Predicting individual stem volumes of sugi (Cryptomeria japonica D. Don) plantations in mountainous areas using small-footprint airborne LiDAR

This study investigated which predictor variables with respect to crown properties, derived from small-footprint airborne light detection and ranging (LiDAR) data, together with LiDAR-derived tree height, could be useful in regression models to predict individual stem volumes. Comparisons were also made of the sum of predicted stem volumes for LiDAR-detected trees using the best regression model with field-measured total stem volumes for all trees within stands. The study area was a 48-year-old sugi (Cryptomeria japonica D. Don) plantation in mountainous forest. The topographies of the three stands with different stand characteristics analyzed in this study were steep slope (mean slope ± SD; 37.6° ± 5.8°), gentle slope (15.6° ± 3.7°), and gentle yet rough terrain (16.8° ± 7.8°). In the regression analysis, field-measured stem volumes were regressed against each of the six LiDAR-derived predictor variables with respect to crown properties, such as crown area, volume, and form, together with LiDAR-derived tree height. The model with sunny crown mantle volume (SCV) had the smallest standard error of the estimate obtained from the regression model in each stand. The standard errors (m³) were 0.144, 0.171, and 0.181, corresponding to 23.9%, 21.0%, and 20.6% of the average field-measured stem volume for detected trees in each of these stands, respectively. Furthermore, the sum of the individual stem volumes, predicted by regression models with SCV for the detected trees, occupied 83%–91% of field-measured total stem volumes within each stand, although 69%–86% of the total number of trees were correctly detected by a segmentation procedure using LiDAR data.     

Influence Analysis Energy and Environment with DSM

As a large burning coal country, resolving the SO2 letting problem is the most important thing in the environment protection work. Electric power industry reveals the supply's load rate declining and the discrepancy between apex and vale augments year after year. It makes the load adjustment become an imminency task in the electric power industry. The article popularizes the light power saving technology in the inhabitant living lighting power through reinforcing the DSM technology. It studies the influence on energy and environment after using the technology. It studies avoidable electricity quantity, avoidable electricity power, avoidable apex load, avoidable coal consuming and avoidable SO2 lettling. At last, it makes a concrete analysis with a city's example.     

峰谷分时电价预测建模与影响分析

电力系统需求侧实现合理分配调度是未来电网发展的必然趋势,分时电价的推行将成为电力需求侧管理的有效措施之一。本文通过沈阳地区居民用户具体负荷用电的情况分析,实现分时电价的预测建模,提高电力系统运行的稳定性、减缓发电侧的电力投资、切实合理分配居民用电费用的使用,为智能电网需求侧的主动配网提供合理的依据。     

酸马奶提取植物乳杆菌DSM20174细菌素的理化特性研究

为研究从酸马奶中提取的植物乳杆菌DSM20174细菌素的理化特性,本试验提纯植物乳杆菌DSM20174细菌素,经过硫酸铵沉淀、透析后得到细菌素粗提液,再利用SephadexG-100凝胶柱层析进行纯化后,细菌素的比活力明显增加,达到154.70 AU/mL,得率为43.5%.采用牛津杯法测定纯化的植物乳杆菌DSM20174细菌素在3种不同方式处理下对牛源野生致病性大肠杆菌O78抑菌效果的影响.结果显示:①植物乳杆菌DSM20174细菌素在5组温度处理下,随着温度的升高抑菌作用降低,各组抑菌作用差异显著(P<0.05).即使121 ℃处理30 min后,抑菌直径仍达14.90 mm.②植物乳杆菌DSM20174细菌素在pH 2.0~12.0由低到高的11组酸碱处理下,pH越大抑菌直径越小,且除了pH 9.0和pH 10.0之间差异不显著(P>0.05)外,其余各组抑菌作用均差异显著(P<0.05). ③植物乳杆菌DSM20174细菌素经胰蛋白酶、胃蛋白酶、木瓜蛋白酶3种酶处理后抑菌直径变化明显,处理前后抑菌作用均差异显著(P<0.05).结果表明植物乳杆菌DSM20174细菌素是较好的抑菌活性物质,但不是热稳定性物质;具有较广泛的pH适用范围,且pH越小时其抑菌活性越强,在最适生长pH时抑菌活性有所增强;不是蛋白酶稳定性物质.     

沟壁坡度对侵蚀沟三维重建误差的影响

以无人机为主体的天地一体化立体测量为地表精准快速测量提供了有利条件。无人机拍摄正射影像时,陡坡影响拍摄视角,可能对地表三维测量精度产生影响。选取发展大型切沟(BG)、稳定中型切沟(MG)和小型浅沟(SG),采用三维激光扫描(Terrestrial Laser Scanning,TLS)和无人机正射摄影(Structure from Motion,SfM)2种方法获取地表DSM(Digital Surface Model,数字表面模型),并以TLS的DSM为基准,分析了坡度对SfM的DSM的高程误差的影响。结果表明:(1)高程误差均随沟壁坡度呈指数增加,拟合程度较好(P<0.0001,R^2>0.80),拐点出现在60°附近,坡度<60°时高程误差变化幅度为0~10 cm,坡度超过60°后高程误差急剧增大为10~60 cm;(2)侵蚀沟愈活跃,其坡比愈大,高程误差占比愈集中在较大坡度的范围内。对于发育中切沟BG,约75%的高程误差量集中在15°~75°;对于趋于稳定的中型切沟MG,约66%的高程误差量集中在0~60°;而对于小型浅沟SG,约54%的高程误差量集中在0~40°。     

集群式影像处理系统的技术研究

随着经济社会的快速发展,国家基础建设对基础地理信息的需求量越来越大,需要一种能够在少量人工干预的条件下,经过一系列自动化处理,快速输出包括数字表面模型(DSM)、数字高程模型(DEM)、正射影像(DOM)等产品,并能生成一系列其他中间产品的系统设备.该系统采用多种先进算法,包括原始图像增强、快速自动生成和滤除连接点、自动提取密集DSM、传统几何校正、由DTM自动生成等高线、自动生成镶嵌影像等.通过对系统的多次测试,能够高质量地完成基于POS数据的无地面控制点空三加密、自动DEM匹配、自动DOM生产以及影像地图自动切片等任务.     

需求侧管理(DSM)在农网中的应用

需求侧管理(DSM)是电网移峰填谷的有效手段之一。根据北宁市柳家乡变电所目前的供电、用电特点和电价结构,提出了一套DSM计划并进行了成本—效益分析,实例分析表明将需求侧管理(DSM)应用于农村电网移峰填谷可以取得明显的经济效益和社会效益。     

Fire models and methods to map fuel types: The role of remote sensing

Understanding fire is essential to improving forest management strategies. More specifically, an accurate knowledge of the spatial distribution of fuels is critical when analyzing, modelling and predicting fire behaviour. First, we review the main concepts and terminology associated with forest fuels and a number of fuel type classifications. Second, we summarize the main techniques employed to map fuel types starting with the most traditional approaches, such as field work, aerial photo interpretation or ecological modelling. We pay special attention to more contemporary techniques, which involve the use of remote sensing systems. In general, remote sensing systems are low-priced, can be regularly updated and are less time-consuming than traditional methods, but they are still facing important limitations. Recent work has shown that the integration of different sources of information and methods in a complementary way helps to overcome most of these limitations. Further research is encouraged to develop novel and enhanced remote sensing techniques.     

高精度DEM支持下的多时期航片杉木人工林树高生长监测

【目的】集成多时期航片数据和由机载激光雷达数据获取的密集林区数字高程模型,估测多时期杉木人工林冠层高度,并对其生长情况进行定量监测,为多时期航片监测森林生长趋势和评价林地生产力提供可能。【方法】首先基于分类后的激光雷达点云数据获得林下高精度数字高程模型和森林数字表面模型,利用航片数据构建立体像对,通过自动立体匹配算法生成森林冠层的摄影测量数字表面模型,然后借助数字高程模型将2种数字表面模型进行高度归一化,提取研究区多时期森林冠层高度。利用1996、2004年历史航片和2014年数字航片以及激光雷达数据,构建18年内皖南杉木人工林3期森林冠层高度,并对其精度进行分析。【结果】1)由2014年数字航片和激光雷达数据获取的森林冠层高度的R^2为0. 52,RMSE为1. 79 m; 2)由2014年数字航片处理得到的森林冠层高度与对应样地实测上层木的平均高验证精度较高,平均绝对误差1. 59 m,平均相对误差15%,最大绝对误差3. 45 m,最大相对误差30. 80%,测量精度85. 00%; 3)由1996、2004、2014年航片得到3期杉木人工林冠层高度,其增长趋势与树高生长曲线预测趋势一致。【结论】在多山复杂地形条件下,利用航片可准确定量反映山脊向阳面的森林冠层高度变化,但对于山谷阴影处,则会出现冠层高度被低估情况,利用多期航片结合高精度DEM数据可定量反映上层木的冠层高度变化。     

长绒毛栓菌(Trametes villosa DSM 9591)产漆酶的发酵条件优化

[目的]通过响应面法优化长绒毛栓菌发酵培养基,提高漆酶的产量。[方法]首先通过Plackett-Burman筛选出影响漆酶产量的3个主要因素;随后以葡萄糖浓度、二甲基苯胺浓度、摇床转速3因素自变量,采用Box-Behnken设计方法进行响应面试验,得到最佳发酵条件。[结果]回归分析得到最佳发酵条件方程,最佳的发酵条件为葡萄糖浓度12.37 g/L,二甲基苯胺浓度1.348 mmol/L,转速200r/min,此时漆酶的产量最高,经验证达4.1 U/ml,比初始条件提高了1.56倍。在10 L的发酵罐中,在1.0 VVM、350 r/min条件下培养时,漆酶产量最高可达13.6 U/ml。[结论]该研究得到了长绒毛栓菌产漆酶最佳的培养条件,为漆酶生产提供了更好的方法,为其今后的工业化生产奠定了基础。