Vrije Universiteit amsterdamGlobal evaluation of four AVHRR–NDVI data sets: Intercomparison and assessment against Landsat imagery Hylke E. Beck a, *,

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vrije Universiteit amsterdamGlobal evaluation of four AVHRR–NDVI data sets: Intercomparison and assessment against Landsat imagery Hylke E. Beck a, *, Tim R. McVicar b, Albert I.J.M. van Dijk b, Jaap Schellekens c, Richard A.M. de Jeu a, L. Adrian Bruijnzeel a a VU University Amsterdam, The Netherlands b CSIRO Land and Water, Australia c Deltares, The Netherlands * Corresponding publication: Beck, H.E., et al., Global evaluation of four AVHRR–NDVI data sets: Intercomparison and assessment against Landsat imagery, Remote Sensing of Environment (2011), doi: /j.rse

vrije Universiteit amsterdamGlobal evaluation of four AVHRR–NDVI data sets: Intercomparison and assessment against Landsat imagery (1)Introduction (2)AVHRR-NDVI dataset intercomparison (3)AVHRR-NDVI dataset validation (4)Conclusion/Summary Outline

vrije Universiteit amsterdamGlobal evaluation of four AVHRR–NDVI data sets: Intercomparison and assessment against Landsat imagery (1) Introduction NOAA’s AVHRR sensors operating since 1981 Confused as to which global AVHRR-NDVI dataset to use: PAL, GIMMS, LTDR, FASIR, GVI, PAL-II, or …? All are based on the AVHRR Global Area Coverage archive Significant differences between these datasets! Which one do I use? Validation studies limited (e.g., regional, small sample size) Idea: validate using forest cover change data? Better idea: use FAO global database of Landsat samples

vrije Universiteit amsterdamGlobal evaluation of four AVHRR–NDVI data sets: Intercomparison and assessment against Landsat imagery (1) Introduction Four global AVHRR-NDVI datasets: –PAL (8 km, 10 days) –GIMMS (8 km, 15 days) –LTDR V3 (8 km, 10 days) –FASIR (12 km, 10 days) GIMMS the most popular LTDR still in development

vrije Universiteit amsterdamGlobal evaluation of four AVHRR–NDVI data sets: Intercomparison and assessment against Landsat imagery (2) AVHRR-NDVI dataset intercomparison AVHRR-NDVI dataset intercomparison: Annual means of ‘growing season’ months Global assessment at 0.5° resolution Where do the datasets agree/disagree Median, variance, trend, and correlation (here only trend is discussed)

vrije Universiteit amsterdamGlobal evaluation of four AVHRR–NDVI data sets: Intercomparison and assessment against Landsat imagery (2) AVHRR-NDVI dataset intercomparison Trends in desert areas! Large differences in Congo and Sahel! GIMMS dataset distinctly different patterns!

vrije Universiteit amsterdamGlobal evaluation of four AVHRR–NDVI data sets: Intercomparison and assessment against Landsat imagery (2) AVHRR-NDVI dataset intercomparison AVHRR-NDVI dataset intercomparison: Average for 0.5° latitude bands LTDR V3 overestimates variance 40°S-30°S GIMMS has lowest trends GIMMS higher trends in tundra Positive trends over almost whole latitudinal range for all datasets

vrije Universiteit amsterdamGlobal evaluation of four AVHRR–NDVI data sets: Intercomparison and assessment against Landsat imagery AVHRR-NDVI dataset intercomparison: Kruskal-Wallis test used for hypothesis of equal trends Blue: similar trends Red: different trends Inconsistent trends in Africa and Europe Highly consistent trends in Australia (2) AVHRR-NDVI dataset intercomparison

vrije Universiteit amsterdamGlobal evaluation of four AVHRR–NDVI data sets: Intercomparison and assessment against Landsat imagery (2) AVHRR-NDVI dataset intercomparison AVHRR-NDVI dataset intercomparison: The most popular dataset (GIMMS) is also the most different Greening almost the whole latitudinal range and in most regions for all datasets Most greening in Europe More favorable conditions globally for vegetation growth

vrije Universiteit amsterdamGlobal evaluation of four AVHRR–NDVI data sets: Intercomparison and assessment against Landsat imagery (3) AVHRR-NDVI dataset validation AVHRR-NDVI dataset validation: FAO Landsat database of 20 x 20 km 2 samples 11,764 Landsat-5 samples covering all major land-cover types Landsat suitable for validation NDVI from bands 3 and 4 Absolute-values comparison (see paper) Temporal-change comparison MODIS-NDVI for verification Every dot represents one or more Landsat samples!

vrije Universiteit amsterdamGlobal evaluation of four AVHRR–NDVI data sets: Intercomparison and assessment against Landsat imagery (3) AVHRR-NDVI dataset validation AVHRR-NDVI dataset validation: Landsat sample pairs x-axis: AVHRR- or MODIS-NDVI change y-axis: Landsat-NDVI change Root Mean Square Difference (RMSD) indicates performance GIMMS second best MODIS best

vrije Universiteit amsterdamGlobal evaluation of four AVHRR–NDVI data sets: Intercomparison and assessment against Landsat imagery (3) AVHRR-NDVI dataset validation AVHRR-NDVI dataset validation: Higher RMSD in dense canopy land-cover types NDVI saturation and non-linearity Tropical forests: water vapor and clouds Boreal forests: large SZA’s

vrije Universiteit amsterdamGlobal evaluation of four AVHRR–NDVI data sets: Intercomparison and assessment against Landsat imagery AVHRR-NDVI dataset validation: LTDR V3 most accurate in terms of absolute values (see paper) GIMMS probably (!) most accurate in terms of temporal change MODIS more accurate than all AVHRR-NDVI datasets, confirms method Interesting: simple average of the AVHRR-NDVI datasets is better than GIMMS, information is lost by maximum-value compositing? (3) AVHRR-NDVI dataset validation

vrije Universiteit amsterdamGlobal evaluation of four AVHRR–NDVI data sets: Intercomparison and assessment against Landsat imagery (4) Conclusion/Summary Significant differences in trends for almost half of the total land surface Dataset choice has large implications PAL and LTDR V3 lack calibration GIMMS (the most popular dataset) is the most different GIMMS probably has the best calibration However, LTDR dataset still in development; may surpass GIMMS

vrije Universiteit amsterdamGlobal evaluation of four AVHRR–NDVI data sets: Intercomparison and assessment against Landsat imagery Thank you! Questions? Also check our publication, ask for a hardcopy: Beck, H.E., et al., Global evaluation of four AVHRR–NDVI data sets: Intercomparison and assessment against Landsat imagery, Remote Sensing of Environment (2011), doi: /j.rse