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.

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.

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.

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

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

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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.

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.

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.

Measuring Radiometric Quantities of Light Source by Way of Algebraic Insert

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Evaluation and adjustment of the radiometric degradation of HY-1B satellite COCTS via a stable marine site

The Chinese Ocean Color and Temperature Scanner(COCTS)on-board the Chinese second ocean color satellite,HY-1B,obtained approximately 6 years of data between 2007 and 2013 in China coastal seas and the adjacent waters.However,its radiometric performance has hardly been analyzed,which confuses its applicability in ocean remote sensing.This study tracked the long-term radiometric responsivity trend of HY-1B COCTS based on a stable marine target.Firstly,we identified a temporally stable maritime site of 12°~15°N and 116°~119°E according to the water and atmospheric optical properties using Aqua MODIS products.Then,the time-series of top-of-atmosphere(TOA)reflectance was obtained for each band of HY-1B COCTS and Aqua MODIS over this site according to the criteria of sun-target-view geometry.Finally,exponential or linear degradation models were built and used to adjust the radiometric levels of HY-1B COCTS.Results indicate that the radiometric performance exhibited continuous degradation for all bands at varying levels between 0.4%and 8.1%yr^(−1).The worst degradation occurred at 412 nm,with an annual average rate of 8.1%.The degradation at 443 nm reached 5.5%yr^(−1)following 412 nm.The radiometric performance at 490 nm,520 nm,and 565 nm was relatively stable with a drift of~3%yr^(−1).The 670 nm,750 nm,and 865 nm bands remain most stable with the degradation of~1%yr^(−1).Taking Terra MODIS as a reference,the temporal consistency of HY-1B COCTS was significantly improved for each band after radiometric adjustment.Cloud-free imageries between 2007 and 2013 showed relatively high spatial consistency.The bias of TOA reflectance was~5%in visible bands and~10%in near-infrared bands after degradation correction.These improvements confirm the application potentials of HY-1B COCTS in ocean remote sensing.

Support vector machine regression(SVR)-based nonlinear modeling of radiometric transforming relation for the coarse-resolution data-referenced relative radiometric normalization(RRN)

Radiometric normalization,as an essential step for multi-source and multi-temporal data processing,has received critical attention.Relative Radiometric Normalization(RRN)method has been primarily used for eliminating the radiometric inconsistency.The radiometric trans-forming relation between the subject image and the reference image is an essential aspect of RRN.Aimed at accurate radiometric transforming relation modeling,the learning-based nonlinear regression method,Support Vector machine Regression(SVR)is used for fitting the complicated radiometric transforming relation for the coarse-resolution data-referenced RRN.To evaluate the effectiveness of the proposed method,a series of experiments are performed,including two synthetic data experiments and one real data experiment.And the proposed method is compared with other methods that use linear regression,Artificial Neural Network(ANN)or Random Forest(RF)for radiometric transforming relation modeling.The results show that the proposed method performs well on fitting the radiometric transforming relation and could enhance the RRN performance.

Radiometric normalization of overlapping LiDAR intensity data for reduction of striping noise

Airborne LiDAR data are usually collected with partially overlapping strips in order to serve a seamless and fine resolution mapping purpose.One of the factors limiting the use of intensity data is the presence of striping noise found in the overlapping region.Though recent researches have proposed physical and empirical approaches for intensity data correction,the effect of striping noise has not yet been resolved.This paper presents a radiometric normalization technique to normalize the intensity data from one data strip to another one with partial overlap.The normalization technique is built based on a second-order polynomial function fitted on the joint histogram plot,which is generated with a set of pairwise closest data points identified within the overlapping region.The proposed method was tested with two individual LiDAR datasets collected by Teledyne Optech’s Gemini(1064 nm)and Orion(1550 nm)sensors.The experimental results showed that radiometric correction and normalization can significantly reduce the striping noise found in the overlapping LiDAR intensity data and improve its capability in land cover classification.The coefficient of variation of five selected land cover features was reduced by 19–65%,where a 9–18%accuracy improvement was achieved in different classification scenarios.With the proven capability of the proposed method,both radiometric correction and normalization should be applied as a pre-processing step before performing any surface classification and object recognition.

High-accuracy primary and transfer standards for radiometric calibration

The first research and experimental results obtained in China of high-accuracy radiometric calibration based on cryogenic radiometer are reported. Uncertainties of cryogenic radiometer and trap detectors at 7 wavelengths in the visible spectrum (488-786 nm) were less than 0.023% and 0.035% respectively, which proved the reasonability and possibility of establishing and transferring high-accuracy radiometric standards based on detectors.

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.

Study on the relative radiometric correction of CBERS satellite CCD image

The main payload on CBERS-01/02 of China-Brazil Earth Resources Satellite (CBERS) is a push-broom CCD camera with moderate spatial and radiant resolution. Because at lab the data for calibration at satellite assembly stage were unable to be collected, and also because the onboard calibrator after launch was in a different state from imaging, the calibration of CCD image got a series of difficulties involved. In practice, two methods are used in the processing on the ground station: One is extracting calibration data by statistics from the image itself, and the other is the method of histogram match. It was proved that the latter can calibrate the image much better, because it can remove the effect of unstable response of the camera largely and also can overcome the nonlinearity of the camera basically by using Look-Up Table (LUT) calculated from histogram statistics of different temporal images. Considering the problems of CBERS-01, a lot of calibration tests were done before the launch of CBERS-02, in which a set of lab coefficients for relative calibration was formulated after the data collection by using integration-hemisphere in the stage of satellite assembly test. During the on-orbit test, it was found that the calibration result from such coefficients was not satisfying, especially there being response difference between 3 detector arrays, which was attributed to the unstable dark currents of the CCD camera. This paper comes up with a statistic method to remove such response difference. In this method the middle detector array was used as reference to find the response differences of adjacent similar features between these arrays and it was proved to have a broad adaptability.

Stepwise decomposition and relative radiometric normalization for small footprint LiDAR waveform

As an advanced generation instrument of earth observation,small footprint full waveform light detection and ranging(LiDAR) technology has been widely used in the past few years.Decomposition and radiative correction is an important step in waveform data processing,it influences the accuracy of both information extraction and further applications.Based on a stepwise strategy,this study adopts Gaussian mixture model to approximate the LiDAR waveform.In addition to waveform decomposition,a relative correction model is proposed in this paper,the model considers the transmit pulses as well as the different of the travel path for implementing LiDAR waveform relative correction.Validation of the stepwise decomposition and relative correction model are carried out on LiDAR waveform acquired over Zhangye,China.The results indicate that stepwise decomposition identified the number of peaks in LiDAR waveforms,center position and width of each peak well.The relative radiometric correction also improves the similarity of waveforms which acquired at the same target.

VICARIOUS RADIOMETRIC CALIBRATION OF SATELLITE FY-ID SENSORS AT VISIBLE AND NEAR INFRARED CHANNELS

For the problem of in-flight test site radiometric calibration for the FY-1D Meteorological Satellite onboard sensor's visible and near infrared channels,this paper described the calibration method,satellite-ground synchronous observation data acquired at China Dunhuang Calibration Test Site,parameter derivation and radiative transfer computation during the calibration,and the calibration result analysis.At FY-1D seven channels (with central wavelength at Channels 1:630 nm,2:865 nm;6:1610 nm;7:455 nm,8:505 nm;9:555 nm;10:932 nm),calibration coefficients obtained during the ground site calibration were compared with that respectively of pre- launch calibration.It is demonstrated that results of FY-1D onboard two sensors' (A and B) at channels 1,2,6 and 10 were close to pre-calibration,and the absolute difference of Gobi desert reflectance computed using test site and pre-launch calibration coefficients was no more than 2%. At other channels,large pre-launch calibration errors resulted in a poor consistency between the test site and pre-launch calibration.The errors can be corrected by the test site calibration results. Based on a rough estimation,the overall error of the calibration was about 6%. The paper also presented the in-flight vicarious calibration at the visible and near infrared channels of FY-1C sensor A which was launched in 1999 and has been put into operational mode since 2002.The results exhibit that FY-1C sensor's response has 23% attenuation at Channels 7 and 8,while only minor degradation at the other channels was found. During the mission,calibrations were also conducted at NOAA-17's Channels 1 and 2 (1:430 -830 nm,2:500--1072 nm).A very good consistency has been achieved between the test site and pre-launched calibration results.

Outdoor relative radiometric calibration method using gray scale targets

The radiometric calibration of remote sensors is a basis and prerequisite of information quantification in remote sensing. This paper proposes a method for outdoor relative radiometric calibration using gray scale targets. In this method, the idea of two substitutions is adopted. Sunlight is used to replace the integrating sphere light source, and gray scale targets are used to re-place the diffuser. In this way, images at different radiance levels obtained outdoors can calculate the relative radiometric cali-bration coefficients using the least square method. The characteristics of this method are as follows. Firstly, compared with la-boratory calibration, it greatly reduces the complexity of the calibration method and the test cost. Secondly, compared with the existing outdoor relative radiometric calibration of a single radiance level, it uses test images of different radiance levels to re-duce errors. Thirdly, it is easy to operate with fewer environmental requirements, has obvious advantages in the rapid calibra-tion of airborne remote sensors before or after flight and is practical in engineering. This paper theoretically and experimental-ly proves the feasibility of this method. Calibration experiments were conducted on the wide-view multispectral imager (WVMI) using this method, and the precision of this method was evaluated by analyzing the corrected images of large uniform targets on ground. The experiment results have demonstrated that the new method is effective and its precision meets the re-quirement of the absolute radiometric calibration.