The DOI matches its Crossref record; 27 of the 27 references it cites were found in a registry or an index.
Evaluation of the consistency of long-term NDVI time series derived from AVHRR,SPOT-vegetation, SeaWiFS, MODIS, and Landsat ETM+ sensors
Abstract
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 intercalibrated, sensor-independent NDVI data record. This paper suggests that continuity is achievable given the similarity between these datasets
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Cites
Red and photographic infrared linear combinations for monitoring vegetation
Tucker, C. J. (1979) · Remote Sensing of Environment · doi:10.1016/0034-4257(79)90013-0 · Cited by 11,754
Self-citationOverview of the radiometric and biophysical performance of the MODIS vegetation indices
Huete, A., Didan, K., Miura, T., Rodriguez, E. P., Gao, X., & Ferreira, L. G. (2002) · Remote Sensing of Environment · doi:10.1016/s0034-4257(02)00096-2 · Cited by 9,869
Self-citationAERONET—A Federated Instrument Network and Data Archive for Aerosol Characterization
Holben, B. N., Eck, T. F., Slutsker, I., Tanré, D., Buis, J. P., Setzer, A., Vermote, E., Reagan, J. A., Kaufman, Y. J., Nakajima, T., et al. (1998) · Remote Sensing of Environment · doi:10.1016/s0034-4257(98)00031-5 · Cited by 7,743
Climate-Driven Increases in Global Terrestrial Net Primary Production from 1982 to 1999
Nemani, R. R., Keeling, C. D., Hashimoto, H., Jolly, W. M., Piper, S. C., Tucker, C. J., Myneni, R. B., & Running, S. W. (2003) · Science · doi:10.1126/science.1082750 · Cited by 3,671
Self-citationIncreased plant growth in the northern high latitudes from 1981 to 1991
Myneni, R. B., Keeling, C. D., Tucker, C. J., Asrar, G., & Nemani, R. R. (1997) · Nature · doi:10.1038/386698a0 · Cited by 3,442
Self-citationSecond Simulation of the Satellite Signal in the Solar Spectrum, 6S: an overview
Vermote, E. F., Tanre, D., Deuze, J. L., Herman, M., & Morcette, J.-J. (1997) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/36.581987 · Cited by 3,178
Characteristics of maximum-value composite images from temporal AVHRR data
HOLBEN, B. N. (1986) · International Journal of Remote Sensing · doi:10.1080/01431168608948945 · Cited by 3,002
Derivation of Leaf‐Area Index from Quality of Light on the Forest Floor
Jordan, C. F. (1969) · Ecology · doi:10.2307/1936256 · Cited by 2,694
An extended AVHRR 8‐km NDVI dataset compatible with MODIS and SPOT vegetation NDVI data
Tucker, C. J., Pinzon, J. E., Brown, M. E., Slayback, D. A., Pak, E. W., Mahoney, R., Vermote, E. F., & El Saleous, N. (2005) · International Journal of Remote Sensing · doi:10.1080/01431160500168686 · Cited by 2,305
Self-citationJustice, C. O., Vermote, E., Townshend, J. R. G., Defries, R., Roy, D. P., Hall, D. K., Salomonson, V. V., Privette, J. L., Riggs, G., Strahler, A., et al. (1998) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/36.701075 · Cited by 1,635
Cited by
Proxy global assessment of land degradation
Bai, Z. G., Dent, D. L., Olsson, L., & Schaepman, M. E. (2008) · Soil Use and Management · doi:10.1111/j.1475-2743.2008.00169.x · Cited by 987
Chin, M., Diehl, T., Tan, Q., Prospero, J. M., Kahn, R. A., Remer, L. A., Yu, H., Sayer, A. M., Bian, H., Geogdzhayev, I. V., et al. (2014) · Atmospheric Chemistry and Physics · doi:10.5194/acp-14-3657-2014 · Cited by 311
Hamel, S., Garel, M., Festa‐Bianchet, M., Gaillard, J., & Côté, S. D. (2009) · Journal of Applied Ecology · doi:10.1111/j.1365-2664.2009.01643.x · Cited by 231
Assessing eco-scarcity as a cause of the outbreak of conflict in Darfur: a remote sensing approach
Brown, I. A. (2010) · International Journal of Remote Sensing · doi:10.1080/01431161003674592 · Cited by 60
Saybani, M. R. (2011) · Scientific Research and Essays · doi:10.5897/sre11.333 · Cited by 7
Metadata
- Authors
- Brown, M. E., Pinzon, J. E., Didan, K., Morisette, J. T., & Tucker, C. J.
- Venue
- IEEE Transactions on Geoscience and Remote Sensing
- Published
- 2006-07
- Volume
- 44
- Issue
- 7
- Pages
- 1787-1793
- ISSN
- 0196-2892 (ISSN-L)
- OpenAlex
- W2162371906
- Cited by
- 367
- References
- 27
- FWCI
- 14.31
- Type
- journal article
- Language
- en
- Open access
- closed
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