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Norman, S.

Publications and source records attributed to Norman, S..

Land-cover classification of California using mosaicking and high-speed processing

A land cover classification of Landsat MSS data has been made for the entire state of California. Digital mosaicking of 32 Landsat scenes with registered digital elevation, slope, and aspect was prepared. Stratified unsupervised clustering generated the spectral classes which were identified into 16 categories, mostly forest types, using U-2 CIR photos. A verification using 81 primary sample units resulted in a forest/nonforest accuracy of 80.2% and a commercial conifer and hardwood accuracy of 75.1%. The results are now being used in many projects throughout the state.

Peterson, D. L.↗

Bulk processing techniques for very large areas - Landsat classification of California

In 1977, California Law AB452 was passed to provide a mandate for the California Department of Forestry (CDF) to design and implement an information system to assess the forest land base for multiple uses and values. In connection with this mandate, a land-cover map of the entire state, emphasizing forest types, was produced. In producing this map, the latest techniques in digital image mosaicking were combined with the highspeed processing capability available on the ILLIAC IV parallel processor and other computer systems at the Ames Research Center (ARC). An operational and very responsive analysis method was developed at ARC that permitted on-time response to weekly workshops conducted with CDF field personnel to identify all 1,200 spectral classes and to produce final products. Over 100,000,000 acres were classified in the period between December 1, 1978, and April 15, 1979. All analyses were conducted using existing software.

Newland, W.↗