塔克拉玛干沙漠腹地几种植物根系分形特征

在塔克拉玛干沙漠腹地采用全根挖掘法挖掘河西菊(Hexinia polydichowma(Ostenf.)H.L.Yang)、沙拐枣(Calligonuin roborovskii A.Los.)、罗布麻(Apocynum venetum L.)、阿克苏牛皮消(Cynanchum amplexicaule Hemsl)根系.运用分形理论对其分形特征进行研究,分析根系分支状况以及根系分形特征与拓扑特征之间的关系.研究发现:(1)在塔克拉玛干沙漠腹地,四种植物根系具有很好的分形特征,分形维数大小与拓扑参数连接总数、外部连接数之间具有较好的相关关系.(2)根丰度是描述根系在土层中扩展能力的有效指标,与根系长度、平均连接长度之间具有很好的指数关系分别可以用以下方程表示:y1=2.7 694e1.5496x,y2=0.0369e2.0 267x(其中y1、y2分别为总根长、平均连接长度,R2分别为:0.9 353、0.9 832),根丰度直接反映了根系空间占有能力与营养物质的吸收效率.通过对塔克拉玛干沙漠腹地四种植物根系分支状况与分形特征的研究表明.分形理论可以很好的反映根系空间占有能力与资源吸收效率,所以说分形理论是对根系几何、功能特征进行定量化研究的有效方法.     

高分子材料SH固沙性能与微结构相关性研究

SH作为一种环保型、节约型有机高分子固化材料,用于沙漠治理具有广阔的应用前景。采用不同浓度SH、不同加固方式对沙体进行加固,加固后沙体微结构会发生变化,其物理力学性能也会出现显著变化。通过图形处理软件对固化后沙体的SEM图像进行计算分析;利用多元逐步回归分析方法对其性能参数与微结构参数之间的相关性进行计算,并对其相关性进行分析评价。计算结果表明,二者之间存在着良好的相关关系,各向异性、等效直径、扁圆度、充填比和面积比是对固化沙土力学性质影响较为显著的5个微结构参数。从微观角度证明了SH是一种较为理想的高分子固沙材料。     

工程岩体断裂构造发育程度的定量评价研究IAEG信息(会讯)

岩体断裂构造发育程度及其均匀性是影响岩体结构类型、岩体质量优劣及岩体稳定性分析以及工程岩体综合分区利用的重要因素, 因此岩体断裂构造发育程度的定量评价具有重要的工程意义。本文以三峡工程永久船闸边坡工程为例, 系统地讨论了工程岩体断裂构造发育程度的评价方法、定量评价指标的确定原则、断裂构造发育程度的分级标准等。研究表明, 根据岩体断裂构造发育特点, 综合运用多层次模糊综合评判法和人工神经网络技术是评价工程岩体断裂构造发育程度的有效方法。     

Performance of shape indices and classification schemes for characterising perceptual shape complexity of building footprints in GIS

Shape characterisation is important in many fields dealing with spatial data. For this purpose, numerous shape analysis and recognition methods with different degrees of complexity have so far been developed. Among them, relatively simple indices are widely used in spatial applications, but their performance has not been investigated sufficiently, particularly for building footprints (BFs). Therefore, this article focuses on BF shape characterisation with shape indices and classification schemes in a GIS environment. This study consists of four phases. In the first phase, the criteria for BF shape complexity were identified, and accordingly, benchmark data was constructed by human experts in three shape complexity categories. In the second phase, 18 shape indices were selected from the literature and automatically computed in GIS. The performance of these indices was then statistically assessed with histograms, correlation matrix and boxplots, and consequently four indices were found to be appropriate for further investigation. In the third phase, two new indices (Equivalent Rectangular index and Roughness index) were proposed with the objective to measure some BF shape characteristics more efficiently. The proposed indices also were found to be appropriate with the same statistical assessment procedures. In the final phase, BF shape complexity categories were created with the pairs of six appropriate indices and four choropleth mapping classification schemes (equal intervals, natural break, standard deviation, and custom) in GIS. The performance of the index–scheme pairs was assessed against the benchmark data. The findings demonstrated that both new indices and two of the selected indices (Convexity and Rectangularity) delivered higher performance. The custom classification scheme was found more ideal to reveal absolute shape complexity with the index value ranges derived from the boxplots while the other classification schemes were more appropriate to reveal relative shape complexity.     

高液限土路堤填筑的双指标控制方法研究

对于高液限土（包括改良的高液限土）填筑的路堤只用单一的压实度指标控制常常易导致质量隐患。通过试验研究提出一个采用空气率Va和压实度Dc双指标控制高液限土路堤填筑质量的方法,并给出了具体的控制标准。当压实度控制指标Dc≥93%时,高液限黏土和粉土空气率控制标准为4%≤Va≤8%,含砂高液限黏土和粉土空气率控制标准为6%≤Va≤13%。通过系统的试验研究,验证了双指标质量控制的可行性和有效性。研究结果表明,采用空气率和压实度双指标控制,不仅可以保证高液限土填筑路堤的强度和刚度,而且具有较好的水稳定性,为进一步充分利用高液限土作为路堤填料提供了技术支持。     

含盐量对滨海盐渍土物理及水理性质的影响

含盐量的增加使滨海盐渍土含水率与含液率间的差值变大,并导致高估土的干密度,低估土的孔隙比和饱和度。物理性质指标换算和颗粒级配分析试验结果表明,从2%的含盐量开始,随含盐量增加,胶粒含量减少,粘粒和粉粒含量增加,但25μm及以上的粒组含量变化不大。2%以内的含盐量对土的稠度指标影响微弱,当含盐量增加到11%时,盐分结晶形成了较多的晶体颗粒,使土的塑性指数明显下降并呈现出区段性。     

福建及其周边地区地震活动人工神经网络模型的构建

本文通过对福建及其周边地区地震活动人工神经网络模型的构建,研究了人工神经网络方法在基于该区域地震活动性指标的地震分析预报中的应用。选用含一个中章层的前向神经网络模型,并采用与之相适应的ＢＰ算法,以该地区１９７１～１９９７年的地震活动性资料为基础,用神经网络进行实际计算、分析和检验。结果表明：神经网络模型对福建及其周边地区地震震级的预测检验效果较好的,可以在一定精度范围内使震级预测的内符率达１００％     

Evaluating the relationship between biomass,percent groundcover and remote sensing indices across six winter cover crop fields in Maryland,United States

Winter cover crops are an essential part of managing nutrient and sediment losses from agricultural lands. Cover crops lessen sedimentation by reducing erosion, and the accumulation of nitrogen in aboveground biomass results in reduced nutrient runoff. Winter cover crops are planted in the fall and are usually terminated in early spring, making them susceptible to senescence, frost burn, and leaf yellowing due to wintertime conditions. This study sought to determine to what extent remote sensing indices are capable of accurately estimating the percent groundcover and biomass of winter cover crops, and to analyze under what critical ranges these relationships are strong and under which conditions they break down. Cover crop growth on six fields planted to barley, rye, ryegrass, triticale or wheat was measured over the 2012–2013 winter growing season. Data collection included spectral reflectance measurements, aboveground biomass, and percent groundcover. Ten vegetation indices were evaluated using surface reflectance data from a 16-band CROPSCAN sensor. Restricting analysis to sampling dates before the onset of prolonged freezing temperatures and leaf yellowing resulted in increased estimation accuracy. There was a strong relationship between the normalized difference vegetation index (NDVI) and percent groundcover (r² = 0.93) suggesting that date restrictions effectively eliminate yellowing vegetation from analysis. The triangular vegetation index (TVI) was most accurate in estimating high ranges of biomass (r² = 0.86), while NDVI did not experience a clustering of values in the low and medium biomass ranges but saturated in the higher range (>1500 kg/ha). The results of this study show that accounting for index saturation, senescence, and frost burn on leaves can greatly increase the accuracy of estimates of percent groundcover and biomass for winter cover crops.     

Drought in Bulgaria and atmospheric synoptic conditions over Europe

Drought in Bulgaria is analyzed from the multiple viewpoints of statistical occurrence, spatial patterns, and synoptic conditions. A new index of drought, the SD (spatial-dryness) index, characterizes drought by both intensity and spatial extent. The occurrence of the SD index is analyzed using global gridded data sets. Examination of transitional probabilities of multiple months and years with drought occurrence suggests persistence is sufficiently frequent to be important for climate-related environmental planning. Finally, it is shown that specific seasonal synoptic patterns are associated with wet and dry conditions in Bulgaria. This revised version was published online in July 2006 with corrections to the Cover Date.     

北京城市高温遥感指标初探与时空格局分析

利用北京高温天气下的NOAA18/AVHRR卫星资料与气象台站资料,分析了日最高气温与遥感反演的城市地表温度的关系,初步确定了地表高温阈值并建立了高温遥感指标,并利用1989~2008年(缺2002年)6~9月NOAA/AVHRR资料开展了北京地区高温时空格局分析研究。指标初步研究表明:北京气温高温值为35、37、40°C对应的遥感地表高温值分别为44、47、52°C,可以较好地适用于北京平原地区;利用该阈值建立的地表高温强度指标(LSHI)对北京平原高温的监测与气象台站高温监测基本一致,而高温比例指数指标(LSHP)能有效反映出城市高温空间强弱和时间差异。北京遥感地表高温空间格局分析显示:夏季(6~8月)旬平均遥感地表温度≥44°C年出现概率不超过50%,广泛分布于城区和平原区;旬平均遥感地表温度≥47°C年出现概率不超过40%,集中于北京五环内;旬平均遥感地表温度≥52°C年出现概率不超过15%,集中于城区;6~9月高温出现的概率高值区一般都集中于五环内,其中旬平均遥感地表温度≥44°C、≥47°C、≥52°C的出现概率分别为80%~100%、60%~80%、10%~40%。