Fire mapping science can benefit from standard techniques for analyzing time-series data. The Z transform produces the z-score, termed a standardized variable because the units are dimensionless standard deviations. The Z transform represents a simple, older way to characterize non-image data, but is presented here as a new way to enhance fire scar anomalies in image time-series data. The transform is invertible, and can be applied to any continuous, gridded data. Time series data from the Advanced Very High Resolution Radiometer (AVHRR) are featured. When applied in the x,y (i.e., spatial) plane of AVHRR Normalized Difference Vegetation Index (NDVI) data, the Z transform places each NDVI value in the statistical context at the time of image formation, producing Z-standardized NDVI (ZNDVI) values. Invoking the Z transform across the z (time series) plane of ZNDVI images produces a multitemporal Z (MTZ) score for each pixel in a ZNDVI target image for a selected time step. The MTZ image thus depicts the deviation or departure of a given pixel, for a specific step in the series, relative to the mean for that pixel across the time series. A case study demonstrates an MTZ enhancement of AVHRR NDVI data that enhances in the Rincon Mountains east of Tucson, Arizona unusually low NDVI values associated with a 1994 wildfire scar. Enhancements are confirmed using higher-resolution remote sensor data from the Landsat Thematic Mapper (TM).
ASJC Scopus subject areas
- Geography, Planning and Development
- Water Science and Technology