths of interfacial concentration, heat and momentum transition zones (The "boundary layers") are obtained, which are 7.5×10-a, 8.6×10-2 and 4.4×10-1 cm,respectively. Hence one can expect that interfacial concentration gradient will be confined to a narrow layer and in region of major concentration change at the in terface. In order to study a mechanism based on the interfacial mass transport resulting from hydrodynamics, the growth of KNbO3 grain in high temperature Li2B4O7 and KNbO3 solutin was studied. The result shows that the pivotal feature in the KNbO3 crystal growth is the initiated by KNbO3 solute surface tension gra dient which is caused by the slow diffusion of KNbO3 solutes. Direct comparison of the model predictions and experimental observed phenomena demonstrate the predictive capability of this model.     

Quantitative contribution of climate change and anthropological activities to vegetation carbon storage in the Dongting Lake basin in the last two decades

The Dongting Lake Basin is an important hydrological regulation and flood storage area in the Yangtze River Basin, which plays an important role in maintaining regional ecological security. The watershed vegetation and its carbon sequestration capacity have changed dramatically due to climate change and human activities in the last two decades. In this paper, the monthly and annual vegetation net primary productivity (NPP) of the Dongting Lake basin during 2000 to 2020 was firstly estimated using the improved Carnegie-Ames-Stanford Approach (CASA) model. Then the multi-year NPP change trend and its significance were analyzed based on Theil-Sen median and Mann-Kendall method. Subsequently, the Hurst index was used to simulate the vegetation NPP persistence in the study area. Finally, the driving mechanisms of vegetation NPP changes in the study area were explored using partial correlation coefficients and residual analysis. The results demonstrated that: 1) The annual average NPP in the basin showed a fluctuating and increasing trend from 273.54 to 718.30 g C/m²·yr¹ during 2000 to 2020, and except for autumn, all seasons (spring, summer, winter) and annual NPP series showed an upward trend. The spatial distribution of vegetation NPP is characterized by an asymmetrical horseshoe shape in general, with high values in the west, south and east parts, and low values in the Lake area; 2) During the study years, about 84.38 % of the basin area showed a significant and extremely significant increase of NPP; 3) The future trend of vegetation NPP in the basin shows that the area of decrease (22.79 %) is more than the area of increase (11.35 %). The Chang-Zhu-Tan urban agglomeration will generally show a continuous and extremely significant reduction trend, while parts of Dongting Lake will show a continuous and extremely significant increase trend; 4) The correlation between solar radiation and NPP is stronger than the other two meteorological factors (precipitation and temperature). Temperature has a significant inhibitory effect on NPP, solar radiation has a significant promoting effect on NPP, and the effect of precipitation on NPP was relatively complicated. The relative importance of meteorological factors on vegetation NPP was ranked as follows: solar radiation > precipitation > temperature. The impacts of both climate change and human activities on NPP changes showed great spatial variability, and the positive contributions (89.81 % for climate change and 82.87 % for human activities) were both greater than the negative contributions.     

Mapping recent agricultural developments in China from satellite data

Landsat data have been employed to study and map agricultural developments in three regions of China: 1) Pearl River delta; 2) Nen River basin; and 3) Xinjiang Autonomous Region. Manual interpretation procedures used in conjunction with multi-date Landsat images and collateral information permitted rice yields to be estimated for the Pearl River delta in 1978. A combination of manual and computer-assisted analyses of Landsat data of Northeast China revealed that more than 15,000 km² of agricultural land in a 184,500 km² study area had been reclaimed from rangeland and marshland. These analyses also indicated a shift in cropping practices, with the foodcrops wheat and corn replacing cash crops such as soybeans. In the arid west, Landsat image data provided valuable input to a geographic information system (GIS). It appears the GIS approach will prove useful for evaluating agricultural land potential in the remote areas of China.     

GRACE products and land surface models for estimating the changes in key water storage components in the Nile River Basin

The Nile River Basin (NRB) is facing extreme demand for its water resources due to an alarming increase in population and the changing climate. The NRB is not compatible with ground-based in-situ observations owing to its large basin area size and limited hydrological data access from basin countries. Thus, it lends itself to remotely sensed approaches with high spatial resolution and extended temporal coverage. The Gravity Recovery and Climate Experiment (GRACE) avails a unique opportunity to investigate the changes in key components of terrestrial water storage (TWS). GRACE TWS solutions have specific tuning parameters and processing strategies that result in regionally specific variations and error patterns. We explored the TWS time series spatiotemporal changes, trends, uncertainties, and signal-to-noise ratio among different GRACE TWS data. We had also investigated the key terrestrial water storage components such as surface water, soil moisture, and groundwater storage changes. The results show that GRACE spherical harmonic solutions' uncertainty is higher than the mass concentration (mascon) over the NRB, and the Center for Space Research-mascons had the best performance. The evapotranspiration correlation (R² = 0.85) has the highest correlation with GRACE’s TWS, whereas the normalized difference vegetation index (R² = 0.82) has the second highest correlation. Notably, significant long-term (2003–2017) negative groundwater and soil moisture trends demonstrate a potential depletion of the NRB. Despite an increase in precipitation and the TWS time series, the rate of decline increased rapidly after 2008, thereby indicating the possibility of human-induced change (e.g. for irrigation purposes). Therefore, the results of this study provide a guide for future studies related to hydro-climatic change over the NRB and similar basins.