Remote Sensing Assessment of Paspalum quadrifarium Grasslands in the Flooding Pampa, Argentina
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CitationHerrera, L. P., Hermida, V. G., Martínez, G. A., Laterra, P., & Maceira, N. (2005). Remote sensing assessment of Paspalum quadrifarium grasslands in the Flooding Pampa, Argentina. Rangeland Ecology & Management, 58(4), 406-412.
PublisherSociety for Range Management
JournalRangeland Ecology & Management
AbstractThe knowledge of the distribution, area, and current conservation status of relict natural grasslands dominated by the tall-tussock grass Paspalum quadrifarium Lam. (‘‘pajonal’’) in the Flooding Pampa (Argentina) is relevant for the identification of conservation sites and sustainable management and land-use planning. Since European settlement, vast areas of pajonal were converted to croplands and short-grass prairies. The only available vegetation map of these grasslands was made in the mid-20th century. We evaluated 2 methods of land-cover classification (supervised and unsupervised) using a Landsat TM satellite image over an area of 2 258.21 km2 in Ayacucho county, where pajonal still persists as an important ecosystem. At the paddock scale, this grassland community presents a complex structure in which the pajonal is not a pure category but a mosaic of tall and short grasses. Six categories of land cover were adopted (crops, sown pastures, short grasses, pajonal, wetlands, and urban areas). A very good overall accuracy was obtained for both classifications (86.9% and 87.9% for supervised and unsupervised classifications, respectively). However, both producer’s and user’s accuracies for the pajonal and short grasses were better for the unsupervised classification than for the supervised classification. The pajonal class occupied only 20% of the study area with patch size ranging between 0.09 and 1 653 ha. This work suggests an important replacement of tall-tussock grass by short-grass matrix, which represents noticeable structural and functional changes. The unsupervised classification of Landsat image seems a particularly suitable method for mapping complex vegetation units like the highly fragmented pajonal of the Flooding Pampa and should be an important tool for management and tracking future changes.