不同尺度的土壤含水量主被动微波联合反演方法研究

土壤含水量是水文、农业和气象等领域的关键参数,而微波遥感是目前监测土壤含水量最有效的手段之一。本文利用主动微波与被动微波数据,结合其他多源遥感数据,运用随机森林算法分别在主动微波数据分辨率尺度和被动微波数据分辨率尺度下完成主被动微波数据的土壤含水量联合反演。首先对被动微波尺度的地表覆盖类型与归一化植被指数(NDVI)参数进行空间分辨率优化,再利用回归ReliefF方法对两种尺度所用的输入变量的重要性进行评估,并对输入变量进行优选,最后对比主被动微波数据土壤含水量联合反演和单独利用主动/被动微波数据进行反演的精度,分析主被动微波联合反演方法的有效性。结果表明:在主动微波尺度,主被动微波联合反演的精度相比单独利用主动微波数据反演的精度有所提升,相关系数r由0.691升至0.744,RMSE由0.0848 cm^(3)/cm^(3)降至0.0796 cm^(3)/cm^(3);在被动微波尺度,主被动微波联合反演的精度反而比单独利用被动微波数据反演的精度更低,相关系数r由0.944变为0.939,RMSE由0.0435 cm^(3)/cm^(3)变为0.0451 cm^(3)/cm^(3)。因此在主动微波尺度更适合进行主被动微波的联合反演。

基于卷积神经网络的高分六号卫星多光谱图像压缩

高分六号多光谱图像的空间冗余和谱间冗余较高,为了降低高分六号多光谱图像所占用的存储空间,提高国产高分多光谱图像的压缩效率,提出一种基于卷积神经网络的端到端多光谱图像压缩模型SMIC。SMIC模型由自编码器、量化结构、熵编码3个部分组成。自编码器通过卷积下采样提取图像的特征,降低数据的空间维度。量化结构采用多进制量化将特征矩阵离散化,减少图像压缩过程中的信息损失。熵编码采用高斯混合模型进行编码,降低码流,减少图像所占用的存储空间。实验结果表明:在相同码率下SMIC模型的高分六号多光谱图像压缩效果明显优于传统图像压缩算法JPEG,重建图像的质量明显提高,图像的峰值信噪比较JPEG高约2 dB,且SMIC重建图像的误差值主要集中在[-100,100]范围内,区间占比达到80%以上;SMIC模型重建图像的NDVI与原始图像NDVI的决定系数R2为0.93;SMIC模型的冬小麦提取准确率为87.16%,误检率为4.47%,冬小麦提取结果验证了SMIC模型能够满足部分定量遥感的应用需求。

高分六号卫星遥感估算大气细颗粒物方法研究

针对目前利用高分六号卫星开展地区高空间分辨率大气细颗粒物监测研究较少的问题,提出了基于高分六号卫星宽幅相机数据的气溶胶光学厚度及大气细颗粒物遥感反演的技术方法,并在京津冀及周边地区开展了应用实验和对比分析。首先,基于改进暗像元法反演了高分六号卫星数据的气溶胶光学厚度;然后,结合地面大气细颗粒物监测数据与多种气象辅助数据,基于随机森林算法,构建了多参量综合的大气细颗粒物估算模型,对京津冀地区的大气细颗粒物浓度进行了估算。研究表明:高分六号气溶胶光学厚度反演结果与地基站点监测结果的相关系数为0.94,反演精度较高;大气细颗粒物估算结果与地基站点监测结果的决定系数达到0.79以上,较好地反映了京津冀地区的大气细颗粒物空间分布。

尼泊尔生态系统质量评估与时空格局变化——基于参照条件的评估方法

良好的生态系统质量是维持人类社会供给需求和可持续发展目标实现的重要保障。针对尼泊尔自然地理环境复杂多样,区域间气候差异明显的特点,结合基于参照条件的评估方法可以得到生态系统质量的相对水平值,其结果能够反映出不同的变化信息。植被是区域生态系统质量变化的重要指示器,利用尼泊尔五大地理区以及四种主要植被生态系统类型划分出20个生态评估区,从表征植被生态系统的水平结构、生产功能和垂直结构3个方面计算生态参数相对密度指标(RVI),结合主成分分析法构建植被生态系统质量指数(VEQI),并以其国家自然保护区为参照,构建基于参照条件的生态系统质量评估模型,计算了尼泊尔2016和2020年基于参照条件的植被生态系统质量指数(VEQI')并分析其生态系统质量的时空格局变化。结果表明:(1)2016至2020年,尼泊尔生态系统质量现实值VEQI的平均值增加了3.49%,总体上,在参照生态系统质量(VEQIref)提高(约1.41%)的背景下,生态系统质量相对水平值VEQI'增加了1.42%;(2)对于尼泊尔地区,评估区89%分位数的VEQI与其对应的国家自然保护区的参照值具有很强的相关性,总体差异较小,可以代替作为参照值;(3)从空间格局变化趋势来看,尼泊尔生态系统质量变好、基本稳定和变差的面积分别占植被生态系统总面积的74.16%、14.25%和11.59%。与数量不足、较难收集利用的野外观测台站数据相比,国家自然保护区更接近理想参照生态系统的假设,通过有限的自然保护区确定生态评估区的参照值,实现生态系统质量的快速评估,其结果具有更好的时空可比性,可以为区域生态质量变化评估及量化分析等方面提供参考。

基于卫星遥感监测技术的长江安徽段土地利用与水质调研分析

中共十八大以来,围绕长江经济带发展这一区域重大战略,习近平总书记多次召开长江经济带发展座谈会,指出把修复长江生态环境摆在压倒性位置,“共抓大保护,不搞大开发”。利用卫星遥感先进技术对长江安徽段沿江主要城市重点区域进行城市建设、生态环境、工农业业、港口治理、污染防治等方面进行遥感监测,结果表明:(1)长江生态环境保护取得了巨大成效,体现在新安江、巢湖、菜子湖等重点水域水质有了大幅改善,近年水质参数维持在良好水平。(2)土地利用变化分析可知:长江沿线城市经济活力强,发展迅速,体现在土地利用变化方面:合肥市、芜湖市2019年-2020年耕地占比减少较为明显,2021年-2022年期间有所回升。合肥市、安庆市2019年-2022年建筑用地占比增加较为明显,淮南市耕地占比减少较为明显,建筑面积略有减少,植被覆盖增加较为明显。(3)重点调研区域中,土地利用变化主要体现在城市建设、矿山开采与修复、码头整顿与治理、交通道路建设、水利改造工程、工业区改造等。这些变化表明城市基础设施逐步完善,促进了城市经济发展,改善了居民生活环境。(4)通过全省植被变化大气参数分析结果表明植被总体呈现恢复状态,空气质量呈现上升趋势,然而不同月份间大气质量有起伏,表明需要对大气进行长时序的监测与全面应急备案。

Improvement of Glacial Lakes Detection under Shadow Environment Using ASTER Data in Himalayas, Nepal

The detection of glacial lake change in the Himalayas, Nepal is extremely significant since the glacial lake change is one of the crucial indicators of global climate change in this area, where is the most sensitive area of the global climate changes. In the Himalayas, some of glacial lakes are covered by the dark mountains′ shadow because of their location. Therefore, these lakes can not be detected by conventional method such as Normalized Difference Water Index (NDWI), because the reflectance feature of shadowed glacial lake is different comparing to the ones which are located in the open flat area. The shadow causes two major problems: 1) glacial lakes which are covered by shadow completely result in underestimation of the number of glacial lakes; 2) glacial lakes which are partly identified are considered to undervalue the area of glacial lakes. The aim of this study is to develop a new model, named Detection of Shadowed Glacial Lakes (DSGL) model, to identify glacial lakes under the shadow environment by using Advanced Space-borne Thermal Emission and Reflection Radiometer (ASTER) data in the Himalayas, Nepal. The DSGL model is based on integration of two different modifications of NDWI, namely NDWIs model and NDWI she model. NDWIs is defined as integration of the NDWI and slope analysis and used for detecting non-shadowed lake in the mountain area. The NDWIshe is proposed as a new methodology to overcome the weakness of NDWIs on identifying shadowed lakes in highly elevated mountainous area such as the Himalayas. The first step of the NDWIshe is to enhance the data from ASTER 1B using the histogram equalization (HE) method, and its outcome product is named ASTER he . We used the ASTER he for calculating the NDWI he and the NDWIshe . Integrated with terrain analysis using Digital Elevation Model (DEM) data, the NDWI she can be used to identify the shadowed glacial lakes in the Himalayas. NDWIs value of 0.41 is used to identify the glacier lake (NDWIs≥0.41), and 0.3 of NDWIshe is used to identify the shadowed glacier lake (NDWIshe≤0.3). The DSGL model was proved to be able to classify the glacial lakes more accurately, while the NDWI model had tendency to underestimate the presence of actual glacial lakes. Correct classification rate regarding the products from NDWI model and DSGL model were 57% and 99%, respectively. The results of this paper demonstrated that the DSGL model is promising to detect glacial lakes in the shadowed environment at high mountains.

遥感共性产品真实性检验系统框架设计

真实性检验是近年来定量遥感领域研究的热点和难点。近年来,我国在真实性检验理论研究、标准规范制定和场网建设方面均取得了巨大的进步。目前,真实性检验技术系统尚不成熟,各环节缺乏有效的组织和对接,缺少高质量且具备业务化运行的真实性检验场网体系。根据当前国内外的研究现状,结合近年来的相关工作积累,给出了真实性检验的概念和内涵,在此基础上,提出了一个真实性检验总体架构,并对各部分的组成、技术体系、存在的问题及未来的发展原则给出理解和设计,为今后我国陆地卫星真实性检验场网的建设和运行提供参考。

被动微波土壤水分产品真实性检验研究进展

随着全球气候变化和陆面数据同化研究对土壤水分反演精度要求的不断提高,大尺度被动微波土壤水分产品的真实性检验变得极为重要。如何获取可以代表卫星观测尺度"真值"、并能表征空间异质性的土壤水分观测场,成为被动微波土壤水分产品真实性检验的关键问题。土壤水分观测场的构建涉及地面观测、同步观测、尺度转换等关键环节,可通过"点代面"和"多源信息融合"这2个技术途径进行构建。简要总结了应用于大尺度土壤水分的5种典型的真实性检验方法,包括实测样本数据检验、影像数据交叉检验、模型模拟检验、影响因素检验和传统地统计检验。这5种方法或缺乏对先验知识的有效利用,或忽略地面实测的重要性,或在综合利用多源数据类型的先验知识信息方面不足。随着贝叶斯最大熵理论的发展,基于贝叶斯最大熵理论和先验知识的大尺度土壤水分产品真实性检验有望发展成为一种可靠的方法。贝叶斯最大熵理论的优势在于,能够提供灵活的数据利用方式,使多种来源、多种类型的数据集有机会同时被用于卫星观测尺度的时空分析,生成高分辨率土壤水分数字地图,从而为大尺度土壤水分产品的真实性检验研究提供一个新的途径。

Multi-parameters of Thermal Infrared Remote Sensing Anomalies of the Earthquake

Temporal and spatial anomalies associated with the Yushu earthquake, including the Outgoing Longwave Radiation( OLR), the Land Surface Temperature( LST) and surface temperature from the National Center for Environmental Prediction( NCEP) are studied using thermal infrared remote sensing data in this paper. All results confirmed the previous observations of thermal anomalies in the seismic region prior to this earthquake.Among the multi-parameter anomalies, the underground water temperature anomaly appeared first and lasted for the longest time; OLR anomaly,an infrared parameter which indicates the radiation characteristics of the land surface medium,was the first to be detected; LST anomalies appeared later than OLR. NCEP temperature indicates the average atmosphere temperature with a certain vertical thickness; therefore,it was the last detected anomaly. The anomalies of OLR and LST lasted for a similar time length and were all located in the south or southwest of the epicenter.

高分一号卫星影像谐波模型模拟方法研究

随着遥感技术的发展,遥感应用的广度和深度得到了大幅度提升,遥感用户对遥感数据的空间分辨率及时间分辨率的需求也越来越高。遥感影像空间分辨率与时间分辨率之间的矛盾难以调和,再加上云、雾、雪和云阴影等因素的影响,限制了高时空分辨率干净遥感影像的获取,为此尝试研发一种影像模拟方法,以便拓展高空间分辨率遥感影像的时间分辨率。利用无云、雾、雪和云阴影的高分一号(GF-1)卫星时间序列影像为每个波段每个像元构建以日期为参数的谐波模型,进而建立基于谐波模型的影像模拟方法,实现指定日期GF-1卫星影像的模拟。基于谐波模型的影像模拟方法生成的模拟影像与真实影像在视觉上十分接近,在定量评估方面也取得了较好的效果,两者之间各波段大多数像元差值处于-0. 03~0. 03间,均方根误差保持在0. 02~0. 05间,表明基于谐波模型的影像模拟方法具有较高的精度与稳定性,可有效提升GF-1卫星影像的时间分辨率,具有一定的实用价值。

中国遥感真实性检验基础设施建设发展态势分析

遥感产品的真实性检验研究是当前遥感领域研究的热点和难点。真实性检验基础设施的建设是实现遥感产品真实性检验的关键环节。近年来,中国先后启动国家民用空间基础设施真实性检验场网(简称空基场网)和高分专项国家真实性检验场站网(简称高分站网)的建设,形成由60余个站点组成,具备40余种遥感产品检验能力的场网体系。本文在介绍了国内外已有场网的基础上,详细介绍了空基场网和高分站网的建设目标、站点组成和测量产品。结合当前空基场网和高分站网的建设现状,提出了建设中国真实性检验的思路,探讨了建设真实性检验站网的技术体系,从理论研究、标准规范制定、场网建设和产品验证评价4个方面进行分析,为中国今后真实性检验站网建设和遥感产品的真实性检验提供参考。

高分辨率定量遥感的偏振光效应与偏振遥感新领域

随着航空航天高分辨率观测手段的逐步成熟,定量遥感在有效解决了光学地表多尺度效应后,更高分辨率的光学偏振效应在地表、大气、仪器3大要素方面逐步全面凸显出来,并直接决定或影响高分辨率观测系统的定量遥感效能实现和质量保障。例如,植被冠层极其微弱的多次散射反射偏振效应,如果不加扣除其模型误差达到136%;大气衰减本质是大气偏振效应,是遥感反演的最大误差源,误差达到5%—30%,偏振手段扣除大气误差目前已可以降低一半以上的误差;观测仪器扣除多次散射透射偏振光后,可以实现5 nm分辨率下0.1—0.3 nm高光谱定标能力,并借助偏振强化光噪声分离出中心波长偏移和带宽退化的误差根源。借助偏振"强光弱化,弱光强化",能够实现稳定度达10^(-8)月球辐亮度基准观测,为遥感辐亮度定标不确定度由7%到1%—2%跨越提供可能。

亚洲大洋洲区域综合地球观测系统计划进展

亚洲大洋洲区域综合地球观测系统是为实现国际地球观测组织总体战略目标而设立的区域地球观测合作计划,旨在面向亚大区域国家对地球观测技术的应用需求,保障亚大区域地球观测空间信息的精准获取与主动服务,增强地球观测技术支撑区域可持续发展的综合能力。该计划由地球观测组织亚大区域成员国共同提出,并对亚大地区的所有国家和参与组织开放。通过国际地球观测组织亚大区域政府间合作机制,在国家、区域和全球层面建立有效的合作框架,积极协调区域内的地球观测资源设施的互联互通、技术合作与共享服务,促进亚大区域国家在社会经济关键领域的应用,共同应对可持续发展、全球变化和重大灾害的挑战。

Classification of hyperspectral remote sensing images using frequency spectrum similarity

An algorithm of hyperspectral remote sensing images classification is proposed based on the frequency spectrum of spectral signature.The spectral signature of each pixel in the hyperspectral image is taken as a discrete signal,and the frequency spectrum is obtained using discrete Fourier transform.The discrepancy of frequency spectrum between ground objects' spectral signatures is visible,thus the difference between frequency spectra of reference and target spectral signature is used to measure the spectral similarity.Canberra distance is introduced to increase the contribution from higher frequency components.Then,the number of harmonics involved in the proposed algorithm is determined after analyzing the frequency spectrum energy cumulative distribution function of ground object.In order to evaluate the performance of the proposed algorithm,two hyperspectral remote sensing images are adopted as experimental data.The proposed algorithm is compared with spectral angle mapper (SAM),spectral information divergence (SID) and Euclidean distance (ED) using the product accuracy,user accuracy,overall accuracy,average accuracy and Kappa coefficient.The results show that the proposed algorithm can be applied to hyperspectral image classification effectively.

Forest NPP estimation based on MODIS data under cloudless condition

Based on light-use efficiency model, an MODIS-derived daily net primary production (NPP) model was developed. In this model, a new model for the fraction of photosynthetically active radiation absorbed by vegetation (FPAR) is developed based on leaf area index (LAI) and albedo parameters, and a pho- tosynthetically active radiation (PAR) is calculated from the combination of Bird's model with aerosol optical thickness and water vapor derived from cloud free MODIS images. These two models are inte- grated into our predicted NPP model, whose most parameters are retrieved from MODIS data. In order to validate our NPP model, the observed NPP in the Qianyanzhou station and the Changbai Mountains station are used to compare with our predicted NPP, showing that they are in good agreement. The NASA NPP products also have been downloaded and compared with the measurements, which shows that the NASA NPP products underestimated NPP in the Qianyanzhou station but overestimated in the Changbai Mountains station in 2004.

HJ-1A HSI on-orbit radiometric calibration and validation research

The calibration experiment data at Dunhuang radiometric calibration site in October, 2008 were used to achieve the on-orbit radiometric calibration for HJ-1A hyper spectral imager (HSI). Two other field experiments data were used to validate the Dunhuang calibration results. One field experiment took place in Inner-Mongolia, China in September, 2008, and the other field experiment took place in Lake Frome, Australia in February, 2009. Finally, the ‘confidence interval of calibration error’ concept was put forward for quantitatively computing the calibration coefficient error confidence interval. The results showed that the Dunhuang calibration results in 2008 had high reliability. The confidence intervals of calibration error for all HSI channels were between 2% to 12%, which could satisfy the requirement of the HSI quantitative applications.

Uncertainty analysis of cross-calibration for HJ-1 CCD camera

Radiometric calibration of sensor is the basis of quantitative remote sensing,and uncertainty analysis is critical to ensure the accuracy of cross-calibration.Therefore,firstly,cross-calibration formulas were improved by redefining calibration coefficient and spectral band matching factor.In these formulas,cci was redefined as the calibration coefficient of normalized apparent reflectance,and spectral band matching factor as the ratio of normalized apparent reflectance.Secondly,based on the contrast of ideal and actual conditions in cross-calibration,8 sources of cross-calibration uncertainty were proposed:calibration uncertainty of standard sensor;pixel matching uncertainty;spectral band matching factor uncertainty caused by site altitude setting error,atmospheric parameters setting error,surface spectrum source,surface bidirectional reflectance characteristic,and error of atmospheric radiative transfer model;and uncertainty caused by other factors which were not considered.Finally,the contribution of each uncertainty was further analyzed and discussed for the HJ-1 CCD camera.The results provide many valuable references for evaluating the feasibility of alternative cross-calibration measurements.

基于随机森林的京津冀地区PM_(2.5)遥感反演及变化分析

大气细颗粒物PM_(2.5)是影响人类生存环境和身体健康的主要大气环境污染物,研究PM_(2.5)质量浓度季节变化的规律及空间分布特征,对于大气污染物的预防和治理有着重要的意义。利用2018~2020年MODIS卫星L2级AOD产品、MERRA-2气象数据以及地面站点PM_(2.5)实测数据,基于改进的随机森林算法,构建AOD-PM_(2.5)反演模型,对京津冀地区PM_(2.5)质量浓度进行估算,并分析PM_(2.5)质量浓度空间分布特征以及季节变化规律。结果表明:①春夏秋冬4组模型决定系数(R2)均值分别为0.78、0.66、0.83、0.83,模拟精度较高。②2018~2020年京津冀地区春夏秋冬四季PM_(2.5)浓度呈显著的空间分布特征及季节变化规律。其中PM_(2.5)污染最大值出现在冬季,最小值出现在夏季。③历年同季节相比,京津冀地区PM_(2.5)污染范围和浓度数值均有所减小,2020春季和秋季PM_(2.5)污染范围与2018年、2019年相比改善较明显。

Modeling diurnal variation of ground thermal radiance images using energy balance model and endmember composing technique

Modeling and analyzing dynamic changes of land thermal radiance scenes play an important role in thermal remote sensing.In this paper,the diurnal variation of ground surface thermal scene is mainly discussed.Firstly,based on the land surface energy balance equation,the diurnal variation of land surface temperatures(LSTs) over bare land covers were simulated by an analytical thermal model with second harmonic terms,and the diurnal LST variation of vegetation canopy was simulated using the Cupid model.Secondly,normalized difference vegetation index(NDVI),normalized difference water index(NDWI),and ratio resident-area index(RRI) were used to evaluate the endmember abundance of four land cover types including vegetation,bare soil,impervious and water area,which were calculated from IKONOS visible and near infrared(VNIR) bands.Finally,the thermal radiance scenes at various times and view angles were modeled based on the linear-energy-mixing hypothesis.The results showed that the simulated daily LST variations for vegetated and bare surfaces are correlated with the measured values with a maximum standard deviation of 2.7°C,that land thermal radiant textures with high-resolution are restored from the linear-energy-mixing method,and that the information abundance of the scene are related to the distribution of land cover,the imaging time,and the view angle.

A twin-channel difference model for cross-calibration of thermal infrared band

Based on the conduction and transformation of the thermal infrared radiative transfer equation of water target,a twinchannel difference model(DM) was proposed to improve the calibration precision by conquering the limitation that the atmospheric condition when image is acquiring cannot be truly obtained in the traditional radiometric simulation calibration method.The analysis of surface,atmosphere and top-of-atmosphere(TOA) radiative energy decomposition demonstrated that the apparent TOA radiance of the uncalibrated channel is the differential combination of two reference channels.The DM avoids impacts from atmospheric temperature and density.The only impact is from water vapor(WV) content.Based on the fitting error analysis of 742 mid-latitude atmospheric profiles(column WV content:0-5×10 3 atm cm) selected from TIGR database,the DM is insensitive to WV content.The maximum error is less than 0.2 K when the view zenith angels(VZAs) of reference channels and uncalibrated channel are less than 30.The error becomes 0.3 K when VZAs range from 30 to 40 and 0.6 K when VZAs are in 40-50.Because the uncertainty increases when VZAs are larger than 50,the best range of VZAs is 30-50.The vicarious calibration results at Lake Qinghai field indicated that the calibration precision of the DM cross-calibration by using MODIS bands 31 and 32 as reference channels to calibrate IRS band 08 is similar to that of vicarious calibration.Therefore,the DM is a reliable alternative tool for sensor on-orbit calibration and validation with high precision and frequency.