宁夏土壤侵蚀动态变化与原因分析

通过对 1990年和 1999年两次土壤侵蚀遥感普查数据的对比 ,从类型、面积、强度、分布等方面对宁夏土壤侵蚀的动态变化进行了较为详细的分析。结果表明 :宁夏回族自治区各类型区水土流失面积有所减小 ,土壤侵蚀的剧烈程度普遍减弱。初步分析认为 ,土壤侵蚀变化的原因 ,除两次普查存在方法上的系统误差外 ,水土保持的作用功不可没。针对不同类型区土壤侵蚀的特点 ,提出了今后应采取的相应防治方略。     

基于首轮内检测数据的成品油管道内腐蚀分析及对策

为了做好在役成品油管道内腐蚀的监测和防控,通过进一步挖掘首轮内检测数据的价值,提出了分析思路:通过差异分析水线区域内的内腐蚀绝对深度的离散情况,结合内腐蚀与焊缝、弯头等管道附件的相对位置以及管道工艺运行情况等数据信息,半定量定位内腐蚀敏感区。以某成品油管道为例,对两条管段内的腐蚀情况进行分析,发现管内的腐蚀集聚是由于管道施工建设期产生的内腐蚀逐渐发展形成的。定位了以管节为基本单元的腐蚀敏感管段,建议将管道内检测数据作为工程建设质量评估的关键数据,新建管道尽早开展以实施内检测为目标的管道清管作业,增加清管频次,尽快将管内铁锈清除干净,随后开展常规清管作业,从而有效减缓内腐蚀的发展。(图2,表4,参20)     

作物遥感估产的现状及其展望

 总结了国内外作物遥感估产的状况，并对作物遥感的技术集成和便利化服务、数据处理、农业标准化、农学机理、扩大用户需求共4个方面作了展望。     

田间环境参数动态监测系统平台设计与实现

信息技术飞速发展,农业不再是简单的田间的播种、收割农作物,而是对于农作物成长过程的更多的管理。面对多变的天气,及时快速的发现异常,则能够让农户减少损失。本设计是用PHP+MySQL数据库开发的,基于B/S结构的田间环境参数动态监测系统平台,它将网络应用技术运用到农业生产中来,使之能够监测农作物生产环境的动态并及时反馈,让农户能够随时随地查看农场环境信息。通过提供农业相关资讯,环境监测以及农户们交流的服务平台,本平台让农民们可以利用信息技术进行科学化管理,学习更多的技术和知识,最终实现提高单位面积产量的目标。     

基于深度学习算法的京津冀地区综合干旱评估模型构建

及时准确的干旱评估对社会经济发展和农业生产具有重要的指导意义,当前的干旱评估指标通常仅考虑植被或降水等单方面影响因素,在实际干旱评估中存在一定的局限性。本研究综合考虑降水、温度、地形等多个干旱致灾因子,以主要产粮基地京津冀地区为例,基于2007-2017年地表温度（Land Surface Temperature,LST）、归一化植被指数（Normalized Difference Vegetation Index,NDVI）以及降水等多源数据,利用深度学习框架Tensorflow构建以标准化降水蒸散发指数（Standardized Precipitation Evapotranspiration Index,SPEI）为目标值的综合干旱评估模型。利用决定系数（R2）和均方根误差（RMSE）对模型进行测试;利用站点标准化降水指数（Standardized Precipitation Index,SPI）、土壤相对湿度数据以及2016年京津冀地区的气象灾害数据,从时间和空间上对模型的可靠性进行验证。结果表明：模型的训练集和测试集在不同月份上均表现较好（R2均大于0.5而RMSE均小于0.55）。模型输出的综合干旱指数（Comprehensive Drought Index,CDI）在密云站上与SPI和SPEI接近,变化趋势基本一致,并且与站点SPI和土壤相对湿度的相关系数分别大于0.7和0.4,均通过了0.01水平的显著性检验。空间上,相较于SPEI,CDI计算的2016年3-7月京津冀地区干旱事件结果与实际情况符合度更高,表明该模型适用于京津冀地区干旱评估。     

Pathogenicity and Virulence of the Two Dutch VCGs of Verticillium dahliae to Woody Ornamentals

Two experiments were performed in two consecutive years to test whether isolates of different vegetative compatibility groups (VCGs) differ in their ability to cause disease in woody ornamentals, to study the host specificity of the isolates and to get an insight into disease development in woody hosts. A range of woody ornamental plant species, including Acer campestre, Acer platanoides, Acer pseudoplatanus, Catalpa bignonioides, Cotinus coggygria, Robinia pseudoacacia, Rosa canina, Syringa vulgaris and Tilia cordata, were root-dip inoculated with six isolates of Verticillium dahliae, belonging to the two VCGs that occur in the Netherlands (VCG NL-1 and VCG NL-2). Isolates belonging to each VCG caused severe symptoms of verticillium wilt in most plant species tested. Disease progress differed between plant species, but was generally the same for the two VCGs. No overall differences in virulence were observed between the two VCGs for external wilt symptoms, number of dead plants, or shoot length. No significant VCG × plant species interactions were present for these characteristics. However, isolates of VCG NL-1 caused more vascular discolouration than did isolates of VCG NL-2. Isolates within VCGs often differed considerably in their virulence to certain hosts, as shown by highly significant isolate × plant species interactions. Isolates were more virulent on their original host. These findings imply that VCG identification does not contribute to disease prediction for a range of woody hosts.     

Is single-step genomic REML with the algorithm for proven and young more computationally efficient when less generations of data are present?

Efficient computing techniques allow the estimation of variance components for virtually any traditional dataset. When genomic information is available, variance components can be estimated using genomic REML (GREML). If only a portion of the animals have genotypes, single-step GREML (ssGREML) is the method of choice. The genomic relationship matrix (G) used in both cases is dense, limiting computations depending on the number of genotyped animals. The algorithm for proven and young (APY) can be used to create a sparse inverse of G (GAPY~-1) with close to linear memory and computing requirements. In ssGREML, the inverse of the realized relationship matrix (H⁻¹) also includes the inverse of the pedigree relationship matrix, which can be dense with a long pedigree, but sparser with short. The main purpose of this study was to investigate whether costs of ssGREML can be reduced using APY with truncated pedigree and phenotypes. We also investigated the impact of truncation on variance components estimation when different numbers of core animals are used in APY. Simulations included 150K animals from 10 generations, with selection. Phenotypes (h² = 0.3) were available for all animals in generations 1–9. A total of 30K animals in generations 8 and 9, and 15K validation animals in generation 10 were genotyped for 52,890 SNP. Average information REML and ssGREML with G⁻¹ and GAPY~-1 using 1K, 5K, 9K, and 14K core animals were compared. Variance components are impacted when the core group in APY represents the number of eigenvalues explaining a small fraction of the total variation in G. The most time-consuming operation was the inversion of G, with more than 50% of the total time. Next, numerical factorization consumed nearly 30% of the total computing time. On average, a 7% decrease in the computing time for ordering was observed by removing each generation of data. APY can be successfully applied to create the inverse of the genomic relationship matrix used in ssGREML for estimating variance components. To ensure reliable variance component estimation, it is important to use a core size that corresponds to the number of largest eigenvalues explaining around 98% of total variation in G. When APY is used, pedigrees can be truncated to increase the sparsity of H and slightly reduce computing time for ordering and symbolic factorization, with no impact on the estimates.     

银川地区水稻分布遥感制图方法研究

重点介绍水稻分布图的制作方法。在下垫面地物类型分析和卫星资料精地标订正的基础上，通过对研究区域内作物植被指数变化规律分析，选用不同时次、光谱质量较好的植被指数图像，经植被指数积温模式订正、象元分解，绘制出银川地区水稻空间分布图，为水稻面积信息的提取奠定基础，经过抽样调查检验，遥感调查水稻的空间分布与实况基本吻合。     

基于GIS和RS的小江流域景观格局动态变化分析

以小江流域不同时期遥感数据为基础,应用多种景观格局指数,对小江流域的景观格局效应进行了分析与探讨.结果表明,各种土地利用类型的斑块形状都极不规则,而且还呈明显增大趋势;小江流域的景观类型多样性在研究期间呈递增趋势,但增幅不大,同时景观优势度指数则表现出递减趋势,表明该研究区中各景观类型所占比例的差异在不断减小,这从景观均匀度指数上也得到了验证.在各种土地利用类型中,居民点与工矿用地的破碎度最大,草地的破碎化程度最低,这与居民点与工矿用地的分布比较分散有关.     

基于无人机遥感与随机森林的荒漠草原植被分类方法

荒漠草原是草原中最旱生的类型,属于草原的极限生态状态,也是气候变化和生态系统演变的预警区。利用无人机高光谱遥感技术快速、准确地提取荒漠草原草地植被类型,对动态监测草原生态安全和合理开发草地畜牧业具有重要意义。以无人机搭载高光谱成像系统采集内蒙古荒漠草原遥感图像,获得具有高空间分辨率和高光谱分辨率的图像;通过光谱连续统去除变换,增强草地植被之间的光谱差异,并构建植被指数;采用分步波段选择法选择荒漠草原植被的特征波段,实现高光谱数据降维;构建融合光谱特征、植被特征、地形特征和纹理特征等24个变量的随机森林分类模型,并与支持向量机（SVM）、K-最近邻（KNN）和最大似然分类（MLC）法进行比较。结果表明,在4种分类方法中随机森林分类算法分类效果最好,总体分类精度达到91.06%,比SVM、KNN和MLC等机器学习算法分别高7.9、15.61、18.33个百分点,Kappa系数达到0.90,比SVM、KNN和MLC算法分别高0.13、0.23和0.26。无人机高光谱低空遥感和随机森林算法的结合为荒漠草原草地植被分类提供了新途径。