黑龙江大兴安岭卫星热点预报森林火灾准确性研究

卫星监测是现阶段我国主要森林火灾监测方法,其本质是测报地面的高温热源,利用粗分辨率的遥感数据进行林火监测时不能区分高温热源性质、精确定位火场,对于热点数据的地面核查反馈工作造成一定困难。提升热点数据处置的技术水平是森林防火研究的热点。本文基于2005—2015年黑龙江省大兴安岭林区卫星热点数据和同时期森林火灾历史资料,利用ARCGIS和统计分析,得出结论如下:1)卫星热点初判林火发生次数的准确率79.7%,不同卫星初判热源差异较大,NOAA-16、NOAA-18、NOAA-19和FY-1D的报准率均在80%左右,监测次数综合达到1 928次,占总数的2/3,是监测林火的主力卫星。2)卫星预报初判林火发生位置平均误差为5 787.9 m;不同卫星初判热源差异较大,NOAA-19和Terra预报热点的误差较小,但监测数量偏少;NOAA-15和NOAA-17的监测数量虽然较多,但其误差非常大,NOAA-15有7 064.7 m,NOAA-17达到万米以上。3)在卫星监测到的219次森林火灾和历史资料记录的165次火灾中,有147次森林火灾能够对应,卫星的多报、少报问题主要集中于呼玛县,在连续监测同一场森林火灾时,容易出现多报、少报的现象。建议在无法提高卫星性能的情况下,改进卫星图像的处理技术,完善卫星图像的判读标准,提高判读的准确性,同时完善地面核查反馈的方案,以增加核查效率,降低核查经济成本,同时基于不同卫星的性能差异,建议在进行林火监测时应以预报精确的风云系列极轨卫星为主,以性能稳定的NOAA系列卫星为辅。      

未知产量品系胶树苗期产量预测方法的准确度

采用苗期产量预测方法对未知产量品系的3龄胶树进行产量预测,结果如下: 用“小叶柄胶法”,高产品系的选对率达80%,低产品系的误选率为10%;3龄幼树小叶柄胶值与其成龄芽接树头三割年平均产量之间呈极显著相关(n=42,r=0.5559~**)。用“叶脉胶法”,高产品系的选对率为63.6%,低产品系的误选率为8%;3龄幼树叶脉胶等级与其成龄芽接树头三割年平均产量之间亦呈极显著相关(n=42,r=0.5218~(**))。     

影响简易瞬态工况法(VMAS)测量精度因素分析

控制在用车的排放已经成为共识,国家标准规定了几种在用汽车排放的测量方法,简易瞬态工况法(VMAS)是其中之一.给出了简易瞬态工况法(VMAS)检测设备系统的组成和测量原理,从设备自身、被检车辆、人为因素、燃油品质和周围环境等几个方面分析了影响简易瞬态工况法(VMAS)测量精度的因素.     

Evaluating the accuracy of mapping weeds in seedling crops using airborne digital imaging: Avena spp. in seedling triticale

Airborne multispectral imaging has been used to map patches of Avena spp. (wild-oats) in a field of seedling triticale (X Triticosecale , Wittmack). Images of the target field were acquired using a four-camera airborne digital imaging system, recording in the infrared, red, green and blue wave-bands. Spectral information derived from images of 0.5-, 1.0-, 1.5- and 2.0-m spatial resolution were correlated with detailed on-ground weed density measurements to investigate the effect of image resolution on mapping accuracy. Comparisons between normalized-difference vegetation index (NDVI) or soil-adjusted vegetation index (SAVI) images and weed data achieved correlations of up to 71%. The highest correlation was achieved with the 0.5-m-resolution images and the lowest with the 2.0-m-resolution images. At 0.5-m resolution, NDVI images could not reliably discriminate weed populations of less than 28 weeds m^–2 from weed-free regions, while SAVI images could not discriminate populations of less than 17 weeds m^–2. At 1.0-, 1.5- and 2.0-m resolution, SAVI images could not discriminate populations of less than 23 weeds m^–2, while NDVI images again demonstrated a higher discrimination threshold. Results suggest that airborne multispectral imaging could be used as part of a stratified weed sampling system.     

基于聚焦滤波的林业专题地图制图综合方法

森林资源规划设计调查成果总是以连续的面状图斑呈现。当大比例尺二类调查成果图缩编为更小比例尺地图时,常常需要制图综合。如何在制图综合时既要简化多边形边界,又要保持各类型林相面积和位置的相对不变,是林业专题制图的一个难题。经大量实验发现,将实施制图综合的连续面状图斑要素从矢量格式转换为栅格格式,经Focal滤波器以Majority方式滤波处理后,再将滤波后结果从栅格数据转换为矢量数据,可较好地实现森林资源专题连续面状要素信息的制图综合。以云南省某地一个1万 hm²的实验区为例,使用该方法将1∶2.5万的森林资源二类调查成果图缩编为1∶25万。结果表明,缩编后,多边形边界简化,目视效果较好,各类型林相面积变化绝对值平均为0.2%,位置精确度平均值为94.68%。此方法已应用于云南森林资源状况图集相关专题图等的生产实践。     

小麦赤霉病自动监测预警系统应用效果评价

2018年在江苏、陕西、河南、湖北、安徽共18个县(市)安装了小麦赤霉病预报器,在周边设置未防治麦田进行赤霉病调查,并与预警软件平台预测结果相比较,评价小麦赤霉自动监测预警系统的准确性。评价结果表明,2018年该系统预测的准确性达71.8%。结合陕西省植保总站、西安市植保站、渭南华州区植保站、商洛洛南县植保站、安徽凤台县植保站2016年-2018年对该系统的评价结果,证实该系统预测准确性较高,系统工作稳定,自动化程度高,可为小麦赤霉病的科学防控提供重要的参考依据,具有一定的应用前景。     

龙门式点样仪精度的研究

为了实现龙门式点样仪的高精度运动控制,采用一种消除反向误差方法,消除双输出轴电机驱动设备两侧松紧程度不同的同步带轮运动过程中,设备返回启动位置时,连接两侧运动机构的桥梁与启动时产生的夹角,提高了设备的重复定位精度;改进了一种标定方法,提高了设备的定位精度。通过基于ARM9的微控制器对是否采用上述方法进行对比实验,利用激光跟踪仪测量了设备的重复定位精度以及定位精度。实验结果表明:未采用上述方法,设备重复定位精度为0.09 mm,定位精度为0.07 mm。采用上述方法,设备的重复定位精度可达0.01 mm,定位精度可达0.03 mm。     

Genomic estimation of additive and dominance effects and impact of accounting for dominance on accuracy of genomic evaluation in sheep populations

The objectives of this study were to estimate the additive and dominance variance component of several weight and ultrasound scanned body composition traits in purebred and combined cross‐bred sheep populations based on single nucleotide polymorphism (SNP) marker genotypes and then to investigate the effect of fitting additive and dominance effects on accuracy of genomic evaluation. Additive and dominance variance components were estimated in a mixed model equation based on “average information restricted maximum likelihood” using additive and dominance (co)variances between animals calculated from 48,599 SNP marker genotypes. Genomic prediction was based on genomic best linear unbiased prediction (GBLUP), and the accuracy of prediction was assessed based on a random 10‐fold cross‐validation. Across different weight and scanned body composition traits, dominance variance ranged from 0.0% to 7.3% of the phenotypic variance in the purebred population and from 7.1% to 19.2% in the combined cross‐bred population. In the combined cross‐bred population, the range of dominance variance decreased to 3.1% and 9.9% after accounting for heterosis effects. Accounting for dominance effects significantly improved the likelihood of the fitting model in the combined cross‐bred population. This study showed a substantial dominance genetic variance for weight and ultrasound scanned body composition traits particularly in cross‐bred population; however, improvement in the accuracy of genomic breeding values was small and statistically not significant. Dominance variance estimates in combined cross‐bred population could be overestimated if heterosis is not fitted in the model.     

黄土高原沟壑区典型小流域高精度DEM制作及其应用研究

高精度数字高程模型(DEM)是水土流失规律研究与流域地形空间分析中重要的空间数据。以黄土高原沟壑区的南小河沟流域为例,以1：1万地形图为数据源,探讨了在Arcgis和ArcView地理信息平台下,生成高精度DEM及提取流域土壤侵蚀指标的步骤和方法。结果表明,提取的地形信息能准确地反映该区域地形起伏变化与破碎状况,满足当前“数字流域”建设的需要。     

Investigating the persistence of accuracy of genomic predictions over time in broilers

Accuracy of genomic predictions is an important component of the selection response. The objectives of this research were: 1) to investigate trends for prediction accuracies over time in a broiler population of accumulated phenotypes, genotypes, and pedigrees and 2) to test if data from distant generations are useful to maintain prediction accuracies in selection candidates. The data contained 820K phenotypes for a growth trait (GT), 200K for two feed efficiency traits (FE1 and FE2), and 42K for a carcass yield trait (CY). The pedigree included 1,252,619 birds hatched over 7 years, of which 154,318 from the last 4 years were genotyped. Training populations were constructed adding 1 year of data sequentially, persistency of accuracy over time was evaluated using predictions from birds hatched in the three generations following or in the years after the training populations. In the first generation, before genotypes became available for the training populations (first 3 years of data), accuracies remained almost stable with successive additions of phenotypes and pedigree to the accumulated dataset. The inclusion of 1 year of genotypes in addition to 4 years of phenotypes and pedigree in the training population led to increases in accuracy of 54% for GT, 76% for FE1, 110% for CY, and 38% for FE2; on average, 74% of the increase was due to genomics. Prediction accuracies declined faster without than with genomic information in the training populations. When genotypes were unavailable, the average decline in prediction accuracy across traits was 41% from the first to the second generation of validation, and 51% from the second to the third generation of validation. When genotypes were available, the average decline across traits was 14% from the first to the second generation of validation, and 3% from the second to the third generation of validation. Prediction accuracies in the last three generations were the same when the training population included 5 or 2 years of data, and a decrease of ~7% was observed when the training population included only 1 year of data. Training sets including genomic information provided an increase in accuracy and persistence of genomic predictions compared with training sets without genomic data. The two most recent years of pedigree, phenotypic, and genomic data were sufficient to maintain prediction accuracies in selection candidates. Similar conclusions were obtained using validation populations per year.