TY - JOUR
T1 - Evaluation of the consistency of Long-term NDVI time series derived from AVHRR, SPOT-vegetation, SeaWiFS, MODIS, and landsat ETM+ sensors
AU - Brown, Molly E.
AU - Pinzón, Jorge E.
AU - Didan, Kamel
AU - Morisette, Jeffrey T.
AU - Tucker, Compton J.
N1 - Funding Information:
Manuscript received November 1, 2004; revised August 12, 2005. This work was supported in part by USAID’s Famine Early Warning System Network. M. E. Brown and J. E. Pinzón are with the SSAI/NASA Goddard Space Flight Center, Greenbelt, MD 20771 USA (e-mail: [email protected]). J. T. Morisette and C. J. Tucker are with the NASA Goddard Space Flight Center, Greenbelt, MD 20771 USA. K. Didan is with the TBRS Laboratory, Soil, Water and Environmental Sciences, University of Arizona, Tucson, AZ 85721 USA. Digital Object Identifier 10.1109/TGRS.2005.860205
PY - 2006/7
Y1 - 2006/7
N2 - This paper evaluates the consistency of the Normalized Difference Vegetation Index (NDVI) records derived from Advanced Very High Resolution Radiometer (AVHRR), SPOT-Vegetation, SeaWiFS, Moderate Resolution Imaging Spectroradiometer, and Landsat ETM+. We used independently derived NDVI from atmospherically corrected ETM+ data at 13 Earth Observation System Land Validation core sites, eight locations of drought, and globally aggregated one-degree data from the four coarse resolution sensors to assess the NDVI records agreement. The objectives of this paper are to: 1) compare the absolute and relative differences of the vegetation signal across these sensors from a user perspective, and, to a lesser degree, 2) evaluate the possibility of merging the AVHRR historical data record with that of the more modern sensors in order to provide historical perspective on current vegetation activities. The statistical and correlation analyses demonstrate that due to the similarity in their overall variance, it is not necessary to choose between the longer time series of AVHRR and the higher quality of the more modern sensors. The long-term AVHRR-NDVI record provides a critical historical perspective on vegetation activities necessary for global change research and, thus, should be the basis of an Intel-calibrated, sensor-independent NDVI data record. This paper suggests that continuity is achievable given the similarity between these datasets.
AB - This paper evaluates the consistency of the Normalized Difference Vegetation Index (NDVI) records derived from Advanced Very High Resolution Radiometer (AVHRR), SPOT-Vegetation, SeaWiFS, Moderate Resolution Imaging Spectroradiometer, and Landsat ETM+. We used independently derived NDVI from atmospherically corrected ETM+ data at 13 Earth Observation System Land Validation core sites, eight locations of drought, and globally aggregated one-degree data from the four coarse resolution sensors to assess the NDVI records agreement. The objectives of this paper are to: 1) compare the absolute and relative differences of the vegetation signal across these sensors from a user perspective, and, to a lesser degree, 2) evaluate the possibility of merging the AVHRR historical data record with that of the more modern sensors in order to provide historical perspective on current vegetation activities. The statistical and correlation analyses demonstrate that due to the similarity in their overall variance, it is not necessary to choose between the longer time series of AVHRR and the higher quality of the more modern sensors. The long-term AVHRR-NDVI record provides a critical historical perspective on vegetation activities necessary for global change research and, thus, should be the basis of an Intel-calibrated, sensor-independent NDVI data record. This paper suggests that continuity is achievable given the similarity between these datasets.
KW - Advanced Very High Resolution Radiometer (AVHRR)
KW - Moderate Resolution Imaging Spectroradiometer (MODIS)
KW - SPOT
KW - Vegetation
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U2 - 10.1109/TGRS.2005.860205
DO - 10.1109/TGRS.2005.860205
M3 - Article
AN - SCOPUS:33746378166
SN - 0196-2892
VL - 44
SP - 1787
EP - 1793
JO - IEEE Transactions on Geoscience and Remote Sensing
JF - IEEE Transactions on Geoscience and Remote Sensing
IS - 7
M1 - 1645279
ER -