Forage Production of the Argentine Pampa Region Based on Land Use and Long-Term Normalized Difference Vegetation Index Data
AuthorDi Bella, Carlos M.
Negri, Ignacio J.
Jaimes, Florencia R.
Jobbágy, Esteban G.
Garbulsky, Martin F.
Deregibus, Victor A.
Keywordslinear spectral unmixing
net primary production
MetadataShow full item record
CitationDi Bella, C. M., Negri, I. J., Posse, G., Jaimes, F. R., Jobbágy, E. G., Garbulsky, M. F., & Deregibus, V. A. (2009). Forage production of the Argentine pampa region based on land use and long-term Normalized Difference Vegetation Index data. Rangeland Ecology & Management, 62(2), 163-170.
PublisherSociety for Range Management
JournalRangeland Ecology & Management
AbstractInformation about forage productivity and its interactions with cultural practices or climatic variation is necessary to plan livestock management and to increase production without damaging the environment. Remote sensing provides a valuable data source to achieve these goals. Here we characterize forage production over a large region (92 million hectares) by analyzing spatial, seasonal, and interannual variability with Normalized Difference Vegetation Index (NDVI) data. We identified 23 homogeneous zones that enclose multiple counties with similar characteristics of land use and productivity. A long-term series (1981-2000) of Advanced Very High Resolution Radiometer images were used to calculate monthly NDVI and the annual integral of NDVI (I-NDVI), which is an estimate of primary productivity, for each county. County agricultural land use data were used to resolve pure forage and crop NDVI patterns over time using a spectral unmixing model. The annual integral of NDVI was significantly associated with geographic longitude and average precipitation but not with latitude. Improved relationships between forage production and I-NDVI can be obtained by collecting more accurate forage estimates in the field and calculating radiation use efficiencies. Images of high temporal resolution allow the inference of seasonal changes, and images of high spatial resolution allow a more precise description of the forage resources.