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.     

Simulating methane emission from a Chinese rice field as influenced by fertilizer and water level

Natural and agricultural wetlands are considered to be the major sources of global atmospheric methane (CH₄). A one‐dimensional model was developed to simulate methane emission and used to examine the influence of various physical processes on the rate of methane emission. Three processes involved in the methane emission are implemented in the model: production, reoxidation and transport. Three transport pathways were considered: diffusion across water–air or soil–air interfaces, ebullition and diffusion through plants. These pathways are influenced by soil properties, plant growth, water‐table conditions, temperature and external inputs (e.g. fertilizer). The model was used to examine the seasonal variation of the methane emission at a rice field in Hunan, China, which was observed during a field experiment for consecutive (early and late) rice seasons in 1992. The observed seasonal variations of methane emission, and role of plants in transporting methane to the atmosphere, are captured by the model simulation. Further model applications were conducted to simulate effects of fertilizer and water‐level condition on the methane emission. The results indicate that unfermented organic fertilizer produces a higher methane emission rate than mineral fertilizer. The simulations with treatments of a deep‐water covering and constant moisture reduced the methane emission. The rice field study provides a framework for further development of the model towards simulations based on spatially distributed variables (e.g. water table, soil temperature and vegetation) at a regional scale. Copyright © 2003 John Wiley & Sons, Ltd.     

Glacier change and glacier runoff variation in the Tuotuo River basin,the source region of Yangtze River in western China

Glaciers in the Tuotuo River basin, western China, have been monitored in recent decades by applying topographical maps and high-resolution satellite images. Results indicate that most of glaciers in the Tuotuo River basin have retreated in the period from 1968/1971 to 2001/2002, and their shrinkage area is 3.2% of the total area in the late 1960s. To assess the influence of glacier runoff on river runoff, a modified degree–day model including potential clear-sky direct solar radiation has been applied to the glaciated regions of the river basin over the period 1961–2004. It was found that glacier runoff has increased in the last 44 years, especially in the 1990s when a two-thirds increase in river runoff was derived from the increase in glacier runoff caused by loss of ice mass in the entire Tuotuo River basin.     

缢蛏Sinonovacula constricta卵子发生的超微结构分析

本文描述了缢蛏卵子发生过程细胞学和超微结构的特征。在卵黄发生前期,卵母细胞胞质中存在着核质外排小体和大量的核糖体。在卵黄发生期,卵质中可见发达的内质网、环孔瓣状体和大量的线粒体及高尔基体等;卵核上有核膜泡和核膜小管的结构,并可观察到核孔数目大量增加。文中讨论了上述几种结构在卵子发生过程中的作用以及它们之间的关系。     

广州地区稻田甲烷排放及中国稻田甲烷排放的空间变化

１９９３年在广州地区采用中国科学院大气物理研究所研制的自动采集和分析系统测量了稻田甲烷的排放率，首次获得了占我国２０－２５％左右水稻收获面积的华南地区稻田甲烷排放特征值。从而宏观地使我国五个主要水稻生态区的甲烷排放率都有了实测资料。稻田甲烷排放率的季节变化主要与气温及灌溉水状态的变化的较大关系，日变化规律以下午出现极大为主。本实验田的甲烷排放率低。     

新疆及邻区体波震级初步分析研究

依据《地震震级的规定（GB 17740—2017）》,分析了2009—2017年新疆地震台网所记录的新疆及邻区476次中深源地震事件,测定了13601个m_b（短周期体波震级）和12035个m_B（BB）（宽频带体波震级）的数据样本,回归分析m_b和m_B（BB）得到回归方程及量规函数,结果显示m_b和m_B（BB）相关系数为0.966,表明两者显著相关。因此,建议对于中强型中深源地震可以直接从原始速度型宽频带数字地震记录上测定长周期体波震级m_B（BB）,提高地震速报测定的速度和精度。通过震级偏差统计和台站场地响应计算,分析新疆地震台网中的XKR、HTA、ATS和KSZ等地震台站震级偏差较大的原因为砂岩、灰岩、砂土层等类型的台基放大了场地响应,说明台基类型对体波震级偏差的影响较大。与NEIC测定的体波震级对比时,发现新疆地震台网测定体波震级平均偏大0.42级,且偏差随着震源深度的增加有增大的趋势。     

Assessment of global meteorological,hydrological and agricultural drought under future warming based on CMIP6

在全球变暖背景下,分析和预测干旱的变化趋势和传播规律对于区域生态环境安全和灾害管理具有重要意义.本文基于第六次国际耦合模式比较计划(CMIP6),分析了SSP2-4.5和SSP5-8.5两种变暖情景下的气象(标准化降水指数SPI和标准化降水蒸发指数SPED,水文(标准化径流指数SRI)和农业(标准化土壤水分指数SSI)...     

Thinning and shrinkage of Laohugou No. 12 glacier in the Western Qilian Mountains, China, from 1957 to 2007

Landsat images, real-time kinematic GPS measurements, and topographic maps were used to determine changes in ice elevation, volume, and areal extent of the Laohugou No. 12 glacier (Qilian Mountains, China) between 1957 and 2007. The glacier experienced significant thinning and areal shrinkage in the ablation zone, but slight thickening in part of the accumulation zone. Elevation decreased by 18.6±5.4 m between 1957 and 2007 in the regions covered by the GPS measurements. The total volume loss for the entire glacier was estimated to be 0.218 km3 using a third-order polynomial fit method. The area diminished by 0.28 km2 between 1957 and 1994, 0.26 km2 between 1994 and 2000, and 0.28 km2 between 2000 and 2007, suggesting that the rate of loss in glacial coverage has increased since the mid-1990s. Significant increases in annual mean air temperature may have contributed to shrinkage and thinning of the glacier.     

Effectiveness of grass strips in trapping suspended sediments from runoff

Little information is available concerning the performance of grass strips for erosion control from steep cropland. An experiment was conducted on 5‐m‐long grass strips with slopes of 3°～15° that were subjected to silt laden runoff and simulated rainfall, to investigate the sediment trapping processes. The grass strips had three treatments including intact grass control (C), no litter (dead grass material covering the soil surface was removed) (NL), and no litter or leaves (only 2～3 cm grass stems and roots were reserved) (NLL). Generally the grass strips had a high effectiveness in trapping sediment from steep cropland runoff. Sediment trapping efficiency (STE) decreased with increasing slope gradient, and even for a 15° slope, STE was still more than 40%. Most sediment deposited in the backwater region before each grass strips. The removal of grass litter or/and leaves had no significant influence on STE. The sediment median size (D₅₀) in inflow was greater than that in outflow, and the difference (ΔD₅₀) decreased with increasing slope. A positive power relationship between STE and ΔD₅₀ can be obtained. Grass strips were more effective in trapping sediments coarser than 10 or 25 µm, but sediments finer than 1 µm were more readily removed from runoff than particles in the range of 2 to approximately 10 µm. Grass litter had less influence on flow velocity than leaves because the deposited sediment partially covered the litter layer. Mean flow velocity and its standard deviation were negatively correlated with STE, and they can help make good estimation of STE. Results from this study should be useful in planting and managing forage grass to effectively conserve soil loss by runoff from steep slopes on the Loess Plateau of China. Copyright © 2010 John Wiley & Sons, Ltd.     

Plant drought tolerance trait is the key parameter in improving the modeling of terrestrial transpiration in arid and semi-arid regions

陆面过程蒸腾作用的模拟制约着天气,气候降水预测的精确度.近几十年来,为了更好地描述植被蒸腾的水力约束,陆面过程模式发展了基于植物性状的植物水力胁迫方案.然而,我们对于植物性状在蒸腾模拟中的地位仍然缺乏了解,植物性状对蒸腾的重要性仍需进一步量化.本研究利用Morris方法评估植物性状参数在通用陆面模式植物水力胁迫方案(CoLM-P₅₀HS)中的重要性,针对17种植物性状,筛选出最为重要的:耐旱性状(P₅₀),气孔性状,和光合作用性状.在12个FLUXNET站点中,参数的重要性由归一化敏感度来衡量.P₅₀的重要性随着降水的减少而增加,而气孔性状和光合作用性状的重要性则随着降水的减少而减少.在干旱或半干旱地区,P₅₀比气孔性状和光合作用性状更重要,这意味着当植物经常经历干旱时,水力安全策略比植物生长策略更关键.而耐旱性状的巨大变异性进一步暗示了多种植物水力安全策略的共存.忽视P₅₀的变异性可能会对陆面过程模式蒸腾作用的模拟造成严重误差.因此,为了更好地表示植物水力功能的变异性,需要增加对耐旱性状的观测并耦合到陆面模式中.