Lidar遥感基本原理及其发展

介绍了航空激光扫描(Airborne laser scanning)或者Lidar遥感信息获取系统的基本原理、系统的组成、数据获取的方法及其步骤;对近数十年来应用激光扫描遥感信息获取地形表面模型方面取得的主要成果、应用现状做了简要回顾和评述;结合GIS和影像融合方法对Lidar遥感技术未来发展趋势进行了展望。     

“雷达干涉测量”课程教学设计与实践

雷达干涉测量作为遥感对地观测领域中的热点学科,受到测绘、地质、矿业、水利、国土资源、航空航天、地震等各行各业的广泛关注。为了适应科技发展对雷达干涉测量高级人才的需求,许多高校开设了或即将开设“雷达干涉测量”等相关课程。结合东北大学在“雷达干涉测量”课程教学及实践中的经验,围绕课程教学设计、教学方法、教学实践中遇到的问题及解决方案等方面进行了详细探讨,为促进高素质雷达遥感人才培养工作贡献力量。     

高光谱和LiDAR联合反演森林生物量研究

估算森林地上生物量(AGB)对于全球实现碳中和目标至关重要。本文以美国缅因州Howland森林为研究区域,借助地面实测样地数据,对比分析协同不同数据源(高光谱和LiDAR)和机器学习算法(随机森林、支持向量机、梯度提升决策树和K最邻近回归)的研究,以改善Howland森林的生物量估计精度。结果表明,采用LiDAR和高光谱植被指数变量模型的最佳精度分别为0.874和0.868,协同高光谱和LiDAR变量并采用梯度提升决策树回归模型的精度为0.927,即多源遥感数据要优于单一数据源。高光谱和LiDAR数据的协同使用对于提高类似于Howland地区或更广泛区域的生物量估计的准确性,具有普遍的适用性与一定的应用前景。     

The negative alpha filter: a new Processing technique for polarimetric SAR interferometry

In this letter we develop a new concept, the negative alpha filter, which we suggest has application for quantitative estimation of surface parameters beneath vegetation using polarimetric synthetic aperture radar (SAR) interferometry (POLInSAR). We first derive the filter and then validate it using simulations of L-band coherent forest scattering. We then show initial results of applying the filter to airborne data from the German Aerospace Center's E-SAR L-band sensor.     

A survey of remote sensing-based aboveground biomass estimation methods in forest ecosystems

Remote sensing-based methods of aboveground biomass (AGB) estimation in forest ecosystems have gained increased attention, and substantial research has been conducted in the past three decades. This paper provides a survey of current biomass estimation methods using remote sensing data and discusses four critical issues – collection of field-based biomass reference data, extraction and selection of suitable variables from remote sensing data, identification of proper algorithms to develop biomass estimation models, and uncertainty analysis to refine the estimation procedure. Additionally, we discuss the impacts of scales on biomass estimation performance and describe a general biomass estimation procedure. Although optical sensor and radar data have been primary sources for AGB estimation, data saturation is an important factor resulting in estimation uncertainty. LIght Detection and Ranging (lidar) can remove data saturation, but limited availability of lidar data prevents its extensive application. This literature survey has indicated the limitations of using single-sensor data for biomass estimation and the importance of integrating multi-sensor/scale remote sensing data to produce accurate estimates over large areas. More research is needed to extract a vertical vegetation structure (e.g. canopy height) from interferometry synthetic aperture radar (InSAR) or optical stereo images to incorporate it into horizontal structures (e.g. canopy cover) in biomass estimation modeling.     

利用极化合成孔径雷达干涉测量技术生成DEM

极化合成孔径雷达干涉测量(PolInSAR)是目前雷达遥感的前沿领域之一,它综合了极化和雷达干涉技术(InSAR)的特点.文中应用极化干涉相干最优化技术处理了Amazon雨林地区的真实L波段PALSAR全极化数据,得到该地区的数字高程模型(DEM).与常规的单极化InSAR技术进行对比,证明了利用极化干涉技术可以显著提...     

激光扫描测高技术的发展与现状

回顾了机载激光扫描测高技术的发展历史，总结了当前国内外的研究现状，展望了今后发展趋势及应用前景，并指出了机载激光扫描测高目前还有待于进一步解决的关键问题，最后对我国发展研究应用这一技术提出了若干建议。     

无人机机载合成孔径雷达冰情凌汛监测应用研究

黄河河段特殊的地理位置和气候条件造成每年季节性的冰凌灾害,利用传统监测手段在夜间监测具有许多困难。随着无人机机载微型化合成孔径雷达(MiniSAR)技术发展,使得全天时、全天候航空遥感监测成为可能。本文通过对无人机机载合成孔径雷达监测系统集成构建,利用该套系统验证了黄河冰情凌汛应急监测的适用性,最后指出了无人机机载合成孔径雷达在行业应用中的推广价值。     

Assessing the performance of two unsupervised dimensionality reduction techniques on hyperspectral APEX data for high resolution urban land-cover mapping

Despite the high richness of information content provided by airborne hyperspectral data, detailed urban land-cover mapping is still a challenging task. An important topic in hyperspectral remote sensing is the issue of high dimensionality, which is commonly addressed by dimensionality reduction techniques. While many studies focus on methodological developments in data reduction, less attention is paid to the assessment of the proposed methods in detailed urban hyperspectral land-cover mapping, using state-of-the-art image classification approaches. In this study we evaluate the potential of two unsupervised data reduction techniques, the Autoassociative Neural Network (AANN) and the BandClust method – the first a transformation based approach, the second a feature-selection based approach – for mapping of urban land cover at a high level of thematic detail, using an APEX 288-band hyperspectral dataset. Both methods were tested in combination with four state-of-the-art machine learning classifiers: Random Forest (RF), AdaBoost (ADB), the multiple layer perceptron (MLP), and support vector machines (SVM). When used in combination with a strong learner (MLP, SVM) BandClust produces classification accuracies similar to or higher than obtained with the full dataset, demonstrating the method’s capability of preserving critical spectral information, required for the classifier to successfully distinguish between the 22 urban land-cover classes defined in this study. In the AANN data reduction process, on the other hand, important spectral information seems to be compromised or lost, resulting in lower accuracies for three of the four classifiers tested. Detailed analysis of accuracies at class level confirms the superiority of the SVM/Bandclust combination for accurate urban land-cover mapping using a reduced hyperspectral dataset. This study also demonstrates the potential of the new APEX sensor data for detailed mapping of land cover in spatially and spectrally complex urban areas.     

In Search of the Statistical Properties of High-Resolution Polarimetric SAR Data for the Measurements of Forest Biomass Beyond the RCS Saturation Limits

The purpose of this letter is to present the results on the study of searching effective parameters that describe the relation between high-resolution synthetic aperture radar (SAR) images and forest parameters. The study is based on the non-Gaussian texture analysis of the polarimetric airborne Pi-SAR data over coniferous forests in Hokkaido, Japan. The radar cross section (RCS) in terms of a forest biomass is first analyzed. It is found that the L-band RCS increases steadily with the biomass and saturates at approximately 40 tons/ha. These results are similar to the previous studies. The probability density function of the image amplitude is then investigated, and among Rayleigh, log-normal, Weibull, and K-distributions, the K-distribution is found to fit best to the L-band data of all polarizations, although the Weibull distribution fits equally well. Further, the correlation between the tree biomass and the order parameter of the K-distribution in the cross-polarization images is found to be very high, and the order parameter increases consistently with the biomass to approximately 100 tons/ha, which is well beyond the saturation limit of the L-band RCS. Thus, the order parameter of the K-distribution can be a promising new parameter to estimate the forest biomass from high-resolution polarimetric SAR data in a much wider range than the conventional RCS method     

Estimates of forest structure parameters from GLAS data and multi-angle imaging spectrometer data

Quantitative estimates of forest vertical and spatial distribution using remote sensing technology play an important role in better understanding forest ecosystem function, forest carbon storage and the global carbon cycle. Although most remote sensing systems can provide horizontal distribution of canopies, information concerning the vertical distribution of canopies cannot be detected. Fortunately, laser radars have become available, such as GLAS (Geoscience laser altimeter system). Because laser radar can penetrate foliage, it is superior to other remote sensing technologies for detecting vertical forest structure and has higher accuracy. GLAS waveform data were used in this study to retrieve average tree height and biomass in a GLAS footprint area in Heilongjiang Province. However, GLAS data are not spatially continuous. To fill the gaps, MISR (multi- angle imaging spectrometer) spectral radiance was chosen to predict the regional continuous tree height by developing a multivariate linear regression model. We compared tree height estimated by the regression model and GLAS data. The results confirmed that estimates of tree height and biomass based on GLAS data are considerably more accurate than estimates based on traditional methods. The accuracy is approximately 90%. MISR can be used to estimate tree height in continuous areas with a robust regression model. The R², precision and root mean square error of the regression model were 0.8, 83% and 1 m, respectively. This study provides an important reference for mapping forest vertical parameters.     

InSAR林下地形测绘方法与研究进展

传统光学遥感技术手段在森林覆盖区难以准确获取林下地形,原因在于其只能测量森林冠层顶部高程。微波信号能够穿透森林冠层并记录森林垂直结构信息,为解决林下地形测绘难题带来了契机,如何准确获取林下地形已成为微波遥感领域的研究热点。首先介绍了面向林下地形测绘的合成孔径雷达（synthetic aperture radar,SAR）干涉测高原理及数据获取手段。然后对利用SAR进行林下地形测绘的方法进行了分类,主要包括基于合成孔径雷达干涉测量（interferometric synthetic aperture radar,InSAR）、极化合成孔径雷达干涉测量（polarimetric InSAR,PolInSAR）及基于多基线InSAR/PolInSAR数据的层析SAR（tomographic SAR,TomoSAR）技术的林下地形测绘方法,并介绍了上述3种方法的应用进展。最后在此基础上,从数据获取、误差改正及散射模型构建3个角度分析了林下地形测绘所面临的问题。     

相向飞行全极化SAR图像对建筑物的立体重构

用多方向飞行的全极化SAR图像可能提取特定三维目标的高度与位置信息,进而实现目标物的几何立体重构。全极化SAR图像数据与单极化SAR相比,可以选择多种极化组合数据,提供对于特定目标几何特征敏感的数据类型,通过多方向飞行SAR图像反演该目标或目标群的高度与位置信息。本文用两幅相向飞行的PI-SAR(日本机载极化与干涉SAR,X波段、1.5m分辨率)图像,提取日本仙台电视塔高度、日本东北大学建筑物群的立体重构。     

机载激光雷达技术的数据处理与4D产品制作

主要介绍了机载激光雷达的点云数据的获取、处理流程及其关键技术,并结合自己的工作经验详细阐述了运用点云数据制作4D产品的过程,预测未来遥感与GIS技术在数据获取方面的发展趋势,即借助机载激光雷达,再现真实三维场景。     

Tropical Dry Deciduous Forest Stand Variable Estimation Using SAR Data

Optical remote sensing data have been extensively used to derive biophysical properties that relate forest type and composition. However, stand density, stand height and stand volume cannot be estimated directly from optical remote sensing data owing to poor sensitivity between these parameters and spectral reflectance. The ability of microwave energy to penetrate within forest vegetation makes it possible to extract information on both the crown and trunk components from radar data. The type of polarization employed determines the radar response to the various shapes and orientations of the scattering mechanisms within the canopy or trunk. This study mainly presents experimental results obtained with airborne E-SAR using polarimetric C and L bands over the tropical dry deciduous forest of Chandrapur Forest Division, Maharashtra. A detailed documentation of the relationship between SAR C & L bands backscattering and forest stand variables has been provided in the present study through linear correlation. Linear correlation of the single channel SAR derived estimates with the field measured means show a good correlation between L HV backscattering coefficient with stand volume (r² = 0.71) and L HH backscattering coefficient with stand density (r² = 0.75). The results imply that SAR data has significant potential for stand menstruation in operational forestry.     

Tree species identification within an extensive forest area with diverse management regimes using airborne hyperspectral data

Information on tree species composition is crucial in forest management and can be obtained using remote sensing. While the topic has been addressed frequently over the last years, the remote sensing-based identification of tree species across wide and complex forest areas is still sparse in the literature. Our study presents a tree species classification of a large fraction of the Białowieża Forest in Poland covering 62 000 ha and being subject to diverse management regimes. Key objectives were to obtain an accurate tree species map and to examine if the prevalent management strategy influences the classification results. Tree species classification was conducted based on airborne hyperspectral HySpex data. We applied an iterative Support Vector Machine classification and obtained a thematic map of 7 individual tree species (birch, oak, hornbeam, lime, alder, pine, spruce) and an additional class containing other broadleaves. Generally, the more heterogeneous the area was, the more errors we observed in the classification results. Managed forests were classified more accurately than reserves. Our findings indicate that mapping dominant tree species with airborne hyperspectral data can be accomplished also over large areas and that forest management and its effects on forest structure has an influence on classification accuracies and should be actively considered when progressing towards operational mapping of tree species composition.     

航空高光谱遥感区域成矿背景研究——以甘肃柳园-方山口地区为例

高光谱遥感是当前地质遥感研究的前沿和热点,国内外的相关研究集中在数据处理、矿物填图、模型构建等方面,利用航空高光谱遥感技术进行区域成矿背景的研究较少。然而,要解决好高光谱遥感找矿问题,首先必须研究区域成矿背景,特别是找矿方向和有利的找矿区段,否则构建的找矿模型将不能充分发挥作用。本文以核工业北京地质研究院国家级遥感重点实验室装备的航空高光谱成像系统在甘肃柳园—方山口地区获取的可见光-近红外(CASI),短波红外(SASI)高光谱遥感数据为数据源,利用矿物填图方法所填的区域矿物分布图,探讨了柳园—方山口地区的区域成矿条件,厘定了找矿要素,构建了区域成矿构造格架,分析了区域已知矿产的空间分布规律,探索了该区的区域找矿方向和最佳找矿地段。在此基础上,利用建立的高光谱遥感找矿预测方法,新发现了7处找矿靶区,取得了显著的地质找矿效果。该成果不仅对指导柳园—方山口地区进一步找矿有重要作用,而且提出的一套高光谱遥感技术研究区域成矿背景的思路、途径和方法,对其他地区的高光谱遥感地质应用也具有重要的借鉴价值。     

极化干涉SAR森林高度反演方法研究

在分析随机体散射体/地表二层(RVoG)散射模型的基础上,利用德国宇航局机载SAR系统(ESAR)获取的POLInSAR数据和森林高度地面观测数据,对多种已有的森林高度反演模型进行了比较评价,从物理机制上对试验结果进行了分析、解释,进而发展了一种基于极化相干优化和非体散射去相干补偿的综合反演方法,实验结果表明,基于该方法的树高反演效果总体上优于其他方法。     

Predicting biomass dynamics at the national extent from digital aerial photogrammetry

The demand for precise mapping and monitoring of forest resources, such as above ground biomass (AGB), has increased rapidly. National accounting and monitoring of AGB requires regularly updated information based on consistent methods. While remote sensing technologies such as airborne laser scanning (ALS) and digital aerial photogrammetry (DAP) have been shown to deliver the necessary 3D spatial data for AGB mapping, the capacity of repeat acquisition, remotely sensed, vegetation structure data for AGB monitoring has received less attention. Here, we use vegetation height models (VHMs) derived from repeat acquisition DAP data (with ALS terrain correction) to map and monitor woody AGB dynamics across Switzerland over 35 years (1983-2017 inclusive), using a linear least-squares regression approach. We demonstrate a consistent relationship between canopy height derived from DAP and field-based NFI measures of woody AGB across four inventory periods. Over the environmentally heterogeneous area of Switzerland, our models have a comparable predictive performance (R² = 0.54) to previous work predicting AGB based on ALS metrics. Pearson correlation coefficients between measured and predicted changes in woody AGB over time increased with shorter time gaps (< 2 years) between image capture and field-based measurements, ranging between 0.76 and 0.34. A close temporal match between field surveys and remote sensing data acquisition is thus key to reliable mapping and monitoring of AGB dynamics, especially in areas where forest management and natural disturbances trigger relatively fast canopy dynamics. We show that VHMs derived from repeat DAP capture constitute a cost effective and reliable approach to map and monitor changes in woody AGB at a national extent and can provide an important information source for national carbon accounting and monitoring of ecosystem service provisioning.     

高光谱数据在数据库中的高效存储技术研究

通过分析高光谱数据的特点 ,结合数据库系统开发实践 ,提出了高光谱数据集 ,包括图像、光谱、属性等 ,在关系数据库中的存储规范。结合ORACLE数据平台 ,提出了 3种高光谱数据的存储模式 ,并结合应用实例进行对比 ,分析了各自的优缺点以及适用条件。