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

With the requirement of quantitative application of remote sensing, it is more pressing to improve the accuracy of remote sensing. Slater proposed a calibration method using a large homogeneous surface target [1], which has been proved promising and has been applied to many sensors[2―10], such as TM, ETM+, HRVIR. However, this method re-quired so much labor and fund that it could not produce enough calibration coefficients. In addition, it could not be applied to history data. Later, many…     

Water target based cross-calibration of CBERS-02 CCD camera with MODIS data

In order to make quantitative watercolor sensing with China-Brazil Earth Resources Satellite (CBERS-02) CCD camera, the MODIS data with higher accuracy is used to cross-calibrate the CCD camera over water targets. In homogeneous clear water area, two pairs of images obtained over the same area on the same day by the two sensors are selected. The top-of-atmosphere (TOA) radiances of the multispectral bands of CCD are calculated with the water and aerosol parameters from MODIS based on a water-atmosphere radiative transfer algorithm. The stripes in CCD image that caused by unequal response of the CCD array detectors are firstly removed before making the cross-calibration. The same part of CCD detectors is selected for the calibrations in the two images to eliminate the residual error of destriping and uniformity correction for the focus plane irradiance. It is shown that the calibration results from two different images are consistent. The error of this method is about 5%.     

Water target based cross-calibration of CBERS-02 CCD camera with MODIS data

The CBERS-02, the second satellite of China Brazil Earth Resources Satellite series, was launched on Oct. 21, 2002. Onboard the satellite, there are three major sensors, a CCD camera, a wide field imager and an infrared multispectral scanner (http://www. cresda.com). The purpose of this paper is to calibrate the CCD camera with a methodol- ogy of cross-calibration. The spatial resolution of the multispectal bands of CCD camera is 19.5 m, the swath is about 115 km. It is capable of side…     

In flight MTF monitoring and compensation for CCD camera on CBERS-02

In this article, the approach of simulating ideal tarp scene was proposed to determine the MTF for CCD camera on CBERS-02. The MTF acquired from this technique was compared to those from some common methods. MTFs achieved from different approaches were employed to compensate the CCD images based on three restoration algorithms: the iterative method, the Wiener filter and the modified inverse filter (MIF). The two-dimensional MTF was established with the value at frequency 0.5 for 45° directional MTF as the value at its four corners. This article addressed the variations of the restored CCD images with different techniques of constructing two-dimensional MTF, restoring algorithms and determining the in-flight MTFs. Results showed images restored with the MTF determined from the technique of simulating ideal tarp scene represent the real scene best. And the restoration technique based on the MIF would produce better restored images than the other two techniques. This research also demonstrated that the two-dimensional MTF used for restoration should be interpolated under the control of the MTF for 45° axis, rather than by multiplying the cross-orbit MTF with along-orbit MTF.     

In flight MTF monitoring and compensation for CCD camera on CBERS-02

All image systems cause a blurring of the scene radiance field during image acquisi- tion. Accurate characterization of this blurring is referred to as the modulation transfer function (MTF)[1]. The MTF is a fundamental imaging system design specification and system quality metric often used in remote sensing. It results from the cumulative effects of the instrumental optics (diffraction, aberrations, focusing error), integration on a pho- tosensitive surface, charge diffusion along the arra…     

Comparison of the influence factors onNDVI for CCD camera and WFI imager on CBERS-02

CCD and WFI are payloads in the visible light and near infrared bands on CBERS satellites and they have not been applied widely, especially WFI. This article mainly probes into the potential of these two sensors’ application in the vegetation monitoring and analyses the influences of radiometric calibration, atmosphere conditions and sun-observing geometry, etc. onNDVI obtained from these two sensors respectively. In addition it analyses the effect of the spectral response difference of red and near infrared spectral bands in CCD and WFI sensors onNDVI. Results indicate that radiometric calibration is the most important factor onNDVI, which cannot be applied to vegetation monitoring without radiometric calibration. Results also demonstrate that near surfaceNDVI is different greatly from that of TOA which change with atmosphere conditions. The study shows thatNDVI is also affected by the non-lambertian character of surface and the change of the atmospheric path with the observing geometry. AndNDVI of WFI is higher than that of CCD. They are very different because of their spectral diffirence, but they have a good linear relevant relationship.

     

Comparison of the influence factors on NDVI for CCD camera and WFI imager on CBERS-02

China Brazil Earth Resources Satellites (CBERS) have many payloads, among them there are a high resolution Charge Coupled Device (CCD) Camera and the Wide Field Image (WFI). CCD’s spatial resolution in nadir is 19.5 meters and its swath width is 113 kilometers. It has 4 wave bands and a panchromatic wave band in visible and near infra- red spectral band. Side looking is one of the main functions of CCD and the side looking range is ±32°. WFI has one visible band and one near inf…     

Biomass estimation and uncertainty analysis based on CBERS-02 CCD camera data and field measurement

The study on terrestrial ecosystem carbon cycle has been the focus of global change research and regional sustainable development research. It is well known that terrestrial ecosystem is the largest unknown area[1] in seeking the missing carbon sink[2]. Because it is allowed in the Kyoto Protocol that adding CO2 absorption by foresting and reforesting can offset greenhouse gases emission, the mechanism of carbon sequestration and thedistribution and mapping of carbon pool have been the focus …     

Biomass estimation and uncertainty analysis based on CBERS-02 CCD camera data and field measurement

The study site is located in Qianyanzhou experimental station and the surrounding area. Based on CBERS-02 satellite data and field measurement, we not only discussed the relationship between NDVI and biomass of two species of coniferous plantations, namely,Pinus massoniana Lamb andPinus elliottii Engelm, but also introduced the biomass models based on NDVI. The comparison between measured biomass in Qianyanzhou and biomass derived from CBERS-02 CCD data showed that it is feasible to estimate biomass based on NDVI. But its limitations cannot be ignored. This kind of model depends on the dominant vegetation species. There are some effect factors in estimating biomass based on NDVI. This paper analyzes these factors based on fine-resolution CBERS-02 CCD data and some conclusions are drawn: In Qianyanzhou, the area with good vegetation coverage, the nonlinearity of NDVI has little influence on scaling-up of NDVI. As a result of surface heterogeneity, scaling-up can cause NDVI within each pixel to change. Because scaling-up can cause pixel attribute to change, the applicability of biomass model is one of the sources of error in estimating biomass.     

Estimating surface evapotranspiration using combined MODIS and CBERS-02 data

Spatial scale error is one of the most serious problems in the estimates of land surface heat fluxes of sensible and latent from satellite-borne data such as MODIS 1km resolution reflectance and emissive data. One of the feasible and economic ways to decrease the spatial scale error is to use high resolution land use class data together with the MODIS data. CBERS-02 data were used to produce land use class of Baiyangdian area, Hebei Province, China in the autumn of 2004. The area ratio of each class in MODIS pixel was calculated, and used to derive the heat fluxes of the mixed pixel. The results showed that the estimated heat fluxes of soil, sensible and latent have been changed remarkably after using the high resolution land class data. It could be concluded from the comparison between simulated and ground-measured fluxes as well as the theoretical analysis that high resolution land class data are useful to diminishing the scale error of heat fluxes estimated from low resolution satellite data.

     

Estimating surface evapotranspiration using combined MODIS and CBERS-02 data

Land surface evapotranspiration is one of the most important components in water cycle between earth and atmosphere, and plays a very important role in the atmosphere, hydrosphere, and biosphere of the planet. It is an urgent task to understand the evapotranspiration process over different surface types and conditions in agriculture, hydrogeology, forest, and ecology for the purpose of using water resources properly. Additionally, land surface evapotranspiration is a key parameter in the synop…     

Cotton pixel identification with CBERS-02 CCD data based on spectral knowledge

In this paper thein-situ experiment data are collected from the Spectral Library to estimate the possible values of the primary structural parameters in each cotton growing season by statistics. Based on these values the spectra of the cotton major growing seasons were simulated and analyzed using the canopy reflectance model, SAILH. In this way we also simulated the cotton pixel spectra corresponding to CBERS-02 CCD and took them as the reference spectra for spectra fitting. Then No. 143 Regiment of No. 8 Agricultural Division of Xinjiang Production and Construction Corps (XPCC) was chosen as the study area, and two spectra fitting methods, Mahalanobis distance and spectra angle, were used to identify cotton pixel from CBERS-02 CCD image of the study area. At last we analyzed the effect of the calibration coefficients error on cotton identifying. The results showed that within 4% error the spectral angle classifier can still have a good performance.     

Cotton pixel identification with CBERS-02 CCD data based on spectral knowledge

CBERS-02 has three sensors, Charged Coupled Device (CCD), Infrared Multispectral Scanner (IRMSS) and Wide Field Imager (WFI). Similar to Landsat TM, CCD has 4 visible and near-infrared bands and one panchromatic band. The wavelength ranges are respectively 0.45-0.52 μm, 0.52-0.59 μm, 0.63-0.69 μm, 0.77-0.89 μm and 0.51 -0.73 μm. The spatial resolution is 19.5 m. CBERS-02 has three ground stations in Beijing, Guangzhou and Urumchi, which makes it cover the whole territory. …     

Comparison of the influence factors on<Emphasis Type="Italic">NDVI</Emphasis> for CCD camera and WFI imager on CBERS-02

CCD and WFI are payloads in the visible light and near infrared bands on CBERS satellites and they have not been applied widely, especially WFI. This article mainly probes into the potential of these two sensors’ application in the vegetation monitoring and analyses the influences of radiometric calibration, atmosphere conditions and sun-observing geometry, etc. onNDVI obtained from these two sensors respectively. In addition it analyses the effect of the spectral response difference of red and near infrared spectral bands in CCD and WFI sensors onNDVI. Results indicate that radiometric calibration is the most important factor onNDVI, which cannot be applied to vegetation monitoring without radiometric calibration. Results also demonstrate that near surfaceNDVI is different greatly from that of TOA which change with atmosphere conditions. The study shows thatNDVI is also affected by the non-lambertian character of surface and the change of the atmospheric path with the observing geometry. AndNDVI of WFI is higher than that of CCD. They are very different because of their spectral diffirence, but they have a good linear relevant relationship.     

Absolute radiometric calibration of CBERS-02 IRMSS thermal band

The China-Brazil Earth Resources Satellite (CBERS) was jointly developed by China and Brazil since 1988. The first CBERS (CBRES-01) was successfully launched on Oc- tober 14, 1999 and the second one (CBERS-02) on October 21, 2003. After finishing on-orbit tests of CBERS-02 in China, it was relegated to China Center for Resources Satellite Data and Applications (CRESDA) and switched to application and routine op- eration stage since January 2004. There are three sensors on C…     

Absolute radiometric calibration of CBERS-02 IRMSS thermal band

Based on the laboratory calibration before launch of CBERS-02 IRMSS thermal infrared channel, the onboard blackbody calibration, the radiometric crosscalibration against TERRA MODIS corresponding channel and the in-flight field calibration at Lake Qinghai: water surface radiometric calibration test site of China on Aug. 17, 2004 are carried out in this research. When making onboard blackbody calibration of CBERS-02 IRMSS, it is necessary to understand inside structures and light path in IRMSS camera and receive and process calibration blackbody signals at normal and high temperatures. Onboard blackbody calibration results of each detector are very important to relative radiometric calibration of images processing and absolute radiometric calibration of each detector. In-flight field calibration mainly contains field experiments, obtaining synchronous images, spectrum marching and MODTRAN radiative transmission computation. Radiometric cross-calibration of CBERS-02 IRMSS thermal band against TERRA MODIS selected 6 times synchronous images of two sensors passing through Lake Qinghai and Lake Taihu from August to December, 2004 to compute the cross calibration data. Combining the in-flight field calibration and radiometric cross calibration data, the absolute radiometric calibration coefficients are calculated by the linear regression method. This new calibration model can obviously control the radiometric calibration uncertainties aroused by the single point method used in the in-flight calibration of CBERS-02 IRMSS, this kind of sensors cannot receive the cosmic background radiation. In this research, the radiometric calibration coefficients obtained through the linear regression model are 8.53 (gain, unit: DN/W m^?2sr^?1μm^?1) and 44.92 (offset, unit: DN).     

Atmospheric correction of CBERS CCD images with MODIS data

China Brazil Earth Resource Satellite (CBERS) CCD images have much potential for inland water environmental monitoring. However, their atmospheric accuracy correction can affect their quantitative applications. This paper contains an atmospheric correction algorithm for CBERS CCD images with MODIS data from the same day, the use of which improves the atmospheric correction algorithm of ocean color remote sensing developed by Gordon (1993, 1994) and makes it applicable to inland waters. The improved algorithm retrieves atmospheric parameters from MODIS data and uses them to perform the atmospheric correction of CBERS CCD images. Experimental results show that the atmospheric correction algorithm of CBERS CCD images assisted by MODIS data is reliable. Furthermore, MODIS data can be freely obtained on a daily basis, making the algorithm developed in this paper useful for environmental monitoring of inland waters.     

Study of thin cloud removal method for CBERS-02 image

For several years, China Brazil Earth Resources Satellie (CBERS) data have been ap- plied to agriculture, irrigation works, zoology construction, environment protection, sustainable development, resource survey, etc. The applications have played important roles in country economic construction, and they have brought favorable social and economic benefits. They provide references for government decision-making and effi- cient information for the development of correlative industries. Furthe…     

Study of thin cloud removal method for CBERS-02 image

The China Brazil Earth Resources Satellite (CBERS) ended the dependence on foreign satellites. Along with the series of CBERS and the enhancement of satellite applications, it is necessary to search correlative data processing methods. Because cloud appears in the atmosphere, an image with clear sky conditions is often hard to obtain. How to remove cloud is an important sector of increasing image quality. An improved homomorphism filtering method is adopted to remove thin cloud qualitatively at first, and all bands are selected to classify pixels. Based on the fact that visible band images contain more aerosol effects than infrared bands, visible bands are used to determine clear or hazy regions and the reflectances of different surface classes in clear regions are calculated. At last the mean reflectance of the same classes in clear and hazy regions is matched to remove cloud. The image visual effect is improved; meanwhile, the ground reflectance is retrieved to meet the needs of remote sensing quantification.     

航空遥感面阵CCD相机像移速度计算方法

为提高航空遥感相机的照相分辨率,必须对航空遥感相机进行像移补偿。探讨一种面阵CCD相机像移速度的计算方法——坐标变换法,其原理是利用地面上相同点在相机姿态变换前后像面不同坐标值之间的矩阵关系求出像移量及像移速度。利用该方法计算航空遥感相机在垂直工作方式下像面中心点与像面上任一点由于飞机的姿态变化与飞机的飞行运动引起的前向像移速度和横向像移速度,并将此方法推广到倾斜式相机像移速度的计算中。