一种非凸包边界约束不规则三角网生成算法

为研究非凸空间离散数据的空间划分,建立了耦合数据集的凸凹性、数据规模、离散度的空间划分的数学模型。利用Laves划分标识[3⁶]对非凸空间离散数据进行有限区域变比例划分,然后通过地形曲面微分单元与数据规模的偏导函数关系,耦合离散度计算空间划分的单元间距和数量。最后通过构建DEM,可视化验证和对比分析发现,耦合模型能够计算出非凸离散空间数据空间划分单元的间距和数量,也能实现不同分辨率的划分单元的无缝拼接;且当试验数据从110组递增至440组时,该模型耗时仅是[4⁴]标识划分和Delaunay的1/10～1/3,且随数据规模成倍增加时耗时基本呈线性增长,收敛性较好,但耗时随离散度增加而增长。     

Evaluating the fitness for use of spatial data sets to promote quality in ecological assessment and monitoring

This article proposes and illustrates a practical methodological framework to evaluate the fitness for use of spatial data sets for environmental and ecological applications, focusing on user requirements for specified application contexts. The methodology is based on the use of metadata to analyze similarity between the data characteristics and the user’s needs or expectations for several quality indicators. Additionally, the concept of ‘critical factors’ is introduced in this framework, allowing users to define which quality indicators have greater importance given their own requirements or expectations and the specified application contexts. The proposed methodology further allows integrating and interconnecting the spatial data quality (SDQ) evaluation methodology with metadata geoportals in WebGIS platforms, facilitating its operation by users from non-spatial disciplines and with often limited expertise on this subject. Examples of the evaluation of fitness for use for specific application contexts within the project BIO_SOS (‘Biodiversity Multi-SOurce Monitoring System: From Space To Species’ FP7 project) are presented. By providing a prompt and straightforward evaluation tool, the proposed methodology can encourage the implementation of SDQ evaluation routines in ecological assessment and monitoring programs, promoting a more adequate use of geospatial data and ultimately contributing to well-supported policy and management decisions.     

Assessment of future runoff trends under multiple climate change scenarios in the Willamette River Basin,Oregon, USA

We investigated trends in future seasonal runoff components in the Willamette River Basin (WRB) of Oregon for the twenty‐first century. Statistically downscaled climate projections by Climate Impacts Group (CIG), eight different global climate model (GCM) simulations with two different greenhouse gas (GHG) emission scenarios, (A1B and B1), were used as inputs for the US Geological Survey's Precipitation Runoff Modelling System. Ensemble mean results show negative trends in spring (March, April and May) and summer (June, July and August) runoff and positive trends in fall (September, October and November) and winter (December, January and February) runoff for 2000–2099. This is a result of temperature controls on the snowpack and declining summer and increasing winter precipitation. With temperature increases throughout the basin, snow water equivalent (SWE) is projected to decline consistently for all seasons. The decreases in the centre of timing and 7‐day low flows and increases in the top 5% flow are caused by the earlier snowmelt in spring, decreases in summer runoff and increases in fall and winter runoff, respectively. Winter runoff changes are more pronounced in higher elevations than in low elevations in winter. Seasonal runoff trends are associated with the complex interactions of climatic and topographic variables. While SWE is the most important explanatory variable for spring and winter runoff trends, precipitation has the strongest influence on fall runoff. Spatial error regression models that incorporate spatial dependence better explain the variations of runoff trends than ordinary least‐squares (OLS) multiple regression models. Our results show that long‐term trends of water balance components in the WRB could be highly affected by anthropogenic climate change, but the direction and magnitude of such changes are highly dependent on the interactions between climate change and land surface hydrology. This suggests a need for spatially explicit adaptive water resource management within the WRB under climate change. Copyright © 2010 John Wiley & Sons, Ltd.     

Spatial and temperal patterns in bacterioplankton communities across a river-lake continuum

Bacterioplankton play critical roles in biogeochemical cycling. Although spatial and temporal variations in bacterioplankton community compositions (BCCs) within individual habitat have been reported, knowledge gaps remain for studies conducted within different habitats. In this work, we examined the seasonal and spatial variability of BCCs in Nanfei River and Lake Chaohu which had significant environmental heterogeneity using a high-throughput sequencing technique of 16S rRNA gene amplicons. The results showed that spatial variation has a more obvious impact on the BCCs than seasonal changes. The microbial diversity gradually decreased and BCCs changed obviously along water flow direction from Nanfei River to the western and estern parts of Lake Chaohu over all seasons. LEfSe analysis showed that Nanfei River had higer abundance of species belonging to the orders Rhodocyclales, Methylococcales, Campylobacterales and Flavobacteriales, samples from eastern part of Lake Chaohu were abundant in taxonomies including the order Rickettsiales, while the western part had high abundance of taxonomies belonging to the order Chroococcales. The redundancy analysis (RDA) indicated that BCCs in Nanfei River were associated with high nutrient (TP, PO₄-P, TN, NH₃-N, NO₂-N and NO₃-N) concentrations and electrical conductivity. Variance partitioning RDA analysis indicated that the combined effects of all variables may be most important affecting BCCs. This study may provide a framework for modeling the change in bacterioplankton communities through different habitats from a river to lake.     

ANALYSIS OF THE ATMOSPHERIC AEROSOL OPTICAL DEPTH OVER CHINA IN 1980s*

This paper retrieves the yearly and monthly mean 0.75μm aerosol optical depth(AOD) of 41 A-class solar radiation stations over China from 1979 to 1990,and analyzes the spatial and temporal distribution of AOD over China mainland.The data employed are daily direct solar radiation and sunshine duration,as well as the TOMS version-7 ozone observation data in the same time.The results indicate that the Siehuan Basin is the largest center of yearly mean AOD over China.and the other two larger centers lie in Wuhan City and the South Xinjiang Basin,separately.AOD values are also relatively larger in the middle-and-lower reaches area of Changjiang River.Shandong Peninsula and coastal area of Guangdong Province:while in Yunnan Province,coastal area of Fujian Province.most parts of Northwest and Northeast China,AOD values are relatively smaller.The distribution of AOD varies with different months.In most parts of China.the maximum of AOD occurs in spring season;but the minimum varies in different regions,From 1979 to 1990.in the Qinghai-Xizang Plateau,West Siehuan Basin,North Guizhou Province.most areas of the middle-and-lower reaches of Changjiang River,Shandong Peninsula and west part of South Xinjiang Basin.AOD shows an increasing trend.But in Northeast China,most part of Northwest China,Yunnan-Guizhou Plateau,western Guangxi Region and the coastal areas of East China,AOD shows decreasing tendency.Generally,the seasonal variation characteristics of AOD in China can be classified into four typical models,i.e.,mono-modal types A and B,bimodal and Poly-modal.     

1993～2003年郑州市土地利用/覆被变化特征研究

以河南省郑州市为例,利用RS、GIS软件对1993年和2003年两时次TM、ETM 影像进行遥感解译,采用GIS空间分析和数理统计分析等方法,研究了10 a来该市土地利用变化过程尤其是土地沙化的变化过程及其社会经济驱动机制。结果表明:10 a来,西部山区、东部沙化地区以及黄河沿岸地区土地利用类型的变化比较大,特别是东部地区用地变化比较剧烈;旱地、草地、工交建设用地面积明显增加,沙化土地、水田、林地、水体面积呈现减少的趋势;沙化现象得到了有效遏制,草地面积的增加,改善了研究区的生态环境。此外,林地面积的大量减少,应引起重视,可实行退耕还林或植树造林以建立良好的生态环境。     

2022年云南宁蒗MS 5.5地震前云南地区异常特征分析

通过对2022年1月2日宁蒗M_S 5.5地震前震中附近地区地震学、地下流体、定点形变等观测资料进行分析,发现本次地震前多学科异常呈现以下特征： ① M_S 5.5地震发生在宁蒗地区M_S ≥ 5.0地震平静近10年背景下,震中附近M_L ≥ 3.0地震于震前1年形成空区,主震发生在空区边缘,空区长轴180 km,按照川滇地区统计公式计算,未来发生地震的震级为5.8±0.5,与宁蒗M_S 5.5地震大小相当; 2015年以来,震中附近50 km范围内M_L ≥ 3.0地震呈平静—活跃—平静—发震的特征; ②地球物理观测异常均于震前7个月内出现,集中分布在滇西北地区距震中300 km范围内,且水温和水位测项异常出现较早; ③定点形变采用NS向与EW向幅值相加来描述同一观测资料的变化,数据曲线幅值增大可作为临震异常3个月短期指标,距震中越近,观测台项异常比例越高;④大部分宏观异常出现在震前3个月内,宏观异常增多可作为时间预测判据。综合上述多学科异常,认为地震学异常出现最早,可用于判定发震区域,用流体和定点形变观测异常追踪时间,宏观异常更多作为短期判定指标,可为宁蒗地区M_S ≥ 5.0地震资料积累提供跟踪思路和方法。     

基于Intergraph GIS的基础空间数据库一体化建设研究

阐述了基于Intergraph GIS的城市基础空间数据的结构和建库的内容,提出了一体化的建库、质量控制、空间数据动态更新以及基于版本信息的历史数据存储与恢复的方法,介绍了一体化建库实例。     

一种云端一体化的土地督察遥感监测方法

针对目前土地遥感监测工作中存在的监测频次低和数据现势性差等问题,通过统筹获取国产卫星影像数据提升监测频次,设计了多源遥感影像的空间网格组织和调度方法,改变传统的影像切片发布模式,建立实时影像服务方法,大幅提升了土地督察遥感监测时效。通过在国家土地督察济南局试点应用,研发了云端一体化的土地督察遥感监测服务平台,实践证明基于空间网格的影像组织管理效率优于传统金字塔切片管理模式,有效支撑了违法用地、永久基本农田保护和城市开发边界突破等监测预警,应用成效显著。     

1965-2015年新疆夏季不同等级降水的空间分布特征

根据新疆51个台站1965-2015年夏季逐日降水资料,将降水划分为小雨、中雨及大雨3个等级,分析了新疆近51 a夏季不同等级降水量、降水日数及降水强度的空间分布特征,并讨论了各等级降水日、降水量及降水强度与总降水量的空间相似程度以及各等级降水对夏季总降水的贡献。结果表明：新疆降水主要集中在夏季,并以小雨为主。以天山山脉为界,南北两疆降水空间分布存在明显差异,北疆夏季降水量（日）占年降水量（日）的36%~45%（36%~39%）,南疆夏季降水量（日）占年降水量（日）的51%~63%（48%~60%）;新疆夏季不同等级降水量、降水日及降水强度的空间分布不均匀。新疆夏季总降水量与各等级降水量的空间相似系数最为密切,与各等级降水强度的空间相似系数相对较小;新疆夏季小雨贡献率最大,中雨其次,大雨最小,夏季降水量和降水日的变化主要受小雨的影响。