基于时序Landsat遥感数据的新疆开孔河流域农作物类型识别

快速、准确地获取农作物类别信息对农业部门的生产管理、政策制定具有重要作用。目前基于时间序列数据进行农作物分类主要是采用长时间序列的中低分辨率影像,大量的混合像元限制了农作物的分类精度。在农作物分类的特征选择方面主要是采用归一化植被指数(normalized differential vegetation index, NDVI),而其他特征量的应用还相对较少。该文以新疆开孔河农业区为研究区域,利用2016年的Landsat7 ETM+、Landsat8 OLI影像数据集,基于时间加权的动态时间规整(time weighted dynamic time warping,TWDTW)方法开展农作物类型识别研究,主要包括香梨、小麦、辣椒、棉花等。根据野外采集的样本点构建主要农作物的NDVI和第一主成分(principal component analysis 1,PCA1)时间序列,以反映不同农作物间的物候差异。基于NDVI数据分别利用DTW和TWDTW算法计算各未知像元序列与标准序列间的相似性程度,得到农作物的分类结果,2种方法的分类精度分别为65.69%、82.68%,表明时间权重的加入提高了DTW算法识别不同农作物的能力。结合NDVI与PCA1后,TWDTW的分类精度又提高了2.61个百分点,部分农作物的误分现象明显减少,说明PCA1能够进一步扩大作物间的差异性,提高分类精度。同时,还通过选取有限时相的影像组合进行分类,试验结果表明TWDTW算法在中高分辨率数据较少的情况下能够得到较为满意的分类结果,说明TWDTW算法在中高分辨率影像越来越丰富的时代具有应用潜力。     

基于综合灰色关联度加权法的玉米品种评价

【目的】利用综合灰色关联度加权法对玉米品种的各主要性状进行综合评价分析,为农作物新品种评价提供科学参考。【方法】采用2008年广西玉米区域试验数据,利用决策分析中的多属性决策理论,运用综合灰色关联度的方法确定各性状的客观权重,然后对玉米品种进行评价。【结果】玉米品种HM-2的综合评价值最大,其次是哈宝7号,最小的是XQ-9;玉米品种HM-13产量最高,其次为联玉19,产量最低的是KY116。【结论】在实际生产中,不能只考虑产量这一单一性状来选育新品种,应尽量选择对产量和环境的互作有影响的几个重要性状进行综合评价。综合灰色关联度加权法可有效减少某些人为的设定因素,使新品种的选育、评价和鉴定更科学、客观、符合实际。在玉米的育种实践工作中,其可作为辅助工具,以选育出高产、稳产、低风险、综合性状优良的玉米新品种。     

农业综合产出对投入资源的敏感性研究

用弹性系数讨论农业产出对投入资源的敏感性和资源投入的合理性,采用加权TOPSIS法综合多种产出,分析安徽省农业资源利用情况。结果表明：从全省来看,农业综合产出对农药、从业人员和灌溉等资源投入的敏感性较高;2003、2005和2007年的资源投入不尽合理,而2004、2006和2008年的资源投入比较合理。从皖南山区来看,2002、2003、2005和2007年的资源投入不尽合理,2001、2004、2006和2008年的资源投入则比较合理。安徽省农业实践说明,适度减少投入仍有可能提高产出。     

云南省年均降雨量空间插值模拟方法比较

用反距离权重法、普通克里金法、基于样条函数法和回归模型计算法对云南省内134个气象站1993—2007年年均降雨量进行空间插值,将插值预测结果与检测点数据作对比分析,结果表明：4种插值法均能反映云南省内年均降雨量的空间分布特征,反距离权重法插值误差最小,精度最高,回归模型模拟插值误差较大,但能直观地反映年均降雨量随地理位置及海拔高度立体变化而变化的特征。     

Modelling within‐field spatial variability of crop biomass – weed density relationships using geographically weighted regression

The objective of this study is to offer a new framework for exploring and modelling the spatial variation in crop biomass – weed density relationships, adapting geographically weighted regression (GWR) to include a non‐linear regression model. The relationship between crop biomass and weed density is usually modelled by non‐linear regression models, in which the spatial heterogeneity of the relationship is ignored, although the effect of weeds on crop can differ in relation to topographic and edaphic variability. GWR attempts to capture spatial variability by calibrating a regression model to each location in space. We show the application of the method in different cereal cropping systems, with one or two weed species. The results indicate that GWR can significantly improve model fitting over non‐linear least squares (NLS) in some situations. Furthermore, the parameter estimates can be mapped to illustrate local spatial variations in the regression relationship under study and eventually to relate the spatial variability of the model to the environmental heterogeneity. We discuss the value of the GWR for analysing the observed spatial variability and for improving model development and our understanding of spatial processes.     

区域土壤CEC与相关控制因子的空间非平稳关系评估

土壤阳离子交换量(CEC)对土壤的保肥能力具有重要影响。了解土壤CEC的空间分布及相关控制因子的影响有助于区域土壤肥力的精准调控。以往多采用传统的最小二乘(OLS)回归模型探索相关因子对土壤CEC的影响。然而,该类模型是一种总体回归方法,不能反映局部空间区域内相关因子对土壤CEC的影响。采用一种局部空间回归技术——地理加权回归(GWR)探索表层和亚表层土壤中CEC与相关控制因子(土壤黏粒、土壤有机质和土壤pH)之间的空间非平稳关系。结果表明,各控制因子在不同的子区域和深度对土壤CEC的影响均有明显差异;同时,GWR模型有效地揭示了土壤CEC与相关土壤控制因子的空间非平稳关系。所得的空间非平稳关系图可以为更精确地调控区域土壤肥力提供依据。     

基于加权Voronoi图扩展断裂点的农村居民点布局优化

为探寻农村居民点布局优化的最佳方法,以三江平原腹地大榆树镇为研究区,构建农村居民点结节性指数评价体系,基于最邻近指数及变异系数确定居民点斑块的等级类型,通过加权Voronoi图扩展断裂点模型、空间点格局及两步移动算法,确定研究区农村居民点布局调整的最优方案。结果表明:(1)结节性指数大的居民点斑块主要分布于镇中心及交通干线附近,区位优势显著,且基础设施齐全,农机化水平高;结节性指数小的居民点位置较为偏远,且布局散乱。(2)中心村、基层村、迁移村和零星村的居民点数量分别为13,20,22,13,基于此提出了重点拓展、控制发展、迁移合并和重点整治4种布局优化策略。(3)通过加权Voronoi图扩展断裂点模型及两步移动算法确定了部分农村居民点的迁并方向,制定了大榆树镇农村居民点空间布局调整的最优方案。为三江平原地区农村居民点布局调整及农业生产提供理论依据。     

Implications of SNP weighting on single‐step genomic predictions for different reference population sizes

We investigated the importance of SNP weighting in populations with 2,000 to 25,000 genotyped animals. Populations were simulated with two effective sizes (20 or 100) and three numbers of QTL (10, 50 or 500). Pedigree information was available for six generations; phenotypes were recorded for the four middle generations. Animals from the last three generations were genotyped for 45,000 SNP. Single‐step genomic BLUP (ssGBLUP) and weighted ssGBLUP (WssGBLUP) were used to estimate genomic EBV using a genomic relationship matrix ( G ). The WssGBLUP performed better in small genotyped populations; however, any advantage for WssGBLUP was reduced or eliminated when more animals were genotyped. WssGBLUP had greater resolution for genome‐wide association (GWA) as did increasing the number of genotyped animals. For few QTL, accuracy was greater for WssGBLUP than ssGBLUP; however, for many QTL, accuracy was the same for both methods. The largest genotyped set was used to assess the dimensionality of genomic information (number of effective SNP). The number of effective SNP was considerably less in weighted G than in unweighted G . Once the number of independent SNP is well represented in the genotyped population, the impact of SNP weighting becomes less important.     

IMAGING DIAGNOSIS—MAGNETIC RESONANCE IMAGING FEATURES OF A MULTIFOCAL OLIGODENDROGLIOMA IN THE SPINAL CORD AND BRAIN OF A DOG

An 8‐year‐old neutered male Toy Poodle was presented with chronic, progressive tetraparesis, and possible seizures. Magnetic resonance images demonstrated an extensive, T1 and T2 hyperintense contrast enhancing mass in the cervical spinal cord. Three nodules were present on the surface of the thalamus, with enhancement most evident on delayed images. A diagnosis of high‐grade oligodendroglioma was confirmed with postmortem histopathology and immunohistochemical labeling. Oligodendroglioma should be considered as a differential for T1 hyperintense intraaxial or intramedullary lesions with contrast enhancement. If enhancement is not visualized on postcontrast images, delayed images may be beneficial.     

Validation of a geographic weighted regression analysis as a tool for area-wide integrated pest management programs for Ceratitis capitata Wiedemann (Diptera: Tephritidae) on Terceira Island,Azores

Extrapolation from quantitative sampling to the surrounding areas is an essential feature of many aspects of real world applications in pest management decision-making. However, these decisions are only as good as the accuracy of the methods that provided the information. The problem of estimating Mediterranean fruit fly population densities from trap grids is a specific case. The efficiency of three methods to estimate fruit flies trapped per day values for non-sampled areas in Terceira Island is evaluated, the inverse distance weighted, ordinary Kriging and the geographic weighted regression (GWR). Each method has its own specificities and merits. The results demonstrate that the GWR method is capable of estimating hotspots for the next season and can be used to identify ecological corridors over a non-sampled area. The high spatial heterogeneity and topographical conditions present on Terceira Island may explain why a more mathematically complex method is more reliable than simpler methods for use in possible future wide-area control program for medfly.