Removing sun glint from optical remote sensing images of shallow rivers

Sun glint is the specular reflection of light from the water surface, which often causes unusually bright pixel values that can dominate fluvial remote sensing imagery and obscure the water‐leaving radiance signal of interest for mapping bathymetry, bottom type, or water column optical characteristics. Although sun glint is ubiquitous in fluvial remote sensing imagery, river‐specific methods for removing sun glint are not yet available. We show that existing sun glint‐removal methods developed for multispectral images of marine shallow water environments over‐correct shallow portions of fluvial remote sensing imagery resulting in regions of unreliable data along channel margins. We build on existing marine glint‐removal methods to develop a river‐specific technique that removes sun glint from shallow areas of the channel without over‐correction by accounting for non‐negligible water‐leaving near‐infrared radiance. This new sun glint‐removal method can improve the accuracy of spectrally‐based depth retrieval in cases where sun glint dominates the at‐sensor radiance. For an example image of the gravel‐bed Snake River, Wyoming, USA, observed‐versus‐predicted R² values for depth retrieval improved from 0.66 to 0.76 following sun glint removal. The methodology presented here is straightforward to implement and could be incorporated into image processing workflows for multispectral images that include a near‐infrared band. Copyright © 2016 John Wiley & Sons, Ltd.     

Application of remote sensing to forest hydrology

The paper reviews the application of remote sensing to forest hydrology. After discussing the general advantages and disadvantages of satellite remote sensing, the estimation of precipitation, changes in soil moisture, runoff, radiation components, sensible heat flux, latent heat flux, soil heat flux, changes in energy storage in biomass, primary production and monitoring the extent, type and density of forests are reviewed. Finally, the paper looks forward to future developments and concludes that these are likely to come from the use of multitemporal data, combined analysis of different types of remotely sensed data and of remotely sensed and ground data, improved image analysis techniques and combining satellite data with models.     

基于遥感影像的区域景观格局分析

以资源丰富的南京市浦口区35个村庄为研究对象,基于遥感影像、地理信息技术以及景观生态学理论,分析并揭示区域景观格局演变特征.结合浦口区分村域的景观资源利用指数、资源利用类型指数、居民聚集指数以及产业结构指数构建乡村发展模式.研究结果表明:浦口区域乡村景观格局的变化特征较为明显,呈现出CL景观的快速缩减;研究区的景观格局在人类活动作用下,斑块聚集度增强,多样性指数及均匀度指数均为持续上升,各个景观类型在研究区域表现趋于稳定;最后,根据村域指数分布结果和区域景观资源分布情况,提出生态有机农业型、生态休闲旅游型、生态科学技术型3种发展模式,为促进区域乡村可持续发展提供了科学依据,同时对我国乡村规划建设具有重要的理论意义.     

我国高分辨率遥感技术在地震研究中的应用

本文概述了我国高分辨率遥感技术在地震监测预报、灾害预防和应急救援防震减灾三大业务体系中的应用现状,重点介绍了“高分遥感地震监测与应急应用示范”项目的进展.该项目针对防震减灾业务体系发展的应用需求,在整合地震行业现有技术和资源的基础上,突破了高分辨率对地观测系统卫星遥感数据在地震构造调查、地震监测和地震应急救援等方面应用的关键技术,制定行业应用规范,建设高分遥感地震业务应用示范系统,并开展应用示范.该项目的成功实施,使得我国高分辨率遥感技术在地震中的应用从以往分散的科学研究提升到一个业务化应用的状态,从而能更加有效地服务于防震减灾工作.      

基于单亲遗传算法的SAR图像混合像元分解

已有的遥感影像混合像元分解理论方法都要求遥感影像的通道数目大于地物种类,而合成孔径雷达(SAR)的自身特点决定了SAR图像不可能有过多的通道数目,为解决SAR图像地物种类大于通道数目情况下的混合像元分解问题,本文基于单亲遗传算法提出了一种新的混合像元分解方法,创建了一种新的染色体编码方式及进化迭代方式,新算法很好地实现混合像元的分解,可以分解出比通道数目更多的地物种类.并从北京地区ENVISAT-ASAR图像中截取天安门附近区域作为数据源进行实验,实验结果表明了本文算法的正确性和有效性.     

基于Contourlet变换和ICA的多时相遥感图像变化检测

为了提高多时相遥感图像变化检测的精确度和运算效率,本文提出了一种基于Contourlet变换和独立分量分析(ICA-Independent component analysis)的变化检测算法.利用Contourlet变换多尺度、多方向性和各向异性等性质,对图像数据进行多尺度分解,再对分解后的数据进行独立分量分析,利用改进的基于牛顿迭代的固定点ICA算法分离出互相独立的数据分量,然后将分离后的数据分量转变成图像分量,最终对变化图像分量经阈值分割实现变化检测.实验结果表明,与现有的基于PCA、基于ICA、基于小波变换与ICA三种变化检测算法相比,本文算法能有效地分离出变化信息,减少了计算的复杂性,得到的变化图像具有更高的精确度,且对背景有较强的稳健性.     

城市湖泊时空演变的遥感分析——以武汉市为例

在GIS技术支持下,以多时相Landsat TM/ETM 遥感影像为数据源,利用NDWI指数提取武汉市1991年、1995年、2000年、2002年的湖泊水域面积信息,引入湖泊萎缩强度等测度指标,从时空两方面对主城区湖泊水域变化和26个主要湖泊的发展演化特征进行了系统地分析.结果表明,从1991年到2002年,武汉市主城区湖泊水域面积急剧减少,达38.67km2;主要湖泊水域的面积变化具有时空分异特征,湖泊萎缩变化与湖泊所处地区的城市建设水平、道路交通规划、政策导向等因素密切相关.分析认为,城市湖泊转变为公园后,萎缩现象得到明显遏制,通过立法加强湖泊保护力度并尽早制定城市湖泊的规划管理措施,是保护武汉幸存湖泊的有力手段.     

北京城市热岛的时空变化分析

利用1987、1999、2000、2001、2002和2005年六幅陆地卫星影像研究北京市规划区地表城市热岛（SUHI）．首先用决策树分类法进行分类,得到六幅不同时相的土地利用／覆盖分类图像．根据Artis＆Carnahan算法利用热红外通道的灰度值计算地表辐射亮温,基于分类结果进行比辐射率纠正,计算地表温度．通过分析北京市规划区1987～2005年间地表城市热岛的特征,发现不同土地利用／土地覆盖类型与地表城市热岛有密切关系;2001年、2002年和2005年影像中市区的热岛分布的破碎度增加,由原来的集中分布慢慢向周围扩散,并在市区中心植被覆盖高的区域出现蓝色“凉爽”区;地表城市热岛增加的区域与城市扩展区域一致,城市化过程是城市热岛面积不断增加的主要的原因．     

遥感技术在地震研究中的应用进展

本文介绍了遥感技术在地震监测和研究中的应用和进展,分析了卫星热红外遥感、InSAR技术和气体遥感方法在地震前后地表热红外增温、形变和气体含量改变的研究现状,初步探讨了该方法的成因机制.本文同时分析了该技术在地震预报中存在的问题,提出了未来的研究重点.     

Application of effective medium approximation theory to ocean remote sensing under wave breaking

Based on the effective medium approximation theory of composites, the empirical model proposed by Pandey and Kakar is remedied to investigate the microwave emissivity of sea surface under wave breaking driven by strong wind. In the improved model, the effects of seawater bubbles, droplets and difference in temperature of air and sea interface (DTAS) on the emissivity of sea surface covered by whitecaps are discussed. The model results indicate that the effective emissivity of sea surface in-creases with DTAS increasing, and the impacts of bubble structures and thickness of whitecaps layer on the emissivity are included in the model by introducing the effective dielectric constant of whitecaps layer. Moreover, a good agreement is obtained by comparing the model results with the Rose’s ex-perimental data.     

丽江地区遥感影像线环结构特征与场地稳定性分析

丽江地区活动性构造发育,地震发生频繁。以遥感影像线环结构理论论述了该区主要活动断裂和活动环块的遥感影像特征和地质地貌特征,并分析活动构造与场地稳定性的关系,进而划分出该区内易发震地区与相对稳定的地区。     

向导式遥感震害评估系统研制

依托国家科技支撑计划重点项目子专题,在总结、归纳已有震害评估系统处理方式、流程及优缺点的前提下,研究了符合实际工作状况的遥感震害评估系统.该系统集成了基于ENVI/IDL、ERDAS开发的影像处理模块,可辅助提取高分辨率遥感影像中房屋倒塌、道路损毁、滑坡、泥石流、堰塞湖等震害信息.尤其是面向对象分类模块,对遥感影像各种特征进行了综合处理.基于ArcEngine开发的空间数据管理与分析模块,可处理道路空间位置分布、地震烈度划分、行政区划及属性等信息.并实现了对各模块向导式的流程化调用,有效提高了震后灾害评估工作的效率.该系统已在地震应急工作中发挥了有力的作用.     

A classification method of building structures based on multi-feature fusion of UAV remote sensing images

In order to improve the accuracy of building structure identification using remote sensing images, a building structure classification method based on multi-feature fusion of UAV remote sensing image is proposed in this paper. Three identification approaches of remote sensing images are integrated in this method: object-oriented, texture feature, and digital elevation based on DSM and DEM. So RGB threshold classification method is used to classify the identification results. The accuracy of building structure classification based on each feature and the multi-feature fusion are compared and analyzed. The results show that the building structure classification method is feasible and can accurately identify the structures in large-area remote sensing images.     

Quality assessment from a hydrological perspective of a digital elevation model derived from WorldView-2 remote sensing data

Abstract

A digital elevation model (DEM) derived from a stereo pair of WorldView-2 (WV-2) images was assessed against ground-truth GPS point datasets. Two assessment methods were used: (a) vertical accuracy assessment and (b) hydrological assessment of surface runoff variables. Three agricultural plots with different topographic slopes were selected to perform a vertical accuracy assessment, followed by a comparative assessment of a set of hydrological variables. The results show an overall vertical accuracy of 0.45 m, confirming the potential of WV-2 stereo images to extract elevation information at high spatial resolution. Concerning plot-scale micro-topographic features, the WV-2 DEM performed better on the plot with rolling slopes (5–10%), extracting variables such as the total length and drainage area of flow paths with relative errors lower than 20%. However, some limitations were detected in the extraction of variables such as terrain slope, drainage points of flow paths and terrain depressions in areas of flatter slopes (<5%).

Editor Z.W. Kundzewicz; Associate editor D. Gerten     

Application of ensemble kalman filter to geophysical parameters retrieval in remote sensing:A case study of kernel-driven BRDF model inversion

Remote sensing can provide multi-spatial resolution, multi-temporal resolution multi-spectral band and multi-angular data for the observation of land surface. At present, one of research focuses is how to make the best of these data to retrieve geophysical parameters in conjunction with their a priori knowledge and simul-taneously consider the influence of data uncertainties on inversion results[1-5]. The essence of remote sensing lies in inversion. It is difficult to precisely retrieve parame…     

基于无人机和卫星遥感影像的升金湖草滩植被地上生物量反演

湿地植被地上生物量是衡量湿地生态系统健康状况的重要指标,对于珍稀水禽越冬繁殖、全球碳循环、生态净化具有重要意义,是生态学与遥感解译的研究热点之一.针对于地上生物量的测算,卫星遥感数据覆盖范围广但其空间分辨率较低,无人机遥感数据空间分辨率高但采集范围小,同时受湿地面积、观测系统及外界环境等条件的影响,使得遥感影像地上生物量反演更加复杂和困难.本研究基于无人机和高分一号数据对升金湖草滩植被地上生物量反演进行研究,结合升金湖保护区4个样区无人机可见光影像与相应样区实测样本数据,建立地上生物量与可见光波段、多种可见光植被指数的线性、幂函数、多项式、对数回归模型,并通过可决系数（R²）、平均绝对误差（MAE）和均方根误差（RMSE）对模型进行精度评价,选择最优模型对无人机影像进行地上生物量反演;通过可见光波段反演得到的生物量,与高分一号WFV归一化差分植被指数（Normalized Difference Vegetation Index,NDVI）影像相结合进行回归建模,获取整个升金湖草滩植被地上生物量分布.结果表明,利用无人机红光波段建立的多项式方程对地上生物量反演有着最高模拟精度,R²=0.86、预测精度MAE=111.33 g/m²、RMSE=145.42 g/m²,且红光波段生物量反演方法得到的结果与实际生物量分布一致性较高,高分一号WFV NDVI与无人机反演生物量构建的多项式模型为最优模型,R²为0.91.本研究利用无人机和高分一号数据进行生物量反演研究,整合多源遥感数据优点,以获取更加丰富和准确的信息,进而提高地上生物量反演精度,为湿地监测和湿地恢复管理提供数据和技术支撑,具有重要研究意义和应用价值.     

Reconstruction of missing data in remote sensing images using conditional stochastic optimization with global geometric constraints

This paper addresses the issue of missing data reconstruction for partially sampled, two-dimensional, rectangular grid images of differentiable random fields. We introduce a stochastic gradient–curvature (GC) reconstruction method, which is based on the concept of a random field model defined by means of local interactions (constraints). The GC reconstruction method aims to match the gradient and curvature constraints for the entire grid with those of the sample using conditional Monte Carlo simulations that honor the sample values. The GC reconstruction method does not assume a parametric form for the underlying probability distribution of the data. It is also computationally efficient and requires minimal user input, properties that make it suitable for automated processing of large data sets (e.g. remotely sensed images). The GC reconstruction performance is compared with established classification and interpolation methods for both synthetic and real world data. The impact of various factors such as domain size, degree of thinning, discretization, initialization, correlation properties, and noise on GC reconstruction performance are investigated by means of simulated random field realizations. An assessment of GC reconstruction performance on real data is conducted by removing randomly selected and contiguous groups of points from satellite rainfall data and an image of the lunar surface.     

On the remote sensing of plasma sheet from low-altitude spacecraft

The possibility to estimate plasma sheet parameters from low-altitude measurements looks quite attractive, but it critically depends on how isotropic the plasma pressure is in the flux tube. To evaluate the ion pressure anisotropy we compare the values of pressure in the ionospheric and equatorial parts of the field line. Ionospheric values were computed from proton measurements at NOAA low-altitude satellites, they were compared with pressure estimates computed from empirical magnetic field models as well as with average values known from direct plasma sheet measurements. Three different methods of mapping the plasma pressure from plasma sheet to low altitude have been tried; each uses the particle isotropic boundaries observed at low altitudes and/or computed from magnetospheric models. Excluding observations obtained during substorm expansion, from these comparisons we conclude that in the plasma sheet, at geocentric distances 9–20R_E, the pressure estimates in the ionospheric and equatorial parts of the plasma sheet flux tube agree very well, suggesting a good pressure isotropy and thus justifying a possibility to monitor the plasma sheet parameters based on low-altitude measurements. The results also illustrate the usefulness of isotropic boundaries as a label of tail current intensity and as reliable tool for establishing mapping between magnetosphere and ionosphere.     

An operational two-layer remote sensing model to estimate surface flux in regional scale: Physical background

Based on the improved interaction mechanism of two-layer model, this paper proposed Pixel Component Arranging and Comparing Algorithm (PCACA) and theoretically positioning algorithm, estimated the true temperature of mixed pixel in four extreme points in combination with the measurements of dry and wet points in calibration fields and improved the reliability of positioning dry and wet line. A new two-layer energy-separation algorithm was proposed,which was simple and direct without resistance network parameters for each pixel. We also proposed a new thought about the effect of advection. The albedo of mixed pixel was also separated with PCACA. In combination with two-layer energy-separation algorithm, the net radiation of mixed pixel was separated to overcome the uncertainty of conventional energy-separation algorithm using Beer's Law. Through the validation of retrieval result, this method is proved to be feasible and operational. At the same time, the uncertainty of this algorithm was objectively analyzed.