Mapping sub‐pixel fluvial grain sizes with hyperspatial imagery

This study presents an investigation of image texture approaches for mapping sub‐pixel fluvial grain‐size features from airborne imagery, allowing for the rapid acquisition of surface sand and coarse fraction (>1·41 mm) grain‐size information. Imagery at 30 mm resolution was acquired over four gravel bars from the Fraser River (British Columbia, Canada). Combined first‐order and second‐order image texture approaches (windowed standard deviation filter and the grey level co‐occurrence matrix) were used. First‐order image texture, through the application of a standard deviation filter and subsequent thresholding was used to detect the presence of surface sand, with optimal accuracy achieved at 91 ± 1·9%. A wide‐ranging parameter space investigation was used to derive optimum parameters for the grey‐level co‐occurrence matrix. Subsequently first‐order and second‐order image textures were used in multiple linear regression to achieve good calibrations with several sub‐pixel grain‐size percentiles; relative error at 1·44%, 3·18%, 6·80% and 10·6% for D₅, D₁₆, D₃₅ and D₅₀, respectively. The larger percentiles of D₈₄ and D₉₅ had relative errors of 24·7% and 29·7%, respectively. The breakdown of calibration precision for larger percentiles is attributed to a ‘pixel averaging effect’. It is concluded that multispectral imagery is not required, because sufficient image texture information can be derived from standard colour imagery. Recommendations are suggested for the application of this method to other localities and data sets, thus reducing exhaustive parameter searches in future studies.     

机载多普勒天气雷达及应用研究进展

机载多普勒天气雷达由于其灵活机动性,在台风、暴雨等灾害性天气系统中尺度三维精细结构研究中发挥着重要作用.对机载多普勒天气雷达技术及其资料应用进行了概要性综述,主要从机载多普勒天气雷达发展历程、4种主要机载多普勒雷达技术特点、雷达天线扫描策略、单多普勒雷达风场反演技术、双多普勒雷达风场反演技术、雷达资料同化以及目标观测等方面进行阐述和分析;着重讨论了应用中需要解决的问题.最后,指出发展具有快速扫描和双偏振功能的机载相控阵多普勒雷达是机载天气雷达的发展方向,它可以获取高时空分辨率的探测数据,能够对云和降水系统的三维精细动力结构、热力结构以及微物理结构等进行综合研究.     

三峡工程库底清理中的遥感动态监测

 以巴东县、巫山县和云阳县二期移民库底清理为例,开展遥感动态监测，结合小型遥控飞机获取的影像数据特点，采用合适的图 像处理技术及人机交互解译获取信息，为工程管理及时提供实时性强和真实可靠的定位、定性、定量数据，进而,为长期动态监测奠定 基础。     

Detection of gullies in roughly textured terrain using airborne laser scanning data

Airborne laser scanning data contain information about surface features, some of which are of subtle form. These features are usually embedded within the terrain, and rarely form distinct shape-transition to their surroundings. While some efforts have been made in extracting linear elements from laser scanning data, attention was mostly turned to dominant elements that are very clear and distinct. We present in this paper a detection model for gullies of various dimensions using airborne laser scanning data. Gullies are regarded as one of the main landform-reshaping agents, having a pejorative effect on the environment and on regional development. They are commonly observed along receding lakes as a common response to water-level drop. The paper demonstrates how a multi-scale approach enables the extraction of various gully forms, from well developed to subtle. It then proposes an optimization driven model for handling fragmentation in the detection. Results show that using the proposed model, gully networks can be reconstructed and ∼30 cm deep features can be identified and separated from their surroundings using moderate point density data.     

机载LiDAR点云更新1∶1万DEM关键技术探讨

结合TerraSolid对机载激光雷达数据进行后处理的生产流程,重点分析利用LiDAR数据提取DEM的几个关键技术:滤波技术、航带拼接技术、特征线\特征点参与DEM构建技术以及点云人工编辑分类后航带间高差超限的补救性处理方法。     

A graph edit dictionary for correcting errors in roof topology graphs reconstructed from point clouds

In the task of 3D building model reconstruction from point clouds we face the problem of recovering a roof topology graph in the presence of noise, small roof faces and low point densities. Errors in roof topology graphs will seriously affect the final modelling results. The aim of this research is to automatically correct these errors. We define the graph correction as a graph-to-graph problem, similar to the spelling correction problem (also called the string-to-string problem). The graph correction is more complex than string correction, as the graphs are 2D while strings are only 1D. We design a strategy based on a dictionary of graph edit operations to automatically identify and correct the errors in the input graph. For each type of error the graph edit dictionary stores a representative erroneous subgraph as well as the corrected version. As an erroneous roof topology graph may contain several errors, a heuristic search is applied to find the optimum sequence of graph edits to correct the errors one by one. The graph edit dictionary can be expanded to include entries needed to cope with errors that were previously not encountered. Experiments show that the dictionary with only fifteen entries already properly corrects one quarter of erroneous graphs in about 4500 buildings, and even half of the erroneous graphs in one test area, achieving as high as a 95% acceptance rate of the reconstructed models.     

A visible band index for remote sensing leaf chlorophyll content at the canopy scale

Leaf chlorophyll content is an important variable for agricultural remote sensing because of its close relationship to leaf nitrogen content. The triangular greenness index (TGI) was developed based on the area of a triangle surrounding the spectral features of chlorophyll with points at (670 nm, R₆₇₀), (550 nm, R₅₅₀), and (480 nm, R₄₈₀), where R_λ is the spectral reflectance at wavelengths of 670, 550 and 480, respectively. The equation is TGI = −0.5[(670 − 480)(R₆₇₀ − R₅₅₀) − (670 − 550)(R₆₇₀ − R₄₈₀)]. In 1999, investigators funded by NASA's Earth Observations Commercialization and Applications Program collaborated on a nitrogen fertilization experiment with irrigated maize in Nebraska. Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data and Landsat 5 Thematic Mapper (TM) data were acquired along with leaf chlorophyll meter and other data on three dates in July during late vegetative growth and early reproductive growth. TGI was consistently correlated with plot-averaged chlorophyll-meter values at the spectral resolutions of AVIRIS, Landsat TM, and digital cameras. Simulations using the Scattering by Arbitrarily Inclined Leaves (SAIL) canopy model indicate an interaction among TGI, leaf area index (LAI) and soil type at low crop LAI, whereas at high LAI and canopy closure, TGI was only affected by leaf chlorophyll content. Therefore, TGI may be the best spectral index to detect crop nitrogen requirements with low-cost digital cameras mounted on low-altitude airborne platforms.     

Performance of dense digital surface models based on image matching in the estimation of plot-level forest variables

Recent research results have shown that the performance of digital surface model extraction using novel high-quality photogrammetric images and image matching is a highly competitive alternative to laser scanning. In this article, we proceed to compare the performance of these two methods in the estimation of plot-level forest variables. Dense point clouds extracted from aerial frame images were used to estimate the plot-level forest variables needed in a forest inventory covering 89 plots. We analyzed images with 60% and 80% forward overlaps and used test plots with off-nadir angles of between 0° and 20°. When compared to reference ground measurements, the airborne laser scanning (ALS) data proved to be the most accurate: it yielded root mean square error (RMSE) values of 6.55% for mean height, 11.42% for mean diameter, and 20.72% for volume. When we applied a forward overlap of 80%, the corresponding results from aerial images were 6.77% for mean height, 12.00% for mean diameter, and 22.62% for volume. A forward overlap of 60% resulted in slightly deteriorated RMSE values of 7.55% for mean height, 12.20% for mean diameter, and 22.77% for volume. According to our results, the use of higher forward overlap produced only slightly better results in the estimation of these forest variables. Additionally, we found that the estimation accuracy was not significantly impacted by the increase in the off-nadir angle. Our results confirmed that digital aerial photographs were about as accurate as ALS in forest resources estimation as long as a terrain model was available.