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一般地形大光斑激光测高回波模拟研究 总被引：1，自引：0，他引：1
国内对基于陆地模型的地表回波仿真的研究较多,主要分析了三种特定的地表模型:平面、阶梯、斜坡地形,取得了不错的进展,但是却不具有一般性。针对这种情况,本文从一般性地表模型出发,根据实际的地形三维离散点,用Delaunay三角形剖分拟合出地表模型,用剖分后的三角面片返回的能量代表整个地表返回的能量,拟合出回波波形。通过和GLAS系统获取的相同区域的实际回波波形进行相关性比较,结果发现两者具有很好的相关性,验证了算法的正确性。文章结论为后续继续深入开展激光大光斑内精细地形信息分析、激光测高数据与光学影像复合处理提供了理论基础,为发展我国自主的星载激光测高卫星的有关指标论证提供参考。 相似文献
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《International Journal of Digital Earth》2013,6(2):106-132
Improvements in the acquisition of three-dimensional (3D) information from the Airborne Laser Scanner (ALS) increase its applications for studying Earth's surface. The use of ALS data in natural resource inventories is still in an experimental stage in central Europe. Here, a survey was completed in Germany, where plot-level features from LANDSAT Thematic Mapper and ALS data were applied. An automated process was developed for forest stratification using orthoimages. A genetic algorithm was applied for variable screening. Variable subsets of different sizes were employed for simultaneous predictions of structural forest attributes using the ‘Random Forest’ (RF) method. Performance was assessed by leave-one-out cross-validations on bootstrap resample data. Results indicate that the stratification of forest notably improved the results of predictions. The improvements were more obvious for the strata-related attributes. Accuracy was enhanced as the number of selected variables increased. However, parsimonious models are still essentially required for practical applications. The RF errors were slightly greater than those from least squares regression, as the non-parametric methods do not share the same mix of error components as regression. Through the combination of remote sensing and modelling, we conclude that our results are helpful for bridging the gap between regional earth observation and on-the-ground forest structure. 相似文献
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This article reviews the recent literature concerning airborne laser scanning for forestry purposes in Italy, and presents the current methodologies used to extract forest characteristics from discrete return ALS (Airborne Laser Scanning) data. Increasing interest in ALS data is currently being shown, especially for remote sensing-based forest inventories in Italy; the driving force for this interest is the possibility of reducing costs and providing more accurate and efficient estimation of forest characteristics. This review covers a period of approximately ten years, from the first application of laser scanning for forestry purposes in 2003 to the present day, and shows that there are numerous ongoing research activities which use these technologies for the assessment of forest attributes (e.g., number of trees, mean tree height, stem volume) and ecological issues (e.g., gap identification, fuel model detection). The basic approaches – such as single tree detection and area-based modeling – have been widely examined and commented in order to explore the trend of methods in these technologies, including their applicability and performance. Finally this paper outlines and comments some of the common problems encountered in operational use of laser scanning in Italy, offering potentially useful guidelines and solutions for other countries with similar conditions, under a rather variable environmental framework comprising Alpine, temperate and Mediterranean forest ecosystems. 相似文献
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Jens Göpfert Franz Rottensteiner Christian Heipke 《ISPRS Journal of Photogrammetry and Remote Sensing》2011,66(6):858-871
For historical reasons many national mapping agencies store their topographic data in a dual system consisting of a Digital Landscape Model (DLM) and a Digital Terrain Model (DTM). The DLM contains 2D vector data representing objects on the Earth’s surface, such as roads and rivers, whereas the DTM is a 2.5D representation of the related height information, often acquired by Airborne Laser Scanning (ALS). Today, many applications require reliable 3D topographic data. Therefore, it is advantageous to convert the dual system into a 3D DLM. However, as a result of different methods of acquisition, processing, and modelling, the registration of the two data sets often presents difficulties. Thus, a straightforward integration of the DTM and DLM might lead to inaccurate and semantically incorrect 3D objects.In this paper we propose a new method for the fusion of the two data sets that exploits parametric active contours (also called snakes), focusing on road networks. For that purpose, the roads from a DLM initialise the snakes, defining their topology and their internal energy, whereas ALS features exert external forces to the snake via the image energy. After the optimisation process the shape and position of the snakes should coincide with the ALS features. With respect to the robustness of the method several known modifications of snakes are combined in a consistent framework for DLM road network adaptation. One important modification redefines the standard internal energy and thus the geometrical model of the snake in order to prevent changes in shape or position not caused by significant features in the image energy. For this purpose, the initial shape is utilized creating template-like snakes with the ability of local adaptation. This is one crucial point towards the applicability of the entire method considering the strongly varying significance of the ALS features. Other concepts related to snakes are integrated which enable our method to model network and ribbon-like characteristics simultaneously. Additionally, besides ALS road features information about context objects, such as bridges and buildings, is introduced as part of the image energy to support the optimisation process. Meaningful examples are presented that emphasize and evaluate the applicability of the proposed method. 相似文献
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Zhengyang Hou Qing Xu Timo Tokola 《ISPRS Journal of Photogrammetry and Remote Sensing》2011,66(6):776-786
In this study, the potential of remote sensing in tropical forests is examined in relation to the diversification of sensors. We report here on the comparison of alternative methods that use multisource data from Airborne Laser Scanning (ALS), Airborne CIR and ALOS AVNIR-2 to estimate stem volume and basal area, in Laos. Multivariate linear regression analyses with stepwise selection of predictors were implemented for modelling. The predictors of ALS metrics were calculated by means of the canopy height distribution approach, while predictors from both spectral and textual features were respectively generated for Airborne CIR and ALOS AVNIR-2 data. With respect to the estimation capacity from individual data sources after leave-one-out cross-validation, the ALS data proved superior, with the lowest RMSE of 36.92% for stem volume and 47.35% for basal area, whereas Airborne CIR and ALOS AVNIR-2 remained at similar accuracy levels, but fell well behind the ALS data. By integrating ALS metrics with other predictors from Airborne CIR or ALOS AVNIR-2, hybrid modelling was further tested respectively. The results showed that only the hybrid model for stem volume involving ALS and Airborne CIR improved the accuracy of 1.9% in terms of relative RMSE than that of using ALS alone. 相似文献
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王继承 《测绘与空间地理信息》2015,(4):147-149
详细介绍了徕卡ALS70机载激光扫描系统的检校原理、检校厂布设原理以及检校方法,并以台安县作为检校场地进行检校实验,检校后,台安县120 km2的0.7 m点间距的点云数据精度完全符合我国相关技术要求规定,证明了该检校场地布设和检校方法是安全可靠的,是可以大范围地应用在点云数据检校生产当中。 相似文献
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机载激光雷达（LiDAR）是近10年出现的高新技术之一,能迅速获取密集的地面3维数据,并广泛应用于各个领域。本文主要介绍了我院通过试验,获取及处理ALS70机栽激光雷达点云数据的方法。 相似文献
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Site productivity is essential information for sustainable forest management and site index (SI) is the most common quantitative measure of it. The SI is usually determined for individual tree species based on tree height and the age of the 100 largest trees per hectare according to stem diameter. The present study aimed to demonstrate and validate a methodology for the determination of SI using remotely sensed data, in particular fused airborne laser scanning (ALS) and airborne hyperspectral data in a forest site in Norway. The applied approach was based on individual tree crown (ITC) delineation: tree species, tree height, diameter at breast height (DBH), and age were modelled and predicted at ITC level using 10-fold cross validation. Four dominant ITCs per 400 m2 plot were selected as input to predict SI at plot level for Norway spruce (Picea abies (L.) Karst.) and Scots pine (Pinus sylvestris L.). We applied an experimental setup with different subsets of dominant ITCs with different combinations of attributes (predicted or field-derived) for SI predictions. The results revealed that the selection of the dominant ITCs based on the largest DBH independent of tree species, predicted the SI with similar accuracy as ITCs matched with field-derived dominant trees (RMSE: 27.6% vs 23.3%). The SI accuracies were at the same level when dominant species were determined from the remotely sensed or field data (RMSE: 27.6% vs 27.8%). However, when the predicted tree age was used the SI accuracy decreased compared to field-derived age (RMSE: 27.6% vs 7.6%). In general, SI was overpredicted for both tree species in the mature forest, while there was an underprediction in the young forest. In conclusion, the proposed approach for SI determination based on ITC delineation and a combination of ALS and hyperspectral data is an efficient and stable procedure, which has the potential to predict SI in forest areas at various spatial scales and additionally to improve existing SI maps in Norway. 相似文献