Cross-calibration between MWRI and AMSR2 to improve consistency of snow depth products

The Microwave Radiation Imager (MWRI), boarded on the FY-3 series satellites: FY-3B, FY-3C, and FY-3D, is thefirst satellite-based microwave radiometer in China, commencing passive microwave brightness temperature dataacquisition since 2010. The Advanced Microwave Scanning Radiometer 2 (AMSR2) boarded on the Global ChangeObservation Mission 1st-Water (GCOM-W1), has been operational since 2012. Despite the FY-3 series satellitesare equipped with the same MWRI and all MWRIs sharing comparable parameters and configurations as AMSR2,disparities in observation times and satellite platforms result in inconsistencies in the data obtained by differentsatellites, which further impacting the consistency of retrieved geophysical parameters. To improve the consistency of brightness temperatures from FY-3B, FY-3C, FY-3D/MWRI, and GCOM-W1/AMSR2, cross-calibrationswere conducted among brightness temperatures at ten-channel from above four platforms. The consistency ofderived snow depth from MWRIs and AMSR2 in China before and after the calibration were also analyzed. Theresults show that the correlation coefficients of brightness temperatures at all channels between sensors exceed0.98. After cross-calibration, the RMSEs and biases of brightness temperatures at all frequencies and snow depthin China derived from them reduce to varying degrees. The consistencies in both brightness temperatures andsnow depth of FY-3B/MWRI, FY-3D/MWRI, and AMSR2 are higher than those of FY-3C and others. These findingsadvocate for the utilization of cross-calibrated brightness temperatures from FY-3B/MWRI, FY-3D/MWRI, andAMSR2, which share similar satellite overpass time, to derived a long-term snow depth dataset.

Radiometric cross-calibration of the CBERS-02 CCD camera with the TERRA MODIS

For the application of the CCD camera, the most important payload on CBERS-02, the key is to provide long-term stable radiometric calibration coefficients. Although the vicarious calibration had been proved successful, it had its limitations such as test site requirement and unsuitable for historical data. Cross-calibration is one of the alternative methods, but it needs synchro surface spectrum to achieve spectral band matching factors. Our effort is to probe the influences on these factors. Simulations with a lot of surface spectrum showed that the factors changed with the viewing geometry, atmospheric condition and surface targets. However, simulating with the same viewing geometry and atmospheric condition, the spectral band matching factors of the same or similar surface targets’ spectrum acquired from different dates and different places would like to be consistent to each other within 1%―5%. Thus, the synchro measurement data can be substituted by the same or similar target from other source. Based on this method, using the MODIS as the reference, the cross-calibration was performed for CCD camera. The research demonstrated that the traditional method with single calibration site was inappropriate for CCD camera, since the offsets for its four spectral bands were not zeros. With four calibration sites, these offsets were obtained. And the camera was detected to degrade with dates based on four times of cross-calibrations.

Radiometric Cross-Calibration for Multiple Sensors with the Moon as an Intermediate Reference

The instrument cross-calibration is an effective way to assess the quality of satellite data. In this study, a new method is proposed to cross-calibrate the sensors among satellite instruments by using a RObotic Lunar Observatory(ROLO) model and Apollo sample reflectance in reflective solar bands(RSBs). The ROLO model acts as a transfer radiometer to bridge between the instruments. The reflective spectrum of the Apollo sample is used to compensate for the difference in the instrument's relative spectral responses(RSRs). In addition, the double ratio between the observed lunar irradiance and the simulated lunar irradiance is used to reduce the difference in instrument lunar viewing and illumining geometry. This approach is applied to the Moderate Resolution Imaging Spectroradiometer(MODIS), the Sea-Viewing Wide Field-of-View Sensor(Sea Wi FS), and the Advanced Land Imager(ALI) on board three satellites, respectively. The mean difference between MODIS and Sea Wi FS is less than 3.14%, and the difference between MODIS and ALI is less than 4.75%. These results indicate that the proposed cross-calibration method not only compensates for the RSR mismatches but also reduces the differences in lunar observation geometry. Thus,radiance calibration of any satellite instrument can be validated with a reference instrument bridged by the moon.

Sentinel-2 MSI Radiometric Characterization and Cross-Calibration with Landsat-8 OLI

Near-nadir observations by the Multispectral Instrument (MSI) onboard the Sentinel-2 and the Operational Land Imager (OLI) onboard Landsat 8 were collected during two Simultaneous Nadir Overpasses (SNO). Multispectral images with 10, 20, and 30 m resolution from a spatially uniform area in the Saharan desert were acquired for direct comparison of MSI and OLI Top- Of-Atmosphere (TOA) reflectances. This paper presents an initial radiometric cross-calibration of the 8 corresponding spectral bands of the Sentinel-2 MSI and Landsat 8 OLI sensors. With the well-calibrated Landsat 8 OLI as a reference, the comparison indicates that 6 MSI bands are consistent with OLI within 3% in terms of spectral band adjustment factors Bi . The Near-Infra-Red (NIR) and cirrus bands are exceptions. They yield radiometric differences on the order of 8% and 15% respectively. Cross-calibration results show that the radiometric difference of the 7 corresponding bands are consistent to OLI within 1% or better, except on cirrus band. A pixel-by-pixel match between the MSI and OLI observations for different land covers showed that. This initial study suggests that the red-edge band B8A of MSI can be used to replace the NIR band B08 when conducting vegetation monitoring.

Robust Radiometric Normalization of the near Equatorial Satellite Images Using Feature Extraction and Remote Sensing Analysis

Relative radiometric normalization (RRN) minimizes radiometric differences among images caused by inconsistencies of acquisition conditions rather than changes in surface. Scale invariant feature transform (SIFT) has the ability to automatically extract control points (CPs) and is commonly used for remote sensing images. However, its results are mostly inaccurate and sometimes contain incorrect matching caused by generating a small number of false CP pairs. These CP pairs have high false alarm matching. This paper presents a modified method to improve the performance of SIFT CPs matching by applying sum of absolute difference (SAD) in a different manner for the new optical satellite generation called near-equatorial orbit satellite and multi-sensor images. The proposed method, which has a significantly high rate of correct matches, improves CP matching. The data in this study were obtained from the RazakSAT satellite a new near equatorial satellite system. The proposed method involves six steps: 1) data reduction, 2) applying the SIFT to automatically extract CPs, 3) refining CPs matching by using SAD algorithm with empirical threshold, and 4) calculation of true CPs intensity values over all image’ bands, 5) preforming a linear regression model between the intensity values of CPs locate in reverence and sensed image’ bands, 6) Relative radiometric normalization conducting using regression transformation functions. Different thresholds have experimentally tested and used in conducting this study (50 and 70), by followed the proposed method, and it removed the false extracted SIFT CPs to be from 775, 1125, 883, 804, 883 and 681 false pairs to 342, 424, 547, 706, 547, and 469 corrected and matched pairs, respectively.

Cross-calibration of brightness temperature obtained by FY-3B/MWRI using Aqua/AMSR-E data for snow depth retrieval in the Arctic

This study cross-calibrated the brightness temperatures observed in the Arctic by using the FY-3B/MWRI L1 and the Aqua/AMSR-E L2A.The monthly parameters of the cross-calibration were determined and evaluated using robust linear regression.The snow depth in case of seasonal ice was calculated by using parameters of the crosscalibration of data from the MWRI Tb.The correlation coefficients of the H/V polarization among all channels Tb of the two sensors were higher than 0.97.The parameters of the monthly cross-calibration were useful for the snow depth retrieval using the MWRI.Data from the MWRI Tb were cross-calibrated to the AMSR-E baseline.Biases in the data of the two sensors were optimized to approximately 0 K through the cross-calibration,the standard deviations decreased significantly in the range of 1.32 K to 2.57 K,and the correlation coefficients were as high as 99%.An analysis of the statistical distributions of the histograms before and after cross-calibration indicated that the FY-3B/MWRI Tb data had been well calibrated.Furthermore,the results of the cross-calibration were evaluated by data on the daily average Tb at 18.7 GHz,23.8 GHz,and 36.5 GHz(V polarization),and at 89 GHz(H/V polarization),and were applied to the snow depths retrieval in the Arctic.The parameters of monthly cross-calibration were found to be effective in terms of correcting the daily average Tb.The results of the snow depths were compared with those of the calibrated MWRI and AMSR-E products.Biases of 0.18 cm to 0.38 cm were observed in the monthly snow depths,with the standard deviations ranging from 4.19 cm to 4.80 cm.

Uncertainty Evaluation for Comparison Result of National Radiometric Standardsand World Radiometric Reference

Theuse of data of National Radiometric Standardtook place in the WMO International Pyrheliometer Comparisons IPCXI to evaluate the expended uncertainty of the comparison resultbetweenN ational Radiometric Standards( NRS) and the World Radiometric Reference( WRR) in Davos/World Radiometric Center. The result of expended uncertaintyis 0.17%,which meets the requirements of the World Meteorological Organization( WMO) and has reached the world advanced level.In this paper,the method can be used as a reference and basis for evaluating the uncertainty of thecomparison results of the Provincial solar radiation standard.

Geological Mapping Using Satellite Remote Sensing and Spectro-Radiometric Measurements in Cyprus

Our goal is to map the different geological features using satellite remotely sensed images of Cyprus acquired both from Landsat5/7 TM/ETM+,ASTER and Quickbird sensors.We want to distinguish such features on the basis of their spectral characteristics.Detailed reflectance spectra have been acquired using the SVC HR-1024 field spectroradiometer.This spectral information with results of a field visit has been used to determine how to process the spectra using image data. Other goals of this study are to explore the differences between the map arrived through image processing and

Modeling the radiometric imaging process of weld pool

In the vision monitoring or controlling the arc welding process, it is a prerequisite to get a clear image of weld pool. However, the disturbance of arc radiation makes imaging of weld pool difficult and optical filters are usually used to improve the image quality. In this paper, a radiometric imaging model is established to investigate the influence of the filter on the image quality of the weld pool, in which the spectral distribution of weld pool radiation, the spectral transmittance of the filter, the spectral sensitivity of the camera are all considered. With the proposed model, the influence of the factors on weld pool imaging can be inferred and the selection of optical filters is discussed.

Estimating vertical vegetation density through a SPOT5 imagery at multiple radiometric correction levels

There is growing concern about remote sensing of vertical vegetation density in rapidly expanding peri-urban interfaces. A widely used parameter for such density, i.e., leaf area index （LAI）, was measured in situ in Nanjing, China and then correlated with two vegetation indices （VI） derived from multiple radiometric correction levels of a SPOT5 imagery. The VIs were a normal- ized difference vegetation index （NDVI） and a ratio vegetation index （RVI）, while the four radiometric correction levels were i） post atmospheric correction reflectance （PAC）, ii） top of atmosphere reflectance （TOA）, iii） satellite radiance （SR） and iv） digital number （DN）. A total of 157 LAI-VI relationship models were established. The results showed that LA! is positively correlated with VI （r varies from 0.303 to 0.927, p 〈 0.001）. The R： values of＂pure＂ vegetation were generally higher than those of mixed vegetation. The average R2 values of about 40 models based on DN data （0.688） were higher than that of the routinely used PAC （0.648）. Independent variables of the optimal models for different vegetation quadrats included two vegetation indices at three radiometric correction lev- els, indicating the potential of vegetation indices at multiple radiometric correction levels in LAI inversion. The study demonstrates that taking heterogeneities of vegetation structures and uncertainties of radiometric corrections into account may help full mining of valuable information from remote sensing images, thus improving accuracies of LAI estimation.

Estimation Accuracy for Reciprocal Analysis of Sensible and Latent Heat Flux Focusing on Radiometric Temperature and Lag-Time

There is no word to describe the importance of evapotranspiration research for water resource utilization. We have already proposed a new method for the reciprocal estimation of the sensible (H) and latent heat fluxes (lE) by using a single height temperature (Tz) and humidity (rehz) based on the observed net radiation (Rn) and ground heat flux (G). This research is more advanced than the previous research because it uses a Ts observed by a radiometer and identifies the observed data satisfactorily heat balance relationship in every hour at nine sites. First, we confirmed that the estimated H and lE are very close reproductions of the identified H and lE. Second, by analyzing the relative ground surface temperature (Ts - T0) [Ts: ground surface temperature, T0: observed temperature near the soil surface], the hourly and seasonal changes of (Ts - T0) were clarified, resulting in a marked difference in the (Ts - T0) from previous research in arid and semi-arid regions. Next, the estimation accuracy of H, lE and rehs (the humidity of the soil surface) was determined by observing the slope of the estimated and observed relationship, resulting in the reasonable accuracy (0.85 - 1.15 times) of rehs at seven of the nine sites. Furthermore, the annual evapotranspiration was estimated by comparing the identified and estimated H and lE, resulting in a reasonable accuracy (0.85 - 1.15) at five of the nine sites in the case of the application of constraint b. Moreover, the effect of the lag-time between the net radiation Rn and both Tz and Ts for the estimation accuracy on H and lE was tested, and no remarkable difference was found because the effect was included already in the original data. The above results will contribute greatly to the advance of water resource planning and hydrometeorology. This research was conducted using FLUXNET data.

Petrographic, Radiometric and Paleomagnetic Studies for Some Alkaline Rocks, South Nusab El Balgum Mass Complex, South Western Desert, Egypt

Nusab El Balgum mass complex represents one of the alkaline igneous activities in the south Western Desert of Egypt. Petrographic investigations defined some different rock types in south of the complex represented by alkaline volcanics (pyroclastics [rhyolitic crystal tuffs], spherulitic rhyolites, alkaline rhyolite dykes), sub-volcanic peralkaline granites and structurally controlled mylonitic volcanoclastics. These rocks recorded significant concentrations in terms of the two radioactive elements Th and eU, which displayed considerable spatial variations, especially within the peralkaline granites. The abundance of Th and eU is mainly related to favorable combination of structural and pos-magmatic hydrothermal conditions. Paleomagnetic results give well-defined stable remanent magnetization directions of reliable VGP positions, which are presented and discussed in the context of the African APWP. Rock types, magnetization directions and VGP positions with the corresponding ages are as follows: 1) Rhyolitic crystal tuffs;D/I = 340.0°/—19.4°, α95 = 6.8°;VGP Lat./Long. = 51.4°N/240.5°E, A95 = 5.9° (Late Triassic). 2) Spherulitic rhyolites;D/I = 346.7°/—6.6°, α95 = 3.5°;VGP Lat./Long. = 60.4°N/237.0°E, A95 = 3.0° (Late Triassic/Early Jurassic). 3) Alkaline rhyolite dykes;D/I = 341.3°/16.7°, α95 = 5.4°;VGP Lat./Long. = 67.0°N/262.8°E, A95 = 4.2<span

Combined Radiometric Analysis Related to Guava Leaf Phenology in Response to Soil Application of Paclobutrazol (PBZ)

The leaf-response to three-soil applied treatments of Paclobutrazol (PBZ;1000, 2000 and 0 ppm-control) was studied in a high-density plantation of eight guava (Psidium guajava) genotypes trees. All materials were prunned in vase form, with two to three major branches, yearly prunning for triggering the annual production cycle, and average height of 2.0 m. The dataset comprises fourth radiometric indices highly related to plant physiological activities. The dataset model took into account data collection dates, guava genotypes, and the positional effect of sun radiation on leaves based on their proximity to the canopy level and downward to the base of the woody seasonal-branch. Unexpectedly, there were no significant differences (NS) in PBZ treatments for genotypes, leaf position and radiometric indices. Analysis of the radiometric indices data revealed that anthocyanin (ARI index) and chlorophyll (PRI index) have a strong inverse relationship. Significant differences (P ≤ 0.05) were found between guava genotypes, and anthocyanin content;these results show that guava genotypes have varied responses, which could derive in their classification based-on drought resistance or low water requirements, however, it is important to note that additional research is required to determine the scope of these indications.

Radiometric Characteristics of the Landsat Collection 1 Dataset

This study evaluates the long-term radiometric performance of the USGS new released Landsat Collection 1 archive, including the absolute calibration of each Landsat sensor as well as the relative cross-calibration among the four most popular Landsat sensors. A total of 920 Landsat Collection 1 scenes were evaluated against the corresponding Pre-Collection images over a Pseudo-Invariant Site, Railroad Valley Playa Nevada, United States (RVPN). The radiometric performance of the six Landsat solar reflective bands, in terms of both Digital Numbers (DNs) and at-sensor Top of Atmosphere (TOA) reflectance, on the sensor cross-calibration was examined. Results show that absolute radiometric calibration at DNs level was applied to the Landsat-4 and -5 TM (L4 TM and L5 TM) by –1.119% to 0.126%. For L4 TM and L5 TM, the cross-calibration decreased the radiometric measurement level by rescaling at-sensor radiance to DN values. The radiometric changes, –0.77% for L4 TM, 0.95% for L5 TM, –0.26% for L7 ETM+, and –0.01% for L8 OLI, were detected during the cross-calibration stage of converting DNs into TOA reflectance. This study has also indicated that the long-term radiometric performance for the Landsat Collection 1 archive is promising. Supports of these conclusions were demonstrated through the time-series analysis based on the Landsat Collection 1 image stack. Nevertheless, the radiometric changes across the four Landsat sensors raised concerns of the previous Landsat Pre-Collection based results. We suggest that Landsat users should pay attention to differences in results from Pre-Collection and Collection 1 time-series data sets.

Solar Multi-Spectral Radiometric Observations of Atmospheric Optical Thickness over Passarlapudi Gas Well Blow-Out Site in India

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Measuring Radiometric Quantities of Light Source by Way of Algebraic Insert

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敦煌戈壁地表反射率光谱的旋翼无人机测量及定标评估

利用敦煌中国遥感卫星辐射校正场的星地同步观测试验,实现对我国在轨气象、海洋、陆地资源、环境减灾、测绘地震、高分、军事等系列卫星光学成像载荷太阳反射波段的绝对辐射定标,是目前的重要手段之一。然而,中国遥感卫星辐射校正场传统的地表反射率光谱星地同步测量方法是基于汽车跑场观测,不仅耗费较大的人力物力、容易造成场地破坏,而且获取的测量数据缺乏区域代表性。鉴于此,自2016年起,在敦煌星地同步观测试验中以旋翼无人机低空同步测量为主,跑场测量为辅,完成从航线设计、航高选择、仪器参数配置、采样策略、航空数据处理的全链路摸底测试。多次飞行试验表明,采用多旋翼无人机低空飞行来代替汽车跑场同步测量,不仅提高了地表反射特性测量的空间一致性和代表性,还提高了地表反射率光谱的测量效率,也对宝贵的中国遥感卫星辐射校正场敦煌戈壁场区地表进行了有效保护,极大的节约了人力物力成本。通过传统跑场测量和航飞测量的地表反射率光谱数据对比分析,发现多次测量数据的均值一致性较好,并且航飞测量的数据标准差更小。利用TERRA MODIS的同步观测来对无人机测量数据开展辐射定标评估,结果表明航飞数据的相对偏差均在5%以内,可以代替跑场数据完成定标,精度满足要求。随着无人机性能的进一步优化和提高,在不久的将来必将得到更加广泛和深入的应用,在外场定标试验领域也将发挥更大更重要的作用。

基于幂加权最小二乘拟合的红外相机辐射定标方法

分析了现有线性度计算方法的不足,提出基于偏差/测量值的新线性度评价方式,通过该方式最小二乘拟合的低端温度偏差比高端大一个数量级,并采用加权拟合提高系统响应线性度。在分析不同光谱的温度和辐亮度拟合函数基础上,提出一种基于辐亮度倒数幂加权最小二乘线性拟合的地面和星上辐射定标方法,确认最佳权重幂次,建立了幂次n=1的加权最小二乘拟合外黑体线性定标方程、内黑体线性定标方程、内外黑体辐亮度转换模型。针对星上内黑体高精度两点定标建立了基于加权最小二乘拟合内外黑体辐亮度转换模型;针对星上黑体发射率退化提出了基于恒星定标的红外相机星上内黑体辐亮度定标修正方法,建立了外黑体辐亮度、内黑体辐亮度和恒星辐亮度转换模型。采用加权线性拟合后,积分时间10 ms的低温端外黑体反演偏差由1.63 K下降到0.52 K,内黑体偏差反演温度偏差由0.83 K下降到0.39 K,系统响应线性度明显提升。

低空无人机多光谱传感器辐射定标

高精度辐射定标对于无人机遥感数据定量化应用至关重要.以大疆精灵4 RTK多光谱传感器为例,基于多种典型地物和人工靶标,实现了该传感器全动态范围的辐射定标.在开展真实性检验后,探讨了曝光时间和光谱响应函数对定标结果的影响.研究表明,定标结果具有较高的定标精度,各波段RMSE均优于3.25%,且脉冲型光谱响应函数更适用于该传感器.另外,曝光时间会对中高亮度地物产生较大影响,容易出现过饱和现象.

FY-3D MERSI-Ⅱ反射太阳波段长期响应衰减估计及订正方法

遥感仪器的长期辐射响应衰减估计与订正是提高卫星遥感数据稳定性和准确性的关键。利用MERSI-Ⅱ在沙漠和DCC稳定目标上空的长时间观测数据,建立仪器辐射响应与时间的函数关系模型,并通过逆方差加权平均方法融合两种稳定目标的结果,获取仪器辐射响应退化量和辐射定标系数的序列估计。辐射响应衰减跟踪监测结果表明,MERSI-Ⅱ自在轨开始业务运行到2022年9月,波长小于500 nm的3个蓝光波段(通道1,通道8—9)和波长大于1000 nm的4个近红外-短波红外波段(通道5—7,通道19)存在明显衰减,年衰减率为1.47%~4.32%。L1级产品精度检验也发现,7个明显衰减通道的业务定标偏差均超过±5%,其中通道5和8偏差最大,约为-20%。应用本研究获取的辐射定标系数序列后,L1产品辐射定标精度随时间变化平稳,定标偏差维持在±3%以内,同时L2级产品精度也明显提升,表明了该研究建立的辐射衰减估计与订正方法的有效性。