Engineering topics
Publications and source records attributed to Scheer, George.
California chaparral ecosystems are exceptionally fire adapted and typically are subject to wildfire at decadal to century frequencies. The hot dry Mediterranean climate summers and the chaparral communities of the Santa Monica Mountains make wildfire one of the most serious economic and life-threatening natural disasters faced by the region.
California chaparral ecosystems are exceptionally fire adapted and typically are subject to wildfire at decadal to century frequencies. The hot dry Mediterranean climate summers and the chaparral communities of the Santa Monica Mountains make wildfire one of the most serious economic and life-threatening natural disasters faced by the region. Additionally, the steep fire-burned hillsides are subject to erosion, slumpage, and mud slides during the winter rains. The Santa Monica Mountain Zone (SMMZ) is a 104,000 ha eastwest trending range with 607 m of vertical relief and located in the center of the greater Los Angeles region. A series of fires in the fall of 1993 burned from Simi Valley to Santa Monica within a few hours. Developing techniques to monitor fire hazard and predict the spread of fire is of major concern to the region. One key factor in the susceptibility to fire is the water content of the vegetation canopy. The development of imaging spectrometry and remote sensing techniques may constitute a tool to provide this information.
The acreage of grassland and grassland-savannah is extensive in California, making direct measurement and assessment logistically impossible. Grasslands cover the entire Central Valley up to about 1200 m elevation in the Coast Range and Sierra Nevada Range. Kuchler's map shows 5.35 M ha grassland with an additional 3.87 M ha in Oak savannah. The goal of this study was to examine the use of high spectral resolution sensors to distinguish between dry grass and soil in remotely sensed images. Spectral features that distinguish soils and dry plant material in the shortwave infrared (SWIR) region are thought to be primarily caused by cellulose and lignin, biochemicals which are absent from soils or occur as breakdown products in humid substances that lack the narrow-band features. We have used spectral mixing analysis (SMA) combined with Geographic Information Systems (GIS) analysis to characterize plant communities and dry grass biomass. The GIS was used to overlay elevation maps, and vegetation maps, with the SMA results. The advantage of non-image data is that it provides an independent source of information for the community classification.