A CRPS-Based Spatial Technique for the Verification of Ensemble Precipitation Forecasts

Traditional precipitation skill scores are affected by the well-known“double penalty”problem caused by the slight spatial or temporal mismatches between forecasts and observations. The fuzzy (neighborhood) method has been proposed for deterministic simulations and shown some ability to solve this problem. The increasing resolution of ensemble forecasts of precipitation means that they now have similar problems as deterministic forecasts. We developed an ensemble precipitation verification skill score, i.e., the Spatial Continuous Ranked Probability Score (SCRPS), and used it to extend spatial verification from deterministic into ensemble forecasts. The SCRPS is a spatial technique based on the Continuous Ranked Probability Score (CRPS) and the fuzzy method. A fast binomial random variation generator was used to obtain random indexes based on the climatological mean observed frequency, which were then used in the reference score to calculate the skill score of the SCRPS. The verification results obtained using daily forecast products from the ECMWF ensemble forecasts and quantitative precipitation estimation products from the OPERA datasets during June-August 2018 shows that the spatial score is not affected by the number of ensemble forecast members and that a consistent assessment can be obtained. The score can reflect the performance of ensemble forecasts in modeling precipitation and thus can be widely used.     

The Digital Belt and Road program in support of regional sustainability

The Belt and Road initiative has a significant focus on infrastructure, trade, and economic development across a vast region, and it also provides significant opportunities for sustainable development. The combined pressure of climate variability, intensified use of resources, and the fragility of ecosystems make it very challenging, however, to achieve future sustainability. To develop the path in a sustainable way, it is important to have a comprehensive understanding of these issues across nations and evaluate them in a scientific and well-informed approach. In this context, the Digital Belt and Road (DBAR) program was initiated as an international venture to share expertise, knowledge, technologies, and data to demonstrate the role of Earth observation science and technology and big Earth data applications to support large-scale development. In this paper, we identify pressing challenges, present the research priorities and foci of the DBAR program, and propose solutions where big Earth data can make significant contributions. This paper calls for further joint actions and collaboration to build a digital silk road in support of sustainable development at national, regional and global levels.     

Geometric-constrained multi-view image matching method based on semi-global optimization

Targeting at a reliable image matching of multiple remote sensing images for the generation of digital surface models, this paper presents a geometric-constrained multi-view image matching method, based on an energy minimization framework. By employing a geometrical constraint, the cost value of the energy function was calculated from multiple images, and the cost value was aggregated in an image space using a semi-global optimization approach. A homography transform parameter calculation method is proposed for fast calculation of projection pixel on each image when calculating cost values. It is based on the known interior orientation parameters, exterior orientation parameters, and a given elevation value. For an efficient and reliable processing of multiple remote sensing images, the proposed matching method was performed via a coarse-to-fine strategy through image pyramid. Three sets of airborne remote sensing images were used to evaluate the performance of the proposed method. Results reveal that the multi-view image matching can improve matching reliability. Moreover, the experimental results show that the proposed method performs better than traditional methods.     

Super-resolution enhancement of UAV images based on fractional calculus and POCS

Abstract

A super-resolution enhancement algorithm was proposed based on the combination of fractional calculus and Projection onto Convex Sets (POCS) for unmanned aerial vehicles (UAVs) images. The representative problems of UAV images including motion blur, fisheye effect distortion, overexposed, and so on can be improved by the proposed algorithm. The fractional calculus operator is used to enhance the high-resolution and low-resolution reference frames for POCS. The affine transformation parameters between low-resolution images and reference frame are calculated by Scale Invariant Feature Transform (SIFT) for matching. The point spread function of POCS is simulated by a fractional integral filter instead of Gaussian filter for more clarity of texture and detail. The objective indices and subjective effect are compared between the proposed and other methods. The experimental results indicate that the proposed method outperforms other algorithms in most cases, especially in the structure and detail clarity of the reconstructed images.     

Modelling coastal land use change by incorporating spatial autocorrelation into cellular automata models

This paper presents a spatial autoregressive (SAR) method-based cellular automata (termed SAR-CA) model to simulate coastal land use change, by incorporating spatial autocorrelation into transition rules. The model captures the spatial relationships between explained and explanatory variables and then integrates them into CA transition rules. A conventional CA model (LogCA) based on logistic regression (LR) was studied as a comparison. These two CA models were applied to simulate urban land use change of coastal regions in Ningbo of China from 2000 to 2015. Compared to the LR method, the SAR model yielded smaller accumulated residuals that showed a random distribution in fitting the CA transition rules. The better-fitting SAR model performed well in simulating urban land use change and scored an overall accuracy of 85.3%, improving on the LogCA model by 3.6%. Landscape metrics showed that the pattern generated by the SAR-CA model has less difference with the observed pattern.     

西藏班戈错水菱镁矿藻类成矿实验及其成因分析

目前关于天然水菱镁矿的形成认识主要有蒸发沉积成因和生物成因两类。前人在室内成功制备出水菱镁矿矿物,证实了该矿物的无机成因理论,但是实验结晶条件明显高于西藏班戈错的寒冷气候条件和水化学条件,并且班戈错湖水通过自然蒸发结晶也难以形成水菱镁矿矿物,而这一认识与周边阶地上正在形成水菱镁矿的现象相矛盾。因此,自然蒸发沉积可能不是现阶段班戈错水菱镁矿的主要形成过程,而已有研究表明,藻类具备诱导形成碳酸盐矿物的能力,本文利用西藏班戈错Ⅲ湖湖水及其藻类开展室内模拟实验,并与无藻类的湖水自然结晶结果相对照,探讨藻类生命活动与班戈错水菱镁矿的成因联系。研究发现,藻类不仅能够适应高盐度盐水环境（矿化度117.3 g/L）,并且在其光合作用过程中还能显著提高周围水体pH值（最高可达10.564）,诱导并促进球碳镁石在藻类网状节点处结晶沉淀,该矿物进一步脱水即能够形成水菱镁矿矿物;而人为提高班戈错Ⅲ湖湖水Mg2+浓度也仅能结晶形成三水菱镁矿矿物,无球碳镁石或水菱镁矿结晶析出。因此,西藏班戈错水菱镁矿的形成过程与藻类生物成矿作用密切相关,但是有关球碳镁石向水菱镁矿转变的具体条件以及藻类成矿作用的具体分子机制仍不清楚,有待于进一步研究。     

中国铝土岩系中伴生钪资源富集规律及富集机制初探

钪(Sc)作为新世纪的重要资源,广泛分布于自然界中,但其分布极为稀散,钪的独立矿物稀少,独立矿床几乎没有。铝土岩系中的钪资源储量巨大,本文统计了中国各铝土矿成矿带Sc数据,在对比山西(断隆)成铝区、华北陆块南缘成铝区、渝南—黔北成铝带、黔中成铝区和滇东南—桂西成铝区的数据基础上,发现滇东南—桂西成铝区的Sc含量最高,含钪铝土岩系形成时代主要为石炭纪和二叠纪。通过对比分析A/S与钪的关系,在A/S小于2.5,钪的含量总体较高,且与A/S正相关,大于2.5后,与A/S负相关。从而得出在铝土岩系中,Sc分布在顶层的黏土岩、中部的铁质铝土矿以及底部的铁质黏土岩、铁质岩,尤其是在含铁铝土岩系中高度富集。通过对比分析铝土岩系各元素含量,发现钪与铁、铌、钒、铬元素成正相关,综合铝土岩系中其他元素的矿物表现形式,推测钪在铝土岩系中的赋存形式可能为：类质同象、离子吸附、和超显微非结构混入物。本文初步探讨总结钪在铝土岩系中可能的赋存形式、时空分布规律及钪的迁移转化机制,为铝土矿中伴生钪资源的综合利用开发提供理论支撑。     

黑龙江通河县曙光石场地区土壤地球化学特征与成矿预测

为查明曙光石场地区各成矿元素和矿(化)体的分布特征,在1∶2万土壤地球化学测量的基础上,对研究区多种成矿元素进行聚类分析和因子分析。研究表明:区内Ag、Pb、Zn、Bi、Sn单元素异常个数多、变异系数值较高,具有较强的成矿潜力;区内Ag-Pb-Zn元素组合异常套和极好,异常强度较强,与岩浆热液型成矿作用相关,具有较好的找矿前景;根据单元素异常的套合情况及元素共生组合规律圈定组合异常六处并进行了槽探工程验证,在Ht-4组合异常处发现一铅锌银矿点,矿体、矿化体产于上石炭统唐家屯组流纹质凝灰岩中。     

滇西盈江地区新泡山离子吸附型稀土矿床成矿条件及找矿前景

滇西盈江地区是近年来离子吸附型稀土矿床找矿突破较大的地区,典型代表为腾冲岩浆弧内新发现的新泡山稀土矿床,为一中型离子吸附型稀土矿床,是滇西高海拔地区新发现的典型矿床。新泡山稀土矿床的发现对今后高海拔地区的找矿工作具有重要的示范意义。通过对新泡山稀土矿床的地质特征、风化壳结构特征、矿体垂向变化特征进行研究,认为新泡山稀土矿床类型为富钕轻稀土离子吸附型稀土矿床,并伴生有重稀土钇。滇西盈江地区与花岗岩有关的离子吸附型稀土矿主要受控于母岩稀土元素丰度、气候以及地形地貌。"沟-谷-盆"地貌两侧及周缘低缓山丘和平缓山坡、山脊是有利的成矿部位。结合区域找矿成果,认为研究区稀土矿找矿潜力较大,可达超大型远景规模,在后续的找矿工作中应加强对重稀土元素钇的评价。     

滇西勐兴铅锌矿床热液方解石碳氧同位素、稀土元素特征及其指示意义

勐兴铅锌矿床是滇西保山地块内系列低温热液矿床中的典型代表,但地质科研工作相对薄弱。由于方解石是该矿床中分布广泛且与热液活动息息相关的重要脉石矿物,其形成贯穿整个成矿过程,故对其C-O同位素及稀土元素组成特征进行系统研究,以便探讨矿床成矿流体来源及演化。结果显示,该矿床两阶段方解石的δ~(13)C_(PDB)和δ~(18)O_(SMOW)值与海相碳酸盐岩较为接近,且从阶段Ⅰ→阶段Ⅱ呈微弱下降趋势,表明成矿流体中的C主要来源于围岩碳酸盐岩的溶解,阶段Ⅱ成矿流体在与围岩反应之前可能已经发生CO2热液去气作用;阶段Ⅰ方解石的稀土总量、特征参数及配分模式与结晶灰岩较为一致,而阶段Ⅱ方解石与生物碎屑灰岩较为相似,表明阶段Ⅰ方解石中的REE主要来源于结晶灰岩,而后生物碎屑灰岩对阶段Ⅱ方解石中的稀土贡献较大。以上数据及其矿床地质特征均显示该矿床为MVT型铅锌矿床,结合区域构造演化,认为勐兴矿床的形成与中特提斯洋闭合后腾冲地块与保山地块陆陆碰撞挤压密切相关。