Photogrammetric Engineering & Remote Sensing · 1993 · 335 citations · 0 references
Natural SciencesEarth SciencesMeteorologyAtmospheric ScienceRemote SensingTime Series AnalysisEl Niño-southern OscillationLand Cover Change DetectionRegional ClimatologyRemote Sensing Change DetectionSeasonality AnalysisVegetation IndicesChange Detection From Time SeriesEl Niño-southern Oscillation VariabilityEnvironmental Time Series AnalysisPrincipal ComponentsSatellite Image Time Series AnalysisSensor DriftSensor Drift AnalysisTime Series Remote Sensing Analysis
The potential of using Standardized Principal Components for the analysis of long time series of spatial environmental data is assessed using a series of 36 monthly AVHRR-derived NDVI images for Africa for the years 1986-88 as an illustration. The first component is found to represent the characteristic NDVI regardless of the season. The second, third, and fourth components relate to seasonal changes in NDVI. The fifth and sixth components uncover a sensor-related drift in the NDVI values due to successively later equatorial crossings of the NOAA-9 satellite. The seventh and eighth components illustrate NDVI anomalies related to significant El Nino/Southern Oscillation (ENSO) events, primarily in southern Africa. The technique is shown to be a comprehensive indicator of change events in time series data that is sensitive to periodic and aperiodic events alike.