Assessment of the Radiometric Performance of Chinese HJ-1 Satellite CCD Instruments

Jiang, Bo; Liang, Shunlin; Townshend, J. R. G.; Dodson, Zan M.

doi:10.1109/jstars.2012.2212236

Cited by 28 publications

(17 citation statements)

References 22 publications

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“…The image quality of the HJ-1A/B CCD is stable, the performances of each band are balanced and the radiometric performance of the HJ-1A/B CCD sensors is similar to the performances of the Landsat-5 TM, Observer-1 (EO-1) Advanced Land Imager, and Terra ASTER. The image quality of the HJ-1A/B CCD is very similar to the image quality of Landsat-5 TM (Jiang et al, 2013). In addition, the accuracy of the TIR band's onboard calibration meets the land surface temperature retrieval requirements but not the sea surface temperature retrieval requirements (J. .…”

Section: Remote Sensing Data Hj-1b Satellite Datamentioning

confidence: 87%

Remote sensing algorithm for surface evapotranspiration considering landscape and statistical effects on mixed pixels

Peng

Xin

Jiao

et al. 2016

Hydrol. Earth Syst. Sci.

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Abstract. Evapotranspiration (ET) plays an important role in surface-atmosphere interactions and can be monitored using remote sensing data. However, surface heterogeneity, including the inhomogeneity of landscapes and surface variables, significantly affects the accuracy of ET estimated from satellite data. The objective of this study is to assess and reduce the uncertainties resulting from surface heterogeneity in remotely sensed ET using Chinese HJ-1B satellite data, which is of 30 m spatial resolution in VIS/NIR bands and 300 m spatial resolution in the thermal-infrared (TIR) band. A temperature-sharpening and flux aggregation scheme (TSFA) was developed to obtain accurate heat fluxes from the HJ-1B satellite data. The IPUS (input parameter upscaling) and TRFA (temperature resampling and flux aggregation) methods were used to compare with the TSFA in this study. The three methods represent three typical schemes used to handle mixed pixels from the simplest to the most complex. IPUS handles all surface variables at coarse resolution of 300 m in this study, TSFA handles them at 30 m resolution, and TRFA handles them at 30 and 300 m resolution, which depends on the actual spatial resolution. Analyzing and comparing the three methods can help us to get a better understanding of spatial-scale errors in remote sensing of surface heat fluxes. In situ data collected during HiWATER-MUSOEXE (Multi-Scale Observation Experiment on Evapotranspiration over heterogeneous land surfaces of the Heihe Watershed Allied Telemetry Experimental Research) were used to validate and analyze the methods. ET estimated by TSFA exhibited the best agreement with in situ observations, and the footprint validation results showed that the R 2 , MBE, and RMSE values of the sensible heat flux (H ) were 0.61, 0.90, and 50.99 W m −2 , respectively, and those for the latent heat flux (LE) were 0.82, −20.54, and 71.24 W m −2 , respectively. IPUS yielded the largest errors in ET estimation. The RMSE of LE between the TSFA and IPUS methods was 51.30 W m −2 , and the RMSE of LE between the TSFA and TRFA methods was 16.48 W m −2 . Furthermore, additional analysis showed that the TSFA method can capture the subpixel variations of land surface temperature and the influences of various landscapes within mixed pixels.

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Section: Remote Sensing Data Hj-1b Satellite Datamentioning

confidence: 87%

Remote sensing algorithm for surface evapotranspiration considering landscape and statistical effects on mixed pixels

Peng

Xin

Jiao

et al. 2016

Hydrol. Earth Syst. Sci.

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show abstract

“…The radiometric calibration for HJ data [14][15][16] allows for many quantitative remote sensing applications monitoring vegetation, atmosphere, and water bodies [17][18][19][20]. Thanks to their wide swath, HJ sensors observe the Earth's surface with view zenith angles up to 35°, making it possible to obtain some angular information for surface Bidirectional Reflectance Distribution Function (BRDF) retrievals, which is not available from the nadir-viewing Landsat sensors.…”

Section: Introductionmentioning

confidence: 99%

Land Surface Albedo Estimation from Chinese HJ Satellite Data Based on the Direct Estimation Approach

Liang

Wang

et al. 2015

Remote Sensing

Self Cite

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Abstract:Monitoring surface albedo at medium-to-fine resolution (<100 m) has become increasingly important for medium-to-fine scale applications and coarse-resolution data evaluation. This paper presents a method for estimating surface albedo directly using top-of-atmosphere reflectance. This is the first attempt to derive surface albedo for both snow-free and snow-covered conditions from medium-resolution data with a single approach. We applied this method to the multispectral data from the wide-swath Chinese HuanJing (HJ) satellites at a spatial resolution of 30 m to demonstrate the feasibility of this data for surface albedo monitoring over rapidly changing surfaces. Validation against ground measurements shows that the method is capable of accurately estimating surface albedo over both snow-free and snow-covered surfaces with an overall root mean square error (RMSE) of 0.030 and r-square (R 2 ) of 0.947. The comparison between HJ albedo estimates and the Moderate Resolution Imaging Spectral Radiometer (MODIS) albedo product suggests that the HJ data and proposed algorithm can generate robust albedo estimates over various land cover types with an RMSE of 0.011-0.014. The accuracy of HJ albedo estimation improves with the increase in view zenith angles, which further demonstrates the unique advantage of wide-swath satellite data in albedo estimation.

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“…Thus, uncertainties of employing MODIS BRDF parameters to account for angular effect in Landsat TM imagery still exist and need further research. In the future, it is anticipated that BRDF information matching TM spatial resolution will be derived from satellite constellations with short revisit cycle and multi-angular viewing ability, like China's HJ-1 A/B [61,62] and the forthcoming European Space Agency (ESA)'s Sentinel-2A/B [63,64]. It will be advisable to interpret BRDF effect in TM scenes using matching BRDF data.…”

Section: Discussionmentioning

confidence: 99%

An Improved Physics-Based Model for Topographic Correction of Landsat TM Images

Bian

Lei

2015

Remote Sensing

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Abstract:Optical remotely sensed images in mountainous areas are subject to radiometric distortions induced by topographic effects, which need to be corrected before quantitative applications. Based on Li model and Sandmeier model, this paper proposed an improved physics-based model for the topographic correction of Landsat Thematic Mapper (TM) images. The model employed Normalized Difference Vegetation Index (NDVI) thresholds to approximately divide land targets into eleven groups, due to NDVI's lower sensitivity to topography and its significant role in indicating land cover type. Within each group of terrestrial targets, corresponding MODIS BRDF (Bidirectional Reflectance Distribution Function) products were used to account for land surface's BRDF effect, and topographic effects are corrected without Lambertian assumption. The methodology was tested with two TM scenes of severely rugged mountain areas acquired under different sun elevation angles. Results demonstrated that reflectance of sun-averted slopes was evidently enhanced, and the overall quality of images was improved with topographic effect being effectively suppressed. Correlation coefficients between Near Infra-Red band reflectance and illumination condition reduced almost to zero, and coefficients of variance also showed some reduction. By comparison with the other two physics-based models (Sandmeier model and Li model), the proposed model showed favorable results on two tested Landsat scenes. With the almost half-century accumulation of Landsat data and the successive launch and operation of OPEN ACCESS Remote Sens. 2015, 7 6297Landsat 8, the improved model in this paper can be potentially helpful for the topographic correction of Landsat and Landsat-like data.

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Assessment of the Radiometric Performance of Chinese HJ-1 Satellite CCD Instruments

Cited by 28 publications

References 22 publications

Remote sensing algorithm for surface evapotranspiration considering landscape and statistical effects on mixed pixels

Remote sensing algorithm for surface evapotranspiration considering landscape and statistical effects on mixed pixels

Land Surface Albedo Estimation from Chinese HJ Satellite Data Based on the Direct Estimation Approach

An Improved Physics-Based Model for Topographic Correction of Landsat TM Images

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