近景摄影测量提高裸露地表粗糙度测量精度

微波遥感观测量对地表参数敏感,可用于对土壤水分、地表粗糙度和植被信息的定量提取。地表粗糙度参数实测值,是遥感反演结果验证、精度评价,以及各类遥感反演算法中的重要参量,但一直缺少一种简便、快捷、高精度的获取手段。该研究将近景摄影测量方法和微波遥感领域传统地表粗糙度测量的针板法进行对比,分析2种方法均方根高度及相关长度的测量结果,表明近景摄影测量法可以有效提高粗糙度实地测量精度;以近景摄影测量法全角度粗糙度参数的均值作为实测真实值,表明传统针板法测量的均方根高度误差达到12%~35.1%,相关长度误差最大能达到19.6%~62.4%;分析了采样间隔和采样数目对粗糙度测量的影响,表明针板法采用1 cm的间隔是实际地表较好的选择,但仅采用2个方向均值的测量方法必然带来很大误差,同时得出测量次数大于12时,测量结果趋于稳定并可认定为真值的结论;此外,研究表明,在一些传统针板法无法提取粗糙度的情况,近景摄影测量法依然有效。该研究表明,近景摄影测量法的非接触式、高精度、采样间隔及采样频率可调节等特征,为微波遥感工作提供了有效的地表粗糙度地面实测手段。     

Comparing biophysical forest characteristics estimated from photogrammetric matching of aerial images and airborne laser scanning data

Recent development in aerial digital cameras and software facilitate the photogrammetric point cloud as a new data source in forest management planning. A total of 151 field training plots were distributed systematically within three predefined strata in a 852.6 ha study area located in the boreal forest in southeastern Norway. Stratum-specific regression models were fitted for six studied biophysical forest characteristics. The explanatory variables were various canopy height and canopy density metrics derived by means of photogrammetric matching of aerial images and small-footprint laser scanning. The ground sampling distance was 17 cm for the images and the airborne laser scanning (ALS) pulse density was 7.4 points m^–2. Resampled images were assessed to mimic acquisitions at higher flying altitudes. The digital terrain model derived from the ALS data was used to represent the ground surface. The results were evaluated using 63 independent test stands. When estimating height in young forest and mature forest on poor sites, the root mean square error (RMSE) values were slightly better using data from image matching compared to ALS. However, for all other combinations of biophysical forest characteristics and strata, better results were obtained using ALS data. In general, the best results were found using the highest image resolution.     

An aerial photograph auto-interpretation system for forest resource inventory

Aerial photographs arc important information sources for forest inventory. With the development of science and technology, an automated approach to aerial photograph interpretation has been sought. This paper introduces an experimental computer system for the auto-interpretation of aerial photographs. On thebasis of the experimental system, several algorithms are developed for the interpretation of density, crown closure, working groups and species composition of forest stands. Experiments show that auto—interpretation works well for some forest inventory data.     

一种数据获取方法在拖拉机车身逆向中的应用

针对国产拖拉机车身设计的特点,介绍了一种采用Comet 250光栅测量与AICON 3D Studio摄影测量相结合的逆向工程数据获取的方法以及相关的原理。通过对"一拖"T70大功率拖拉机机罩进行实测,验证了这种数据获取方法的精度及效率。实例应用结果表明了这种测量方法的可行性,为拖拉机车身设计提供了一个有效测量的途径。     

Measurement and Calculation Methods of a Stem Image Information

The paper shows a study on 2-D stem image information collected by a digital camera. Information on a single stem is obtained through calculations after the application of the direct linear transformation model of close-range photogrammetry and binocular stereo vision technology, so that the calculating problem between stem image information and its 2-D coordinate can be solved. Furthermore, the 2-D processing methodology for measuring tree image information simplifies calculating equations and increases calculating speed. Although computer stereo vision techniques for collecting parameters of a single stem shape are comparative, complicated, and expensive, research indicates the efficiently and feasibility of close-range photogrammetry for stem image information. Translated from the Journal of Beijing Forestry University, 2005, 27(1) (in Chinese)     

遮挡情况下目标三维点云的提取研究

针对三维信息提取过程中的遮挡问题,提出利用多基线数字近景摄影测量方法进行多光线的影像匹配,基于遮挡区域约束的三维点云滤波算法,即去除了遮挡目标,又可提取部分被遮挡区域的三维数据点。试验表明,该方法适应了空间分布的不连续性,在遮挡情况下较好地解决了目标的遮挡问题,同时多方向交会使前方交会具有冗余观测,增加了三维数据点的可靠性。     

Forest variable estimation using photogrammetric matching of digital aerial images in combination with a high-resolution DEM

Abstract

The rapid development in aerial digital cameras in combination with the increased availability of high-resolution Digital Elevation Models (DEMs) provides a renaissance for photogrammetry in forest management planning. Tree height, stem volume, and basal area were estimated for forest stands using canopy height, density, and texture metrics derived from photogrammetric matching of digital aerial images and a high-resolution DEM. The study was conducted at a coniferous hemi-boreal site in southern Sweden. Three different data-sets of digital aerial images were used to test the effects of flight altitude and stereo overlap on an area-based estimation of forest variables. Metrics were calculated for 344 field plots (10 m radius) from point cloud data and used in regression analysis. Stand level accuracy was evaluated using leave-one-out cross validation of 24 stands. For these stands the tree height ranged from 4.8 to 26.9 m (17.8 m mean), stem volume 13.3 to 455 m³ ha^?1 (250 m³ ha^?1 mean), and basal area from 4.1 to 42.9 m² ha^?1 (27.1 m² ha^?1 mean) with mean stand size of 2.8 ha. The results showed small differences in estimation accuracy of forest variables between the data-sets. The data-set of digital aerial images corresponding to the standard acquisition of the Swedish National Land Survey (Lantmäteriet), showed Root Mean Square Errors (in percent of the surveyed stand mean) of 8.8% for tree height, 13.1% for stem volume and 14.9% for basal area. The results imply that photogrammetric matching of digital aerial images has significant potential for operational use in forestry.     

Aerial photo-interpretation using Z/I DMC images for estimation of forest variables

Abstract

Interpretation and tree height measurements in aerial photographs using photogrammetric workstations are frequently performed in standwise forest inventory. Images acquired by digital aerial cameras are now replacing the traditional film-based aerial photographs. In this study, digital images from the airborne Z/I DMC system for standwise estimation of stem volume, tree height and tree species composition were investigated at a 1200 ha forest area located in southern Sweden (58°30′N, 13°40′E). The 56 selected stands were dominated by Norway spruce [Picea abies (L.) Karst.] and Scots pine (Pinus sylvestris L.) with stem volume in the range of 30–630 m³ ha^?1 (average 300 m³ ha^?1) and tree height in the range of 6–28 m (average 20 m). The large-format pansharpened colour infrared images were captured at a flight altitude of 4800 m above ground level corresponding to a pixel size of 0.48 m. The photo-interpretation was conducted by four professional interpreters, independently. In particular, two different base-to-height ratios (i.e. the ratio between the ground distance between image centres at the time of exposure and the flight altitude above ground level) of 0.26 and 0.39 were evaluated, but no significant difference in the estimation accuracy for stem volume and tree height was found. The accuracy for stem volume estimation in terms of relative root mean square error, corrected for systematic errors, was on average 24% (in the range of 17–39%). The corresponding accuracy for tree height estimation was on average 1.4 m (in the range of 0.9–1.6 m). The tree species composition accuracy assessment using a fuzzy set evaluation procedure showed that 95% of the stands were correctly classified. The estimation accuracies are in agreement with previous results using conventional film-based aerial panchromatic photographs.     

人机界面空间几何位置的摄影测量

机械系统人机界面的优化匹配,空间几何位置是其主要因素之一,它的准确测量对产品设计、制造和改进都十分必要。该文将近影摄影测量、计算机视觉和图像处理技术用于人机界面空间几何位置的测量,实现了快捷、方便的非接触式测量。测量仪器采用普通民用摄像机和计算机系统。文中介绍了图像数字化过程和摄影测量的数学模型,给出其求解方法。并对变换误差进行了分析,通过试验确定线性拟合的误差修正模型,详细介绍了修正过程、外部三维控制场的设计和布置,编制了实用的计算机测量和识别软件,并给出了人机界面实验台的测量结果和识别误差。试验表明其测量误差小于２％,可满足一般工程测量的要求。