Determination of Mean Tree Height of Forest Stands by Digital Photogrammetry

The mean tree height of 73 forest stands in a 1000 ha forest area was determined from canopy heights generated by automatic image matching using a digital photogrammetric workstation and digitized panchromatic aerial photographs with a scale of 1:15 000. First, the mean height of each stand was computed as the arithmetic mean of the quantile corresponding to the 75th percentile of the distribution of the canopy heights from the image matching within square grid cells with cell sizes of 236-400 m². The mean heights from the image matching underestimated the true heights by 5.42 m. Secondly, field-measured mean tree heights of 165 georeferenced sample plots distributed systematically throughout the 1000 ha forest area were regressed against the mean heights derived from the image matching. The regression equations were used to predict the mean heights of the 73 stands. In very young forest stands, the predicted mean heights overestimated the true heights by 0.4 m and the precision was 0.9-1.0 m. In young and mature stands, the average difference between predicted height and ground-truth ranged between -1.6 and 0.5 m, and the precision ranged from 1.1 to 2.1 m.     

Stem Diameter Estimation from Aerial Photographs

Remote sensing techniques have proven successful for producing stem maps of forests in leaf-on condition from high-resolution imagery. This paper demonstrates how a mathematical model for the surface of a stem can be used to estimate the breast-height diameter of individual trees from aerial photographs to give information on basal area. The diameters are estimated by likelihood estimation from images of a forest in leaf-off condition where the stems and their shadows are visible. Applied to a homogeneous and monospecific oak ( Quercus robur L.) stand under standard silvicultural treatment in Denmark, the estimation was successful for 56 out of 60 trees. The root mean squared error on the diameter was 4.2 and 3.2 cm using three and five images, respectively. The key conclusion is that it is feasible to infer fairly accurate information about the diameters and three-dimensional positions of stems from aerial photographs.     

Impact of topography on cross-pollination in maize (Zea mays L.)

Understanding cross-pollination is important to achieve the coexistence of genetically modified (GM) and conventional maize (Zea mays L.); it is still not known whether topography favors or hinders cross-pollination. In 2005 and 2006, the effect of gradients of 3.4–6.8° on cross-pollination was investigated in the canton of Zurich, Switzerland. Cross-pollination was revealed by the presence of yellow-grains on a white-grain hybrid at distances up to 17.5 m from the yellow-grain pollen donor hybrid. The measurements of the inclination of the slope were based on aerial images data taken by an unmanned GPS/INS (Global Positioning System/Inertial Navigation System)-based and stabilized model helicopter, which delivered precise altitude-based data for sampling points at tassel height.The rate of cross-pollination increased significantly with decreasing altitude of the receptor field (r = 0.36–0.64). However, the effect seems to be weaker than that of other factors like wind direction and velocity.     

GIS输入的摄影测量方法

为了拓宽ＧＩＳ的输入范围。文章研究了ＧＩＳ输入的摄影测量方法。该方法应用摄影测量理论的空间解析模型，选取已知地图坐标的控制纠正点．求解模型参数、经过坐标变换．以象片区划线的弧为基本单位进行数字化处理，得到地图坐标数据．由此坐标数据提取出弧和结点数据、最后生成与ＡＲＣ／ＮＦＯ系统相兼容的拓扑数据结构。经检验用该方法完全满足成图要求。     

Testing the accuracy of imaging software for measuring tree root volumes

Manually measuring tree root characteristics can be inefficient and limiting. To test the application of a new digital technology in tree root architecture research, root systems from 29 green ash (Fraxinus pennsylvanica 'Patmore') trees were unearthed, cleaned, and photographed to create 3D models using structure from motion (SfM) photogrammetry. Three root segments from each root system were selected, marked, and removed after being photographed. The volumes of these segments (derived from the 3D models) were compared against volumes measured using water displacement. In addition to the root segments, model and water displacement volumes were compared for three complete root systems. Regression analysis showed a strong linear relation between the two volumes measurements (adjusted R² = 0.97 for the root segment data). The RMSE for the root segment volume estimates was 40.37 cm³ (12.3%), with a bias of 17.2 cm³ (5.3%). This error rate was similar to previous published work and suggests the technology used may allow researchers to improve efficiency in data capture, add new measurements (i.e., surface area) to their modeling efforts, and digitally preserve tree root systems for future study.     

Terrestrial photogrammetric stem mensuration for street trees

Much of forest science is dependent on accurate stem measurements, and relatively new photogrammetric techniques may be suitable for modeling stems from the terrestrial perspective. From imagery taken along a windbreak and urban roadways we tested the viability of photogrammetric modeling for producing accurate diameter at breast height measurements. Treatments for different point cloud models differed based on intervals between control points (i.e., every 5 m, 10 m, 25 m, and an absence of target control points) and site conditions (i.e., urban mixed species vs. a windbreak of Pinus taeda) over 100 m sections in the Tampa Bay, FL area. Stem diameter measurements from both the windbreak (n = 53) and the urban sites (n = 93) showed high conformity between field-derived and point cloud model measurements (linear regression showed R² values >0.9 and RMSE values ranging from 7.04 − 12.35%) with the number of control point targets having little influence on modeled DBH accuracy. Modeled stems of larger trees had greater associated error relative to DBH tape measurements, which can be attributed, in part, to problems with estimating diameter from non-circular stems of certain urban species (i.e., Quercus virginiana). Future work will focus on georeferencing these datasets and extracting data on other aspects of stem biometry (e.g., lean angle of stem, stem volume, etc.).     

Forest edge quantification by line intersect sampling in aerial photographs

There is a need for accurate and efficient methods for quantification and characterisation of forest edges at the landscape level in order to understand and mitigate the effects of forest fragmentation on biodiversity. We present and evaluate a method for collecting detailed data on forest edges in aerial photographs by using line intersect sampling (LIS). A digital photogrammetric system was used to collect data from scanned colour infrared photographs in a managed boreal forest landscape. We focused on high-contrast edges between forest (height ≥ 10 m) and adjoining open habitat or young, regenerating forest (height ≤ 5 m). We evaluated the air photo interpretation with respect to accuracy in estimated edge length, edge detection, edge type classification and structural variables recorded in 20 m radius plots, using detailed field data as reference. The estimated length of forest edge in the air photo interpretation (52 ± 8.8 m ha⁻¹; mean ± standard error) was close to that in the field survey (58 ± 9.3 m ha⁻¹). The accuracy in edge type classification (type of open habitat) was high (88% correctly classified). Both tree height and canopy cover showed strong relationships with the field data in the forest, but tree height was underestimated by 2.3 m. Data collection was eight times faster and five times more cost-effective in aerial photographs than in field sampling. The study shows that line intersect sampling in aerial photographs has large potential application as a general tool for collecting detailed information on the quantity and characteristics of high-contrast edges in managed forest ecosystems.     

土壤侵蚀速率近景摄影测量法(CRPE)的野外试验研究

在北京市延庆县水土保持科技示范区内,对土壤侵蚀速率近景摄影测量法(CRPE)进行了野外初步试验应用研究。结果表明:与径流小区观测结果相比,CRPE法土壤侵蚀速率解算精度可达到90%左右;侵蚀针应采取行列式均匀布设方式布设,布设密度对监测精度具有较大影响,最大间距不宜超过1 m,且每行不应少于5根。     

Soil surface roughness measurement—methods, applicability, and surface representation

In a laboratory rainfall simulator study soil surface roughness was measured using contact (roller chain, pin meter) and noncontact devices (laser scanner, photogrammetry). Soil surfaces with two initial roughness conditions (aggregates < 20 mm and < 63 mm) were investigated before and after 90 mm of simulated rainfall. Measured plot area was 50 by 55 cm. A comparison of soil roughness measurement techniques was undertaken with regard to data acquisition and computation efforts, resolution, precision and capability to represent soil surface features.As for the contact methods, resolution (cm range) and precision (mm range) is limited which constrains their application to calculation of simple surface parameters. Resolution and precision in the sub millimeter range could be obtained with the laser scanner, while for the photogrammetric method the measurement uncertainty was approximately 1–2 mm. Measurement time was highest (90 min) for the pin meter technique, though data were ready to use for analyses. Laser scanner measurements took 34 min. Several steps of data post-processing required 30 more minutes. Data acquisition was fastest for photogrammetry (5 min), but expert knowledge as well as special hard- and software were necessary for time-consuming photo analyses, taking about 120 min.The chain and pin meter were compared using a profile index. Profile lengths matched well for smooth surfaces; on rough surfaces, the chain meter gave shorter profile lines. Between profile index from chain measurements and the random roughness derived from pin meter data a polynomial regression could be found. Parameters of distributions of elevations as well as inclinations and depressions were used to compare the laser scanner and the photogrammetric technique. Generally the laser scanner was able to reproduce small aggregates as well as voids in between them, while DEM from stereophotos was smoothed between major aggregates. This led to skewed distributions of elevations and inclinations, as well as to a lower surface area (up to 39%), and a lower depression volume (up to 68%). Shapes of depressions were significantly different as well. The used photogrammetric technique is supposed to be successful in producing adequate DEMs for already smoothed surfaces, e.g. after rainfall events.The study revealed different fields of application and limitations of the compared devices. Using a non-adequate technique for certain situations will definitely have implications on further analyses concerning connectivity of runoff pathways, surface protection from raindrop impact or runoff detachment and sediment transport.     

Automatic Stem Mapping in Three Dimensions by Template Matching from Aerial Photographs

Recent developments in remote sensing have shown promising results for the detection and species classification of individual trees from high-resolution imagery of forests in leaf-on condition. Existing image-analysis algorithms produce a two-dimensional stem map in the observed imagery. This paper develops a new algorithm that generalizes existing template-matching algorithms to produce a stem map in the three dimensions of a forest in leaf-off condition. A self-contained algorithm to produce artificial template images is introduced. The image-analysis algorithm was applied to oak ( Quercus robur L.) grown under standard silvicultural treatment in Denmark. One analysis gave detection rates in the range 85-98% and root mean squared errors on the stem base coordinates below 8.1, 7.6 and 20.5 cm in the x -, y - and z -directions, respectively. It is concluded that it is indeed feasible to produce a quite accurate three-dimensional stem map.