AN EVALUATION OF SATELLITE DATA FOR ESTIMATING THE AREA OF SMALL FORESTLANDS IN THE SOUTHERN LOWER PENINSULA OF MICHIGAN.

摘要

This study evaluated the use and potential of Landsat images for mapping and estimating acreage of small scattered forestlands in Barry County, Michigan. Four Landsat images, two from late winter and two from early fall, were tested. Three of these images, the winter black-and-white band 5, the winter color and the fall color, were employed without modification. The fourth image was a diazo color composite of the fall scene produced by manipulating a black-and-white transparency of each Landsat band to enhance the appearance of the forest resources.;The overall recommendation of the study is that, considering errors, accuracy, and cost, winter color imagery is the best Landsat alternative for mapping small forest tracts. However, since the availability of cloud-free winter images of the study area is significantly lower than images for other seasons, a diazo enhanced image of a fall scene is recommended as the next best alternative.;Forestlands as small as 2.5 acres were mapped from each Landsat data source. The maps for each image were then compared with a detailed forest type map that had been previously prepared by another investigator using color infrared photography and extensive ground truth information. Comparison of the Landsat maps with this source detected mapping errors, which were categorized as those of commission and omission, and then further classified into boundary or identification errors. The commission errors were usually higher than those of omission, and most of the error cases were boundary errors of less than five acres. The most frequently misclassified areas were agriculture lands, treed-bogs, brushlands, and lowland and mixed hardwood stands, while stocking level affected interpretation more than stand size. The overall level of the interpretation performance was expressed three ways, through the estimation of classification, interpretation and mapping accuracies. These accuracies ranged between 74 and 98 percent.