International Journal of Remote Sensing · 2013 · 20 citations · 43 references
Natural SciencesEarth SciencesPhysical GeographyClimatologyRemote SensingTime Series AnalysisHydrometeorological ModelingHydrometeorological Observation SystemsLand Surface ModelingLand Surface MonitoringLand Surface ProcessesRemote Sensing Change DetectionLand Surface HeterogeneityLong-term Land Surface MonitoringSatellite Image Time Series AnalysisTime Series Remote Sensing AnalysisTime Series Trend Analysis
The purpose of this work was to monitor and model land surface phenology over the past ten years in South American Bermejo River Basin using MODIS NDVI product. In order to do this, we evaluated characteristics of the satellite data and available information of the study area ecosystem to choose the best model to capture temporal dynamics of NDVI in local vegetation (sufficiently complex to provide a good fit and simple enough so that each parameter has an immediate ecological meaning). An ecological interpretation of model parameters was provided. Different land surfaces showed distinct fluctuations over time in NDVI values and this information was used to improve an object-oriented classification. A decision tree classification was developed to identify spatial patterns of NDVI functional form, and the fluctuations that these patterns presented from 2000 to 2010. We integrated inter-annual information in a final map that distinguishes stable areas from changing sites. Assuming that inter-annual large spatial scale fluctuations were related to climatic events, we established how vegetated land surfaces within the study area responded to these. Our study was designed to emphasize the interpretation of the spatial and temporal scales of land surface phenology.
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Time Series Analysis: Forecasting and Control
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