Modelling vegetation cover types using multiseasonal remotely sensed data to compare ecotones at multiple spatial and spectral resolutions (Michigan).

摘要

The Army National Guard Bureau has implemented a cooperative project with Utah State University to help with the use, display, and evaluation of environmental data for maintaining land condition. Camp Grayling, Michigan, is comprised of deciduous and evergreen forest types. Use of remote sensing for classification has been limited in this region due to the difficulty of species-level classification using single-date remote-sensing techniques. Also, remote sensing has traditionally focused on mapping homogeneous zones rather than vegetation boundaries, while one of the concerns for land managers is the nature of vegetation edges (ecotones).; This study analyzed each season and band from multiseasonal satellite imagery for their contribution to separating vegetation type and density classes. Then spectral reflectance values for each vegetation and density class were used in discriminant models that define vegetation cover types and densities. These models were then tested against points within 200 m of vegetation boundaries to determine the performance of the models at edges of vegetation types. The reflectance values for vegetation types on Landsat Thematic Mapper (TM), Landsat MultiSpectral Sensor (MSS), and Advanced Very High Resolution Radiometer (AVHRR) imagery were used. (Abstract shortened by UMI.)