基于连续投影算法和光谱变换的冬小麦生物量高光谱遥感估算

为探索基于全波段冠层高光谱以及变换光谱的冬小麦地上部生物量的遥感估算方法，以2016、2017年冬小麦田间试验为基础，通过对冠层光谱和地上部生物量的相关性分析，筛选拔节期、抽穗期的冬小麦冠层光谱、一阶导数光谱、对数变换光谱和连续统去除光谱对地上部生物量的敏感波段，并结合偏最小二乘法(PLS)分别建立拔节期和抽穗期基于SPA算法的冬小麦地上部生物量估测模型，再与基于任意两波段组合的最佳归一化光谱指数、比值光谱指数、差值光谱指数和已报道光谱指数的冬小麦地上部生物量估测模型进行比较。结果表明：(1)SPA算法较好地利用了全波段冠层光谱信息，并显著降低了光谱维度，不同变换光谱的地上部生物量敏感波段个数在4~14之间；(2)拔节期和抽穗期冠层光谱与地上部生物量的相关性高于开花期和灌浆期，各生育时期一阶导数光谱与地上部生物量之间的相关性优于连续统去除光谱、对数变换光谱和光谱指数；(3) 利用抽穗期一阶导数光谱敏感波段建立的预测模型和验证模型达到了较高的精度，其预测模型的决定系数和均方根误差分别为0.78和0.87 t·hm^-2，验证模型的决定系数和均方根误差分别为 0.84和0.69 t·hm^-2，预测相对偏差为2.74。这说明，抽穗期是估算地上部生物量的最佳生育时期，且基于冠层一阶导数变换光谱，结合连续投影算法和偏最小二乘回归方法所构建抽穗期地上部生物量估算模型具有最优的精度和预测能力，可用于地上部生物量的定量估算。     

Deep neural network algorithm for estimating maize biomass based on simulated Sentinel 2A vegetation indices and leaf area index

Accurate estimation of biomass is necessary for evaluating crop growth and predicting crop yield.Biomass is also a key trait in increasing grain yield by crop breeding.The aims of this study were(i)to identify the best vegetation indices for estimating maize biomass,(ii)to investigate the relationship between biomass and leaf area index(LAI)at several growth stages,and(iii)to evaluate a biomass model using measured vegetation indices or simulated vegetation indices of Sentinel 2A and LAI using a deep neural network(DNN)algorithm.The results showed that biomass was associated with all vegetation indices.The three-band water index(TBWI)was the best vegetation index for estimating biomass and the corresponding R2,RMSE,and RRMSE were 0.76,2.84 t ha−1,and 38.22%respectively.LAI was highly correlated with biomass(R2=0.89,RMSE=2.27 t ha−1,and RRMSE=30.55%).Estimated biomass based on 15 hyperspectral vegetation indices was in a high agreement with measured biomass using the DNN algorithm(R2=0.83,RMSE=1.96 t ha−1,and RRMSE=26.43%).Biomass estimation accuracy was further increased when LAI was combined with the 15 vegetation indices(R2=0.91,RMSE=1.49 t ha−1,and RRMSE=20.05%).Relationships between the hyperspectral vegetation indices and biomass differed from relationships between simulated Sentinel 2A vegetation indices and biomass.Biomass estimation from the hyperspectral vegetation indices was more accurate than that from the simulated Sentinel 2A vegetation indices(R2=0.87,RMSE=1.84 t ha−1,and RRMSE=24.76%).The DNN algorithm was effective in improving the estimation accuracy of biomass.It provides a guideline for estimating biomass of maize using remote sensing technology and the DNN algorithm in this region.     

敖汉旗双井林场乔木林资源现状及经营对策

文章在阐述敖汉旗双井林场乔木林资源现状的基础上,分析其存在问题,并结合林场实际情况提出今后经营发展对策,切实提升林场乔木林资源的质量。     

广州市海珠广场绿地提升改造

以广州市海珠广场绿地景观提升改造为例,探究老城区中心广场景观提升的策略和途径。通过原状广场实地调研、环境精准识别,针对绿化景观无序、场内空间封闭、园路铺装失修等现状,结合SWOT模型,对工程项目的内部因素(优势、劣势)和外部因素(机遇、挑战)进行全面分析,制定挖掘文化内涵、改善人居环境、促进生态可持续的景观改造原则。采用适当抽疏、增加花卉、合理规划景观格局、应用海绵城市建设技术等措施,打造兼具"红色"文化传承、门户形象展示、休闲观光、活动举办场所等功能为一体的综合性广场。     

Exploring the characteristics of successful volunteer-led urban forest tree committees in Massachusetts

Citizen engagement through urban forest tree committee volunteer service may aid in providing essential experience, ideas, and skills that support municipal tree management. Using semi-structured, research interviews with tree committee (TC) representatives from across the Commonwealth of Massachusetts, this study addresses current knowledge gaps concerning the general composition, processes, and relationships of volunteer-led urban forest tree committees. Our findings indicate that TC representatives are typically motivated, passionate volunteers who generally desire to work cooperatively with the many associations, organizations, and agencies that comprise the local socio-political landscape. Our findings also indicate it is important that TC representatives make a sustained, concerted effort to work collaboratively with their local tree warden to advance the care of their community’s urban trees. Furthermore, it is also essential that municipal managers and decision-makers attempt to provide TC volunteers with appropriate training opportunities, resources, as well as demonstrate appreciation, to further encourage and solidify volunteer-engagement in urban forestry at the local level.     

Nutrient cycling and biomass flows in a low-quality forest stand improvement system in the Lesser Khingan Range of China

The material flow and bulk internal flow analyses were used to establish a material accumulation and cycling model for a low-quality forest stand improvement system and a series of processes were considered. The model was applied in a one-hectare low-quality forest plot in the Lesser Khingan Range of China. Results showed that during 1997–2007, the stands absorbed 270.19 kg of N, 74.28 kg of P, and 124.39 kg of K from soils, 51.82 kg of N and 2.38 kg of P were directly absorbed by foliage, and 16.25 kg of K was released to soils by eluviation. Until 2007, the accumulated nutrients in the stands included 236.91 kg of N, 65.28 kg of P, and 108.55 kg of K. When horizontal strip clearcutting was applied in 2007, 50% accumulated nutrients in the stands were shifted due to harvesting operations, and 212.74 kg of N, 26.97 kg of P, and 98.88 kg of K were accumulated in soils, declining by 9.47% for N, 3.68% for P, and 17.60% for K, respectively, compared with year 1997. 94.61 t per hectare of biomass was generated, of which the biomass in stands accounted for 87.36%. The felled tree biomass was 36.89 t per hectare, of which 84.90% and 10.03% of biomass were utilized in terms of logs and other means, and the rest was left on site.     

Exploring tree diversity and stand structure of savanna woodlands in southeastern Sudan

Savanna woodlands in Sudan host great biodiversity, provide a plethora of ecosystem goods and services to local communities, and sustain numerous ecological functions. Although the importance of the Acacia trees in these areas is well known, up-to-date information about these woodlands' diversity is limited and changes in their woody vegetation composition, density, diversity and relative frequency are not monitored over time. This study explored tree diversity and stand stage structure in Nuara Reserved Forest, a typical savanna woodland ecosystem in southeastern Sudan. A total of 638 circular sample plots (1000 m² for each) were established using a systematic sampling grid method. The distance between plots was 200 m. In each plot, all living trees with diameter at breast height (DBH) ≥5.00 cm were identified and counted, and their DBH values were recorded. From these data, tree composition, diversity, density and stage structure were assessed. There were 12,259 individual trees representing four species (Acacia seyal, Balanites aegyptiaca, Acacia Senegal and Acacia mellifera) that belong to two families. The dominant species was Acacia seyal. Average tree density was 191 trees/hm² and the Shannon-Weiner index for trees diversity was 0.204. Overall, young trees comprised 86.30% of the forest. The state of tree richness and density in the study area was low compared to other similar environments in the region and around the world. We recommended adoption of a proper management system that includes monitoring of woody vegetation diversity in this forest, and management actions to enhance tree diversity and sustain ecosystem services to local communities. In addition to care for the dominant Acacia seyal stands, more attention and conservation should be devoted to reestablishing Acacia senegal and Acacia mellifera trees because of their high ecological and economic values for local communities.     

基于粗糙遗传算法在打捆机齿轮箱故障诊断中的应用*

自走式连续作业打捆机是一款实现不停机连续打捆作业的新型秸秆收集装备,其关键功能部件齿轮箱发生故障会严重影响正常打捆工作。针对齿轮箱故障的防控和监测,提出一种结合粗糙集和遗传算法的故障诊断方法。该方法使用时域频域分析得到的多项故障特征参数作为条件属性,故障类型作为决策属性,并利用自适应遗传算法得到决策规则表,实现无需先验信息的属性约简和故障诊断。在齿轮箱故障诊断试验中,分别对不同故障类型进行信号采集和诊断分析,结果显示:该方法在无先验信息的条件下将12项故障特征参量约简为3项,根据决策规则表进行故障诊断的准确率为100%,结果表明该方法能准确判断故障的发生和故障类型,对实现故障监测和防控具有重要意义。     

林木氮素吸收偏好性及其形成机制研究进展

森林土壤中可被林木吸收利用的氮（N）素主要以铵态氮（NH₄+-N）和硝态氮（NO₃--N）的形态存在。受全球气候变暖、氮沉降和人类活动等因素的影响，NH₄+和NO₃-的分布存在很大的时间波动性和空间异质性，且NH₄+-N和NO₃--N亏缺已成为限制林地生产力的主要因素。在森林土壤N亏缺和N异质分布的逆境中，在林木长期进化过程中形成了对不同形态N素的吸收偏好，且这种吸收偏好会随生长环境条件而发生改变。特别是对于NH₄+和NO₃-这2种主要形态的偏好选择性已被证明是决定林木生产力、竞争、共存和生态演替的重要因素之一。对不同树种在N异质分布环境下的N吸收偏好和形成机制的研究，是揭示林木N素营养遗传特性和提高林地N素利用效率的关键。文中从森林土壤中N的主要形态及其分布特征、林木对不同形态N素的吸收偏好和形成机制、林木N吸收偏好的影响因素3个方面进行总结阐述，并对未来研究方向进行展望，以期为我国人工林培育中不同树种的造林配置和合理N素施肥技术提供理论依据和参考。     

运用植被指数时序特征对落叶松人工林分类

为探究植被指数时序特征是否有利于落叶松人工林提取,以孟家岗林场为研究试验区域,根据落叶松人工林季相和物候特征,利用Landsat8OLI影像数据提取研究区内5种植被的归一化植被指数(I NDV)、差值植被指数(I DV)、比值植被指数(I RV)、增强型植被指数(I EV),构建相应的植被指数时序特征。采用最大似然和随机森林两种方法对单一时相影像和加入植被指数时序特征的影像进行对比试验。结果表明:影像中加入植被指数时序特征后,最大似然算法的分类总体精度为89.53%,Kappa系数为0.87,比单一时序特征的影像分类精度提高了13.35%;随机森林算法的森林类型分类总体精度为93.22%,Kappa系数为0.92,比单一时序特征的影像分类精度提高了19.8%。因此,加入植被指数时序特征后能得到更高的落叶松人工林提取精度。