·推荐论文摘要·

程宇峰，金淑英，王密，等

·推荐论文摘要·

一种光学遥感卫星多相机成像系统的高精度影像拼接方法

程宇峰，金淑英，王密，等

提出一种基于虚拟大相机的光学遥感卫星多相机系统成像数据的拼接方法，实现多相机影像的高精度拼接。该方法根据各单相机的几何成像模型，构建虚拟大相机的几何成像模型；利用坐标正算、反算过程对各单相机影像进行间接法几何纠正，得到虚拟大相机图像坐标系下的各虚拟单相机影像；将各虚拟单相机影像基于影像坐标信息拼接处理后得到最终的虚拟大相机影像。该方法利用虚拟大相机实现多相机影像的高质量拼接，为后期处理提供了与之相对应的高精度有理函数模型，可用于不同数量、不同分辨率的多相机系统实现全自动智能地面预处理。

遥感；光学遥感卫星；高精度拼接；虚拟大相机；多相机系统；预处理

来源出版物：光学学报,2017,37(8): 0828003

联系邮箱：金淑英，jsy@whu.edu.cn

吉林一号轻型高分辨率遥感卫星光学成像技术

徐伟，金光，王家骐

摘要：为了实现吉林一号光学遥感卫星轻量化设计与高分辨率多光谱多模式成像，采用星载一体化设计理念及敏捷多模式成像策略，完成了吉林一号卫星的指标、方案及关键技术的设计与在轨多模式光学成像。吉林一号整星的质量为450 kg，有效载荷比高达40%，机动能力达2.1(°)/s，可实现大侧摆、同轨立体与条带拼接等多模式成像，结合星上800gB的FLASH存储能力和X波段双通道600 Mbps的数据传输能力，卫星每天可获取近150000km2的图像数据。吉林一号轻型高分辨率光学卫星于2015年发射入轨，运行在656km太阳同步轨道，地面全色和多光谱分辨率分别优于0.72 m和2.88 m，满足多行业应用及商业化运营的需求。

关键词：光学遥感；星载一体化；吉林一号；多模式成像；轻型高分辨

来源出版物：光学精密工程,2017,25(8):1969-1978

联系邮箱：徐伟，xwciomp@126.com

气溶胶卫星遥感产品在林火检测中的适用性

王研峰，张婕，章焕，等

摘要：森林火灾导致火点周围气溶胶光学厚度（AOD）发生显著变化，可利用MODIS气溶胶产品作为识别火点的辅助手段。通过对比火点周围MODIS C510km、C63km、C610km气溶胶产品的有效样本数、空间分布特征来评估不同版本气溶胶产品应用于火灾烟羽检测的可行性，同时对比在火点32方位角条件下AOD的积累效应对烟羽敏感性的差异。结果表明，MODIS C63km气溶胶产品能较准确地表征林火伴生的烟羽特征，C610km和C510km产品效果较差。C63km产品在以火点为中心，扩散半径为24km时，32方位角累积AOD比值对烟羽检测敏感，C510km和C610km产品对烟羽检测的敏感性较差。

关键词：气溶胶产品；林火检测；适用性

来源出版物：兰州大学学报：自然科学版,2017, 53(1):101-105

联系邮箱：王研峰，wangyanfeng_1986@163.com

卫星遥感地表温度降尺度的光谱归一化指数法

李小军，辛晓洲，江涛，等

摘要：针对卫星遥感技术监测地表温度（land surface temperature，LST）存在时空分辨率矛盾这一难题，以TsHARP温度降尺度算法为基础，根据地表覆盖类型的不同，分别选择与 LST相关性更好的光谱指数（归一化植被指数，NDVI；归一化建造指数，NDBI；改进的归一化水体指数，MNDWI；增强型裸土指数，EBSI）提出了新的转换模型，并从定性和定量两个角度评价了TsHARP法和新模型的降尺度精度。结果表明：两种模型在提高 LST空间分辨率的同时又能较好地保持MODIS LST影像热特征的空间分布格局，消除了原始1km影像中的马赛克效应，两种模型均能够达到较好的降尺度效果；全局尺度分析表明，不管是在降尺度结果的空间变异性还是精度方面，本文提出的模型（RMSE：1.635℃）均要优于 TsHARP法（RMSE：2.736℃）；TsHARP法在水体、裸地和建筑用地这些低植被覆盖区表现出较差的降尺度结果，尤其对于裸地和建筑用地更为明显（|MBE|＞3℃），新模型提高了低植被覆盖区地物的降尺度精度；不同季节的降尺度结果表明，两种模型都是夏、秋季的降尺度结果优于春、冬季，新模型的降尺度结果四季均好于TsHARP法，其中春、冬季的降尺度精度提升效果要优于夏、秋季。

关键词：MODIS；降尺度；地表温度；TsHARP算法；地表覆盖

来源出版物：测绘学报,2017, 46(3):353-361

基于能量最优的敏捷遥感卫星在轨任务规划

赵琳，王硕，郝勇，等

摘要：针对敏捷遥感卫星对多个离散观测点在轨自主任务规划问题，在考虑姿态运动方程耦合性的基础上，将问题分解为空间资源调度问题和连续最优控制问题，进而提出了一种结合伪谱法和遗传算法的混合求解算法。该算法针对基于行商问题（TSP）模型建立的空间资源调度问题模型，选用二维编码结构对观测顺序和相对观测时间进行实数编码，并采用遗传算法求解观测序列和观测时间；针对判断观测时间可行性时涉及的时间最优控制问题、以及姿态转移过程中涉及的最小能量消耗问题，将其归结为连续最优控制问题，并基于Gauss伪谱协态变量映射定理，采用Gauss伪谱法进行求解。通过与基于单纯遗传算法的规划算法进行对比试验，本文所提出的基于伪谱法和遗传算法的混合求解策略针对目标问题，在典型工况下姿态转移过程中能量消耗降低60%。

关键词：行商问题（TSP）；能量消耗；时间最优；遗传算法；Gauss伪谱法

来源出版物：航空学报,2017,38(6):202-220

联系邮箱：郝勇，haoyong@hrbeu.edu.cn

以SRTM-DEM为控制的光学卫星遥感立体影像正射纠正

张浩，张过，蒋永华，等

摘要：针对全球测图缺少统一的控制基准的问题，提出了利用 SRTM-DEM 作为控制基准，对光学卫星遥感影像进行正射纠正的方法。首先，对光学卫星影像构建的立体影像对进行自由网平差并制作 DEM；然后，以SRTM-DEM作为控制，将DEM作为单元模型，进行独立模型法DEM区域网平差，获得单元模型的定向参数；最后，改正立体影像的成像几何模型参数，进行正射纠正。选取湖北咸宁和江西某地两个测区的资源三号数据进行试验，试验结果表明，资源三号正视全色影像的平面定向精度由12.93像素提高到6.85像素。

关键词：全球测图；立体像对；独立模型法；DEM 区域网平差；影像定向精度

来源出版物：测绘学报,2016, 45(3):326G331-378

国产高分辨率遥感卫星影像自动云检测

谭凯，张永军，童心，等

摘要：云检测一直是卫星影像处理的难题，特别是混有地物光谱特性的薄云长期成为影像产品生产的阻碍。本文所介绍的国产高分辨率遥感卫星影像自动云检测方法能够有效克服这一难题。首先采用改进的颜色转换模型，将影像由RGB转换至HIS颜色空间，利用影像强度信息与饱和度信息生成基底图，并使用影像近红外与色调信息对其进行优化，生成修正图。然后利用直方图均衡化与双边滤波结合带限定条件的 Otsu阈值分割提取纹理信息，并对修正图进行误差剔除生成云种子图。最后以HIS颜色空间的强度信息为向导，结合云种子图进行云精确提取。与不同自动、人工交互式云检测方法相比，总体精度提高了10%左右，并且能够较好地提升云检测效率。

关键词：国产卫星影像；云检测；改进HIS模型；双边滤波；Otsu阈值分割

来源出版物：测绘学报,2016, 45(5): 581-591

遥感卫星影像K-SVD稀疏表示去噪

夏琴，邢帅，马东洋，等

摘要：常规的去噪方法在去除遥感卫星影像噪声时，往往会造成影像模糊和空间分辨率下降。本文将稀疏表示理论应用于遥感卫星影像去噪，提出了一种改进算法，能够保留低频信息不变，仅对影像的高频信息进行稀疏重建。算法核心是按照是否能够从过完备字典中选择较少原子进行稀疏表示的原则来区分高频信息中的有效信息和噪声。通过3组实验对改进算法与传统去噪方法进行对比检测，实验结果表明，改进算法在去除噪声的同时，能较好地突出影像的边缘和细节信息。

关键词：遥感影像；稀疏表示；去噪；K-SVD；质量评价

来源出版物：遥感学报,2016,20(3): 441-449

联系邮箱：夏琴，xianduan007@163.com

卫星遥感图像的鲁棒无损数据隐藏传输算法

朱厉洪，周诠

摘要：提出一种基于整数离散余弦变换（Int DCT）域的鲁棒无损数据隐藏算法。先对载体图像进行预处理来构建适合信息嵌入的载体，并将无损隐藏的思想引入到预处理中用以存储可恢复原载体图像的信息。为兼顾鲁棒性和图像质量，算法通过修改载体图像Int DCT域高频系数的直方图修改来完成秘密信息的嵌入；最后，与以往算法不同，为保证遥感图像的质量，给出了接收端在含密图像未失真和失真情况下载体恢复的方法。实验结果表明，本文所提出的算法能有效抵抗压缩攻击，并具有良好的图像质量和较大的容量。与以往算法相比，本文算法在性能方面具有明显的优势。

关键词：卫星遥感图像；无损数据；隐藏算法

来源出版物：宇航学报,2015,36(3):315-323

来源出版物：International Journal of Applied Earth Observation andgeoinformation,2017, 58:36-49

联系邮箱：Sun, QS; qingsong.sun@umb.edu

Application of satellite solar-induced chlorophyll fluorescence to understanding large-scale variations in vegetation phenology and function over northern high latitude forestsJeong, SJ; Schimel, D; Frankenberg, C; et al.

Abstract:This study evaluates the large-scale seasonal phenology and physiology of vegetation over northern high latitude forests (40°–55°N) during spring and fall by using remote sensing of solar-induced chlorophyll fluorescence(SIF), normalized difference vegetation index (NDVI) and observation-based estimate ofgross primary productivity(GPP) from2009 to2011. Based ongPP phenology estimation ingPP, thegrowing season determined by SIF time-series is shorter in length than thegrowing season length determined solely using NDVI. This is mainly due to the extended period of high NDVI values, as compared to SIF, by about 46 days (±11 days), indicating a large-scale seasonal decoupling of physiological activity and changes ingreenness in the fall. In addition to phenological timing, mean seasonal NDVI and SIF have different responses to temperature changes throughout thegrowing season. We observed that both NDVI and SIF linearly increased with temperature increases throughout the spring. However, in the fall, although NDVI linearly responded to temperature increases, SIF andgPP did not linearly increase with temperature increases, implying a seasonal hysteresis of SIF andgPP in response to temperature changes across boreal ecosystems throughout theirgrowing season. Seasonal hysteresis of vegetation at large-scales is consistent with the known phenomena that light limits boreal forest ecosystem productivity in the fall.Our results suggest that continuing measurements from satellite remote sensing of both SIF and NDVI can help to understand the differences between, and information carried by, seasonal variations vegetation structure andgreenness and physiology at large-scales across the critical boreal regions.

关键词：solar-induced chlorophyll fluorescence; SIF;NDVI;gPP; phenology; large-scale

来源出版物：Remote Sensing of Environment,2017,190:178-187

联系邮箱：Jeong, SJ; waterbell77@gmail.com

ESA’s Soil Moisture and Ocean Salinity mission:From science to operational applications

Mecklenburg, S; Drusch, M; Kaleschke, L; et al.

Abstract:The Soil Moisture and Ocean Salinity (SMOS)mission, launched in November2009, is the European Space Agency’s (ESA) second Earth Explorer Opportunity mission. The scientific objectives of the SMOS mission directly respond to the need forglobal observations of soil moisture and ocean salinity, two key variables used in predictive hydrological, oceanographic and atmospheric models. SMOS observations also provide information on vegetation, in particular plant available water and water content in a canopy, drought index and flood risks, surface ocean winds in storms, freeze/thaw state and sea ice and its effect on ocean–atmosphere heat fluxes and dynamics affecting large-scale processes of the Earth's climate system.Significant progress has been made over the course of the now 6-year life time of the SMOS mission in improving the ESA provided level1 brightness temperature and level2 soil moisture and sea surface salinity data products. The main emphasis of this paper is to review the status of the mission and provide an overview and performance assessment of SMOS data products, in particular with a view towards operational applications, and using SMOS products in data assimilation. SMOS is in excellent technical condition with no limiting factors for operations beyond2017. The instrument performance fulfils the requirements. The radiofrequency interference (RFI) contamination originates from man-made emitters onground, operating in the protected L-band and adding signal to the natural radiation emitted by the Earth. RFI has been detected worldwide and has been significantly reduced in Europe and the Americas but remains a constraint in Asia and the Middle East. The mission’s scientific objectives have been reached over land and are approaching the mission objectives over ocean. This review paper aims to provide an introduction and synthesis to the papers published in this RSE special issue on SMOS.

关键词：Soil Moisture and Ocean Salinity (SMOS)mission; sea surface salinity; soil moisture

来源出版物：Remote Sensing of Environment,2016,180:3-18

联系邮箱：Mecklenburg, S; susanne.mecklenburg@esa.int

Ship detection in spaceborne optical image with SVD networks

Zou, ZX; Shi, ZW

Abstract:Automatic ship detection on spaceborne optical images is a challenging task, which has attracted wide attention due to its extensive potential applications in maritime security and traffic control. Although some optical image ship detection methods have been proposed in recent years, there are still three obstacles in this task:1)the inference of clouds and strong waves;2) difficulties in detecting both inshore and offshore ships; and3) high computational expenses. In this paper, we propose a novel ship detection method called SVD Networks (SVDNet),which is fast, robust, and structurally compact. SVDNet is designed based on the recent popular convolutional neural networks and the singular value decompensation algorithm.It provides a simple but efficient way to adaptively learn features from remote sensing images. We evaluate our method on some spaceborne optical images ofgaoFen-1 and Venezuelan Remote Sensing Satellites. The experimental results demonstrate that our method achieves high detection robustness and a desirable time performance in response to all of the above three problems.

关键词：Convolutional neural networks (CNNs); optical spaceborne image; ship detection; singular

来源出版物：IEEE Transactions ongeoscience and Remote Sensing,2016, 54(10): 5832-5845

联系邮箱：Shi, ZW; zhengxiazou@buaa.edu.cn

Sentinel-2’s potential for sub-pixel landscape feature detection

Radoux, J; Chome,g; Jacques, DC; et al.

Abstract:Land cover and land use maps derived from satellite remote sensing imagery are critical to support biodiversity and conservation, especially over large areas.With its10 m to20 m spatial resolution, Sentinel-2 is a promising sensor for the detection of a variety of landscape features of ecological relevance. However,many components of the ecological network are still smaller than the10 m pixel,i.e., they are sub-pixel targets that stretch the sensor’s resolution to its limit. This paper proposes a framework to empirically estimate theminimum object size for an accurate detection of a set of structuring landscape foreground/background pairs. The developed method combines a spectral separability analysis and an empirical point spread function estimation for Sentinel-2.The same approach was also applied to Landsat-8 and SPOT-5 (Take 5), which can be considered as similar in terms of spectral definition and spatial resolution,respectively. Results show that Sentinel-2 performs consistently on both aspects. A large number of indices have been tested along with the individual spectral bands and target discrimination was possible in all but one case.Overall, results for Sentinel-2 highlight the critical importance of agood compromise between the spatial and spectral resolution. For instance, the Sentinel-2 roads detection limit was of3 m and small water bodies are separable with a diameter larger than11 m. In addition, the analysis of spectral mixtures draws attention to the uneven sensitivity of a variety of spectral indices. The proposed framework could be implemented to assess the fitness for purpose of future sensors within a large range of applications.

关键词：Sentinel-2; Landsat-8; SPOT-5; sub-pixel detection;spatial resolution; spectral resolution; point spread function

来源出版物：Remote Sensing,2016,8(6): UNSP 488

联系邮箱：Radoux, J; julien.radoux@uclouvain.be

Using satellite remote sensing data to estimate the high-resolution distribution ofground-level PM2.5

Lin, CQ; Li, Y; Yuan, ZB; et al.

Abstract:Althoughground-level monitoring can provide accurate PM2.5measurements, it has limited spatial coverage and resolution. In contrast, satellite-based monitoring can provide aerosol optical depth (AOD) products with higher spatial resolution and continuous spatial coverage, but it cannot directly measureground-level PM2.5concentration.Observation-based and simulation-based approaches have been actively developed to retrieveground-level PM2.5concentrations from satellite AOD and sparseground-level observations. However, the effect of aerosol characteristics(e.g., aerosol composition and size distribution) on the AOD–PM2.5relationship is seldom considered in observation-based methods. Although these characteristics are considered in simulation-based methods, the results still suffer from model uncertainties. In this study, we propose an observation-based algorithm that considers the effect of the main aerosol characteristics. Their related effects on hygroscopicgrowth, particle mass extinction efficiency, and size distribution are estimated and incorporated into the AOD–PM2.5relationship. The method is applied to quantify the PM2.5distribution in China.good agreements between satellite-retrieved andground-observed PM2.5annual and monthly averages are identified, with significant spatial correlations of 0.90 and 0.76,respectively, at 565 stations in China. The results suggest that this approach can measure large scale PM distributions with verified results that are at least asgood as those from simulation-based estimations. The results also show the method's capacity to identify PM2.5spatial distribution with high-resolution at national, regional, and urban scales and to provide useful information for air pollution control strategies, health risk assessments, etc.

关键词：satellite remote sensing; PM2.5; hygroscopicity;mass extinction efficiency; fine mode fraction

来源出版物：Remote Sensing of Environment,2015,156:117-128

联系邮箱：Li, Y; yingli@ust.hk

A multi-temporal and multi-spectral method to estimate aerosol optical thickness over land,for the atmospheric correction of formosat-2,Landsat, venμs and Sentinel-2 images

Hagolle, O; Huc, M; Pascual, DV; et al.

Abstract:The correction of atmospheric effects is one of the preliminary steps required to make quantitative use of time series of high resolution images from optical remote sensing satellites. An accurate atmospheric correction requiresgood knowledge of the aerosol optical thickness(AOT) and of the aerosol type. As a first step, this study compares the performances of two kinds of AOT estimation methods applied to FormoSat-2 and LandSat time series of images: a multi-spectral method that assumes a constant relationship between surface reflectance measurements and a multi-temporal method that assumes that the surface reflectances are stable with time. In a second step, these methods are combined to obtain more accurate and robust estimates. The estimated AOTs are compared toin situmeasurements on several sites of the AERONET (Aerosol Robotic Network). The methods, based on either spectral or temporal criteria,provide accuracies better than 0.07 in most cases, but show degraded accuracies in some special cases, such as the absence of vegetation for the spectral method or a very quick variation of landscape for the temporal method.The combination of both methods in a new spectrotemporal method increases the robustness of the results in all cases.

关键词：remote sensing; atmospheric correction; time series; aerosols; surface reflectance; LandSat; FormoSat-2;Sentinel-2; VENμS

来源出版物：Remote Sensing,2015,7(3):2668-2691

联系邮箱：Hagolle, O; olivier.hagolle@cesbio.cnes.fr

Multi-mission cross-calibration of satellite altimeters: Constructing a long-term data record forglobal and regional sea level change studies

Bosch, W; Dettmering, D Schwatke, C

Abstract:Climate studies require long data records extending the lifetime of a single remote sensing satellite mission. Precise satellite altimetry exploringglobal and regional evolution of the sea level has now completed a two decade data record. A consistent long-term data record has to be constructed from a sequence of different, partly overlapping altimeter systems which have to be carefully cross-calibrated. This cross-calibration is realizedglobally by adjusting an extremely large set of single- and dualsatellite crossover differences performed between all contemporaneous altimeter systems. The total set of crossover differences creates a highly redundant network and enables a robust estimate of radial errors with a dense and rather complete sampling for all altimeter systems analyzed. An iterative variance component estimation is applied to obtain an objective relative weighting between altimeter systems with different performance. The final time series of radial errors is taken to estimate (for each of the altimeter systems) an empirical auto-covariance function. Moreover, the radial errors capture relative range biases and indicate systematic variations in thegeo-centering of altimeter satellite orbits. The procedure has the potential to estimate for all altimeter systems thegeographically correlated mean errors which is not at all visible in single-satellite crossover differences but maps directly to estimates of the mean sea surface.

关键词：satellite altimetry; sea level; calibration; crossover analysis; range bias; radial errors;geographically correlated errors

来源出版物：Remote Sensing,2014, 6(3):2255-2281

联系邮箱：Bosch, W; bosch@dgfi.badw.de

On-orbitgeometric calibration of ZY-3 three-line Array imagery with multistrip data sets

Yongjun, Z; Maoteng, Z; Jinxin, X; et al.

Abstract:ZY-3, which was launched on January9,2012,is the first stereo mapping satellite in China. The initial accuracy of directgeoreferencing with the onboard three-line camera (TLC) imagery is low. Sensorgeometric calibration with bundle block adjustment is used to improve thegeoreferencing accuracy. A new on-orbit sensor calibration method that can correct the misalignment angles between the spacecraft and the TLC and the misalignment of charge-coupled device is described. All of the calibration processes are performed using a multistrip data set. The control points are automatically matched from existing digital ortho map and digital elevation model. To fully evaluate the accuracy of different calibration methods, the calibrated parameters are used as input data to conductgeoreferencing and bundle adjustment with a total of19 strips of ZY-3 TLC data. A systematic error compensation model is introduced as the sensor model in bundle adjustment to compensate for the position and attitude errors. Numerous experiments demonstrate that the new calibration model can largely improve the external accuracy of directgeoreferencing from the kilometer level to better than20 m in both plane and height. A further bundle block adjustment with medium-accuracyground control points (GCPs), using these calibrated parameters, can achieve external accuracy of about 4 m in plane and3min height. Higher accuracy of about1.3min plane and1.7 m in height can be achieved by bundle adjustment using high-accuracygCPs.

关键词：bundle block adjustment; directgeoreferencing;interior orientation parameters (IOPs); multistrip; on-orbitgeometric calibration; three-line camera (TLC); ZY-3

来源出版物：IEEE Transactions ongeoscience and Remote Sensing,2014, 52(1):224-234

联系邮箱：Yongjun Zhang; zhangyj@whu.edu.cn

责任编辑：王微

Evaluation of theglobal MODIS30 arc-second spatially and temporally complete snow-free land surface albedo and reflectance anisotropy dataset

Sun, QS; Wang, ZS; Li, Z; et al.

Land surface albedo is an essential variable for surface energy and climate modeling as it describes the proportion of incident solar radiant flux that is reflected from the Earth’s surface. To capture the temporal variability and spatial heterogeneity of the land surface, satellite remote sensing must be used to monitor albedo accurately at aglobal scale. However, large datagaps caused by cloud or ephemeral snow have slowed the adoption of satellite albedo products by the climate modeling community. To address the needs of this community, we used a number of temporal and spatialgap-filling strategies to improve the spatial and temporal coverage of theglobal land surface MODIS BRDF, albedo and NBAR products. A rigorous evaluation of thegap-filled values showsgood agreement with original high quality data(RMSE = 0.027 for the NIR band albedo, 0.020 for the red band albedo). Thisglobal snow-free and cloud-free MODIS BRDF and albedo dataset (established from2001 to2015) offers unique opportunities to monitor and assess the impact of the changes on the Earth’s land surface.