分形理论及其在林业中的应用与研究进展

简要介绍了分形的基本概念及其发展史,综述和分析了分形理论在土壤性质、生态学、林火初期蔓延、树木动态过程分析、木材科学及工艺、冠层结构特征描述、林业遥感图像中的纹理分析、植物形态模拟、树木特征数据库的建立等多方面的应用。     

日本落叶松冠层光合特性的空间变化

【目的】研究日本落叶松冠层间光合特性的差异,揭示冠层光合特性的空间变化规律,为精确估算冠层生产力及构建冠层生产力模型提供依据。【方法】以8年生日本落叶松为研究材料,根据树冠长度,将树冠等分为8个层级,从上到下分别为第1~8层级,选择每一层级的南向一级侧枝作为光合测定枝条,测定每一枝条上针叶的光合日变化。【结果】多数冠层间光合参数日变化规律相似,净光合速率、蒸腾速率、气孔限制值、光合有效辐射、气温和水汽压亏缺均表现为单峰曲线,气孔导度从上午开始逐渐降低。随着冠层的升高,光合参数增加、比叶面积减小,而气温和水汽压亏缺表现为先增后降的趋势,不同冠层间均差异显著( P <0.05)。净光合速率、光合有效辐射、气孔导度和蒸腾速率与相对冠高存在指数函数关系( R^2 ≥0.94),气温和水汽压亏缺与相对冠高存在一元二次函数关系(R^2 ≥0.79)。通径分析表明,影响净光合速率的主要因素是光合有效辐射,而气温和空气相对湿度影响较小。【结论】光合有效辐射和叶肉细胞的光合活性分别是影响日本落叶松净光合速率空间变化的主要环境因素和生理因素。净光合速率随冠层的升高而显著增加,而冠层底部净光合速率为负值,始终处于碳消耗状态。     

云杉阿扁叶蜂卵分布规律及抽样技术的研究

经抽样调查与统计分析，云杉阿扁叶蜂的卵７５％产于２年生针叶上，７８％的卵为１枚针叶关生１粒卵。卵在单株不同冠向间分无差异。卵的单株垂直分布因树冠各层针叶数量多少而呈现明显差异：树冠各层针叶健全时，卵集中产于下冠层；下层针叶稀少，而中上层针叶健全时，卵集中产于中冠层；中下冠叶均稀少时，卵则集中于产于上冠层。     

基于形态学阈值标记分水岭算法的高分辨率影像单木树冠提取

随着遥感技术的不断发展,利用高空间分辨率遥感影像提取单木树冠,成为获取树冠信息的一种重要手段。结合数学形态学和最大类间方差法提取自适应的分割阈值,分别对前景和背景进行标记,以此构建了改进的分水岭分割方法。选取林区高分辨率的无人机影像为数据源,分别根据传统的分水岭方法和改进的分水岭方法进行实验分析,并从冠层面积、单木树冠分割的数量和质量方面进行精度评价。结果证明:基于形态学阈值标记的分水岭算法具有显著改善过分割的作用,树冠分割结果精度可达64.62%,表明该方法切实可行,且效果较好。     

长白落叶松与水曲柳磷素营养关系的研究

用灌施和管施方法研究了纯林和混交林中长白落叶松与水曲柳对＾３２Ｐ的吸收及利用。结果表明,树木对＾３２Ｐ的吸收,运转很快,施＾３２Ｐ的当日即达冠层。＾３２Ｐ在树冠上层分布最多,中层次之,下层最少。灌施时＾３２Ｐ在树冠阳面分布较多;管施时在树冠阴面分布较多。灌施时混交林中树木对＾３２Ｐ的吸收多地纯林;管施时纯林中树木对＾３２Ｐ,混交林中异种树木间＾３２Ｐ交换量最多。长白落叶松与水曲柳种间营养关系协调,     

华北落叶松不同类型林木的冠结构与光的分布

依据塞罕坝华北落叶松放叶期和生长季７个晴天完整的野外分层实测资料，研究了光在林分优势木、平均木和被压木单株树冠中的衰减和吸收过程，比较了林分中不同类型林木的冠结构与光分布规律的关系。研究发现，光在不同类型林木单株树冠中的传递均呈负指数衰减过程，累积吸收率则呈幂函数递增。并就不同冠层对光吸收的贡献与树冠结构动态分析及抚育间伐修枝方面的关系进行了讨论。     

高空间分辨率遥感森林参数提取探讨

介绍了高空间分辨率遥感在森林参数提取方面的研究和应用情况,并结合国内外学者在此方面所做出的研究成果,对不同森林参数的提取分别做了阐述,包括单木树冠轮廓信息、胸径、森林生物量、树种识别和分类、叶面积指数、森林郁闭度、木材结构和性质。最后分析了高空间分辨率遥感在森林参数提取方面存在的问题,并对该领域的应用前景作了展望。     

与林内小气候舒适度相关的城市森林冠层结构指数选择

【目的】选择与林内小气候舒适度相关的城市森林冠层结构指数,为进一步优化城市森林结构、改善城市森林热环境提供参考。【方法】以与城市森林降温效应相关度较高的一维度冠层结构指标(包括叶面积指数、平均叶倾角、冠层厚度、枝下高、冠高比和冠层通透度)为基础,从林内外空气流动和能量交换的角度,构建多维度城市森林冠层结构指数,通过相关分析筛选对小气候舒适度解释度较高的城市森林冠层结构指数。【结果】一维度冠层结构指标与林内舒适度(S)、舒适度相对变化(Sd)呈弱度相关关系,对S的解释力为0～30. 5%,对Sd的解释力为0～53. 5%;多维度冠层结构指数对S和Sd的解释程度明显提升,对S的解释力为0～37. 5%,对Sd的解释力为30. 9%～55. 1%;热垂直扩散结构指数和热水平扩散结构指数的协同作用对S的解释程度相对较高(43. 5%);垂直冠层指数和树冠垂直均匀指数的协同作用对Sd的解释程度最高(63. 9%)。【结论】城市森林舒适度和舒适度相对变化受多个冠层结构指标和指数共同影响,所构建的多维度冠层结构指数(包括热垂直扩散结构指数、热水平扩散结构指数、综合热扩散结构指数、垂直冠层指数、树冠均匀指数、树冠垂直均匀指数和冠层综合指数)与林内小气候舒适度及其相对变化相关性较高。     

蜀柏毒蛾卵与初龄幼虫种群株内分布规律的研究

本文对蜀柏毒哦1年2代的卵期与初龄幼虫期在单株上分布规律进行探讨。调查各向各层的种群数量,分析它们与全株数量的相关关系。经方差分析与r值检验,两代卵和初龄幼虫对不同树冠方向的分配比例无显著性差异,而对不同冠层则有极显著性差异,卵集中于中下层,幼虫则集中于上中层;各树冠方向各冠层种群数量与全株数量直线相关极显著。     

云杉阿扁叶蜂卵分布规律和抽样技术的研究

通过林间抽样调查，对云杉阿扁叶蜂ＡｃａｎｔｈｏｌｙｄａｐｉｃｅａｃｏｌａＸｉａｏｅｔｚｈｏｕ卵的分布规律作了研究。经归纳分析，７５％的卵集中分布于２年生针叶上，７８％的卵为１枚叶上１粒卵。受害程度不同的单株间卵在树冠上的垂直分布因各冠层针叶数量而有明显差异：树冠各层针叶较健全时，卵集中分布于下冠层；下层针叶稀少，中、上层针叶较健全时，卵集中分布于中冠层；连年严重受害株中下冠针叶稀少，卵则集中于上冠层。严重成灾的林分中，卵在各林冠层的分布已无明显差异。卵的空间分布属聚集型，个体间相互排斥。运用分布信息，求算了不同卵密度下的最适抽样数，设计了决策防治的序贯抽样方案。     

Crown area allometries for estimation of aboveground tree biomass in agricultural landscapes of western Kenya

Classical allometries determine biomass from measurements of diameter at breast height or volume. Neither of these measurements is currently possible to be derived directly from remote sensing. As biomass estimates at larger scales require remotely sensed data, new allometric relations are required using crown area and/or tree height as predictor of biomass, which can both be derived from remote sensing. Allometric equations were developed from 72 trees semi-randomly selected for destructive sampling in three 100?km² sentry sites in western Kenya. The equations developed fit the data well with about 85?% of the observed variation in aboveground biomass explained by crown area. Addition of height and wood density as second predictor variables improved model fit by 6 and 2?% and lowered the relative error by 7 and 2?%, respectively. The equation with crown area in combination with height and wood density estimated representative aboveground biomass carbon to be about 20.8?±?0.02?t?C?ha^?1; which is about 19?% more than the amount estimated using an allometry with diameter at breast height as predictor. These results form the basis for a new generation of allometries using crown area as a predictor of aboveground biomass in agricultural landscapes. Biomass predictions using crown area should be supported by height and wood density and the application of crown area equations for remote sensing based up-scaling should consider crown interactions with competing or coexisting neighboring trees.     

基于航空影像的树冠提取方法研究

用高空间分辨率遥感影像对单木树冠进行自动提取和轮廓描绘是近年来林业遥感领域研究的热点。本文以覆盖实验区的航空影像为例,采用面向对象的多尺度分割方法,逐级对植被对象、树冠对象和分树种模式进行分割,有效地提取了影像中的树冠大小信息。     

航空遥感技术监测松材线虫病的应用

探讨了通过航空录像技术获取林木健康信息及手持式GPS地面定位变色树木的方法。结果表明,遥感监测所获取的地面变色的树木数据资料能够较为准确地与地面对应。利用该方法能够对有松材线虫病症状的松林准确、快速定位,从而起到及时监测疫情的作用。     

日本落叶松纸浆材优良家系多性状联合选择

以12年生日本落叶松自由授粉家系子代测定林为研究对象,对生长、干形和材性性状进行相关分析、通径分析及间接选择研究,利用综合选择指数法开展了日本落叶松纸浆材优良家系选择,并为湖北等亚热带高海拔山区筛选出一批生长、干形和材性兼优的家系,最后提出了日本落叶松纸浆材选育指标及优良家系利用途径。研究表明:生长性状与纤维长度之间存在显著正相关关系,与壁腔比之间存在显著负相关关系,与木材密度、1%NaOH抽出物、综纤维素含量间相关不显著;木材密度与主枝长之间,纤维长度与主枝长、主枝粗和新枝粗之间,晚材壁腔比与主枝粗、主枝长、皮厚、冠幅、新枝数之间,1%NaOH抽出物与主枝长之间存在显著正相关关系。各控制性状对单木材积直接作用的大小依次为:胸径、树高、主枝长、壁腔比、主枝粗、皮厚、冠幅、晚材纤维长和早材纤维长,其中胸径和树高2个性状对单株材积性状的直接作用占材积总变异的63%,虽然冠幅、壁腔比等性状对单木材积的直接控制作用很小,但这些性状通过胸径对单木材积具有很大的间接遗传控制作用,由这9个性状组成的控制系统可以说明单木材积变异的98.66%。     

基于无人机影像与Mask R-CNN的单木树冠检测与分割

对无人机遥感影像中单木树冠进行检测与分割并获取树冠冠幅与树冠面积参数,可以为城市中不同场景下的林业资源调查提供高效快捷的途径。以银杏树为研究对象,创建基于无人机遥感影像的银杏单木树冠数据集,并使用卷积神经网络Mask R-CNN算法结合正射影像图对城市中不同场景下的树冠进行检测和树冠边界勾绘以获取相关树冠参数。结果表明,加入无人机银杏树冠影像数据集训练后的网络模型,可以较好地适用于城市不同场景下的银杏单木树冠检测与分割。在4个测试场景下的86棵银杏单木树冠目标总体查准率达到93.90%,召回率达到89.53%,F1-score为91.66%,平均精度均值为90.86%,且可以提取到较为准确的银杏单木树冠的冠幅值与树冠面积,预测冠幅的平均相对误差与均方根误差分别为7.50%和0.55,预测树冠面积的平均相对误差与均方根误差分别为11.15%和2.48。将无人机影像与深度学习算法结合应用到城市林业资源调查中,可以得到较为准确的树冠检测与轮廓分割结果,有效地提高城市林业资源调查效率。     

Tree Species Classification using Semi-automatic Delineation of Trees on Aerial Images

The purpose of this study was to develop a method for classifying tree species from remote sensing images by combining a semi-automatic pattern recognition technique and spectral properties of trees. Five stands in southern Finland were studied. Individual trees in the digital colour infrared (CIR) aerial photographs were segmented by a method based on the recognition of tree crown patterns at subpixel accuracy. The images were filtered with the Gaussian N-by-N smoothing operator and local maxima above a threshold level were segmented. The segments were classified into three tree species classes. The kappa coefficients for stands varied from 0.43 to 0.86 when the training data and test data were from the same aerial photograph. When training data from other photographs were used as reference data, the kappa coefficients ranged from 0.40 to 0.75. The method described provides an interesting approach for detecting tree species semi-automatically in digital aerial data.     

基于遥感图像的林况因子提取研究进展

随着遥感技术的不断发展,部分林况因子调查逐渐从传统的人工地面调查转向遥感调查,虽然提高了工作效率和精度,但也存在一些尚未解决的问题。文中系统总结了基于遥感图像的树种、树高、树冠、胸径、位置、郁闭度、年龄、株数、蓄积量、生物量等林况因子目视判读和计算机提取研究的现状及存在的问题,并对今后发展提出了建议。     

Modelling the economically viable wood in the crown of European beech trees

Long-term forest development programs in Germany aim on an increase of close-to-nature broadleaf forest stands. This means that the economic importance of European beech is expected to increase. The economic potential of a tree basically consists of the stem as well as the economically viable wood volume in the crown. Due to the high morphological variability of European beech crowns, taper models are often not satisfactory for predicting the economically viable wood volume arising from crowns. Prediction models with a higher precision are recently still lacking. Aim of this study is thus the development of prediction model for the economically viable crown wood volume of European beech trees.We determined the distribution of the wood volume in the crown over the branch diameters using the multistage ‘randomized branch sampling’ method (RBS). The tree-specific wood volume distribution on the branch diameters were used to cluster all sampled trees into 3 groups. Additionally, we developed a method able to distinguish between economically viable and unviable crown branches. Basing on the RBS measurements as well as revenues and processing costs, we modeled the economically viable wood volume from the crown for each tree. To calculate the wood volume under bark, we parameterized a bark thickness function from disk samples of the trees.We showed that the European beech crowns could be clustered into 3 groups differing in their wood volume distribution. The economically viable wood volume in the crown significantly depended on this grouping parameter as well as diameter at breast height (DBH). By contrast, the total amount of wood in the crown only depended on DBH. The differing viable wood volumes in the crowns were thus explained by different wood distributions and not by differing total crown wood volume. To make the results applicable in practice forestry, the modelling results were used to develop a regression formula able to predict the economically viable wood volume in the crown depending on the DBH and the crown type. As the crown type can also be predicted via measurable tree covariates, the regression model of the viable wood volume in the crown can be used as a support tool for the management of European beech stands. Sensitivity analysis quantifies how harvest revenues and costs translate into different viable tree volume.     

面向对象的退耕还林造林效果遥感特征提取技术研究

以河北省张家口市2002年的退耕还林地为研究对象,以高空间分辨率(以下简称高分辨率)遥感(Quick-bird-快鸟,分辨率0.6m)为信息载体。运用严格的传感器物理模型对快鸟预正射影像进行正射处理,采用Median滤波、Gaussian滤波和均值滤波三种滤波技术对图像进行增强处理。采用面向对象的图像信息提取技术,提取退耕还林地树冠特征值,进而计算退耕还林造林保存率。研究结果表明:由遥感数据自动提取的树冠尺寸(直径)在1.2m以上,平均保存率为85.11%,精度达到了89.837%。