A machine learning approach for predicting computational intensity and domain decomposition in parallel geoprocessing

ABSTRACT

High performance computing is required for fast geoprocessing of geospatial big data. Using spatial domains to represent computational intensity (CIT) and domain decomposition for parallelism are prominent strategies when designing parallel geoprocessing applications. Traditional domain decomposition is limited in evaluating the computational intensity, which often results in load imbalance and poor parallel performance. From the data science perspective, machine learning from Artificial Intelligence (AI) shows promise for better CIT evaluation. This paper proposes a machine learning approach for predicting computational intensity, followed by an optimized domain decomposition, which divides the spatial domain into balanced subdivisions based on the predicted CIT to achieve better parallel performance. The approach provides a reference framework on how various machine learning methods including feature selection and model training can be used in predicting computational intensity and optimizing parallel geoprocessing against different cases. Some comparative experiments between the approach and traditional methods were performed using the two cases, DEM generation from point clouds and spatial intersection on vector data. The results not only demonstrate the advantage of the approach, but also provide hints on how traditional GIS computation can be improved by the AI machine learning.     

Drought assessment in a south Mediterranean transboundary catchment

ABSTRACT

Predicting the impacts of climate change on water resources remains a challenging task and requires a good understanding of the dynamics of the forcing terms in the past. In this study, the variability of precipitation and drought patterns is studied over the Mediterranean catchment of the Medjerda in Tunisia based on an observed rainfall dataset collected at 41 raingauges during the period 1973–2012. The standardized precipitation index and the aridity index were used to characterize drought variability. Multivariate and geostatistical techniques were further employed to identify the spatial variability of annual rainfall. The results show that the Medjerda is marked by a significant spatio-temporal variability of drought, with varying extreme wet and dry events. Four regions with distinct rainfall regimes are identified by utilizing the K-means cluster analysis. A principal component analysis identifies the variables that are responsible for the relationships between precipitation and drought variability.     

An Artificial Intelligent design for GPS Surveying Networks

Metaheuristic techniques, which are based on ideas of Artificial Intelligence, are among the best methods for solving computationally the GPS surveying network problem. In this paper, the ant colony optimization metaheuristic, which is inspired by the behavior of real ant colonies, is developed to efficiently provide a general framework for optimizing GPS surveying networks. In this framework, a set of ants co-operate together using an indirect communication procedure to find good GPS observation schedules. A GPS surveying network can be defined as a set of stations, co-ordinated by a series of sessions formed by placing receivers on the stations. The problem is to search for the best order in which to observe these sessions to give the best schedule at minimum cost. Computational results obtained by applying the proposed technique on several networks, with known and unknown optimal schedules, prove the effectiveness of the proposed metaheuristic technique to solve the GPS surveying network problem.     

Automatic Location of Swarm Earthquakes from Local Network Data

An advanced method of automated seismic phase picking and exact location and magnitude determination of swarm micro-earthquakes from local network data is presented. The phase picker is applied in two steps: first, S-wave groups are identified using a polarisation detector, and then corresponding P-wave groups are searched for. The times of maximum P- and S-amplitudes are then used as starting points for the determination of accurate P- and S-arrival times. The maximum S-wave amplitudes are utilised for determining local magnitudes. The whole procedure is checked by simultaneous preliminary hypocentre location providing estimates of local magnitudes and a compatibility check of the candidate P- and S-phases. The closest station to the earthquake cluster is used as a master, and the phase search at the remaining stations is governed by the P- and S-phases identified at the master station. Thanks to the use of apriori information on the approximate position of hypocentres, the procedure is also capable of picking the individual P- and S-phases of sequences of overlapping swarm events. The performance of the procedure was tested by comparison of the automatically and interactively created catalogues of the January 1997 NW-Bohemia micro-earthquake swarm. With stations located at epicentral distances between 0 and 20 km, the difference between hypocentre coordinates obtained by automatic and interactive processing did not exceed 80 m for 86% events. All events above magnitude 0.5 were identified, and the automatically determined polarity of first P-wave motion proved to be correct in 89% of them.     

Linking pesticides and human health: A geographic information system (GIS) and Landsat remote sensing method to estimate agricultural pesticide exposure

Accurate pesticide exposure estimation is integral to epidemiologic studies elucidating the role of pesticides in human health. Humans can be exposed to pesticides via residential proximity to agricultural pesticide applications (drift). We present an improved geographic information system (GIS) and remote sensing method, the Landsat method, to estimate agricultural pesticide exposure through matching pesticide applications to crops classified from temporally concurrent Landsat satellite remote sensing images in California. The image classification method utilizes Normalized Difference Vegetation Index (NDVI) values in a combined maximum likelihood classification and per-field (using segments) approach. Pesticide exposure is estimated according to pesticide-treated crop fields intersecting 500 m buffers around geocoded locations (e.g., residences) in a GIS. Study results demonstrate that the Landsat method can improve GIS-based pesticide exposure estimation by matching more pesticide applications to crops (especially temporary crops) classified using temporally concurrent Landsat images compared to the standard method that relies on infrequently updated land use survey (LUS) crop data. The Landsat method can be used in epidemiologic studies to reconstruct past individual-level exposure to specific pesticides according to where individuals are located.     

华东地区气溶胶分布和变化特征研究

利用中分辨率光谱仪(MODIS)获得的气溶胶光学厚度(AOD)、细粒子比例(FMF)和臭氧检测仪(OMI)获得的气溶胶指数(AI)统计分析了2005—2014年我国华东地区气溶胶光学性质的时空分布特征,同时利用潜在源分析(PSCF)模型对我国华东地区AOD和AI的潜在源区进行分析。研究结果表明:华东地区的AOD、FMF和AI时空分布存在较大的差异,2005—2014年AOD和AI的平均值高值主要分布在华东地区北部,FMF的高值区则分布在华东南部地区;10 a间华东地区AOD呈现出先升高后降低的趋势,FMF波动幅度不明显,AI值有所上升;整个华东地区AOD的季节变化较为明显,春夏两季AOD明显高于秋冬两季。华东北部和中部地区夏季由于较高的相对湿度,AOD最大可达0.8以上。而在华东南部地区,夏季受到降水的影响,AOD维持在0.2~0.4之间。FMF季节变化趋势与AOD不同,夏季最大达到0.58,春季最小仅为0.26。AI平均值在冬季最大高达0.63,夏季最小,为0.27。PSCF分析显示华东地区AOD主要源区以局地排放为主,同时也存在由河南、湖北和湖南等周边省市近距离输送影响;AI以局地和北方远距离输送为主,同时也受到河南、湖北等周边省市近距离输送的影响。     

Human genome behaviour: a powerful mechanism for optimizing the use of space technology in surveying networks design

An approach based on the behaviour of human genome is developed to efficiently provide a general framework for optimizing the use of space technology in surveying networks design. The developed approach attempts to apply the successful self-organizing principles based upon the biological evolution to artificial intelligence. It mimics the phenomena of natural selection observed in nature to achieve its goals by continuously adopting a population of candidate solutions and improving its performance over successive generations. The goal of adaptation is to find the best solution that optimizes the design of a surveying network based on the use of satellite observations. This network can be defined as a set of stations, co-ordinated by a series of sessions formed by placing receivers on the stations. The problem is to search for the best order for observing these sessions to give the best observation schedule at minimum cost. The obtained results prove the effectiveness of the developed technique in term of solution quality and computational efforts. The Corresponding Author in formed me that his address is likely to change soon. Please contact me, leick@spatial.maine.edu for the latest on this change.     

基于优化参数的地震P、S波震相到时自动拾取及质量评估

准确拾取P、S波震相到时是深入开展地震波研究工作的基础,本文改进了自动拾取参数优化函数算法和质量评估方案,引入了拾取到时优化方案,使用基于参数优化的频带-带宽拾取算法、AICD拾取算法和峰度拾取算法对腾冲地区7个宽频带地震台站记录的地震资料开展了地震P、S波到时自动拾取,对拾取结果进行了优化和质量判定.结果表明：经参数优化、拾取优化后,采用3种方法自动拾取的P、S波到时与人工拾取到时的时差在0.1 s内的记录占比分别达到74.66%、70.98%.这些参数值均优于算法改进前的同类参数,证明了优化方法的可靠性.     

Role of the Rossiter-McLaughlin effect in the study of close binaries

This paper is devoted to binary stars belonging to the class of eclipsing-variable systems.Photometric and spectroscopic analysis of eclipses allows us to determine geometric parameters of the orbit and physical characteristics of stellar components as well as inclinations of stellar equators to the orbital plane. Estimations of inclinations can be obtained from measurement of the Rossiter-McLaughlin effect, which is discussed using examples of some eccentric binaries with an anomalous apsidal effect. Our task is to find the complete spectrum of solutions of the equation of apsidal motion, depending on the inclinations of the polar axes of the components to the orbital one for these systems, based on their individual spectroscopic and photometric observational data. The matrix of solutions allows us to select those pairs of polar inclinations that provide agreement with the observational apsidal period.     

“天地图·宁夏”图面整理浅析

在全国“天地图”省级节点建设工作中,位于西北的宁夏回族自治区也是重要一环,文章阐述了在“天地图·宁夏”项目成果整理阶段,如何在适当的软硬件环境下,根据相应的数据基础,运用AdobeIllustrator软件,进行图面配置的方法,特别是配图时必须解决好的几个常见问题,如：调整道路的叠放顺序、POI符号及其注记处理、道路编码整理规范、水系注记的表达方式、地物矛盾的处理原则等,以期通过实践摸索,反复比较、改进,找到配图表达的最优方案,以期达到良好效果。