果园变量喷雾技术研究现状与前景分析

果园变量喷雾是提高农药有效利用率、提升果品品质的重要手段之一,已经成为国内外学者研究的热点课题。为明确果园变量喷雾技术与装备已处的研究阶段、所面临的挑战和未来发展的方向,该文从果园变量喷雾技术中冠层结构探测与重构、施药智能决策和变量喷雾执行系统3个主要环节,重点概述了冠层结构探测的主要技术手段及其优缺点,认为机器视觉技术、超声波传感技术、LIDAR(light detection and ranging)探测技术及其相互之间的组合传感技术是未来最主要发展的冠层结构探测技术;综述了当前所采用的基于果园面积GA(ground area)模型、基于冠层高度的LWH(leaf wall height)模型、基于树体面积的LWA(leaf wall area)模型和基于冠层体积的TRV(tree row volum)模型,在此基础上阐述了这4种模型之间的内在联系;在分析了对靶开关决策、离散型决策和连续型决策模型的现状和特点的基础上,提出基于模糊算法的施药量智能连续决策是未来重要的发展方向;从果园变量喷雾机所采用的传感技术、决策模型和所取得的技术指标方面论述了当前世界最典型的装备现状,进一步分析了施药量调控系统、风量调控系统和喷雾位置调控系统的研究现状,提出了风量快速调控系统和喷雾位置快速响应系统的发展方向,以期为果园变量喷雾技术与装备研究提供参考。     

利用大光斑激光雷达估测小兴安岭平均树高

研究通过获取覆盖中国黑龙江省小兴安岭的GLAS第三激光器Laser3I数据,并用IDL和MATLAB对GLAS波形数据进行处理来提取树高,利用小兴安岭二类调查数据做精度检验,得到精度为92.67%。结果显示：大光斑激光雷达能够高精度地提取树高,可为林业生产及时提供必要的数据支持。     

Estimation of above ground forest biomass from airborne discrete return laser scanner data using canopy-based quantile estimators

A conceptual model describing why laser height metrics derived from airborne discrete return laser scanner data are highly correlated with above ground biomass is proposed. Following from this conceptual model, the concept of canopy-based quantile estimators of above ground forest biomass is introduced and applied to an uneven-aged, mature to overmature, tolerant hardwood forest. Results from using the 0th, 25th, 50th, 75th and 100th percentiles of the distributions of laser canopy heights to estimate above ground biomass are reported. A comparison of the five models for each dependent variable group did not reveal any overt differences between models with respect to their predictive capabilities. The coefficient of determination (r ² ) for each model is greater than 0.80 and any two models may differ at most by up to 9%. Differences in root-mean-square error (RMSE) between models for above ground total, stem wood, stem bark, live branch and foliage biomass were 8.1, 5.1, 2.9, 2.1 and 1.1 Mg ha^?1, respectively.     

Dendrometric and dasometric analysis of the bushy biomass in Mediterranean forests

The aim of this study was to define the dendrometric and dasometric parameters of five Mediterranean bushy plant species, to make their environmental assessment and to determine correlations with LIDAR data. The species studied were: Quercus coccifera, Rosmarinus officinalis, Ulex parviflorus, Cistus albidus, and Erica multiflora. We calculated the global form factor for each species so as to be able to determine the volume of the plants by measuring their base diameter and length. The model volume closest to the real volume was the cylinder, which had form factor values of between 0.8 and 2.33. We also studied the evolution of the moisture content of the vegetation after cutting. The initial values were from 20 to 30%, with a dry density of 1 t/m³. We defined an occupation factor to determine the relationship between the real volume occupied by the plants in an area and a model volume (hemisphere, paraboloid, cone, and cylinder). The occupation factor was similar for the five species studied in dm³ of material per m³ of (model) apparent volume: 3.5 dm³/m³ for the cylinder; 12.5 dm³/m³ for the cone; 8.5 dm³/m³ for the paraboloid; and 14.5 dm³/m³ for the hemisphere. These factors enabled us to calculate the biomass contained in an apparent volume of bushes (including materials and hollows) by density. The prediction models tested in this study will thus serve to determine the biomass of a bushy forest area when the Canopy Height Model (CHM) is calculated from LIDAR data.     

利用机载激光雷达数据提取单株木树高和树冠

机载激光雷达是一种主动遥感技术。在林业应用方面,高采样密度激光雷达能够获取单株木三维结构特征,采用不同的数据处理方法,可以得到不同精度的单株木参数。该文利用高采样密度的机载激光雷达数据（离散回波,平均激光点间隔0.52 m、平均光斑直径0.3 m）,研究了单株木的树高提取技术和树冠边界识别算法,针对单株木的树冠特征,提出了一种双正切角树冠识别算法;最后,使用重庆铁山坪林场的9个外业样地数据,对单株木树高和冠幅,以及样地平均树高和平均冠幅进行了验证。结果表明,单株木树高和冠幅的R2分别为0.34和0.03,样地平均树高和平均冠幅的R2分别为0.97和0.71,样地尺度的相关性明显高于单株木尺度的相关性。      

叶面积指数间接测量方法分析

叶面积指数(LAI)被定义为植物所有叶片表面积总和与植株所占的土地面积的比值,是表征植物生长趋势的重要参数。总结了当前LAI间接测量研究中的2个重要分支:遥感定量法和LIDAR测量法;详细地介绍了这2个分支下的3种方法:统计模型法、光学模型法、LIDAR测量法,阐述了各自的原理和研究进展;在此基础上,讨论了3种方法的优缺点及未来的发展趋势。     

基于机载小光斑全波形LIDAR的作物高度反演

为了填补利用激光雷达反演作物冠层高度的空白,本文以全波形激光雷达发射与回波波形的高斯性为理论基础,首先通过对波形的拟合,实现作物与土壤波形的剥离,然后确定回波波形上各关键点,最后结合作物冠层结构的特征获得作物冠层高度。验证结果表明：反演作物冠层高度的绝对误差在0.06 m以内,相对误差小于5.2%。该方法对于反演其他植被结构参数也具有重要的借鉴意义。     

应用高斯聚类的单木分割及树高和冠幅的提取

针对机载激光雷达点云中基于栅格化的冠层高度模型(CHM)所导致的原始点云数据丢失问题,提出了一种应用高斯模型聚类的单木信息提取方法。采用形态学开运算和高斯平滑方法形成高斯冠层最大模型(GCMM)能减少无关局部最大值对单木分割的影响,利用局部最大值法初步探测树冠顶点,通过最速下降法建立混合高斯模型得到树木位置和冠幅。利用聚类分析划分临近点云归属,进而实现单木参数准确提取,并提取单木最高点为树高。将点云分割方法应用于美国蓝岭地区6块圆形针叶林样地(r=30 m)。结果表明:单木分割F为0.89,正确分割单木树高提取精度95%,冠幅提取精度91%。结合实测数据对提取到的树高和冠幅进行相关性分析,树高R2=0.92,平均误差为-0.83 m;冠幅R2=0.84,平均误差为-0.42 m。相比于分水岭算法,高斯模型聚类方法F提高了11.2%,正确分割单木树高及冠幅提取精度提高了5.5%、5.8%,树高R2提高0.08,平均误差减少0.58 m;冠幅R2提高0.11,平均误差减少0.63 m。     

基于LIDAR数据的林冠层三维信息模型的提取与应用

该文应用机载激光雷达数据,获得了高精度的树冠底部地形信息及树高信息,提取了包含植被冠层高度的数字表面模型,即林冠层三维信息模型(DCM),结合研究区的数字高程模型(DEM)可以获得用常规方法很难准确获取的森林植被参数,如冠层垂直结构、森林高度、郁闭度等.在此基础上,制作了研究区的林木高度图,具有直观、形象等特点,有助于林业部门及时、准确地掌握森林资源相关信息,并可利用DCM获得森林密度、胸高断面积、蓄积量(生物量)及单木参数等森林植被参数.     

基于LIDAR和GIS技术的坡面侵蚀沟空间发育分析

三维激光扫描技术（LIDAR）和地理信息系统（GIS）技术的综合应用是土壤侵蚀定量研究的重要手段,结合LIDAR和GIS技术,将LIDAR动态监测的连续4场次模拟降雨实验数据导入GIS数据处理软件并生成DEM,采用断面分析方法,提取坡长方向上单位长度侵蚀沟断面的宽度和深度,分析坡面侵蚀沟发育特征。结果表明,坡面3.5～5.5 m坡长处是沟蚀发育最为活跃的区段,且随着降雨过程的进行,沟蚀发育活跃区向坡面上部移动。侵蚀沟发育早期以溯源侵蚀为主,后期以沟壁侧蚀和崩塌为主。断面分析方法能够比较准确地分析坡面沟蚀发育的时空分布特征,为土壤侵蚀的定量研究提供了一种新的研究方法。