Status of MODIS spatial and spectral characterization and performance

Link, Daniel; Wang, Zhipeng; Xiong, Xiaoxiong

doi:10.1117/12.2224307

Cited by 3 publications

(3 citation statements)

References 17 publications

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“…In order to identify the number of hotspots, we utilized the Aqua-Modis satellite with a spatial resolution of 1000m [10] obtained from http://modiscatalog.lapan.go.id/monitoring. Hotspots are determined by the thermal activity layer in Modis instrument and corrected by de-striping and geometric correction process.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Surface Concentration of Black Carbon in Riau Province During the 2019 Forest Fires Using Merra-2 Reanalysis Data

Sari

Andarini

'Adany

et al. 2022

JMG

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Indonesia experienced forest fires almost every year, especially in the area of Riau Province, where as a result, pollutants such carbon dioxide and black carbon present in the air over Riau. Due to its size and its light absorption ability, black carbon is known to have bad impacts on the climate. This study aims to analyse the effect of forest fires that happened in Riau province, Indonesia in September 2019 towards the production of black carbon, as well as to estimate backward air movement trajectory in order to confirm the air mass sources of the black carbon. The data of black carbon concentration used in this study is an hourly temporal data of MERRA-2 with a spatial resolution of 0.5° × 0.625°, while the trajectory calculation uses the HYSPLIT trajectory model. Linear regression of this study has an r value of 0.78 which shows that there is a positive correlation between black carbon concentration and number of hotspots. The range of BC concentrations were 2–11 × 10-9 kg.m-3 with higher concentration occurred during 9–23 September 2019 where it was affected by the south-easterly wind from Jambi and South Sumatera.

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Section: Introductionmentioning

confidence: 99%

Analysis of Surface Concentration of Black Carbon in Riau Province During the 2019 Forest Fires Using Merra-2 Reanalysis Data

Sari

Andarini

'Adany

et al. 2022

JMG

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“…The MODIS bands are calibrated on-orbit using a set of onboard calibrators (OBC), such as the solar diffuser (SD) for calibrating the reflective solar bands (RSB) with its degradation measured by a SD stability monitor (SDSM), 3 the blackbody (BB) for calibrating the thermal emissive bands (TEB) 4 and the spectroradiometric calibration assembly (SRCA) for characterizing the spatial and spectral behavior of the detectors. 5 MODIS also uses external targets such as selected Earth-view reference sites and scheduled observations of the Moon in order to characterize the scan mirror response versus scan angle (RVS) at angles of incidence on the scan mirror other than those of the OBCs. 6,7 MODIS has four focal plane assemblies (FPA), the visible (VIS), near-infrared (NIR), short-and mid-wave infrared (SMIR), and the long-wave infrared (LWIR), which group the bands by wavelength.…”

Section: Introductionmentioning

confidence: 99%

Electronic crosstalk impact assessment in the Terra MODIS mid-wave infrared bands

Wilson

Shrestha

Xiong

2017

Sensors, Systems, and Next-Generation Satellites XXI

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The Moderate Resolution Imaging Spectroradiometer (MODIS) on board the Terra spacecraft is one of the key instruments in NASA's Earth Observing System. Since 2000, MODIS has collected continuous data in 36 spectral bands ranging in wavelength between 0.4 µm and 14.2 µm. Since before launch, signal contamination in the form of electronic crosstalk has been observed in many of the MODIS thermal emissive bands, particularly for bands 27 − 30, a correction for which has been applied to the current Collection 6 algorithm. The mid-wave infrared bands in Terra MODIS, 20 − 25, also show signs of electronic crosstalk contamination, which can be seen clearly during observations of the Moon. In this paper, we'll present an impact assessment of electronic crosstalk on the mid-wave infrared bands in Terra MODIS. We will also derive correction coefficients from the lunar observations, which can be applied to correct the calibrated radiance in the MODIS Level-1B product. We will provide an analysis of these results and potential improvements to the MODIS Level-1B product.

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“…The MODIS bands are calibrated using one of a number of on-board calibrators (OBC), which include a solar diffuser (SD) with its degradation measured by a solar diffuser stability monitor (SDSM), 3 blackbody target (BB), 4 and spectroradiometric calibration assembly (SRCA). 5 Also, MODIS uses Earth-view targets 6 and the Moon 7 to characterize the scan mirror degradation at a different angle of incidence (AOI) than those of the OBC.…”

Section: Introductionmentioning

confidence: 99%

Analysis of the electronic crosstalk effect in Terra MODIS long-wave infrared photovoltaic bands using lunar images

Wilson

Geng

et al. 2016

SPIE Proceedings

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The Moderate Resolution Imaging Spectroradiometer (MODIS) is one of the key sensors among the suite of remote sensing instruments on board the Earth Observing System Terra and Aqua spacecrafts. For each MODIS spectral band, the sensor degradation has been measured using a set of on-board calibrators. MODIS also uses lunar observations from nearly monthly spacecraft maneuvers, which bring the Moon into view through the spaceview port, helping to characterize the scan mirror degradation at a different angles of incidence. Throughout the Terra mission, contamination of the long-wave infrared photovoltaic band (LWIR PV, bands 27 − 30) signals has been observed in the form of electronic crosstalk, where signal from each of the detectors among the LWIR PV bands can leak to the other detectors, producing a false signal contribution. This contamination has had a noticeable effect on the MODIS science products since 2010 for band 27, and since 2012 for bands 28 and 29. Images of the Moon have been used effectively for determining the contaminating bands, and have also been used to derive correction coefficients for the crosstalk contamination. In this paper, we introduce an updated technique for characterizing the crosstalk contamination among the LWIR PV bands using data from lunar calibration events. This approach takes into account both the "in-band" and "out-of-band" contribution to the signal contamination for each detector in bands 27 − 30, which is not considered in previous works. The crosstalk coefficients can be derived for each lunar calibration event, providing the time dependence of the crosstalk contamination. Application of these coefficients to Earth-view image data results in a significant reduction in image contamination and a correction of the scene radiance for bands 27 − 30. Also, this correction shows a significant improvement to certain threshold tests in the MODIS Level-2 Cloud Mask. In this paper, we will detail the methodology used to identify and correct the crosstalk contamination for the LWIR PV bands in Terra MODIS. The derived time-dependent crosstalk coefficients will also be discussed. Finally, the impact of the correction on the downstream data products will be analyzed.

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Status of MODIS spatial and spectral characterization and performance

Cited by 3 publications

References 17 publications

Analysis of Surface Concentration of Black Carbon in Riau Province During the 2019 Forest Fires Using Merra-2 Reanalysis Data

Analysis of Surface Concentration of Black Carbon in Riau Province During the 2019 Forest Fires Using Merra-2 Reanalysis Data

Electronic crosstalk impact assessment in the Terra MODIS mid-wave infrared bands

Analysis of the electronic crosstalk effect in Terra MODIS long-wave infrared photovoltaic bands using lunar images

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