Absolute calibration of VEGETATION derived from an interband method based on the Sun glint over ocean

Hagolle, Olivier; Nicolas, Jean-Marc; Fougnie, Bertrand; Cabot, François; Henry, Patrice

doi:10.1109/tgrs.2004.826805

Cited by 39 publications

(28 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The in-flight calibration of PARASOL was conducted in a similar way as for POLDER [4] or VEGETATION [18] and described in Table 4. In this approach, the ratio of measured radiance, MI, to calculated radiance, CI, computed using various methods is called ⌬A k because it can be interpreted as a calibration error on the analyzed data for the spectral band k. Firstly, an absolute calibration of shorter wavelengths was made using Rayleigh scattering deriving…”

Section: Calibration Resultsmentioning

confidence: 99%

“…Spectral bands from 490 to 1020 can be intercalibrated with the band 670. Principle of the method is described and applied to POLDER-1 in Hagolle et al [4], updated in Hagolle et al [18] in the case of VEGETATION, and ap- plied for calibration of POLDER polarized channel in Toubbé et al [19].…”

Section: Description Of Methodsmentioning

confidence: 99%

“…Several space sensors are equipped with on-board device to monitor possible temporal evolution. SeaWiFS [26], MERIS [27], or MODIS [28] are equipped with solar diffusers while VEGETATION͞SPOT [18] is equipped with an onboard lamp. In all cases, difficulties are encountered: aging of the lamp or diffuser themselves may occur requiring a complementary on-board monitoring through diffuser duplication for example [27,28].…”

Section: Multitemporal Monitoringmentioning

confidence: 99%

“…Complementarily, the moon is used as a natural and external diffuser to monitor SeaWiFS long-term trends using acquisitions for specific lunar phases [29]. Alternative methods using natural targets from the Earth-atmosphere system were developed: over desert sites [23,24], viewing sunglint [18] or over Antarctica [30]. Nevertheless, some limitations are due to perturbing contribution or inaccuracy on the algorithm, such as aerosol perturbation, seasonal effects, bidirectional effects, spectral behavior modeling, or difficulty to obtain a dense temporal sampling.…”

Section: Multitemporal Monitoringmentioning

confidence: 99%

See 3 more Smart Citations

PARASOL in-flight calibration and performance

et al. 2007

View full text Add to dashboard Cite

Since 18 December 2004, the PARASOL satellite is a member of the so-called A-train atmospheric orbital observatory, flying together with Aqua, Aura, CALIPSO, CLOUDSAT, and OCO satellites. These satellites combine for the first time a full suite of instruments for observing aerosols and clouds, using passive radiometer complementarily with active lidar and radar sounders. The PARASOL payload is extensively derived from the instrument developed for the POLDER programs that performs measurements of bidirectionality and polarization for a very wide field-of-view and for a visible͞near-infrared spectral range. An overview of the results obtained during the commissioning phase and the reevaluation after one year in orbit is presented. In-flight calibration methods are briefly described, and radiometric and geometric performances are both evaluated. All algorithms are based on a panel of methods using mainly natural targets previously developed for POLDER missions and adapted or redeveloped in the PARASOL context. Regarding performances, all mission requirements are met except for band 443 (not recommended for use). After one year in orbit, a perfect geometrical stability was found while a slight decrease of the radiometric sensitivity was observed and corrected through an innovative multitemporal algorithm based on observations of bright and scattered convective clouds. The scientific exploitation of PARASOL has now begun, particularly by coupling these specific observations with other A-train sensor measurements.

show abstract

Section: Calibration Resultsmentioning

confidence: 99%

Section: Description Of Methodsmentioning

confidence: 99%

Section: Multitemporal Monitoringmentioning

confidence: 99%

Section: Multitemporal Monitoringmentioning

confidence: 99%

See 2 more Smart Citations

PARASOL in-flight calibration and performance

et al. 2007

View full text Add to dashboard Cite

show abstract

“…In this case, the LAI retrieval processing chain relies on neural networks trained to generate LAI estimates by fusing and scaling MODIS c5 and CYCLOPES v3.1 products [19]. The input data of the retrieval chain are top of canopy directional normalized reflectance from either SPOT/VEGETATION or PROBA-V computed using a kernel-driven bidirectional reflectance distribution function (BRDF) model [54]. The retrieval methodology uses a temporal weighting function giving the higher weight in the last observation of the composing period.…”

Section: Copernicus Proba-v (Geov1)mentioning

confidence: 99%

A Critical Comparison of Remote Sensing Leaf Area Index Estimates over Rice-Cultivated Areas: From Sentinel-2 and Landsat-7/8 to MODIS, GEOV1 and EUMETSAT Polar System

et al. 2018

View full text Add to dashboard Cite

Leaf area index (LAI) is a key biophysical variable fundamental in natural vegetationand agricultural land monitoring and modelling studies. This paper is aimed at comparing, validating and discussing different LAI satellite products from operational services and customized solution based on innovative Earth Observation (EO) data such as Landsat-7/8 and Sentinel-2A. The comparison was performed to assess overall quality of LAI estimates for rice, as a fundamental input of different scale (regional to local) operational crop monitoring systems such as the ones developed during the "An Earth obseRvation Model based RicE information Service" (ERMES) project. We adopted a multiscale approach following international recognized protocols of the Committee on Earth Observation Satellites (CEOS) Land Product Validation (LPV) guidelines in different steps: (1) acquisition of representative field sample measurements, (2) validation of decametric satellite product (10-30 m spatial resolution), and (3) exploitation of such data to assess quality of medium-resolution operational products (~1000 m). The study areas were located in the main European rice areas in Spain, Italy and Greece. Field campaigns were conducted during three entire rice seasons (2014, 2015 and 2016-from sowing to full-flowering) to acquire multi-temporal ground LAI measurements and to assess Landsat-7/8 LAI estimates. Results highlighted good correspondence between Landsat-7/8 LAI estimates and ground measurements revealing high correlations (R 2 ≥ 0.89) and low root mean squared errors (RMSE ≤ 0.75) in all seasons. Landsat-7/8 as well as Sentinel-2A high-resolution LAI retrievals, were compared with satellite LAI products operationally derived from MODIS (MOD15A2), Copernicus PROBA-V (GEOV1), and the recent EUMETSAT Polar System (EPS) LAI product. Good agreement was observed between high-and medium-resolution LAI estimates. In particular, the EPS LAI product was the most correlated product with both Landsat/7-8 and Sentinel-2A estimates, revealing R 2 ≥ 0.93 and RMSE ≤ 0.53 m 2 /m 2 . In addition, a comparison exercise of EPS, GEOV1 and MODIS revealed high correlations (R 2 ≥ 0.90) and RMSE ≤ 0.80 m 2 /m 2 in all cases and years. The temporal assessment shows that the three satellite products capture well the seasonality during the crop phenological cycle. Discrepancies are observed mainly in absolute values retrieved for the peak of rice season. This is the first study that provides a quantitative assessment on the quality of available operational LAI product for rice monitoring to both the scientific community and users of agro-monitoring operational services.

show abstract

Intercalibration of GOES Imager visible channels over the Sonoran Desert

Grotenhuis

et al. 2014

JGR Atmospheres

View full text Add to dashboard Cite

The Geostationary Operational Environmental Satellites (GOES) have been observing the WesternHemisphere since the late 1970s, providing valuable information for weather forecast and climate change studies. Due to the lack of an onboard calibration device for the visible channel, accurate reflectance of the visible channel data depends on vicarious calibration methods to provide postlaunch calibration coefficients to compensate for the degraded responsivity. In this study, the Sonoran Desert, which can be viewed by both GOES-East and GOES-West satellites, is used to intercalibrate the visible channels on board the three-axis stabilized GOES satellite Imagers traceable to the Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 6 (C6) calibration standard. It was found that when the anomalous reflectance in 2004 and 2005 are excluded, the Sonoran Desert is radiometrically, spatially, and spectrally stable at the GOES viewing geometries and thus can be considered as a pseudo-invariant calibration site to develop long-term GOES Imager visible data set. To characterize the desert target reflectance with the MODIS data, GOES observations over 1 year period are used to convert the MODIS reflectance to the GOES viewing and solar illumination geometries. The spectral band adjustment factor for each GOES Imager visible channel is generated with a set of clear-sky Hyperion measurements. A trending algorithm, which consists of a polynomial function for the description of instrument degradation performance and two sine terms for the impacts of the seasonal variations of the solar zenith angle and atmospheric components, is applied to fit the time series of prelaunch calibrated reflectance. The combined calibration uncertainty of the desert calibration method is less than 4% at the Aqua MODIS C6 calibration standard. The difference of the postlaunch calibration coefficients between the desert calibration and the current GOES visible operational calibration methods is mainly within 5%.

show abstract

Absolute calibration of VEGETATION derived from an interband method based on the Sun glint over ocean

Cited by 39 publications

References 16 publications

PARASOL in-flight calibration and performance

PARASOL in-flight calibration and performance

A Critical Comparison of Remote Sensing Leaf Area Index Estimates over Rice-Cultivated Areas: From Sentinel-2 and Landsat-7/8 to MODIS, GEOV1 and EUMETSAT Polar System

Intercalibration of GOES Imager visible channels over the Sonoran Desert

Contact Info

Product

Resources

About