Vegetation classification and distribution mapping report Mesa Verde National Park Our findings highlight the need for appropriate scales of mapping and accuracy assessment of aerial photography interpretation generated vegetation community maps.ĭirectory of Open Access Journals (Sweden)įull Text Available The current work examines the main aspects of wetland vegetation mapping, which can be summarized as analysis of the ecological- vegetational (ecotone gradients vegetation complexes relationships between vegetation distribution and geomorphology vegetation of the hydrographic basin lo which the wetland in question belongs vegetation monitoring with help of four vegetation maps: phytosociological map of the real and potential vegetation, map of vegetation dynamical tendencies, map of vegetation series. The overall accuracy and Kappa coefficient for both thematic maps was 66.67% and 0.63, respectively, calculated from standard error matrices.
The accuracy assessment was based on 50% of a field dataset collected over a 4 year period (2006 to 2009) and the remaining 50% of sites were used for map attribution.
Multivariate and intuitive analysis techniques were employed to identify 22 vegetation communities within the study area.
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Manual stereoscopic line-work was delineated at 1:10,000 and thematic maps generated at 1:25,000 and 1:100,000. Vegetation communities covering an area of 530 km2 on Bullo River Station, Northern Territory, Australia, were mapped using an interpretation of 1:50,000 color aerial photography. However, unlike an algorithm-based classification of satellite imagery, accuracy of aerial photography interpretation generated maps is rarely assessed. ? 2008 American Society for Photogrammetry and Remote Sensing.Īccuracy assessment of vegetation community maps generated by aerial photography interpretation: perspective from the tropical savanna, AustraliaĪerial photography interpretation is the most common mapping technique in the world. A hybrid combination of statistical and photointerpretation methods was used to obtain an overall accuracy of 63 percent for a map with 49 vegetation community and land-cover classes, and 78 percent for a 33-class map of the study area. Variables derived from these data sources represent both actual and potential vegetation community patterns on the landscape. Topographic data facilitated differentiation of vegetation communities based on indirect gradients (e.g., landform position, slope, aspect), which relate to variations in resource and disturbance gradients. Remote sensing data provided variables that discriminated vegetation communities based on differences in color, spectral reflectance, greenness, brightness, and texture. Vegetation communities were differentiated using a large array of variables derived from remote sensing and topographic data, which were fused into independent mathematical functions using a discriminant analysis classification approach. Larsen, D.R.Ī vegetation community map was produced for the Ozark National Scenic Riverways consistent with the association level of the National Vegetation Classification System. Mapping vegetation communities using statistical data fusion in the Ozark National Scenic Riverways, Missouri, USAĬhastain, R.A.
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