Submitted to: American Society for Photogrammetry and Remote Sensing Proceedings
Publication Type: Abstract Only
Publication Acceptance Date: 11/26/2007
Publication Date: 4/28/2008
Citation: Johnson, M.D., Harris, N.R., Louhaichi, M., Clark, P., and Johnson, D.E. 2008. A protocal for monitoring vegetation, bare ground and litter in scaled globally-positioned, ground-level digital imagery. IN: 2008 Annual Conference Proceedings of the ASPRS. April 28-May 2, 2008. Portland, OR. American Society for Photogrammetry and Remote Sensing. Abstract.
Interpretive Summary: Traditional sampling of vegetation cover is quite tedious and slow. We developed a protocol and accompanying hardware and software for collecting ground-level digital imagery. This new sampling system allowed the user to convert imagery to an extremely high-resolution map of the vegetation and ground surface providing measurements of vegetation, litter, and bare ground cover. These results provide agricultural producers, natural resource managers, and researchers with a rapid and accurate means of assessing vegetation cover and ecological site condition.
Technical Abstract: Scientists and managers have used the quadrat as a means of measuring and monitoring vegetation since the foundation of modern plant ecology. Traditional quadrat sampling, unfortunately, is quite tedious and slow. Proper monitoring requires not only careful examination of individual quadrats (samples) but large numbers of samples if the information is to be used in a statistical context. These limitations were acutely felt very early and by the 1930’s overhead photography was being employed to save time, increase accuracy, eliminate personal bias, and create a visual record. Large scale photographs (1:100 to 1:5000) resolve considerable detail, but have been problematic because it is difficult to determine exactly where the photo was taken and their rectification was nearly impossible. Recent advances in differential GPS, digital imaging, and computer technologies have opened new opportunities for rapidly collecting and processing images in the field. We developed a protocol and accompanying hardware and software that collects ground-level digital imagery; and scales, rectifies, classifies, and saves images as bitmaps and their associated world and projection files. Our software allows the user to classify the image, for example, as soil, litter, and bare ground and save the classification as an Arc ASCII grid map. Rectified and classified images can then be used in numerous imaging and GIS packages, such as ERDAS, PCI, ENVI, and ArcGIS. Because the collected digital images are spatially explicit, objects in the images can then be measured and cover values can be quantified.