Effects of band combinations and GIS masking on fire-scar mapping at local scales in east-central Florida, USA
Abbreviated Journal Title
Can. J. Remote Sens.
SPOT-VEGETATION; SCRUB-JAYS; ACCURACY; LANDSAT-7; ECOSYSTEM; IMAGERY; Remote Sensing
The fire-adapted vegetation in east-central Florida provides habitat for many threatened and endangered species, such as the Florida scrub-jay (Aphelocoma coerulescens). Accurate fire occurrence records are critically important for better understanding the relationship between fire and vegetation structure. The rapid growth rates of fire-adapted vegetation in east-central Florida make it difficult to capture detailed fire scars with remote sensing data acquired weeks after the fires. The objective of this study is to develop a reliable remote sensing approach for accurately mapping burned areas in Florida scrub vegetation at the National Aeronautics and Space Administration (NASA) John F. Kennedy Space Center (KSC) and Merritt Island National Wildlife Refuge (MINWR). Landsat thematic mapper (TM) data acquired on 21 April 1987 were used for classification experiments. Geographic information system (GIS) data layers of fire management units (FMUs) with known fire occurrence (presence or absence) were used to mask the original remote sensing data or thematic maps following classification. A separation index (SI) was used to evaluate each individual band for its power to discriminate unburned and burned areas. Twelve classifications with selected band groups derived from Landsat TM data with different geographic extents were compared using an error matrix method. The classification of the four most suitable bands derived for the entire KSC-MINWR area resulted in the highest accuracy. The final map product was generated by overlaying the classified map with the FMU data layer and masking out FMUs that did not burn. This paper addresses a number of issues relevant to the classification of burned areas and includes the effect of geographic extent (GE effect) of remote sensing data on classification, determining the best bands for classification, and cleaning classification results using GIS masking. It also serves as the first published effort to map fire scars in the Florida scrub and flatwoods vegetative communities of the southeastern US using image processing techniques.
Canadian Journal of Remote Sensing
"Effects of band combinations and GIS masking on fire-scar mapping at local scales in east-central Florida, USA" (2007). Faculty Bibliography 2000s. 7636.