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.     

Seasonal patterns of condensation and sublimation cycles in the cryptic and non-cryptic regions of the South Pole

The South Pole of Mars is characterized by an asymmetric residual ice cap composed of water ice and CO₂ ice. On the opposite side of the residual cap, there exists an area called cryptic region which is relatively free of ice during summer time. Many fan-shaped km-scale structures apparently caused by a wind-blown system of dust-laden gas jets occurred dozens degrees of Ls before the complete sublimation of the CO₂ frost layer. We have examined the seasonal cycles of condensation and sublimation in the cryptic and non-cryptic regions by using the topographic data from the MOLA/MGS measurements. Using the MOLA topography data collected over one Martian year (1999–2001), we have studied the temporal elevation change and the seasonal cycle of the carbon dioxide frost on the southern polar caps. We have produced mapping of the seasonal CO₂ frost thickness variation for seven Ls (30°, 60°, 90°, 120°, 150°, 180°, 210°, 240°, 270° and 330°). It is found that the time variations of the CO₂ frost thickness in these two regions are quite similar. The greatest thickness of the CO₂ frost layer is about 0.76–0.78 m in both places occurs at Ls = 150°.     

1998年10月18——-19日磁暴主相的行星际源分析

采用高时间分辨率的地磁指数SYM-H, 同时考虑日地连线引力平衡点(L1点)太阳风地磁效应的滞后性, 精确分析了1998年10月18---19日大磁暴主相的行星际源. 分析结果表明, 磁暴主相的行星际源仅为行星际激波和行星际日冕物质抛射之间的太阳风(Sheath), 磁云对磁暴主相没有贡献. 这个磁暴事例的研究表明, 行星际磁场南向分量与太阳风动压的乘积是影响磁暴主相发展的关键参数.      

Seasonal variability of atmospheric aerosol over the North Indian region during 2005–2009

The Indo-Gangetic basin (IGB) extends 2000 km in length along NW–SE and has 400 km width, in the north the basin is bounded by towering Himalaya. High aerosol optical depth (AOD) is observed over the IGB throughout the year. The Himalaya restricts the transport of aerosols across Tibet and China. We have used ground based Kanpur and Gandhi College Aerosol Robotic Network (AERONET) stations and Multiangle Imaging SpectroRadiometer (MISR) and Moderate Resolution Imaging Spectroradiometer (MODIS) Terra level-3 AOD products for the years 2005–2009 to study the variability of aerosol over the Indo-Gangetic (IG) plains. An increase in both satellite-derived as well as ground observed aerosol loading during 2005–2009 has been found over major cities located in the IG plains. The correlation coefficients between AERONET and MISR data are found to be 0.70, 0.36 0.82, in contrast the correlation coefficients between AERONET and MODIS 0.49, 0.68, and 0.43, respectively during summer, winter and monsoon seasons. The AOD estimation using MISR is found to be close to AERONET data during summer and monsoon seasons, in contrast MODIS estimation is better during winter season.     

Different mechanisms controlling interannual phytoplankton variation in the South China Sea and the western North Pacific subtropical gyre: A satellite study

A time series of remotely-sensed chlorophyll a (chl a) in 1997–2010 was evaluated to determine mechanisms of phytoplankton variation in recent decade in the South China Sea (SCS) and the western North Pacific subtropical gyre (WNPSG). Satellite-derived sea surface temperature (SST) and aerosol optical thickness (AOT) were used as proxies for vertical nutrient supply and atmospheric aerosol, respectively. Chl a in the WNPSG was not significantly correlated with SST (r = 0.18, p > 0.05), but was with AOT (r = 0.31, p < 0.05), indicating the chl a was influenced by atmospheric deposition. Chl a in the SCS was negatively correlated with SST (r = −0.60, p < 0.05) and was positively with AOT (r = 0.20, p < 0.05). The correlation between AOT and chl a in the SCS does not reflect a major contribution from atmospheric deposition to chl a; instead, the relationship resulted from concurrence of the peaks of AOT and wind speed, which drive water mixing and nutrient supply. Consequently, chl a in the SCS would be regulated primarily by the nutrient supply from deep waters. Because SST was controlled by the ENSO teleconnection in the SCS, the chl a was coupled with ENSO events. The present study demonstrated that interannual phytoplankton variation could be controlled by different factors even in neighboring oligotrophic regions.     

Satellite ocean colour algorithm for Prochlorococcus, Synechococcus, and picoeukaryotes concentration retrieval in the South China Sea

An algorithm for retrieval of surface waters cell concentrations (in cell/ml) for three picophytoplankton components, Prochlorococcus (Pro), Synechococcus (Syn), and picoeukaryotes (Peuk) in the South China Sea (SCS), from ocean colour satellite data was developed and tested. Level 3 merged multisensor Ocean Colour Climate Change Initiative satellite data is used. Training is performed using in situ data on abundances of the three phytoplankton components. Several predictors derived from satellite reflectance data were tested. The regression form that assures the highest accuracy of the algorithm was chosen based on cross-validation (CV). According to the CV on test data subset, the algorithm performance is characterized by the r value 0.89, 0.72, and 0.73 and MAPD 38, 71 and 51% for Peuk, Pro, and Syn respectively. This is one of the few studies aimed at the Peuk, Pro, and Syn distribution research in the northern SCS using ocean colour satellite data. This is the only research providing algorithm with accuracy estimates of the Peuk, Pro, and Syn concentrations retrieval from the ocean colour data. Analysis of the developed algorithm allows us to conclude that both mechanisms (specific spectral features caused by pigments composition and spectrum features sensitive to general primary productivity, e.g. band ratios in 443–510?nm range and spectrum absolute values) are important for getting accurate information on the picophytoplankton composition.     

Study of the radiation fields in LEO with the Space Application of Timepix Radiation Monitor (SATRAM)

We present the analysis of data taken by the Space Application of Timepix Radiation Monitor (SATRAM). It is centred on a Timepix detector (300?$\mathrm{\mu }$m thick silicon sensor, pixel pitch 55?$\mathrm{\mu }$m, 256?×?256 pixels). It was flown on Proba-V, an Earth observing satellite of the European Space Agency (ESA) from an altitude of 820?km on a sun-synchronous orbit, launched on May 7, 2013. A Monte Carlo simulation was conducted to determine the detector response to electrons (0.5–7?MeV) and protons (10–400?MeV) in an omnidirectional field taking into account the shielding of the detector housing and the satellite. With the help of the simulation, a strategy was developed to separate electrons, protons and ions in the data. The measured dose rate and stopping power distribution are presented as well as SATRAM’s capability to measure some of the stronger events in Earth’s magnetosphere. The stopping power, the cluster height and the shape of the particle tracks in the sensor were used to separate electrons, protons and ions. The results are presented as well. Finally, the pitch angles for a short period of time were extracted from the data and corrected with the angular response determined by the simulation.     

Traverses for the ISECG-GER design reference mission for humans on the lunar surface

This study explores the Design Reference Mission (DRM) architecture developed by Hufenbach et al. (2015) as a prelude to the release of the 2018 Global Exploration Roadmap (GER) developed by the International Space Exploration Coordination Group (ISECG). The focus of this study is the exploration of the south polar region of the Moon, a region that has not been visited by any human missions, yet exhibits a multitude of scientifically important locations – the investigation of which will address long standing questions in lunar research. This DRM architecture involves five landing sites (Malapert massif, South Pole/Shackleton crater, Schrödinger basin, Antoniadi crater, and the South Pole-Aitken basin center), to be visited in sequential years by crew, beginning in 2028. Two Lunar Electric Rovers (LER) are proposed to be tele-robotically operated between sites to rendez-vous with crew at the time of the next landing. With engineering parameters in mind we explore the feasibility of tele-robotic operation of these LERs between lunar landing sites, and identify potential high interest sampling locations en-route. Additionally, in-depth sample collection and return traverses are identified for each individual landing site across key geologic terrains that also detail crew Extra-Vehicular Activity (EVA). Exploration at and between landing sites is designed to address a suite of National Research Council (2007) scientific concepts.     

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。     

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.