Long-term monitoring of surface reflectance, NDVI and clouds from space: What contribution we can expect due to effect of instrument spectral response variations?

Alexander P. Trishchenko, Josef Cihlar, Zhanqing Li, Byongjun Hwang

Research output: Contribution to journalConference article

3 Citations (Scopus)

Abstract

Since the satellites provide frequent and global observations of atmospheric and terrestrial environment, attempts have been made to use satellite data for long-term monitoring of land reflectances, vegetation indices and clouds properties. Although the construction and characteristics of spaceborne instruments may be quite similar, they are not identical among all missions, even for the same type of instrument like AVHRR. Consequently, the effect of varying spectral response may create an artificial noise imposed upon a subtle natural variability. We report the results of a study on the sensitivity of Normalized Difference Vegetation Index (NDVI), surface and cloud reflectance to differences in instrument spectral response functions (SRF) for various satellite sensors. They include AVHRR radiometers onboard NOAA satellites NOAA-6 - NOAA-16, the Moderate Resolution Imaging Spectroradiometer (MODIS), the VEGETATION sensor (VGT) and the Global Imager (GLI). We also analyzed the SRF effects for several geostationary satellites used for cloud studies, such as GOES-8- 12, METEOSAT-2- 7, GMS -1 -5. The results obtained here demonstrate that the effect of instrument spectral response function cannot be ignored in long-term monitoring studies that employ space observations from different sensors. The SRF effect introduces differences in observed reflectances and retrieved quantities that may be comparable or exceed the range of natural variability and possible systematic trends, the contribution from the calibration, atmospheric and other corrections. Some modeling results were validated against real satellite observations with good agreement.

Original languageEnglish
Pages (from-to)108-119
Number of pages12
JournalProceedings of SPIE - The International Society for Optical Engineering
Volume4815
DOIs
Publication statusPublished - 5 Sep 2002
Externally publishedYes
EventAtmospheric Radiation Measurements and Applications in Climate - Seattle, United States
Duration: 10 Jul 200211 Jul 2002

Fingerprint

Normalized Difference Vegetation Index
normalized difference vegetation index
Spectral Response
spectral sensitivity
Reflectance
Spectral Function
Satellites
Monitoring
Response Function
reflectance
Advanced Very High Resolution Radiometer
Advanced very high resolution radiometers (AVHRR)
AVHRR
sensors
Sensors
Sensor
GOES 8
NOAA satellites
synchronous satellites
atmospheric correction

Cite this

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title = "Long-term monitoring of surface reflectance, NDVI and clouds from space: What contribution we can expect due to effect of instrument spectral response variations?",
abstract = "Since the satellites provide frequent and global observations of atmospheric and terrestrial environment, attempts have been made to use satellite data for long-term monitoring of land reflectances, vegetation indices and clouds properties. Although the construction and characteristics of spaceborne instruments may be quite similar, they are not identical among all missions, even for the same type of instrument like AVHRR. Consequently, the effect of varying spectral response may create an artificial noise imposed upon a subtle natural variability. We report the results of a study on the sensitivity of Normalized Difference Vegetation Index (NDVI), surface and cloud reflectance to differences in instrument spectral response functions (SRF) for various satellite sensors. They include AVHRR radiometers onboard NOAA satellites NOAA-6 - NOAA-16, the Moderate Resolution Imaging Spectroradiometer (MODIS), the VEGETATION sensor (VGT) and the Global Imager (GLI). We also analyzed the SRF effects for several geostationary satellites used for cloud studies, such as GOES-8- 12, METEOSAT-2- 7, GMS -1 -5. The results obtained here demonstrate that the effect of instrument spectral response function cannot be ignored in long-term monitoring studies that employ space observations from different sensors. The SRF effect introduces differences in observed reflectances and retrieved quantities that may be comparable or exceed the range of natural variability and possible systematic trends, the contribution from the calibration, atmospheric and other corrections. Some modeling results were validated against real satellite observations with good agreement.",
keywords = "Clouds, Monitoring, NDVI, Satellite observations, Spectral response function, Surface reflectance",
author = "Trishchenko, {Alexander P.} and Josef Cihlar and Zhanqing Li and Byongjun Hwang",
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TY - JOUR

T1 - Long-term monitoring of surface reflectance, NDVI and clouds from space

T2 - What contribution we can expect due to effect of instrument spectral response variations?

AU - Trishchenko, Alexander P.

AU - Cihlar, Josef

AU - Li, Zhanqing

AU - Hwang, Byongjun

PY - 2002/9/5

Y1 - 2002/9/5

N2 - Since the satellites provide frequent and global observations of atmospheric and terrestrial environment, attempts have been made to use satellite data for long-term monitoring of land reflectances, vegetation indices and clouds properties. Although the construction and characteristics of spaceborne instruments may be quite similar, they are not identical among all missions, even for the same type of instrument like AVHRR. Consequently, the effect of varying spectral response may create an artificial noise imposed upon a subtle natural variability. We report the results of a study on the sensitivity of Normalized Difference Vegetation Index (NDVI), surface and cloud reflectance to differences in instrument spectral response functions (SRF) for various satellite sensors. They include AVHRR radiometers onboard NOAA satellites NOAA-6 - NOAA-16, the Moderate Resolution Imaging Spectroradiometer (MODIS), the VEGETATION sensor (VGT) and the Global Imager (GLI). We also analyzed the SRF effects for several geostationary satellites used for cloud studies, such as GOES-8- 12, METEOSAT-2- 7, GMS -1 -5. The results obtained here demonstrate that the effect of instrument spectral response function cannot be ignored in long-term monitoring studies that employ space observations from different sensors. The SRF effect introduces differences in observed reflectances and retrieved quantities that may be comparable or exceed the range of natural variability and possible systematic trends, the contribution from the calibration, atmospheric and other corrections. Some modeling results were validated against real satellite observations with good agreement.

AB - Since the satellites provide frequent and global observations of atmospheric and terrestrial environment, attempts have been made to use satellite data for long-term monitoring of land reflectances, vegetation indices and clouds properties. Although the construction and characteristics of spaceborne instruments may be quite similar, they are not identical among all missions, even for the same type of instrument like AVHRR. Consequently, the effect of varying spectral response may create an artificial noise imposed upon a subtle natural variability. We report the results of a study on the sensitivity of Normalized Difference Vegetation Index (NDVI), surface and cloud reflectance to differences in instrument spectral response functions (SRF) for various satellite sensors. They include AVHRR radiometers onboard NOAA satellites NOAA-6 - NOAA-16, the Moderate Resolution Imaging Spectroradiometer (MODIS), the VEGETATION sensor (VGT) and the Global Imager (GLI). We also analyzed the SRF effects for several geostationary satellites used for cloud studies, such as GOES-8- 12, METEOSAT-2- 7, GMS -1 -5. The results obtained here demonstrate that the effect of instrument spectral response function cannot be ignored in long-term monitoring studies that employ space observations from different sensors. The SRF effect introduces differences in observed reflectances and retrieved quantities that may be comparable or exceed the range of natural variability and possible systematic trends, the contribution from the calibration, atmospheric and other corrections. Some modeling results were validated against real satellite observations with good agreement.

KW - Clouds

KW - Monitoring

KW - NDVI

KW - Satellite observations

KW - Spectral response function

KW - Surface reflectance

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