基于 PCA 特征融合与 LDA 分类的实木地板纹理判别方法

纹理一致性影响着实木地板档次,针对目前实木地板纹理分类速度慢、精度低的问题,提出一种适合区分直纹、抛物纹、乱纹3类纹理的在线检测方法。方法首先对纹理图像进行缩小,运用视觉心理学的Tamura方法提取粗糙度、对比度、方向度、线性度、规整度、粗略度等6个纹理特征;同时在原图像提取反映图像全局信息的灰度均值、方差、熵等3个统计量;然后,运用主成分分析法（PcA）对3类纹理9个特征进行降维融合操作;最后,采用线性判别分析方法（LDA）构建3类纹理的辨识模型。采用200幅实木地板纹理图像进行实验,当主成分个数为7时,分类正确率稳定达到85％,较传统Tamura方法的83％和全局基本统计量的70％有所提高;特征提取时间为0．5548S,比缩小前图像的Tamura特征提取时间55．7000S明显减低,而分类正确率没有明显变化。     

超高压诱变小麦突变株系的抗旱综合评价

通过对超高压诱变小麦突变株系及其野生品种的多项抗旱生理指标进行比较研究,鉴定突变系是否具有抗旱性变异。以偃展4110及其超高压诱变的突变株系为材料,在正常条件和干旱胁迫条件下进行抗旱生理指标测定。结果表明:有些突变系的抗旱系数与未诱变的对照相比呈显著或极显著差异。用主成分分析将超氧化物歧化酶(SOD)活性、过氧化物酶(POD)活性、脯氨酸(Pro)质量分数、丙二醛(MDA)质量摩尔浓度、光合速率(Pn)、水分利用率(WUE)、相对含水量(RWC)、相对失水速率(RWL)、叶绿素相对含量(SPAD)9个单项的生理指标转换成4个相互独立的综合指标,并通过计算得到这一突变株系的综合抗旱D值。在12个突变系材料中有7个材料的综合抗旱值有显著变化,这些结果说明高压诱变是一项有效的诱变技术,为该技术在抗旱研究中的应用提供依据。     

四川省长江上游水土保持工程生态经济综合评价

小流域水土流失治理策略及其生态经济评价是水土保持学科的热点问题,以整个工程实施范围作为对象的研究成果鲜见报道。该文以四川省长江上游水土保持重点防治综合治理第五期工程整个治理区域为研究对象,以县级行政区内的小流域综合治理区域为评价单元,选取反映项目区社会经济和生态状况的46个指标,通过运用主成分分析法和多元线性回归分析,得出13种治理措施主成分,并对治理前后的生态经济状况进行综合评价和排序,建立了生态经济综合发展水平位次变化与治理措施主成分之间的多元线性回归模型。结果表明：不同的治理措施、治理措施实施的范围大小、实施的力度和强度是影响其对于生态经济发展水平贡献大小的主要原因。     

基于主成分分析的叶面积指数尺度效应

为描述多空间尺度观测数据在表达同一区域农作物叶面积指数(LAI)分布特征时存在的差异,该文提出了一种基于主成分分析(PCA)的LAI尺度效应分析方法。该方法充分考虑了多尺度数据的相关性与差异性,从统计分析角度出发,采用PCA进行数据挖掘和信息重组,引入动态多元线性回归模式基于主成分信息(PCs)反演估算LAI,进而定量描述尺度效应。选取大麦和玉米为试验对象,先以地面最细空间尺度观测数据为基准,通过尺度上推构建一系列不同空间尺度数据;再依据上述尺度效应分析方法进行有效信息提取和LAI估算,并纳入有效主成分个数(NEPCs)、决定系数(R2)和平均相对精度(MRA)等参数定量描述尺度效应。理论分析和数值实践证实了该方法在农作物LAI尺度效应定量分析中的可行性和有效性。     

Empirical modeling of spatial and temporal variation in warm season nocturnal air temperatures in two North Idaho mountain ranges, USA

Accurate, fine spatial resolution predictions of surface air temperatures are critical for understanding many hydrologic and ecological processes. This study examines the spatial and temporal variability in nocturnal air temperatures across a mountainous region of Northern Idaho. Principal components analysis (PCA) was applied to a network of 70 Hobo temperature loggers systematically distributed across 2 mountain ranges. Four interpretable modes of variability were observed in average nighttime temperatures among Hobo sites: (1) regional/synoptic; (2) topoclimatic; (3) land surface feedback; (4) canopy cover and vegetation. PC time series captured temporal variability in nighttime temperatures and showed strong relationships with regional air temperatures, sky conditions and atmospheric pressure. PC2 captured the topographic variation among temperatures. A cold air drainage index was created by predicting PC2 loadings to elevation, slope position and dissection indices. Nightly temperature maps were produced by applying PC time series back to the PC2 loading surface, revealing complex temporal and spatial variation in nighttime temperatures. Further development of both physically and empirically based daily temperature models that account for synoptic atmospheric controls on fine-scale temperature variability in mountain ecosystems are needed to guide future monitoring efforts aimed at assessing the impact of climate change.     

Empirical downscaling of daily minimum air temperature at very fine resolutions in complex terrain

Available air temperature models do not adequately account for the influence of terrain on nocturnal air temperatures. An empirical model for night time air temperatures was developed using a network of one hundred and forty inexpensive temperature sensors deployed across the Bitterroot National Forest, Montana. A principle component analysis (PCA) on minimum temperatures showed that 98% of the spatiotemporal variability could be accounted for using the first two modes which described the coupling and decoupling of surface temperature from free air temperatures, respectively. The spatial character of these modes were strongly correlated with terrain variables and were then modeled to topographic variables derived from a 30 m digital elevation model. PCA scores were modeled using independent predictors from in situ observations and regional reanalysis that incorporate temperature, solar radiation and relative humidity. By applying modeled PC scores back to predicted loading surfaces, nighttime minimum temperatures were predicted at fine spatial resolution (30 m) for novel locations across a broad (∼45,000 km²), topographically complex landscape. Our results suggest that this modeling approach can be used with retrospective and projected predictors to model fine scale temperature variation across time in regions of complex terrain.     

基于主成分分析和BP神经网络的土壤养分近红外光谱检测

基于近红外光谱技术的土壤养分快速、无损检测,有利于精细施肥决策。在一黄豆田采用7 m×7 m的栅格采集54个土样,测定其土壤有机质、速效氮、有效磷、有效钾,并使用FieldSpec 3光谱仪测定土样的近红外漫反射光谱。将54个样本随机分成预测集与验证集,其中预测集40个,验证集14个。通过平滑预处理后,利用主成分分析法(PCA)提取原始光谱8个主成分。然后以8个主成分为输入,分别以所测土壤养分作为输出,建立土壤有机质、速效氮、有效磷、有效钾的预测模型,最后对14个验证样本进行预测。结果表明,在小尺度采样的情况下进行光谱分析,采用主成分分析和人工神经网络相结合的方法建立土壤有机质预测模型,其测量值与预测值的相关性较高,相关度为0.796 2,相对误差较小,其平均值为1.88%,表明该方法预测土壤有机质含量是可行的。但对土壤速效氮、有效磷和有效钾含量的预测并不理想,还有待进一步研究。     

Characteristics of the marine environment and algal blooms in Gamak Bay

This study was conducted to gain insight into the characteristics of algal blooms in relation to the marine environment of Gamak Bay. From the first known occurrence of algal blooms in 1984 until 2006, 23 causal species have been identified, the most common ones being Prorocentrum sp., Cochlodinium polykrikoides, Chaetoceros sp., Skeletonema costatum, and Heterosigma akashiwo. A principal component analysis indicated that blooms of these species develop under different conditions in terms of water temperature, salinity, precipitation, and insolation. Field data showed Cochlodinium polykrikoides to be favored by high temperatures and to be euryhaline, whereas Skeletonema costatum appeared to be eurythermal and euryhaline. Prorocentrum sp. and Chaetoceros sp. appeared to be stenothermal and stenohaline. Finally, Heterosigma akashiwo appeared at the lowest temperature and highest salinity of the five species and was classified here as stenothermal and stenohaline.     

一种新型贝壳鱼礁的大型底栖藻类附着效果初探

在大连市长海县大长山岛海域选取A、B、C 3个区域,于2013年11月向A区和C区分别投放混凝土构件礁和新型贝壳鱼礁,B区作为空白对照区,于投礁1个月、半年和1年后对3个区域开展环境因子和大型底栖藻类资源状况调查,分析藻类群落演替规律及其与环境因子的关系,评价贝壳礁上藻类的附着效果。调查结果表明,投礁1个月后,3个区域藻类种类和数量差异较小,随着投礁时间延长,混凝土构件礁区和贝壳礁区大型底栖藻类的生物量和种类均大于空白对照区,其中贝壳礁区藻类生物量和种类增加得更为显著,且相较于另外2个区域,藻类群落结构更早趋于稳定。环境因子对藻类生物量影响的去趋势对应分析和主成分分析表明,影响不同藻类生物量的环境因子有差别。分别对3个区域的藻类群落和主要环境因子指标进行冗余分析发现,影响3个区域藻类群落变化的最主要环境因子均为水温,影响自然礁石和混凝土构件礁上藻类群落的次要因子为氮、磷营养盐等,而影响贝壳礁上藻类群落的次要因子为溶解氧和叶绿素a。     

鄂西犟河流域表层土壤有机碳时空变化及其影响因素

[目的] 研究土壤有机碳（SOC）在小型丘陵山地集水区的分异规律及其影响因素，为土壤资源的可持续利用以及保护南水北调水源地提供科学依据。[方法] 基于数字高程、Landsat 8 OLI影像和2016—2018年实测土壤有机碳等数据，运用相关分析、主成分分析法等研究湖北省十堰市犟河流域表层土壤有机碳含量的时空变化，厘清其影响因子和主导因素。[结果] 犟河流域SOC含量整体呈条带状分布的格局，由东北向西南逐渐增加，呈中等强度变异。夏秋两季SOC处于流失状态，而冬季SOC含量明显增加。不同质地SOC的平均含量：石灰性冲积土 > 简育高活性淋溶土 > 不饱和雏形土。不同覆盖下SOC平均含量：农田 > 园地 > 混交林 > 针叶林 > 灌木。土壤SOC含量呈现随地表曲率绝对值增大而增大，随比值植被指数（RVI）和归一化植被指数（NDVI）增加而增加的趋势。[结论] 地形因子（地表曲率）是影响犟河流域土壤有机碳的主导因子，植被因子（NDVI和RVI）是次要因子。改变局部小地貌、增加林种、改善水肥管理等措施均可以提高流域土壤有机碳含量。