多时相双极化合成孔径雷达干涉测量土地覆盖分类方法

综合采用时相、极化和干涉3种维度的SAR数据进行土地覆盖分类。以黑龙江省逊克县多时相ALOS PALSAR数据覆盖区为研究区,利用不同时相极化SAR、干涉SAR信号对地物特征的敏感性,结合后向散射强度和干涉相干的时变特征进行地物解译,发展了基于多时相、多极化、干涉SAR数据的SVM土地覆盖分类方法。研究结果表明,引入双极化SAR中不同极化(HH-HV)间的相干系数,并结合所选择的时相特征、极化特征以及干涉相干特征进行分类,可解决双极化SAR影像中林地与城市及建设用地的混分问题,得到更高精度的土地覆盖分类结果。     

永久散射体与短基线雷达干涉测量在城市地表形变中的应用

在介绍永久散射体与短基线集雷达干涉测量方法的基础上,以辽宁省盘锦市为例,运用两种方法研究了其市区地表形变特征。对比升降轨永久散射体方法与短基线方法所得到的形变平均速率和时序分析可知,两种方法所得的研究区域的地表形变趋势较为可靠,且以垂直沉降为主,新城区是最大沉降区域,最大下沉速率达20 mm/a,其他区域较为稳定。     

Coseismic surface deformation of the 2014 Napa earthquake mapped by Sentinel-1A SAR and accuracy assessment with COSMO-SkyMed and GPS data as cross validation

ABSTRACT

The new land observation satellite Sentinel-1A was launched on 25 April 2014 with a C-band synthetic aperture radar (SAR) sensor, which has the significant enhancements in terms of revisit period and high resolution. The Mw 6.1 Napa, California earthquake occurring on 24 August 2014, almost 4 months after the launch, is the first moderate earthquake imaged by the Sentinel-1A. This provides an opportunity to map the coseismic deformation of the event and evaluate the potential of Sentinel-1A SAR for earthquake study. Two techniques including the interferometric SAR (InSAR) and pixel offset-tracking (PO) are, respectively, employed to map the surface deformation along the radar line of sight (LOS), azimuth and slant-range directions. The cross comparison between Sentinel-1A InSAR LOS deformation and GPS observations indicates good agreement with an accuracy of ～2.6?mm. We further estimate the earthquake source model with the external COSMO-SkyMed InSAR and GPS data as constraints, and forward calculate the surface deformation as cross validation with the Sentinel-1A observations. The comparison between the observed and modeled deformation shows that the Sentinel-1A measurement accuracy can achieve 1.6?cm for InSAR technique along LOS direction, and 6.3 and 6.7?cm for PO along azimuth and range directions, respectively.     

极化SAR参数优化与光学波谱相结合的面向对象土地覆盖分类

提出一种基于极化参数优化的面向对象分类方法。该方法结合光学和SAR数据,有效提高了对地物的识别能力。本文方法的关键在于:在■分解中,使用光学影像指导SAR影像选择同质点,使其更精确地估计极化参数并结合光学波谱信息作为输入特征;使用面向对象的分类方法,仅将光学影像作为分割输入,避免SAR噪声引起的分割错误。以美国Bakersfield地区的Sentinel-1/2数据为例,确定7种地物类型,对比分析不同输入与不同分类器对分类结果的影响。研究表明,优化输入参数在纹理丰富区域能够有效提高分类精度;面向对象的分类结果更加稳定并较好地维持地表几何特征;改进分类方法较传统分类方法总体精度提高了近10%,达到92.6%。     

Multi-resolution integration of land cover for sub-pixel estimation of urban impervious surface and forest cover

Abstract

A methodology is presented for estimating percent coverage of impervious surface (IS) and forest cover (FC) within Landsat thematic mapper (TM) pixels of urban areas. High-resolution multi-spectral images from Quickbird (QB) play a key role in the sub-pixel mapping process by providing information on the spatial distributions of ISs and FCs at 2.4 m ground sampling intervals. Thematic classifications, also derived from the Landsat imagery, have then been employed to define relationships between 30 m Landsat-derived greenness values and percent IS and FC. By also utilizing land cover/land use classification derived from Landsat and defining unique relationships for urban sub-classes (i.e. residential, commercial/industrial, open land), confusion between impervious and fallow agricultural lands has been overcome. Test results are presented for Ottawa-Gatineau, an urban area that encompasses many aspects typical of the North American urban landscape. Multiple QB scenes have been acquired for this urban centre, thereby allowing us to undertake an in-depth study of the error budgets associated with the fractional inference process.     

Next generation of global land cover characterization,mapping, and monitoring

Land cover change is increasingly affecting the biophysics, biogeochemistry, and biogeography of the Earth's surface and the atmosphere, with far-reaching consequences to human well-being. However, our scientific understanding of the distribution and dynamics of land cover and land cover change (LCLCC) is limited. Previous global land cover assessments performed using coarse spatial resolution (300 m–1 km) satellite data did not provide enough thematic detail or change information for global change studies and for resource management. High resolution (∼30 m) land cover characterization and monitoring is needed that permits detection of land change at the scale of most human activity and offers the increased flexibility of environmental model parameterization needed for global change studies. However, there are a number of challenges to overcome before producing such data sets including unavailability of consistent global coverage of satellite data, sheer volume of data, unavailability of timely and accurate training and validation data, difficulties in preparing image mosaics, and high performance computing requirements. Integration of remote sensing and information technology is needed for process automation and high-performance computing needs. Recent developments in these areas have created an opportunity for operational high resolution land cover mapping, and monitoring of the world. Here, we report and discuss these advancements and opportunities in producing the next generations of global land cover characterization, mapping, and monitoring at 30-m spatial resolution primarily in the context of United States, Group on Earth Observations Global 30 m land cover initiative (UGLC).     

Optical and SAR sensor synergies for forest and land cover mapping in a tropical site in West Africa

The classification of tropical fragmented landscapes and moist forested areas is a challenge due to the presence of a continuum of vegetation successional stages, persistent cloud cover and the presence of small patches of different land cover types. To classify one such study area in West Africa we integrated the optical sensors Landsat Thematic Mapper (TM) and the Advanced Visible and Near Infrared Radiometer type 2 (AVNIR-2) with the Phased Arrayed L-band SAR (PALSAR) sensor, the latter two on-board the Advanced Land Observation Satellite (ALOS), using traditional Maximum Likelihood (MLC) and Neural Networks (NN) classifiers. The impact of texture variables and the use of SAR to cope with optical data unavailability were also investigated. SAR and optical integrated data produced the best classification overall accuracies using both MLC and NN, respectively equal to 91.1% and 92.7% for TM and 95.6% and 97.5% for AVNIR-2. Texture information derived from optical images was critical, improving results between 10.1% and 13.2%. In our study area, PALSAR alone was able to provide valuable information over the entire area: when the three forest classes were aggregated, it achieved 75.7% (with MCL) and 78.1% (with NN) overall classification accuracies. The selected classification and processing methods resulted in fine and accurate vegetation mapping in a previously untested region, exploiting all available sensors synergies and highlighting the advantages of each dataset.     

Satellite-based analysis of the role of land use/land cover and vegetation density on surface temperature regime of Delhi,India

The knowledge of the surface temperature is important to a range of issues and themes in earth sciences central to urban climatology, global environmental change and human-environment interactions. The study analyses land surface temperature (LST) estimation using temporal ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) datasets (day time and night time) over National Capital Territory Delhi using the surface emissivity information at pixel level. The spatial variations of LST over different land use/land cover (LU/LC) at day time and night time were analysed and relationship between the spatial distribution of LU/LC and vegetation density with LST was developed. Minimum noise fraction (MNF) was used for LU/LC classification which gave better accuracy than classification with original bands. The satellite derived emissivity values were found to be in good agreement with literature and field measured values. It was observed that fallow land, waste land/bare soil, commercial/industrial and high dense built-up area have high surface temperature values during day time, compared to those over water bodies, agricultural cropland, and dense vegetation. During night time high surface temperature values are found over high dense built-up, water bodies, commercial/industrial and low dense built-up than over fallow land, dense vegetation and agricultural cropland. It was found that there is a strong negative correlation between surface temperature and NDVI over dense vegetation, sparse vegetation and low dense built-up area while with fraction vegetation cover, it indicates a moderate negative correlation. The results suggest that the methodology is feasible to estimate NDVI, surface emissivity and surface temperature with reasonable accuracy over heterogeneous urban area. The analysis also indicates that the relationship between the spatial distribution of LU/LC and vegetation density is closely related to the development of urban heat islands (UHI).     

Normalised difference spectral indices and urban land cover as indicators of land surface temperature (LST)

Land cover changes associated with urbanisation modify microclimate, leading to urban heat islands, whereby cities are warmer than the surrounding countryside. Understanding the factors causing this phenomenon could help urban areas adapt to climate change and improve living conditions of inhabitants. In this study, land surface temperatures (LST) of Aarhus, a city in the high latitudes, are estimated from the reflectance of a thermal band (TIRS1; Band 10; 10.60–11.19 μm) of Landsat 8 on five dates in the summer months (one in 2015, and four in 2018). Spectral indices, modelled on the normalised difference vegetation index (NDVI), using all combinations of the first seven bands of Landsat 8 are calculated and their relationships with LST, analysed. Land cover characteristics, in terms of the percentages of tree cover, building cover and overall vegetation cover are estimated from airborne LiDAR data, building footprints and 4-band aerial imagery, respectively. The correlations between LST, the spectral indices and land cover are estimated.The difference in mean temperature between the rural and urban parts of Aarhus is up to 3.96 °C, while the difference between the warmer and colder zones (based on the mean and SD of LST) is up to 13.26 °C. The spectral index using the near infrared band (NIR; Band 5; 0.85-0.88 μm) and a short-wave infrared band (SWIR2; Band 7; 2.11–2.29 μm) has the strongest correlations (r: 0.62 to 0.89) with LST for the whole study area. This index is the inverse of normalised burn ratio (NBR), which has been used for mapping burnt areas. Spectral indices using different combinations of the infrared bands have stronger correlations with LST than the more widely used vegetation indices such as NDVI. The percentage of tree cover has a higher negative correlation (Pearson’s r: -0.68 to -0.75) with LST than overall vegetation cover (r: -0.45 to -0.63). Tree cover and building cover (r: 0.53 to 0.71) together explain up to 68 % of the variation in LST. Modification of tree and building cover may therefore have the potential to regulate urban LST.     

Bi-temporal characterization of land surface temperature in relation to impervious surface area,NDVI and NDBI,using a sub-pixel image analysis

As more than 50% of the human population are situated in cities of the world, urbanization has become an important contributor to global warming due to remarkable urban heat island (UHI) effect. UHI effect has been linked to the regional climate, environment, and socio-economic development. In this study, Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper Plus (ETM+) imagery, respectively acquired in 1989 and 2001, were utilized to assess urban area thermal characteristics in Fuzhou, the capital city of Fujian province in south-eastern China. As a key indicator for the assessment of urban environments, sub-pixel impervious surface area (ISA) was mapped to quantitatively determine urban land-use extents and urban surface thermal patterns. In order to accurately estimate urban surface types, high-resolution imagery was utilized to generate the proportion of impervious surface areas. Urban thermal characteristics was further analysed by investigating the relationships between the land surface temperature (LST), percent impervious surface area, and two indices, the Normalized Difference Vegetation Index (NDVI) and Normalized Difference Built-up Index (NDBI). The results show that correlations between NDVI and LST are rather weak, but there is a strong positive correlation between percent ISA, NDBI and LST. This suggests that percent ISA, combined with LST, and NDBI, can quantitatively describe the spatial distribution and temporal variation of urban thermal patterns and associated land-use/land-cover (LULC) conditions.     

陆地表层覆盖变化对地表反照率影响的四国对比

陆表覆盖变化影响地表特征从而改变地表能量平衡是理解人类活动对全球气候变化影响的关键环节。选择国际气候谈判主要国家的美国、印度和巴西作为中国的对比国,对比分析不同国别、不同气候带典型陆表覆盖类型的地表反照率时空差异,进而模拟开垦和城市化等陆表覆盖变化对反照率的影响差异。结果表明：(1) 2000年—2015年,中国、美国的地表反照率年际变化存在明显的气候带空间分异特征,中国干旱半干旱区和美国中低纬湿润区表现出降低趋势,而中国亚热带湿润和美国高纬与中部干旱区则表现出明显的升高趋势,印度的地表反照率年际变化呈微弱下降趋势,而巴西为微弱上升趋势。(2)无雪覆盖时,耕地、林地、草地和人造地表反照率具有夏高、冬低的时间变化特征,干旱半干旱区反照率明显高于湿润区。4种类型的国别差异体现在,中国亚热带湿润区地表反照率均以上升为主,干旱半干旱区则相反;美国除耕地在干旱区呈较强的升高趋势外,其余类型基本为降低趋势;印度均表现为降低趋势;巴西则表现为略微升高趋势。(3)与无雪覆盖相比,有雪覆盖时不同陆表覆盖类型地表反照率均有所提高,林地提高幅度最小,约0.06—0.26,耕地提高最大,约为0.17—0.38,且中国林地反照率提高幅度略高于美国。(4)原陆表覆盖为林地时,开垦和城镇化均导致地表反照率升高,且干旱区升高幅度高于湿润区,湿润区的升高幅度随纬度降低而减弱;为草地时,开垦主要在巴西、印度和中、美亚热带湿润区引起地表反照率升高。而城镇化引起的反照率变化则受到原有地表覆盖、季节和气候背景影响存在较复杂的国别和气候带差异。     

GPS radio holography as a tool for remote sensing of the atmosphere, mesosphere, and terrestrial surface from space

GPS radio occultation (RO) signals are highly coherent and precise, and thus sufficient for holographic investigation of the atmosphere, ionosphere, and the Earth's surface from space. In principle, three-dimensional radio-holographic remote sensing is possible by using new radio holographic equations to retrieve the radio field within the atmosphere from a radio field known at some interface outside the atmosphere. A simplified two-dimensional form of the radio-holographic equations which are developed under an assumption of local spherical symmetry can be used to obtain two-dimensional radio images of the atmosphere and terrestrial surface. To achieve this, radio holograms recorded by a GPS receiver onboard a low earth orbit (LEO) satellite at two GPS frequencies can be used and focused synthetic aperture principle applied. Analysis of GPS/MET RO data is presented to show the effectiveness of a radio-holographic approach. It is shown that the amplitude of GPS radio signals (in addition to phase data) can be used to obtain detailed altitude profiles of the vertical gradient of refractivity in the atmosphere and electron density in the mesosphere. The results demonstrate the applicability of GPS radio holography for a detailed global study of the natural processes in the atmosphere and mesosphere. Electronic Publication     

航天多波段全极化干涉雷达的地物探测

航天飞机成象雷达 3号及X波段合成孔径雷达 (SIR -C/X -SAR)计划是一项包括中国在内有 13个国家合作进行的大型雷达对地观测研究计划。SIR -C/X -SAR具有L、C、X3个波段及L、C波段HH ,HV ,VH ,VV极化 ,X波段VV极化同时成象的能力 ,可获得全极化及干涉雷达数据 ,是本世纪内最先进的航天成象雷达系统。该文系统介绍了SIR -C/X -SAR中国项目开展以来取得的研究成果。重点阐述了中国雷达试验区及与SIR -C/X -SAR成象飞行同步开展的航天—航空—地面立体同步观测试验和对干沙的穿透性试验 ,以及在相关领域和不同地区的应用 ,包括昆仑山火山群的发现 ,广东肇庆植被覆盖区地质体的识别 ,明、隋两代长城的探测与极化响应分析 ,海洋及城市特征研究 ,并介绍了利用干涉雷达数据生成数字地形模型的结果     

利用地震面波和重力资料联合反演地壳—上地幔三维密度结构的方法探讨

本文探讨了利用地震面波和重力资料联合反演地壳－地幔三维密度结构的反演问题。首先建立了地震面波和重力资料的观测方程,然后应用广义线性反线理论给出了反演问题的解。模型试验结果表明,与单纯面波反演的结果相比,联合反演的解在分析率和方差两个方面都有改善,当加入扰动重力数据时,在０－３００ｋｍ深度范围内联合反演的结果明显好于单纯面波反演的结果。     

Monitoring surface changes in discontinuous permafrost terrain using small baseline SAR interferometry,object-based classification,and geological features: a case study from Mayo,Yukon Territory,Canada

Permafrost-induced deformation of ground features is threating infrastructure in northern communities. An understanding of permafrost distribution is therefore critical for sustainable adaptation planning and infrastructure maintenance. Considering the large area underlain by permafrost in the Yukon Territory, there is a need for baseline information to characterize the permafrost in this region. In this study, the Differential Interferometric Synthetic Aperture Radar (DInSAR) technique was used to identify areas of ground movement likely caused by changes in permafrost. The DInSAR technique was applied to a series of repeat-pass C-band RADARSAT-2 observations collected in 2015 over the Village of Mayo, in central Yukon Territory, Canada. The conventional DInSAR technique demonstrated that ground deformation could be detected in this area, but the resulting deformation maps contained errors due to a loss of coherence from changes in vegetation and atmospheric phase delay. To address these limitations, the Small BAseline Subset (SBAS) InSAR technique was applied to reduce phase error, thus improving the deformation maps. To understand the relationship between the deformation maps and land cover types, an object-based Random Forest classification was developed to classify the study area into different land cover types. Integration of the InSAR results and the classification map revealed that the built-up class (e.g., airport) was affected by subsidence on the order of ?2 to ?4 cm. The spatial extent of the surface displacement map obtained using the SBAS InSAR technique was then correlated with the surficial geology map. This revealed that much of the main infrastructure in the Village of Mayo is underlain by interbedded glaciofluvial and glaciolacustrine sediments, the latter of which caused the most damage to human made structures. This study provides a method for permafrost monitoring that builds upon the synergistic use of the SBAS InSAR technique, object-based image analysis, and surficial geology data.     

On accuracy and reliability of instantaneous network RTK as a function of network geometry, station separation, and data processing strategy

The network-based approach to kinematic GPS positioning significantly increases the distance, over which carrier-phase ambiguity resolution can be performed. This can be achieved either by introducing geometric conditions based on the fixed reference locations, and/or through the use of reference network data to estimate the corrections to GPS observations that can be broadcast to the users. The Multi Purpose GPS Processing Software (MPGPS) developed at The Ohio State University uses the multiple reference station approach for wide area and regional differential kinematic GPS positioning. The primary processing algorithm uses the weighted free-net (WFN) approach with the distance-dependent weighting scheme to derive optimal estimates of the user coordinates and realistic accuracy measures. The WFN approach, combined with the single epoch (instantaneous) ambiguity resolution algorithm is presented here as one approach to real-time kinematic (RTK) GPS. Since for baselines exceeding ~100 km, the instantaneous ambiguity resolution may not always be possible due to the increasing observation noise and insufficient number of observations to verify the integer selection, an alternative approach, based on a single- (or multiple-) baseline solution, supported by a double-difference (DD) ionospheric delay propagated from the previous epoch is also presented. In this approach, some data accumulation, supported by the network-derived atmospheric corrections, is required at the beginning of the rover data processing to obtain the integer ambiguities; after this initialization period, the processing switches to the instantaneous RTK positioning mode. This paper presents a discussion on the effects of the network geometry, station separation and the data reduction technique on the final quality and reliability of the rover positioning solution. A 24-h data set of August 31, 2003, collected by the Ohio Continuously Operating Reference Station (CORS) network was processed by both techniques under different network geometry and reference station separation. Various solutions, such as (1) single-baseline solution for varying base-rover separation, (2) multi-baseline solution with medium-range base separation (over 100 km), and (3) multi-baseline solution with long-range base separation (up to 377 km), were obtained and compared for accuracy and consistency. The horizontal positioning accuracy achieved in these tests, expressed as the difference between the estimated coordinates and the known rover coordinates, is at the sub-decimeter level for the first approach, and at the centimeter-level for the second method, for baselines over 100 km. In the vertical coordinate, decimeter- and sub-decimeter levels were achieved for the two approaches, respectively. Even though all the results presented here were obtained in post-processing, both algorithms are suitable for real-time applications.     

NDSI与NDFSI结合的山区林地积雪制图方法

积雪是冰冻圈的重要组成部分,因其在可见光波段的高反射率、低导热率的特性以及大面积的覆盖,成为全球辐射平衡的重要决定因子。在中纬度的干旱和半干旱山区,季节性的冰雪融水是春季河川径流的主要补给水源,山区积雪分布的变化对融雪期河流径流量的波动具有重要影响。当前的积雪产品在下垫面为山区林地时会低估积雪面积,从而影响了山区水文过程模拟的精度。本文基于Landsat OLI影像,采用归一化差值积雪指数NDSI和归一化差值林地积雪指数NDFSI相结合的方法,对春季融雪期的阿尔泰山区泰加林地进行积雪识别,并采用海拔高度、温度、以及对应的高分数据对提取结果进行了定量分析。结果表明,采用NDSI进行积雪识别时,山区林地的积雪会被大量漏分;对林地像元采用NDFSI阈值法可以区分林地中是否有积雪分布。NDSI和NDFSI相结合的积雪识别方法操作简单,不需要提供森林分布图等辅助数据,可以有效提高山区林地复杂环境下积雪制图的精度。     

A new implementation of narrowband interference detection,characterization, and mitigation technique for a software-defined multi-GNSS receiver

Due to the very low power of satellite signals when reaching the earth’s surface, global navigation satellite system receivers are vulnerable to various types of radio frequency interference, and, therefore, countermeasures are necessary. In the case of a narrowband interference (NBI), the adaptive notch filtering technique has been extensively investigated. However, the research on the topic has focused on the adaptation of the notch frequency, but not of the notch width. We present a fully adaptive solution to counter NBI. The technique is capable of detecting and characterizing any number of narrow interfered bands, and then optimizing the mitigation process based on such characterization, namely the estimates of both interference frequency and width. Its full adaptiveness makes it suitable to cope with the unpredictable and diverse nature of unintentional interfering events. In addition to a thorough performance evaluation of the proposed method, which shows its benefits in terms of signal quality improvement, an analysis of the impact of different NBI profiles on GPS L1 C/A and Galileo E1 is also conducted.     

Accuracy of GPS-derived relative positions as a function of interstation distance and observing-session duration

 Ten days of GPS data from 1998 were processed to determine how the accuracy of a derived three-dimensional relative position vector between GPS antennas depends on the chord distance (denoted L) between these antennas and on the duration of the GPS observing session (denoted T). It was found that the dependence of accuracy on L is negligibly small when (a) using the `final' GPS satellite orbits disseminated by the International GPS Service, (b) fixing integer ambiguities, (c) estimating appropriate neutral-atmosphere-delay parameters, (d) 26 km ≤ L ≤ 300 km, and (e) 4 h ≤T ≤ 24 h. Under these same conditions, the standard error for the relative position in the north–south dimension (denoted S _n and expressed in mm) is adequately approximated by the equation S _n =k _n /T ^0.5 with k _n =9.5 ± 2.1 mm · h^0.5 and T expressed in hours. Similarly, the standard errors for the relative position in the east–west and in the up-down dimensions are adequately approximated by the equations S _e =k _e /T ^0.5 and S _u =k _u /T ^0.5, respectively, with k _e =9.9 ± 3.1 mm · h^0.5 and k _u =36.5 ± 9.1 mm · h^0.5. Received: 5 February 2001 / Accepted: 14 May 2001     

The gains of small circular,square and rectangular filters for surface waves on a sphere

Meissl has derived weighting functions for converting point gravity anomaly degree variances into mean anomaly variances over a circular cap on a sphere. If the cap is sufficiently small so that the cap on a sphere degenerates into a circle on a plane, the problem may be considered that of the gain of a circular filter for a surface wave whose wave number depends on the spherical harmonic degree. The Meissl weights then become replaced by diffraction integrals of optical physics. The expected gain for a square filter for waves coming from random directions is derived and shown to be close to the gain of a circular filter with the same area. The expected gains and cross-gains for rectangular filters are also derived. When weighted by an anomaly degree variance model, these gains and cross-gains can be used to determine rectangular anomaly variances and covariances for arbitrary bandwidths. Using the Tscherning-Rapp model, analytic gravity anomaly variances and covariances are calculated for 1°×1° blocks.