Optimisation of the Population Monte Carlo algorithm: Application to constraining isocurvature models with cosmic microwave background data     

D. Moodley  K. Moodley 《Astronomische Nachrichten》2016,337(6):672-682

We optimise the parameters of the Population Monte Carlo algorithm using numerical simulations. The optimisation is based on an efficiency statistic related to the number of samples evaluated prior to convergence, and is applied to a D ‐dimensional Gaussian distribution to derive optimal scaling laws for the algorithm parameters. More complex distributions such as the banana and bimodal distributions are also studied. We apply these results to a cosmological parameter estimation problem that uses CMB anisotropy data from the WMAP nine‐year release to constrain a six parameter adiabatic model and a fifteen parameter admixture model, consisting of correlated adiabatic and isocurvature perturbations. In the case of the adiabatic model and the admixture model we find that the number of sample points increase by factors of 3 and 20, respectively, relative to the optimal Gaussian case. This is due to degeneracies in the underlying parameter space. The WMAP nine‐year data constrain the admixture model to have an isocurvature fraction of 36.3 ± 2.8 %. (© 2016 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)  相似文献   

ASTER mapping of gypsum deposits of Thumrait region of southern Oman     

Sankaran Rajendran  Sobhi Nasir 《Resource Geology》2021,71(1):41-62

This study demonstrates the use of ASTER data for the mapping of gypsum deposits and associated geological formations that occurred in the Thumrait region of southern Oman. The measurement of spectra over samples of gypsum in the 1,300–2,500 nm wavelength using a PIMA spectrometer showed the presence of distinct absorptions at 1400–1600, 1750, 1940, 2,100, and 2,400 nm characteristics to O? H stretching, H₂O combinations, and S? O bending overtones and stretching, respectively. Studying the unique spectral absorption characters of gypsum samples, we developed a false color composite (FCC) and an image by decorrelation stretch using the spectral bands 7, 3, and 2 of ASTER. The results FCC showed the regions of gypsum occurrences, and the decorrelated image discriminated the gypsum occurrences from other geological formations of the area. The study of surface mineralogy of the region using the VNIR‐SWIR bands by the spectral angle mapper method showed the presence of sulfate, carbonate, and clay minerals of the geological formations in the study area. We compared the results of ASTER with the results obtained using spectral bands 12, 8, and 4 of Sentinel‐2A processed by the same methods. The study showed that the spectral bands of ASTER can be used for mapping the gypsum and associated geological formations.  相似文献   

无人机遥感技术在甘肃北山地区地质填图中的应用     

戴均豪  薛林福  李忠潭  桑学佳  马建雄 《吉林大学学报(地球科学版)》2021,51(6):1908-1920

甘肃北山地区岩浆岩及变质岩出露广泛,植被稀少,地势平缓,是无人机遥感开展地质填图试验的理想目标区。为解决传统地质填图方法受地形、环境限制和投入高及工作周期长等问题,选取北山长流水地区20 km²化探重点工作区为目标区,利用大疆精灵4专业版无人机采集图像,并采用Photoscan软件合成高分辨率正射影像以及三维模型,建立解译标志,对目标区域进行地质解译,获得比前人1：1万地质图更加精细的地质图。该方法较传统填图方法能够解译出地质体形态、岩脉产状、微小断裂等更详细的地质内容,并能提供划分岩脉期次的证据。  相似文献   

降雨型地质灾害预报方法研究进展          下载免费PDF全文

陈悦丽  赵琳娜  王英  王成鑫 《应用气象学报》2019,30(2):142-153

开展降雨型地质灾害预报是减少灾害损失的有效方法。该文在讨论降雨型地质灾害预报相关概念的基础上,结合国内外已有的研究成果,系统总结了隐式统计模型、显式统计模型和动力模型等降雨型地质灾害预报模型的特点和适用条件。近几年区域降雨型地质灾害的预报技术研究有以下新特点:统计模型简单实用,目前已经由单一考虑降雨特征的第1代隐式统计模型,进一步发展为考虑地质、地貌等静态因子的显示统计模型;动力模型逐渐由基于垂直入渗理论的边坡稳定性模型开始向基于水土耦合机制的复杂预报模型发展;降雨型地质灾害业务预报预警的核心是地质灾害预报模型的本地化运行,我国已经基于统计模型搭建了服务于不同区域的业务预报预警系统。结合多源预报降雨资料,搭建基于水土耦合机制的降雨型地质灾害集合预报预警系统是未来可能的发展方向。  相似文献   

扶贫区地下水勘查理论与技术方法进步     

王新峰  龚磊  宋绵  李伟 《地质论评》2023,69(Z1):503-504

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Generating soil thickness maps by means of geomorphological-empirical approach and random forest algorithm in Wanzhou County,Three Gorges Reservoir     

《地学前缘(英文版)》2023,14(2):101514

Soil thickness, intended as depth to bedrock, is a key input parameter for many environmental models. Nevertheless, it is often difficult to obtain a reliable spatially exhaustive soil thickness map in wide-area applications, and existing prediction models have been extensively applied only to test sites with shallow soil depths. This study addresses this limitation by showing the results of an application to a section of Wanzhou County (Three Gorges Reservoir Area, China), where soil thickness varies from 0 to ～40 m. Two different approaches were used to derive soil thickness maps: a modified version of the geomorphologically indexed soil thickness (GIST) model, purposely customized to better account for the peculiar setting of the test site, and a regression performed with a machine learning algorithm, i.e., the random forest, combined with the geomorphological parameters of GIST (GIST-RF). Additionally, the errors of the two models were quantified, and validation with geophysical data was carried out. The results showed that the GIST model could not fully contend with the high spatial variability of soil thickness in the study area: the mean absolute error was 10.68 m with the root-mean-square error (RMSE) of 12.61 m, and the frequency distribution residuals showed a tendency toward underestimation. In contrast, GIST-RF returned a better performance with the mean absolute error of 3.52 m and RMSE of 4.56 m. The derived soil thickness map could be considered a critical fundamental input parameter for further analyses.  相似文献   

Object-based class modelling for multi-scale riparian forest habitat mapping     

《International Journal of Applied Earth Observation and Geoinformation》2015

Object-based class modelling allows for mapping complex, hierarchical habitat systems. The riparian zone, including forests, represents such a complex ecosystem. Forests within riparian zones are biologically high productive and characterized by a rich biodiversity; thus considered of high community interest with an imperative to be protected and regularly monitored. Satellite earth observation (EO) provides tools for capturing the current state of forest habitats such as forest composition including intermixture of non-native tree species. Here we present a semi-automated object based image analysis (OBIA) approach for the mapping of riparian forests by applying class modelling of habitats based on the European Nature Information System (EUNIS) habitat classifications and the European Habitats Directive (HabDir) Annex 1. A very high resolution (VHR) WorldView-2 satellite image provided the required spatial and spectral details for a multi-scale image segmentation and rule-base composition to generate a six-level hierarchical representation of riparian forest habitats. Thereby habitats were hierarchically represented within an image object hierarchy as forest stands, stands of homogenous tree species and single trees represented by sunlit tree crowns. 522 EUNIS level 3 (EUNIS-3) habitat patches with a mean patch size (MPS) of 12,349.64 m² were modelled from 938 forest stand patches (MPS = 6868.20 m²) and 43,742 tree stand patches (MPS = 140.79 m²). The delineation quality of the modelled EUNIS-3 habitats (focal level) was quantitatively assessed to an expert-based visual interpretation showing a mean deviation of 11.71%.  相似文献   

Multitemporal settlement and population mapping from Landsat using Google Earth Engine     

《International Journal of Applied Earth Observation and Geoinformation》2015

As countries become increasingly urbanized, understanding how urban areas are changing within the landscape becomes increasingly important. Urbanized areas are often the strongest indicators of human interaction with the environment, and understanding how urban areas develop through remotely sensed data allows for more sustainable practices. The Google Earth Engine (GEE) leverages cloud computing services to provide analysis capabilities on over 40 years of Landsat data. As a remote sensing platform, its ability to analyze global data rapidly lends itself to being an invaluable tool for studying the growth of urban areas. Here we present (i) An approach for the automated extraction of urban areas from Landsat imagery using GEE, validated using higher resolution images, (ii) a novel method of validation of the extracted urban extents using changes in the statistical performance of a high resolution population mapping method. Temporally distinct urban extractions were classified from the GEE catalog of Landsat 5 and 7 data over the Indonesian island of Java by using a Normalized Difference Spectral Vector (NDSV) method. Statistical evaluation of all of the tests was performed, and the value of population mapping methods in validating these urban extents was also examined. Results showed that the automated classification from GEE produced accurate urban extent maps, and that the integration of GEE-derived urban extents also improved the quality of the population mapping outputs.  相似文献   

TanDEM-X双站SAR干涉测量及研究进展     

孙亚飞  江利明  柳林  孙永玲  汪汉胜 《国土资源遥感》2015,(1)

较全面、系统地介绍了Tan DEM-X/Terra SAR-X双站SAR科学计划,重点涉及其科学目标、Tan DEM-X卫星参数、轨道结构以及干涉数据获取模式等相关内容,并讨论了双站SAR成像、极化In SAR和数字波束成形等干涉测量新技术及其研究进展。这些双站SAR新技术的实现将大大地推动SAR干涉测量在全球地形测绘、冰川学、海洋学及地质学等领域中的应用。  相似文献   

专业认证背景下的测绘工程专业课程体系优化     

谢宏全  周立  焦明连  董春来 《测绘工程》2015,(5):77-80

为了满足工程教育认证制度对高校测绘工程专业人才的培养要求,从测绘工程专业实际出发,对2014级培养方案中的课程体系进行了优化。在介绍课程体系构建背景的基础上,对照工程教育认证标准(2012版)的要求,简要说明了测绘工程专业培养目标、毕业生获取知识和能力、学位授予标准。详细阐述了课程体系优化的背景、课程体系构成与课程体系结构。经过对课程体系的优化能够满足工程教育认证标准中对课程体系的要求,为培养符合工程教育认证标准的毕业生打下扎实的基础。  相似文献