Aisheng Wu

Dr. Aisheng Wu

orcid

Research Focus & Metrics

Academic Career Length

18Years (2009-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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2 January 2013 in Journal of Applied Remote Sensing
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Journal Article
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GTGary Toller
Gary Toller
Jack XiongJack Xiong
Jack Xiong
JSJunqiang Sun
Junqiang Sun
BWBrian N. Wenny
Brian N. Wenny
XGXu Geng
Xu Geng
AWAisheng Wu
Aisheng Wu
The moderate-resolution imaging spectroradiometer (MODIS) was launched on the Terra spacecraft on Dec.18, 1999 and on Aquaon May 4, 2002. The data acquired by these instruments have contributed to the long-term climate data record for more than a decade and represent a key component of NASA’s Earth observing system. Each MODIS instrument observes nearly the whole Earth each day, enabling the scientific characterization of the land, ocean, and atmosphere. The MODIS Level 1B (L1B) algorithms input uncalibrated geo-located observations and convert instrument response into calibrated reflectance and radiance, which are used to generate science data products. The instrument characterization needed to run the L1B code is currently implemented using time-dependent lookup tables. The MODIS characterization support team, working closely with the MODIS Science Team, has improved the product quality with each data reprocessing. We provide an overview of the new L1B algorithm release, designated collection 6. Recent improvements made as a consequence of on-orbit calibration, on-orbit analyses, and operational considerations are described. Instrument performance and the expected impact of L1B changes on the collection 6 L1B products are discussed.

27 September 2020 in Remote Sensing
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Journal Article
Open access
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Jack XiongJack Xiong
Jack Xiong
AAAmit Angal
Amit Angal
TCTiejun Chang
Tiejun Chang
KCKwofu Chiang
Kwofu Chiang
NLNing Lei
Ning Lei
AWAisheng Wu
Aisheng Wu
Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) have successfully operated since their launches in 1999 and 2002, respectively, and generated various data products to support the Earth remote sensing disciplines and users worldwide for their research activities and applications, including studies of the Earth system, and its changes over time and geographic regions. The MODIS data have also significantly contributed to the continuity of multi-decadal satellite data records and led to major advances in the Earth remote sensing field. The long-term data records from MODIS observations have been and will continue to be extended by the Visible Infrared Imaging Radiometer Suite (VIIRS) instruments, currently operated aboard the Suomi-National Polar-Orbiting Partnership (NPP) and NOAA-20 satellites. The data quality of satellite instruments strongly depends on their calibration accuracy and stability. In order to help scientists and users gain a better understanding of MODIS and VIIRS data quality, this paper provides an overview of their on-orbit calibration methodologies, approaches, and results derived from instrument on-board calibrators and lunar observations, as well as select Earth view targets. What is also discussed is the calibration consistency between MODIS and VIIRS and its potential impact on producing multi-sensor long-term data records. As illustrated, the overall performance of both MODIS and VIIRS continues to meet their design requirements.

6 June 2017 in Remote Sensing
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Journal Article
Open access
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TWTruman Wilson
Truman Wilson
AWAisheng Wu
Aisheng Wu
ASAshish Shrestha
Ashish Shrestha
XGXu Geng
Xu Geng
ZWZhipeng Wang
Zhipeng Wang
Jack XiongJack Xiong
Jack Xiong
The photovoltaic bands on the long-wave infrared focal plane assembly of Terra MODIS, bands 27–30, have suffered from steadily increasing contamination from electronic crosstalk as the mission has progressed. This contamination has a great impact on MODIS data products, including image striping and radiometric bias in the Level-1B calibrated radiance product, and incorrect retrieval in atmospheric products that rely on data from bands 27–30, such as the cloud mask and cloud particle phase products. In this work, we describe the development of an electronic crosstalk correction for bands 27–30 of Terra MODIS using observations of the Moon. In this approach, the derived correction coefficients account for both the “in-band” and “out-of-band” contribution to the signal contamination, which is not considered in previous implementations of the lunar-based correction. The correction coefficients are applied to both the on-board calibrator data and the Earth-view data, resulting in a significant reduction in the image striping and radiometric bias in the Level-1B data, as well as a better performance in the Level-2 cloud mask and cloud particle phase products. This approach will be implemented for Terra MODIS Collection 6 in 2017.

1 July 2018 in Journal of Applied Remote Sensing
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Journal Article
Closed access
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Jack XiongJack Xiong
Jack Xiong
AAAmit Angal
Amit Angal
WBWilliam L. Barnes
William L. Barnes
HCHongda Chen
Hongda Chen
VCVincent Chiang
Vincent Chiang
AWAisheng Wu
Aisheng Wu
The Moderate Resolution Imaging Spectroradiometer (MODIS) instruments have successfully operated for more than 18 and 16 years, respectively, on-board the NASA’s Earth Observing System Terra and Aqua spacecraft. Both Terra and Aqua MODIS have significantly contributed to the advance of global Earth remote sensing applications with a broad range of science products that have been continuously produced since the beginning of each mission and freely distributed to users worldwide. MODIS collects data in 20 reflective solar bands (RSB) and 16 thermal emissive bands (TEB), covering wavelengths from 0.41 to 14.4 μm. Its level 1B (L1B) data products, which provide the input for the MODIS high-level science products, include the top of the atmosphere reflectance factors for the RSB, radiances for both the RSB and TEB, and associated uncertainty indices (UI) at a pixel-by-pixel level. This paper provides a brief review of MODIS L1B calibration algorithms, including a number of improvements made in recent years. It presents an update of sensor calibration uncertainty assessments with a focus on several new contributors resulting from on-orbit changes in sensor characteristics, approaches developed to address these changes, and the impact due to on-orbit changes on the L1B data quality. Also discussed are remaining challenges and potential improvements to be made to continuously maintain sensor calibration and data quality, particularly those related to the quality of MODIS L1B uncertainty.

23 January 2016 in Remote Sensing
Verified
Journal Article
Open access
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Jack XiongJack Xiong
Jack Xiong
JBJames Butler
James Butler
KCKwofu Chiang
Kwofu Chiang
BEBoryana Emfremova
Boryana Emfremova
JFJon Fulbright
Jon Fulbright
AWAisheng Wu
Aisheng Wu
The VIIRS instrument on board the S-NPP spacecraft has successfully operated for more than four years since its launch in October 2011. Many VIIRS environmental data records (EDR) have been continuously generated from its sensor data records (SDR) with improved quality, enabling a wide range of applications in support of users in both the operational and research communities. This paper provides a brief review of sensor on-orbit calibration methodologies for both the reflective solar bands (RSB) and the thermal emissive bands (TEB) and an overall assessment of their on-orbit radiometric performance using measurements from instrument on-board calibrators (OBC), as well as regularly scheduled lunar observations. It describes and illustrates changes made and to be made for calibration and data quality improvements. Throughout the mission, all of the OBC have continued to operate and function normally, allowing critical calibration parameters used in the data production systems to be derived and updated. The temperatures of the on-board blackbody (BB) and the cold focal plane assemblies are controlled with excellent stability. Despite large optical throughput degradation discovered shortly after launch in several near- and short-wave infrared spectral bands and strong wavelength-dependent solar diffuser degradation, the VIIRS overall performance has continued to meet its design requirements. Also discussed in this paper are challenging issues identified and efforts to be made to further enhance the sensor calibration and characterization, thereby maintaining or improving data quality.

1 January 2010 in Journal of Applied Remote Sensing
Verified
Journal Article
Closed access
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Jack XiongJack Xiong
Jack Xiong
AAAmit Angal
Amit Angal
TCTaeyoung Choi
Taeyoung Choi
GCGyanesh Chander
Gyanesh Chander
AWAisheng Wu
Aisheng Wu
Remote sensing imagery is effective for monitoring environmental and climatic changes because of the extent of the global coverage and long time scale of the observations. Radiometric calibration of remote sensing sensors is essential for quantitative & qualitative science and applications. Pseudo-invariant ground targets have been extensively used to monitor the long-term radiometric calibration stability of remote sensing sensors. This paper focuses on the use of the Sonoran Desert site to monitor the radiometric stability of the Landsat 7 (L7) Enhanced Thematic Mapper Plus (ETM+) and Terra Moderate Resolution Imaging Spectroradiometer (MODIS) sensors. The results are compared with the widely used Libya 4 Desert site in an attempt to evaluate the suitability of the Sonoran Desert site for sensor inter-comparison and calibration stability monitoring. Since the overpass times of ETM+ and MODIS differ by about 30 minutes, the impacts due to different view geometries or test site Bi-directional Reflectance Distribution Function (BRDF) are also presented. In general, the long-term drifts in the visible bands are relatively large compared to the drift in the near-infrared bands of both sensors. The lifetime Top-of-Atmosphere (TOA) reflectance trends from both sensors over 10 years are extremely stable, changing by no more than 0.1% per year (except ETM+ Band 1 and MODIS Band 3) over the two sites used for the study. The use of a semi-empirical BRDF model can reduce the impacts due to view geometries, thus enabling a better estimate of sensor temporal drifts.