Observed biases in the conterminous U.S. AVHRR satellite data set: A North Carolina case study

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Abstract
The USGS EROS Data Center has produced a national data set for long‐term ecological monitoring termed the “Conterminous U.S. AVHRR (Advanced Very High Resolution Radiometer) Data Set” that includes biweekly maximum‐value composite (MVC) images of NDVI (Normalized Difference Vegetation Index) values, original five channels of calibrated AVHRR satellite data, image viewing and illumination geometry, date of observation, and ancillary data sets pertaining to landcover and political boundaries (Loveland et al., 1991; Eidenshink, 1992). The basic intent of the study was to evaluate the potential of the data set for broad‐scale, multitemporal landscape mapping by assessing the quality and sensitivity of the data set to support such applications. Potential biases existing in the data set were identified and analytical procedures suggested to deal with such biases. Results from analyses within the State of North Carolina suggest that the time series of the NDVI values is influenced by sensitivities to residual cloud contamination, preceeding climatic events, temporal and spatial scales of analyses, and the composition and spatial organization of the study area. Spatial and temporal discontinuities within and between images, irregular space‐time semivariograms, and statistical summaries of the data show the existence of biases in the data set for North Carolina. Possible adjustments to reduce this level of uncertainty include the generation of NDVI composites over longer time periods, exclusion of suspected contaminated data, or the use of spatial and temporal interpolations of contaminated values to reduce their relative impact on each composite image. Regional variations in NDVI responses to viewing and illumination geometry may also be important factors for users to consider.