支持向量机的车载雷达点云目标识别

为了进一步研究移动测量系统的数据处理问题,该文根据点云的基本特征,归纳了由7个特征构成的点云原始特征向量,在此基础上,结合语义环境构建了由17个特征构成的点云扩展特征向量,并采用支持向量机模型对车载LiDAR点云进行行道树点云识别的一系列实验。实验中采用粒子群优化算法和遗传算法对支持向量机进行参数寻优;采用不同特征向量和不同数目样本对点云进行学习和目标识别;分析了特征向量的学习曲线和识别精度。实验结果表明,支持向量机模型能够在行道树点云识别中取得较高的精度。     

混合核特征加权SVM遥感湿地空间分类

针对湿地空间信息的复杂性和SVM的分类性能,设计一种基于混合核函数的特征加权SVM分类模型,综合利用多种特征信息,避免被弱相关特征所支配,从而提供更佳的映射性能和泛化能力。实验结果表明,该分类模型兼具良好的外推和内推能力,能够有效地融合不同信息源特征,得到更完整和准确的分类结果,在总体精度、Kappa系数等多项指标上都表现出更高的水平。     

时变参数灰色模型背景值重构及实现

针对时变参数灰色模型PGM(1,1)的背景值重构收敛速度及稳定性问题,该文运用积分的方法综合序列在Δt内不同变化趋势,导出背景值模型的准确表达式。实现了反映序列对新老信息偏爱程度的最优权值介于(0,1)内,且非不能越过某一阈值;给出了背景值重构模型最优解准确求取的具体算法步骤。基于MATLAB语言的实验结果表明:改进模型预测精度高,易于实现;所研究的带权灰色模型GM(1,n)背景值模型的重构及计算方法验证了PGM(1,1)模型重构及计算实现方法的有效性和实用性。     

局部均值分解与支持向量回归的大坝变形预测

针对现有变形预测方法对于大坝变形的预测效果不理想的问题,该文利用局部均值分解方法获取生产函数分量并进行支持向量回归建模,用此方法对大坝变形进行多尺度分析。通过局部均值分解对大坝变形序列进行分解得到其乘积函数分量,然后利用支持向量机回归进行外推预测,再把各乘积函数分量的预测结果进行叠加重构生成,进而获得大坝变形预测值。通过实例分析,比较GM(1,1)、支持向量机和该文方法3种模型在变形监测数据处理中的拟合和预测结果,表明该文方法充分发掘数据本身所蕴含的物理机制和物理规律,提高了大坝变形多尺度预测精度。     

改进支持向量机的高分遥感影像道路提取

针对支持向量机受分类数的限制在高分辨率遥感影像中无法直接获取高精度道路网信息的问题,该文提出一种新的混合的基于支持向量机的方法:首先,利用模糊C均值聚类方法将输入的遥感影像分为3类,以减少支持向量机的错分现象;其次,运用支持向量机将不同类别的像素分为道路类和非道路类;最后,应用马尔科夫随机场对分类结果进行噪声去除,并采用形态学进行后处理,进而得到精确道路网信息。实验结果表明:该算法不仅能够从高分辨率遥感影像中提取出道路网,而且精度优于直接使用支持向量机算法以及对比算法。     

Temporal replication of the national land cover database using active machine learning

Regional and national level land cover datasets, such as the National Land Cover Database (NLCD) in the United States, have become an important resource in physical and social science research. Updates to the NLCD have been conducted every 5 years since 2001; however, the procedure for producing a new release is labor-intensive and time-consuming, taking 3 or 4 years to complete. Furthermore, in most countries very few, if any, such releases exist, and thus there is high demand for efficient production of land cover data at different points in time. In this paper, an active machine learning framework for temporal updating (or backcasting) of land cover data is proposed and tested for three study sites covered by the NLCD. The approach employs a maximum entropy classifier to extract information from one Landsat image using the NLCD, and then replicate the classification on a Landsat image for the same geographic extent from a different point in time to create land cover data of similar quality. Results show that this framework can effectively replicate the land cover database in the temporal domain with similar levels of overall and within class agreement when compared against high resolution reference land cover datasets. These results demonstrate that the land cover information encapsulated in the NLCD can effectively be extracted using solely Landsat imagery for replication purposes. The algorithm is fully automated and scalable for applications at landscape and regional scales for multiple points in time.     

Remote sensing and information value (IV) model for regional mapping of fluvial channels and topographic wetness in the Saudi Arabia

This study aims to map regions of near surface fluvial channels, mega-basins and topographic wetness in Saudi Arabia using remote sensing data and an information value (IV) model, which is a modified approach of weight of evidence. We used the new version of the Shuttle Radar Topographic Mission (SRTM) to delineate the fluvial channels, mega-basin, and slope. These hydrological parameters were used to index the topographic wetness of each mega-basin in the region based on IV in a Geographic Information System. We validated our method using the Space Imaging Radar-C and Landsat 8 images and compared the textural features (fluvial channels) evident from SRTM digital elevation model and to determine whether these patterns were different. Our results revealed that the region is drained by nine tributaries and that the Err Rub Al Khali and Sahba mega-basins have the highest value of the IV and topographic wetness values; the Arran and coastal mega-basins have the lowest value of the IV and topographic wetness values. An integrated approach is timely and economically effective and can be applied throughout the arid and semi-arid regions to help hydrologists and urban developers.     

An efficient application of fusion approach for hot spot detection with MODIS and PALSAR-1 data

Hot spot detection with satellite images, especially with synthetic aperture radar (SAR) images is still a challenging task. Several researchers have used TM/optical data for identification of hot spot but the use of SAR data is very limited for this type of application. The fusion of SAR data with TM/optical data may add additional information which in turn will lead for enhancement of detection capability of the hot spot. Therefore, this study explores the possibility of fusion of Moderate Resolution Imaging Spectroradiometer (MODIS) and Phased Array L-band Synthetic Aperture Radar (PALSAR) satellite images for the hot spot detection. Image fusion is emerging as a powerful tool where information of various sensors can be used for obtaining better results. For this purpose, vegetation greenness and roughness information which is obtained from MODIS and PALSAR satellite images, respectively, are used for fusion, and then, a contextual-based thresholding algorithm is applied to the fused image for hot spot detection. The proposed approach comprises of two steps: (1) application of genetic algorithm-based scheme for image fusion of MODIS and PALSAR satellite images, and (2) classification of the fused image as either hot spot or non-hot spot pixels by employing a contextual thresholding technique. The algorithm is tested over the Jharia Coal Field region of India, where hot spot is one of the major problems and it is observed that the proposed thresholding technique classifies the each pixel of the fused image into two categories: hot spot and non-hot spot and the proposed approach detects the hot spot with better accuracy and less false alarm.     

Bacterially-mediated weathering of crystalline and amorphous Cu-slags

Two types of Cu-slags (CS: crystalline massive slag and GS: granulated amorphous slag) exhibiting a different chemical and mineral phase composition were compared with respect to their susceptibility to bacterial weathering using Pseudomonas aeruginosa (n° CIP 105094). Abiotic conditions e.g. sterile growth medium and ultrapure water were used for comparison. The experiments were extended up to 112 days with a systematic liquid phase renewal every 14 days. The results revealed significant release of elements in the bacterially mediated weathering experiments. Concentrations of elements (Si, Fe, Cu, Zn and Pb) in the biotic solutions were increased at least by 20% up to 99% compared to abiotic ones. From 3 to 77% of the leached elements were associated to the fraction >0.22 μm. Scanning electron microscope observations demonstrated greater weathering of mineral phases in biotic experiments than in abiotic ones which is in accordance with the solution chemistry exhibiting higher concentrations of elements leached in biotic set-ups. In the case of CS, glass and sulfides weathering was yet observed in abiotic experiment, whereas partial dissolution of fayalite (Fe₂SiO₄) was solely affected by the presence of bacteria. GS having a higher bulk content of metallic elements was found to be more stable than sulfide-bearing CS, while its (GS) glass matrix was found to weather easier under biotic conditions.     

Contamination,bioaccessibility and human health risk of heavy metals in exposed-lawn soils from 28 urban parks in southern China's largest city,Guangzhou

The total concentrations and oral bioaccessibility of heavy metals in surface-exposed lawn soils from 28 urban parks in Guangzhou were investigated, and the health risks posed to humans were evaluated. The descending order of total heavy metal concentrations was Fe > Mn > Pb > Zn > Cu > Cr > Ni > Cd, but Cd showed the highest percentage bioaccessibility (75.96%). Principal component analysis showed that Grouped Cd, Pb, Cr, Ni, Cu and Zn, and grouped Cr and Mn could be controlled two different types of human sources. Whereas, Ni and Fe were controlled by both anthropogenic and natural sources. The carcinogenic risk probabilities for Pb and Cr to children and adults were under the acceptable level (<1 × 10⁻⁴). Hazard Quotient value for each metal and Hazard Index values for all metals studied indicated no significant risk of non-carcinogenic effects to children and adults in Guangzhou urban park soils.