Mapping fractional landscape soils and vegetation components from Hyperion satellite imagery using an unsupervised machine-learning workflow

An unsupervised machine-learning workflow is proposed for estimating fractional landscape soils and vegetation components from remotely sensed hyperspectral imagery. The workflow is applied to EO-1 Hyperion satellite imagery collected near Ibirací, Minas Gerais, Brazil. The proposed workflow includes subset feature selection, learning, and estimation algorithms. Network training with landscape feature class realizations provide a hypersurface from which to estimate mixtures of soil (e.g. 0.5 exceedance for pixels: 75% clay-rich Nitisols, 15% iron-rich Latosols, and 1% quartz-rich Arenosols) and vegetation (e.g. 0.5 exceedance for pixels: 4% Aspen-like trees, 7% Blackberry-like trees, 0% live grass, and 2% dead grass). The process correctly maps forests and iron-rich Latosols as being coincident with existing drainages, and correctly classifies the clay-rich Nitisols and grasses on the intervening hills. These classifications are independently corroborated visually (Google Earth) and quantitatively (random soil samples and crossplots of field spectra). Some mapping challenges are the underestimation of forest fractions and overestimation of soil fractions where steep valley shadows exist, and the under representation of classified grass in some dry areas of the Hyperion image. These preliminary results provide impetus for future hyperspectral studies involving airborne and satellite sensors with higher signal-to-noise and smaller footprints.     

A new spectral index for the extraction of built-up land features from Landsat 8 satellite imagery

Abstract

Extracting built-up areas from remote sensing data like Landsat 8 satellite is a challenge. We have investigated it by proposing a new index referred as built-up land features extraction index (BLFEI). The BLFEI index takes advantage of its simplicity and good separability between the four major component of urban system, namely built-up, barren, vegetation and water. The histogram overlap method and the spectral discrimination index (SDI) are used to study separability. BLFEI index uses the two bands of infrared shortwaves, the red and green bands of the visible spectrum. OLI imagery of Algiers, Algeria, was used to extract built-up areas through BLFEI and some new previously developed built-up indices used for comparison. The water areas are masked out leading to Otsu’s thresholding algorithm to automatically find the optimal value for extracting built-up land from waterless regions. BLFEI, the new index improved the separability by 25% and the accuracy by 5%.     

面向对象的高分辨率卫星影像道路信息提取

本文采用面向对象方法对高分辨率卫星影像道路信息提取。首先加入建筑物矢量数据对影像分割提取出建筑物,然后采用多尺度进行分割,对分割后的对象进行最近邻采样,得到总体分类图。最后根据道路特点构建道路知识库对道路信息优化。试验表明,面向对象的道路信息提取克服了"椒盐现象",取得了较好的提取效果。     

Problems of bias in mapping linear landforms from satellite imagery

Remotely sensed images are an important data source for the mapping of glacial landforms and the reconstruction of past glacial environments. However the results produced can differ depending on a wide range of factors related to the type of sensors used and the characteristics of the landforms being mapped. This paper uses a range of satellite imagery to explore the three main sources of variation in the mapped results: relative size, azimuth biasing and landform signal strength. Recommendations include the use of imagery illuminated with low solar elevation, although an awareness of the selective bias introduced by solar azimuth is necessary. Landsat ETM+ imagery meets the requirements for glacial landform mapping and is the recommended data source. However users may well have to consider alternative data in the form of SPOT, Landsat TM or Landsat MSS images. Digital elevation models should also be considered a valuable data source.     

On RPC model of satellite imagery

The RPC model has recently raised considerable interest in the photogrammetry and remote sensing community. The RPC is a generalized sensor model that is capable of achieving high approximation accuracy. Unfortunately, the computation of the parameters of RPC model is subject to the initial of the parameter in all available liteature. An algorithm for computation of parameters of RPC model without initial value is presented and tested on SPOT-5, CBERS-2, ERS-1 imageries. RPC model is suitable for both push-broom and SAR imagery.     

On RPC model of satellite imagery

IntroductionThe rational polynomial coefficient ( RPC)model is a generalized sensor model that is usedas an alternative solution for the rigorous sensormodel for IKONOS of the spacei maging. As thenumber of sensors increases along with greatercomplexity ,…     

月球卫星三线阵CCD影像EFP光束法空中三角测量

本文对月球卫星摄影三线阵CCD影像的EFP(等效框幅相片)光束法空中三角测量作两种处理:一是与现行摄影测量常用的将平差转到切面坐标系进行,二是在摄影测量坐标系内,长航线自由网EFP光束法平差利用三线CCD推扫特点,在EFP平差中增加对前、后视影像的相机主距的附加改正项,用以补偿由于球面曲率产生的前、后视影像比例尺的差异,平差得到的是平面基准的地面坐标及外方位元素的平差值。前者计算,数学上严格,但长航线要适当分段为切面处理;后者计算数学上有近似性,可方便地用于估算卫星姿态变化率,或作地面模型的几何反演等实验研究。利用嫦娥一号获取的第一条航线,并给出相应的结果。     

高分辨率卫星影像车辆检测的抗体网络

将车辆检测的过程视为一种“抗体”检测“危险抗原”的过程, 其中车辆是“危险抗原”, 车辆检测模板是“抗体”。利用一些车辆图像作为训练样本, 建立一种抗体网络学习并获取一组优化的“抗体”。这些“抗体”经过与待测影像的匹配, 实现对道路车辆目标的有效提取。采用0.6m分辨率的QuickBird全色数据进行实验, 实验结果验证了该方法的有效性和可行性。     

应用预测滤波估计卫星姿态

本文推导了预测滤波法的基本原理,应用了预测滤波作为卫星姿态状态预报算法,并与经典卡尔曼滤波进行了比较。实验表明采用预测滤波法对不同姿态角均能得出较好的估计结果,克服了经典卡尔曼滤波法进行估计存在的估计模型误差和推广卡尔曼滤波(EKF)的线性化误差。     

Quantifying the building stock from optical high-resolution satellite imagery for assessing disaster risk

This study uses high-resolution (HR) satellite imagery to quantify the stock of buildings, referred herein as building stock. The risk assessment requires information on the natural hazards and on the element at risk, that is the building stock in this article. This study combines (1) texture-based image processing to map built-up areas, (2) statistical sampling that allows locating the building samples and (3) photo-interpretation to encoding building footprints. Statistical inference is then used to quantify the building stock per class of building size. Legaspi in the Philippines is used as a case study. The results show that texture-based computer algorithms provide accurate area estimations of the built-up, that the detail of HR imagery allows the mapping of single buildings using photo-interpretation, and that a systematic sampling approach that uses building encoding and built-up maps can be used to quantify the building stock.     

高分辨率遥感影像城中村提取的景观语义指数方法

城中村是中国一类特殊的非正式居民区。本文从城中村的物理特点出发,采用景观语义指数描述复杂的城中村场景,提出基于景观语义指数的高分辨率遥感影像城中村提取方法,并采用“分类置信度-反馈”机制进行实际可操作的大范围城中村制图。以广州市核心城区为例,城中村检测的总体精度达到了90%以上。试验结果表明相对于传统的光谱、纹理特征,景观语义指数能够更好地描述城中村的根本形态特点,更准确的城中村提取。此外,“分类置信度-反馈”机制能够充分参考机器学习的分类概率,以有限的人工干预生产更加准确的城中村制图产品。因此,本文方法能够有效应用于大范围的城中村提取与制图。     

多条带WorldView卫星图像几何定位精度分析

本文针对多个条带WorldView卫星图像,研究了基于有理函数模型的附加参数区域网平差方法,对高分辨率卫星图像定位精度进行了详细分析。青海地区WorldView卫星图像试验结果表明:无地面控制点时,多条带整体区域网定位结果优于各个条带单独平差结果,区域网平差方法结果优于直接前方交会方法;有地面控制点时,多条带区域网平差结果与各个条带单独平差结果相当,且沿路线不大于10km布设一个地面控制点,其精度可满足1∶2000比例尺加密精度要求,可用于公路初步设计。     

Interpretation of satellite imagery for delineation of ravines

Ravines have a vast agricultural potential Survey of ravines has attracted the attention of the Photo-interpreters for quite sometime. LANDSAT, imagery offer a new scope in this field. Study of a LANDSAT imagery was made in order to find out the possibility of delineating broad reclamation units and their areal extent. Pattern analysis with visual interpretation shows that ravines could be classified into at least four reclamation units which could be useful for planning purposes.     

基于深度学习的高分四号卫星图像超分辨率重建

针对高分四号卫星图像中波红外谱段空间分辨率远低于相应的可见光近红外谱段,提出一种基于深度学习的高分四号卫星图像中波红外谱段超分辨率重建方法。首先,设计卷积回归网络进行初步重建,利用8倍下采样的可见光近红外谱段和原始中波红外谱段训练回归网络。然后,设计卷积重建网络进行进一步重建,利用低分辨率初步重建结果和原始中波红外谱段训练重建网络。最后,将原始可见光近红外谱段依次输入到训练好的回归网络和重建网络,得到最终的中波红外谱段超分辨率重建结果。以湖北和江西部分地区真实数据进行试验,结果表明该方法能有效提高中波红外谱段空间分辨率,与其他方法对比均方根误差至少下降了7.54,且目视效果更清晰自然,有利于扩展高分四号卫星的应用范围。     

附加视线向量修正的卫星影像区域网平差

针对传统有理函数模型(RFM)区域网平差方法局限于姿态和轨道测量误差小、相机视场角小及影像交会角良好的情况,提出了附加视线向量修正的卫星影像区域网平差方法。首先利用影像附带的有理多项式系数(RPC)计算出像元视线向量,其次根据该视线向量恢复成像时刻虚拟位置和姿态信息,然后对恢复的虚拟位置和姿态构建误差补偿模型,最后通过最小二乘方法整体解算模型参数和连接点物方坐标。该方法从系统误差产生的原因构建补偿模型,可以规避传统区域网平差方法的近似假设和条件限制。通过对模拟数据以及多套测绘卫星和非测绘卫星数据进行试验的结果表明,该方法处理大姿态角误差、大视场角以及弱交会角等各种严苛条件下的卫星影像能达到比传统方法更好的效果。     

Agriculture field characterization using aerial photograph and satellite imagery

Successfully delineating management zones that differ in crop productivity is an important component of site-specific management. We compared the effectiveness of the digitally scanned color aerial infrared photographs and digital Landsat Thematic Mapper (TM) data for delineating within-field zones. The zones delineated using normalized difference vegetation index (NDVI) from TM data explained 34% of field yield variance compared with 9% for that from digitally scanned color aerial infrared photograph data. The zones from NDVI using Landsat TM were better able to capture spatial differences in plant growth and relatively stable soil attribute of surface soil organic carbon.     

Prevalence of the terrain reversal effect in satellite imagery

The terrain reversal effect is a perceptual phenomenon which causes an illusion in various 3D geographic visualizations where landforms appear inverted, e.g. we perceive valleys as ridges and vice versa. Given that such displays are important for spatio-visual analysis, this illusion can lead to critical mistakes in interpreting the terrain. However, it is currently undocumented how commonly this effect is experienced. In this paper, we study the prevalence of the terrain reversal effect in satellite imagery through a two-stage online user experiment. The experiment was conducted with the participation of a diverse and relatively large population (n = 535). Participants were asked to identify landforms (valley or ridge?) or judge a 3D spatial relationship (is A higher than B?). When the images were rotated by 180°, the results were reversed. In a control task with ‘illusion-free’ original images, people were successful in identifying landforms, yet a very strong illusion occurred when these images were rotated 180°. Our findings demonstrate that the illusion is acutely present; thus, we need a better understanding of the problem and its solutions. Additionally, the results caution us that in an interactive environment where people can rotate the display, we might be introducing a severe perceptual problem.     

Sentinel-3卫星双角度热红外数据的流域尺度地表蒸散发估算与验证

双层能量平衡模型TSEB(Two Source Energy Balance)常用于地表蒸散发的估算研究,对于干旱半干旱流域的水资源调控以及利用有着十分重要的意义.本文在流域尺度上分别利用Sentinel-3双角度观测热红外和近红外数据反演的地表温度LST (Land Surfacer Temperature)和地表组...