In California, the Vegetation Type Map (VTM) project of the 1930's has provided valuable historical vegetation data. Albert Wieslander led this effort to survey the forests of California in the 1930's. His crews surveyed over 150,000 km^, drawing detailed vegetation maps, taking 3000 photos and 17,000 vegetation plots. We developed a technique to digitize the Placerville 30' quadrangle VTM, rendering it to a Geographic Information System (GIS). The map covers 2408.8 km-of the west slope of the Sierra Nevada. In this area VTM crews identified 59 dominant plant species and eight genera or land cover classes and mapped their distribution into 3422 polygons. They identified recently disturbed areas that covered 13.5% of the landscape. We compared the digital VTM quad to CALVEG, a satellite-derived vegetation map from 1996. Land cover change for California Wildlife Habitat Relationship (WHR) vegetation types had occurred on 42.1% of the area. WHR types with the largest gains were: Montane Hardwood, Douglas-Fir, and Annual Grassland. Low elevation hardwoods, particularly Blue Oak Woodland (dominated by Quercus douglasii, Fagaceae), chaparrals and upper elevation conifers were the types that lost the most area. Differences in mapping techniques are unlikely to be the cause of this change because the analysis used controlled for map-based errors. Potential causes of the observed change at these physiognomic levels of classification include human perturbation, succession, and cHmate change.

One-foot resolution imagery is used to develop a detailed land cover map for part of Highway 99 in the San Joaquin Valley of California, US. The land cover map is used to model the probability of occurrence of 12 endangered or threatened species and as input to an urban growth model to examine the likelihood of development of every map unit. The combination of the two model predictions permits the categorization of every map unit with a potential endangered species richness index and predicted degree of development. Polygons with high potential endangered species richness were ranked according to the degree of development pressure. This planning approach is computationally intensive, but the input data are relatively easy to assemble, consisting of: a detailed, and fine-scale, land cover map; species presence locations; statewide climate and landcover maps; a parcel ownership map; population growth projections; and a digital map of the county general plan.