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Albemarle-Pamlico Drainage Basin - Scientific Reports
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Modis Land Cover (PDF, 50pp, 988KB)
Abstract: Currently available land-cover data sets for large geographic regions are produced on an intermittent basis and are often dated. Ideally, annually updated data would be available to support environmental status and trends assessments and ecosystem process modeling. This research examined the potential for vegetation phenology based land-cover classification over the 52,000 km2 Albemarle-Pamlico Estuarine System (APES) that could be performed annually. Traditional hyperspectral image classification techniques were applied using MODIS-NDVI 250 m 16-day composite data over calendar year 2001 to support the multi-temporal image analysis approach. A reference database was developed using archival aerial photography that provided detailed mixed pixel cover type data for 31,322 sampling sites corresponding to MODIS 250 m pixels. Accuracy estimates for the classification indicated that the overall accuracy of the classification ranged from 73% for very heterogeneous pixels to 89% when only homogeneous pixels were examined. These accuracies are comparable to similar classifications using much higher spatial resolution data, which indicates that there is significant value added to relatively coarse resolution data though the addition of multi-temporal observations... Continue Reading.Modis Change Detection (PDF, 43pp, 1473KB)
Abstract: Monitoring the locations and distributions of land-cover changes is important for establishing linkages between policy decisions, regulatory actions and subsequent land-use activities. Past studies incorporating two-date change detection using Landsat data have tended to be performance limited for applications in biologically complex systems. This study explored the use of 250 m multi-temporal MODIS NDVI 16-day composite data to provide an automated change detection and alarm capability on a 1-year time-step for the Albemarle-Pamlico Estuary System (APES) region of the US. Detection accuracy was assessed for 2002 at 88%, with a reasonable balance between change commission errors (21.9%), change omission errors (27.5%), and Kappa coefficient of 0.67. Annual change detection rates across the APES over the study period (2002-2005) were estimated at 0.7% per annum and varied from 0.4% (2003) to 0.9% (2004). Regional variations were also readily apparent ranging from 1.6% to 0.1% per annum for the tidal water and mountain ecological zones, respectfully. This research included the application of an automated protocol to first filter the MODIS NDVI data to remove poor (corrupted) data values and then estimate the missing data values using a discrete Fourier transformation technique to provide high quality uninterrupted data to support the change detection analysis. The methods and results detailed in this article apply only to non-agricultural areas. Additional limitations attributed to the coarse resolution of the NDVI data included the overestimation of change area that necessitated the application of a change area correction factor. Continue Reading.