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利用MODIS可见光通道气溶胶光学厚度的卫星遥感和523 nm波长微脉冲激光雷达 (MPL LIDAR) 对气溶胶消光系数垂直分布的观测，分析了珠江三角洲地区2003年6月一次气溶胶污染过程中气溶胶光学厚度的分布特征、气溶胶消光系数廓线的演变，认为这次污染过程是弱高压控制下的区域性污染，而香港地区污染物浓度的上升与区域性输送有直接关系，结果表明卫星和激光雷达的光学遥感方法提供了研究大气污染的可行手段。 相似文献
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ABSTRACTForest fires can change forest structure and composition, and low-density Airborne Laser Scanning (ALS) can be a valuable tool for evaluating post-fire vegetation response. The aim of this study is to analyze the structural diversity differences in Mediterranean Pinus halepensis Mill. forests affected by wildfires on different dates from 1986 to 2009. Several types of ALS metrics, such as the Light Detection and Ranging (LiDAR) Height Diversity Index (LHDI), the LiDAR Height Evenness Index (LHEI), and vertical and horizontal continuity of vegetation, as well as topographic metrics, were obtained in raster format from low point density data. In order to map burned and unburned areas, differentiate fire occurrence dates, and distinguish between old and more recent fires, a sample of pixels was previously selected to assess the existence of differences in forest structure using the Kruskal–Wallis test. Then, k-nearest neighbors algorithm (k-NN), support vector machine (SVM) and random forest (RF) classifiers were compared to select the most accurate technique. The results showed that, in more recent fires, around 70% of the laser returns came from grass and shrub layers, yielding low LHDI and LHEI values (0.37–0.65 and 0.28–0.46, respectively). In contrast, the areas burned more than 20 years ago had higher LHDI and LHEI values due to the growth of the shrub and tree strata. The classification of burned and unburned areas yielded an overall accuracy of 89.64% using the RF method. SVM was the best classifier for identifying the structural differences between fires occurring on different dates, with an overall accuracy of 68.79%. Furthermore, SVM yielded an overall accuracy of 75.49% for the classification between old and more recent fires. 相似文献
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Airborne hyperspectral data and airborne laserscan or LIDAR data were applied to analyse the sediment transport and the beach morphodynamics along the Belgian shoreline. Between 2000 and 2004, four airborne acquisitions were performed with both types of sensor. The hyperspectral data were classified into seven sand type classes following a supervised classification approach, in which feature selection served to reduce the number of bands in the hyperspectral data. The seven classes allowed us to analyse the spatial dynamics of specific sediment volumes. The technique made it possible to distinguish the sand used for berm replenishment works or for beach nourishments from the sand naturally found on the backshore and the foreshore. Subtracting sequential DTMs (digital terrain models) resulted in height difference maps indicating the erosion and accretion zones. The combination of both data types, hyperspectral data and LIDAR data, provides a powerful tool, suited to analyse the dynamics of sandy shorelines. The technique was demonstrated on three sites along the Belgian shoreline: Koksijde, located on the West Coast and characterized by wide accretional beaches, influenced by dry berm replenishment works and the construction of groins; Zeebrugge, on the Middle Coast, where a beach nourishment was executed one year before the acquisitions started and where the dams of the harbour of Zeebrugge are responsible for the formation of a large accretional beach, and Knokke‐Heist, located on the East Coast and characterized by narrow, locally reflective, beaches, heavily influenced by nourishment activities. The methodology applied allowed retrieval of the main sediment transport directions as well as the amount of sediment transported. It proved to be specifically suited to follow up the redistribution and the re‐sorting of the fill in beach nourishment areas. Copyright © 2007 John Wiley & Sons, Ltd. 相似文献
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This paper describes recent efforts that incorporate remote sensing techniques and platforms into geotechnical earthquake reconnaissance to document damage patterns, collect three-dimensional geometries of failures, and measure ground movements. The most-commonly used remote sensing techniques in geotechnical engineering (satellite imagery and LIDAR), as well as unmanned aerial vehicles (UAV), are introduced and recent case histories of the use of these techniques in reconnaissance efforts are provided. These examples demonstrate the potential for remote sensing to improve our understanding of geotechnical effects both at a regional scale and at a local level. The use of remote sensing to measure ground movements is particularly noteworthy and has the potential to provide data sets that will improve our ability to quantitatively predict the consequences of liquefaction and landslides. However, to realize this potential, investments must be made in collecting appropriate pre-earthquake data. 相似文献