关于若干化探数据处理方法的讨论

化探数据处理中的系统误差校正和异常识别方法很多，移动标准化法、分区标准化法和衬度系数法是其中的几种方法，主要对这几种方法做了简单的介绍并对其效果进行了对比，最后着重讨论了C型变换法的优点。     

利用一种新的神经网络模型识别点状地图符号

着重讨论了用一种新的神经网络模型识别点状地图符号的过程，主要包括网络的结构特点和学习算法以及学习训练过程，并验证了用该网络进行点状地图符号识别的有效性。     

灰色系统GM模型在地下水动态异常识别中的应用

本应用灰色系统理论的ＧＭ模型对地下水动态资料进行了异常识别，发现在１９８１年河北宁晋ＭＳ５．８级地震、１９８３年荷泽ＭＳ５．９级地震、１９８５年河北任县ＭＳ５．０级地震前，有明显的异常显示，通过选择不同建模数据个数及外推个数，发现对豫０１井五日均值资料建模处理，选择２个月的数据１０天滑动逐次建模识别的异常较清楚。同时对所建模型的精度进行了分析，证明该方法在本区豫０１井、鲁０５井资料处理及前兆异常     

1990年景泰6.2级地震前后甘肃东南部地区的区域异常——地震前兆与后效区分

在分析地震活动性，地壳形变和其它前兆资料基础上指出，１９９０年景泰６．２级地震前后甘肃东南部地区的区域异常具有变化速率小，起始时间不同步，异常反央的力学性质不一致等特征，其中以异常变化速率小了为显著。     

气候变化及其对农作物生产潜力的影响

利用国家气象中心整编的1951—1990年全国160站年、月平均气温和总降水量,的资料序列,计算和分析了我国近40年的气候变化,讨论了我国气候变化的区域性和季节性差异;计算了各站的年作物光温生产潜力,探讨了气象变化对农业生产的影响。     

The expert system for earthquake prediction (I)—the overall design and main structure

The Expert System For Earthquake Prediction (ESEP) is summarized in this paper. ESEP embraces three subsystems: long-middle term prediction system, annual prediction system and middle-short term prediction system. Each of the subsystems is composed of seven modules: the controlling module, the data base module, the expert knowledge base module, the method base module, the fact preparation module, the reasoning and decision-making module and the plotting and displaying module. The reasoning model ESEP/R and the knowledge expression model ESEP/K are set up in the ESEP, and new evidence combinations, CON (confine), W (weigh), and SYN (synthesize), have been proposed. The distinctive features of the ESEP are: (1) systemized; (2) several experts’ knowledge can be synthesized; (3) a large amount of data and experts’ experience is embraced; (4) four reasoning models and the synthetic decision-making technic are adopted; (5) several software environments are used; (6) modularization; and (7) possessing the friendly user interfaces. The Chinese version of this paper appeared in the Chinese edition ofActa Seismologica Sinica,14, 1–8, 1992.     

自组织人工神经网络在滇东震旦系—寒武系分界线岩相古地理研究中的应用

运用T.Kohonen自组织人工神经网络,根据滇东24个剖面的渔户村组中谊村段的各种单元素(包括岩段厚度、组成岩段的岩石薄片单因素-白云质、硅质、泥质、磷质、陆屑及盆屑,和岩段的24种光谱元素)的统计资料,建立了该地区震旦系-寒武系分界线的岩相古地理相区识别的计算机智能专家系统,其识别成功率达100％。结果表明,该方法性能良好,可望成为岩相古地理定量研究的一种有效的辅助手段。     

A workflow for Sustainable Development Goals indicators assessment based on high-resolution satellite data

ABSTRACT

For evaluating the progresses towards achieving the Sustainable Development Goals (SDGs), a global indicator framework was developed by the UN Inter-Agency and Expert Group on Sustainable Development Goals Indicators. In this paper, we propose an improved methodology and a set of workflows for calculating SDGs indicators. The main improvements consist of using moderate and high spatial resolution satellite data and state-of-the-art deep learning methodology for land cover classification and for assessing land productivity. Within the European Network for Observing our Changing Planet (ERA-PLANET), three SDGs indicators are calculated. In this research, harmonized Landsat and Sentinel-2 data are analyzed and used for land productivity analysis and yield assessment, as well as Landsat 8, Sentinel-2 and Sentinel-1 time series are utilized for crop mapping. We calculate for the whole territory of Ukraine SDG indicators: 15.1.1 – ‘Forest area as proportion of total land area’; 15.3.1 – ‘Proportion of land that is degraded over total land area’; and 2.4.1 – ‘Proportion of agricultural area under productive and sustainable agriculture’. Workflows for calculating these indicators were implemented in a Virtual Laboratory Platform. We conclude that newly available high-resolution remote sensing products can significantly improve our capacity to assess several SDGs indicators through dedicated workflows.     

Thermal bidirectional gap probability model for row crop canopies and validation

Land surface temperature is a key parameter in monitoring the status of crop water stress by remote sensing, and studying the water and energy balance in cropland ecosystem. The component temperatures of crop and soil are especially significant in remote …     

山西地下水氡中短期异常识别标志及预报方法研究

采用“九五”地震科技攻关地下水化学及 EIS2 0 0 0提供的多种数据处理和异常识别方法 ,对山西省地下水氡观测资料进行了较详细的处理 ,筛选出较好的数据处理方法和异常标志。结果表明 ,除常规的数学处理方法外 ,用水氡的基值变化率和滑动变化率提取异常效果较好 ,如果基值变化率 R0 ≥ 0 .0 6 ,持续时间大于等于 12个月 ,滑动变化率 R≥ 0 .0 5 ,持续时间大于等于 12个月 ,则视为异常